diff --git a/docs/theory.rst b/docs/theory.rst
index 3a16614..3ff10d1 100644
--- a/docs/theory.rst
+++ b/docs/theory.rst
@@ -7,7 +7,7 @@ For a more detailed treatment, see `Grooms et al. (2021) <https://doi.org/10.100
 Filter Scale and Shape
 ----------------------
 
-Any low-pass spatial filter should have a target length scale such that the filtered field keeps length scales larger than the target length scale, and smoothes out smaller scales. In the context of this package the target length scale is called ``filter_scale``.
+Any low-pass spatial filter should have a target length scale such that the filtered field keeps the part of the signal with length scales larger than the target length scale, and smoothes out smaller scales. In the context of this package the target length scale is called ``filter_scale``.
 
 A spatial filter can also have a *shape* that determines how sharply it separates scales above and below the target length scale.
 The filter shape can be thought of in terms of the kernel of a convolution filter
@@ -62,7 +62,7 @@ So with ``n_steps`` = 3 you might get one Laplacian plus one biharmonic step, or
 Once a filter object has been constructed, the method ``plot_shape`` can be used to plot the shape of the target filter and the approximate filter.
 This can be particularly useful if the user is trying to reduce ``n_steps`` from its default value without introducing sigificant errors.
 ``plot_shape`` does not plot the shape of the filter *kernel*.
-Instead, it plots the shape in "Fourier" space.
+Instead, it plots the frequency response of the filter for each wavenumber :math:`k`.
 Length scales are related to wavelengths by :math:`\ell = 2\pi/k`.
 The filter leaves large scales unchanged, so ``plot_shape`` shows values close to 1 for small :math:`k`.
 The filter damps out small scales, so ``plot_shape`` shows values close to 0 for large :math:`k`.
@@ -111,7 +111,7 @@ Anisotropic Filtering
 
 It is possible to have different filter scales in different directions, and to have both the scales and directions vary over the domain.
 This is achieved by replacing :math:`\kappa` in the previous section with a :math:`2\times2` symmetric and positive definite matrix (for a 2D domain), i.e. replacing :math:`\Delta` with :math:`\nabla\cdot(\mathbf{K}\nabla)`.
-``gcm-filters`` currently only supports having the directions of anisotropy be aligned with the grid, so that the user only inputs one :math:`\kappa` for each grid direction, rather than a full :math:`2\times2` matrix.
+``gcm-filters`` currently only supports diagonal :math:`\mathbf{K}`, i.e. the principal axes of the anisotropic filter are aligned with the grid, so that the user only inputs one :math:`\kappa` for each grid direction, rather than a full :math:`2\times2` matrix.
 Just like in the previous section, we require that each of these two :math:`\kappa` be less than or equal to 1, and the interpretation is also the same: the local filter scale in a particular direction is :math:`\sqrt{\kappa}\times` ``filter_scale``.
 
 Suppose, for example, that you want to filter with a scale of 60 in the grid-x direction and a scale of 30 in the grid-y direction.
diff --git a/docs/tutorial.ipynb b/docs/tutorial.ipynb
index 19685cd..248039d 100644
--- a/docs/tutorial.ipynb
+++ b/docs/tutorial.ipynb
@@ -393,132 +393,132 @@
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        "}\n",
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-       "         0.48661887, 0.58225395],\n",
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        "        ...,\n",
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-       "        [0.93015342, 0.44907453, 0.20284064, ..., 0.77384949,\n",
-       "         0.25920195, 0.42477776],\n",
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        "...\n",
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-       "Dimensions without coordinates: time, y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>time</span>: 10</li><li><span>y</span>: 128</li><li><span>x</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-85d7c8fe-2f8e-48f6-9d6a-8f2edd5ae7c9' class='xr-array-in' type='checkbox' checked><label for='section-85d7c8fe-2f8e-48f6-9d6a-8f2edd5ae7c9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.7563 0.3674 0.6265 0.1472 0.9033 ... 0.5985 0.001246 0.28 0.3823</span></div><div class='xr-array-data'><pre>array([[[0.756279  , 0.3674273 , 0.62650849, ..., 0.10204509,\n",
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+       "       [[0.3288639 , 0.17308488, 0.8601216 , ..., 0.21530271,\n",
+       "         0.63338362, 0.7852744 ],\n",
+       "        [0.65445055, 0.66832114, 0.5927022 , ..., 0.16429199,\n",
+       "         0.16918704, 0.50102837],\n",
+       "        [0.41151733, 0.38789761, 0.2331703 , ..., 0.81107977,\n",
+       "         0.13896245, 0.19969136],\n",
        "        ...,\n",
-       "        [0.91934719, 0.48202775, 0.51762493, ..., 0.48126411,\n",
-       "         0.84300516, 0.71309106],\n",
-       "        [0.67031955, 0.83303859, 0.16735166, ..., 0.39426699,\n",
-       "         0.75678361, 0.62240662],\n",
-       "        [0.90826246, 0.94675773, 0.9594789 , ..., 0.00124644,\n",
-       "         0.27999418, 0.38233597]]])\n",
+       "        [0.86026637, 0.81696272, 0.59197368, ..., 0.30807527,\n",
+       "         0.37791543, 0.59068587],\n",
+       "        [0.59863705, 0.4032838 , 0.08840804, ..., 0.8285281 ,\n",
+       "         0.85719792, 0.65468291],\n",
+       "        [0.37486887, 0.83663067, 0.691618  , ..., 0.33628028,\n",
+       "         0.93787455, 0.64841767]]])\n",
        "Dimensions without coordinates: time, y, x"
       ]
      },
@@ -539,7 +539,7 @@
    "metadata": {},
    "source": [
     "To make things a bit more interesting, we will create a \"land mask\"; a binary array representing topography in our made-up ocean.\n",
-    "The convention is here that the array is 1 in the ocean (\"wet points\") and 0 in the land (\"dry points\")."
+    "The convention here is that the array is 1 in the ocean (\"wet points\") and 0 in the land (\"dry points\")."
    ]
   },
   {
@@ -550,7 +550,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x7f1f65561a00>"
+       "<matplotlib.collections.QuadMesh at 0x2b26e0666750>"
       ]
      },
      "execution_count": 3,
@@ -559,7 +559,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -593,7 +593,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x7f1f64a09cd0>"
+       "<matplotlib.collections.QuadMesh at 0x2b26e1b1c490>"
       ]
      },
      "execution_count": 4,
@@ -602,7 +602,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -668,10 +668,13 @@
      "data": {
       "text/plain": [
        "[<GridType.REGULAR: 1>,\n",
-       " <GridType.REGULAR_WITH_LAND: 2>,\n",
-       " <GridType.IRREGULAR_WITH_LAND: 3>,\n",
-       " <GridType.TRIPOLAR_REGULAR_WITH_LAND: 4>,\n",
-       " <GridType.TRIPOLAR_POP_WITH_LAND: 5>]"
+       " <GridType.TRANSFORMED_TO_REGULAR: 2>,\n",
+       " <GridType.REGULAR_WITH_LAND: 3>,\n",
+       " <GridType.TRANSFORMED_TO_REGULAR_WITH_LAND: 4>,\n",
+       " <GridType.IRREGULAR_WITH_LAND: 5>,\n",
+       " <GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND: 6>,\n",
+       " <GridType.TRIPOLAR_POP_WITH_LAND: 7>,\n",
+       " <GridType.VECTOR_C_GRID: 8>]"
       ]
      },
      "execution_count": 6,
@@ -718,23 +721,28 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "So if we use this grid type, we have to include a `wet_mask` grid variable.\n",
-    "\n",
+    "So if we use this grid type, we have to include a `wet_mask` grid variable."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "We are now ready to create our filter object."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=4, dx_min=1, filter_shape=<FilterShape.TAPER: 2>, transition_width=3.141592653589793, ndim=2, n_steps=16, grid_type=<GridType.REGULAR_WITH_LAND: 2>)"
+       "Filter(filter_scale=4, dx_min=1, filter_shape=<FilterShape.TAPER: 2>, transition_width=3.141592653589793, ndim=2, n_steps=16, grid_type=<GridType.REGULAR_WITH_LAND: 3>)"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -754,19 +762,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The repr for the filter object includes some of the parameters it was initiliazed with, to help us keep track of what we are doing.\n",
+    "The repr (i.e., the string representation) for the filter object includes some of the parameters it was initiliazed with, to help us keep track of what we are doing.\n",
     "\n",
-    "Next we plot the shape of the target filter and the approximation. Note that this is not the shape of the filter *kernel*, it is the shape 'in Fourier space,' meaning that we're plotting how the filter attenuates different scales in the data. The filter is 1 at large scales (small wavenumbers $k$, at the left side of the plot) and 0 at small scales (large wavenumbers $k$, at the right side of the plot), meaning that large scales are left unchanged and small scales are damped to zero."
+    "Next we plot the shape of the target filter and the approximation. Note that this is not the shape of the filter *kernel*. Rather, it shows the frequency response of the filter, meaning that we're plotting how the filter attenuates different scales in the data. The filter is 1 at large scales (small wavenumbers $k$, at the left side of the plot) and 0 at small scales (large wavenumbers $k$, at the right side of the plot), meaning that large scales are left unchanged and small scales are damped to zero."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -785,27 +793,27 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "By not specifying `n_steps`, we allow the filter to automatically select a value that leads to a very-good approximation of the target. In the above example using the Taper shape, the filter selects to use 16 steps to filter by a factor of 4.\n",
+    "By not specifying `n_steps`, we allow the filter to automatically select a value that leads to a very-good approximation of the target. In the above example using the Taper shape, the filter elects to use 16 steps to filter by a factor of 4.\n",
     "\n",
     "The user might want to use a smaller number of steps to reduce the cost. The caveat is that the accuracy will be reduced, so the filter might not act as expected. To illustrate, we create a new filter with a smaller number of steps and plot the result. (Note that using a value of `n_steps` lower than the default will raise a warning.)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/ian/Documents/Projects/gcm-filters/gcm_filters/filter.py:255: UserWarning: Warning: You have set n_steps below the default. Results might not be accurate.\n",
-      "  warnings.warn(\n"
+      "/glade/u/home/noraloose/gcm-filters/gcm_filters/filter.py:11: UserWarning: You have set n_steps below the default. Results might not be accurate.\n",
+      "  \n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -839,20 +847,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/ian/Documents/Projects/gcm-filters/gcm_filters/filter.py:255: UserWarning: Warning: You have set n_steps below the default. Results might not be accurate.\n",
-      "  warnings.warn(\n"
+      "/glade/u/home/noraloose/gcm-filters/gcm_filters/filter.py:11: UserWarning: You have set n_steps below the default. Results might not be accurate.\n",
+      "  \n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -872,7 +880,15 @@
     "    grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,\n",
     "    grid_vars={'wet_mask': wet_mask}\n",
     ")\n",
-    "filter_4.plot_shape()\n",
+    "filter_4.plot_shape()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "del filter_8, filter_4"
    ]
   },
@@ -887,15 +903,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 76.4 ms, sys: 6.78 ms, total: 83.1 ms\n",
-      "Wall time: 86.2 ms\n"
+      "CPU times: user 88.5 ms, sys: 30.9 ms, total: 119 ms\n",
+      "Wall time: 123 ms\n"
      ]
     },
     {
@@ -1253,136 +1269,136 @@
        "  fill: currentColor;\n",
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 10, y: 128, x: 256)&gt;\n",
-       "array([[[0.57808346, 0.57159167, 0.53605723, ..., 0.42380628,\n",
-       "         0.47128317, 0.53832381],\n",
-       "        [0.51796103, 0.5064675 , 0.47607245, ..., 0.41564899,\n",
-       "         0.43997698, 0.48980835],\n",
-       "        [0.47207293, 0.46880608, 0.45562155, ..., 0.41782065,\n",
-       "         0.41604955, 0.4486439 ],\n",
+       "array([[[0.54809688, 0.51879934, 0.45514536, ..., 0.54077783,\n",
+       "         0.54456105, 0.54726763],\n",
+       "        [0.51027425, 0.50829846, 0.47952886, ..., 0.50617368,\n",
+       "         0.49433087, 0.49501071],\n",
+       "        [0.46562662, 0.48901278, 0.49296147, ..., 0.48759978,\n",
+       "         0.45046558, 0.44113049],\n",
        "        ...,\n",
-       "        [0.61990063, 0.60268694, 0.56123414, ..., 0.53148674,\n",
-       "         0.56269448, 0.60187529],\n",
-       "        [0.63107469, 0.62990889, 0.59892897, ..., 0.49414191,\n",
-       "         0.53835709, 0.59487888],\n",
-       "        [0.62020502, 0.62145745, 0.5897504 , ..., 0.45245432,\n",
-       "         0.50589834, 0.57520595]],\n",
-       "\n",
-       "       [[0.59323122, 0.63647222, 0.62798396, ..., 0.44635778,\n",
-       "         0.46106912, 0.52004527],\n",
-       "        [0.55492442, 0.60076614, 0.59340881, ..., 0.41582369,\n",
-       "         0.41842523, 0.4777155 ],\n",
-       "        [0.51070179, 0.56796719, 0.57598255, ..., 0.38093767,\n",
-       "         0.37107501, 0.428035  ],\n",
+       "        [0.45416375, 0.50135563, 0.50022922, ..., 0.5021761 ,\n",
+       "         0.43741638, 0.41562048],\n",
+       "        [0.50440694, 0.50890034, 0.46730875, ..., 0.5304542 ,\n",
+       "         0.49895897, 0.4870923 ],\n",
+       "        [0.54747542, 0.51843947, 0.44854823, ..., 0.55195339,\n",
+       "         0.54888113, 0.54681858]],\n",
+       "\n",
+       "       [[0.40788693, 0.42562273, 0.45773465, ..., 0.52748649,\n",
+       "         0.47758809, 0.42671061],\n",
+       "        [0.36856905, 0.41450383, 0.45445759, ..., 0.48377584,\n",
+       "         0.4111449 , 0.36218142],\n",
+       "        [0.35718669, 0.42677321, 0.47436382, ..., 0.43942581,\n",
+       "         0.3617547 , 0.32560637],\n",
        "...\n",
-       "        [0.60047027, 0.60373236, 0.60937557, ..., 0.52570707,\n",
-       "         0.55535464, 0.58379885],\n",
-       "        [0.62778389, 0.63385731, 0.64214575, ..., 0.53296695,\n",
-       "         0.56432668, 0.60300261],\n",
-       "        [0.62063501, 0.61368449, 0.61866165, ..., 0.54534635,\n",
-       "         0.57696132, 0.60898905]],\n",
-       "\n",
-       "       [[0.56095996, 0.6143609 , 0.64004203, ..., 0.50187859,\n",
-       "         0.4754496 , 0.50218149],\n",
-       "        [0.61985048, 0.67251172, 0.68152816, ..., 0.500612  ,\n",
-       "         0.49494918, 0.54534882],\n",
-       "        [0.6329144 , 0.68407263, 0.6843784 , ..., 0.47396791,\n",
-       "         0.48464249, 0.54981035],\n",
+       "        [0.60642019, 0.62574808, 0.62237682, ..., 0.46241346,\n",
+       "         0.51060521, 0.56372545],\n",
+       "        [0.58849856, 0.6271481 , 0.63239052, ..., 0.44797544,\n",
+       "         0.48021383, 0.53201329],\n",
+       "        [0.54100755, 0.58573353, 0.59717044, ..., 0.46130668,\n",
+       "         0.46130901, 0.49061944]],\n",
+       "\n",
+       "       [[0.53729698, 0.52857762, 0.51383054, ..., 0.41468917,\n",
+       "         0.46738022, 0.5187807 ],\n",
+       "        [0.50018455, 0.53593744, 0.54907511, ..., 0.39134667,\n",
+       "         0.41190293, 0.45472288],\n",
+       "        [0.50622026, 0.57975014, 0.61671331, ..., 0.40862194,\n",
+       "         0.40055473, 0.43683165],\n",
        "        ...,\n",
-       "        [0.39009849, 0.4203935 , 0.44261993, ..., 0.42716515,\n",
-       "         0.38034792, 0.36774248],\n",
-       "        [0.41016413, 0.44657908, 0.48000503, ..., 0.44284947,\n",
-       "         0.39648523, 0.38594168],\n",
-       "        [0.47716668, 0.52459963, 0.56103944, ..., 0.47665114,\n",
-       "         0.43523139, 0.43823365]]])\n",
-       "Dimensions without coordinates: time, y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>time</span>: 10</li><li><span>y</span>: 128</li><li><span>x</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d9bed4db-ef1e-4e83-a966-dcc35ada7539' class='xr-array-in' type='checkbox' checked><label for='section-d9bed4db-ef1e-4e83-a966-dcc35ada7539' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.5781 0.5716 0.5361 0.4953 0.4609 ... 0.5391 0.4767 0.4352 0.4382</span></div><div class='xr-array-data'><pre>array([[[0.57808346, 0.57159167, 0.53605723, ..., 0.42380628,\n",
-       "         0.47128317, 0.53832381],\n",
-       "        [0.51796103, 0.5064675 , 0.47607245, ..., 0.41564899,\n",
-       "         0.43997698, 0.48980835],\n",
-       "        [0.47207293, 0.46880608, 0.45562155, ..., 0.41782065,\n",
-       "         0.41604955, 0.4486439 ],\n",
+       "        [0.57293942, 0.51371839, 0.51298786, ..., 0.50467932,\n",
+       "         0.57709032, 0.61065355],\n",
+       "        [0.60624125, 0.55069431, 0.53122392, ..., 0.49139126,\n",
+       "         0.57548905, 0.62723903],\n",
+       "        [0.58699326, 0.54542774, 0.51721811, ..., 0.45694501,\n",
+       "         0.53387825, 0.59084717]]])\n",
+       "Dimensions without coordinates: time, y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>time</span>: 10</li><li><span>y</span>: 128</li><li><span>x</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b638c5fb-eff6-4711-b2bb-8dde43d4502c' class='xr-array-in' type='checkbox' checked><label for='section-b638c5fb-eff6-4711-b2bb-8dde43d4502c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.5481 0.5188 0.4551 0.4015 0.397 ... 0.4291 0.4569 0.5339 0.5908</span></div><div class='xr-array-data'><pre>array([[[0.54809688, 0.51879934, 0.45514536, ..., 0.54077783,\n",
+       "         0.54456105, 0.54726763],\n",
+       "        [0.51027425, 0.50829846, 0.47952886, ..., 0.50617368,\n",
+       "         0.49433087, 0.49501071],\n",
+       "        [0.46562662, 0.48901278, 0.49296147, ..., 0.48759978,\n",
+       "         0.45046558, 0.44113049],\n",
        "        ...,\n",
-       "        [0.61990063, 0.60268694, 0.56123414, ..., 0.53148674,\n",
-       "         0.56269448, 0.60187529],\n",
-       "        [0.63107469, 0.62990889, 0.59892897, ..., 0.49414191,\n",
-       "         0.53835709, 0.59487888],\n",
-       "        [0.62020502, 0.62145745, 0.5897504 , ..., 0.45245432,\n",
-       "         0.50589834, 0.57520595]],\n",
-       "\n",
-       "       [[0.59323122, 0.63647222, 0.62798396, ..., 0.44635778,\n",
-       "         0.46106912, 0.52004527],\n",
-       "        [0.55492442, 0.60076614, 0.59340881, ..., 0.41582369,\n",
-       "         0.41842523, 0.4777155 ],\n",
-       "        [0.51070179, 0.56796719, 0.57598255, ..., 0.38093767,\n",
-       "         0.37107501, 0.428035  ],\n",
+       "        [0.45416375, 0.50135563, 0.50022922, ..., 0.5021761 ,\n",
+       "         0.43741638, 0.41562048],\n",
+       "        [0.50440694, 0.50890034, 0.46730875, ..., 0.5304542 ,\n",
+       "         0.49895897, 0.4870923 ],\n",
+       "        [0.54747542, 0.51843947, 0.44854823, ..., 0.55195339,\n",
+       "         0.54888113, 0.54681858]],\n",
+       "\n",
+       "       [[0.40788693, 0.42562273, 0.45773465, ..., 0.52748649,\n",
+       "         0.47758809, 0.42671061],\n",
+       "        [0.36856905, 0.41450383, 0.45445759, ..., 0.48377584,\n",
+       "         0.4111449 , 0.36218142],\n",
+       "        [0.35718669, 0.42677321, 0.47436382, ..., 0.43942581,\n",
+       "         0.3617547 , 0.32560637],\n",
        "...\n",
-       "        [0.60047027, 0.60373236, 0.60937557, ..., 0.52570707,\n",
-       "         0.55535464, 0.58379885],\n",
-       "        [0.62778389, 0.63385731, 0.64214575, ..., 0.53296695,\n",
-       "         0.56432668, 0.60300261],\n",
-       "        [0.62063501, 0.61368449, 0.61866165, ..., 0.54534635,\n",
-       "         0.57696132, 0.60898905]],\n",
-       "\n",
-       "       [[0.56095996, 0.6143609 , 0.64004203, ..., 0.50187859,\n",
-       "         0.4754496 , 0.50218149],\n",
-       "        [0.61985048, 0.67251172, 0.68152816, ..., 0.500612  ,\n",
-       "         0.49494918, 0.54534882],\n",
-       "        [0.6329144 , 0.68407263, 0.6843784 , ..., 0.47396791,\n",
-       "         0.48464249, 0.54981035],\n",
+       "        [0.60642019, 0.62574808, 0.62237682, ..., 0.46241346,\n",
+       "         0.51060521, 0.56372545],\n",
+       "        [0.58849856, 0.6271481 , 0.63239052, ..., 0.44797544,\n",
+       "         0.48021383, 0.53201329],\n",
+       "        [0.54100755, 0.58573353, 0.59717044, ..., 0.46130668,\n",
+       "         0.46130901, 0.49061944]],\n",
+       "\n",
+       "       [[0.53729698, 0.52857762, 0.51383054, ..., 0.41468917,\n",
+       "         0.46738022, 0.5187807 ],\n",
+       "        [0.50018455, 0.53593744, 0.54907511, ..., 0.39134667,\n",
+       "         0.41190293, 0.45472288],\n",
+       "        [0.50622026, 0.57975014, 0.61671331, ..., 0.40862194,\n",
+       "         0.40055473, 0.43683165],\n",
        "        ...,\n",
-       "        [0.39009849, 0.4203935 , 0.44261993, ..., 0.42716515,\n",
-       "         0.38034792, 0.36774248],\n",
-       "        [0.41016413, 0.44657908, 0.48000503, ..., 0.44284947,\n",
-       "         0.39648523, 0.38594168],\n",
-       "        [0.47716668, 0.52459963, 0.56103944, ..., 0.47665114,\n",
-       "         0.43523139, 0.43823365]]])</pre></div></div></li><li class='xr-section-item'><input id='section-17811672-a091-45ff-ac18-9cbdc2a2c631' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-17811672-a091-45ff-ac18-9cbdc2a2c631' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-dfc16dbb-6af3-40d7-9ceb-6eff85980953' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dfc16dbb-6af3-40d7-9ceb-6eff85980953' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "        [0.57293942, 0.51371839, 0.51298786, ..., 0.50467932,\n",
+       "         0.57709032, 0.61065355],\n",
+       "        [0.60624125, 0.55069431, 0.53122392, ..., 0.49139126,\n",
+       "         0.57548905, 0.62723903],\n",
+       "        [0.58699326, 0.54542774, 0.51721811, ..., 0.45694501,\n",
+       "         0.53387825, 0.59084717]]])</pre></div></div></li><li class='xr-section-item'><input id='section-3cbe5bf9-5893-4d9b-8691-53f15f6f33bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3cbe5bf9-5893-4d9b-8691-53f15f6f33bc' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-bc304e87-4015-4a78-8ad8-840c24c878ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bc304e87-4015-4a78-8ad8-840c24c878ea' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (time: 10, y: 128, x: 256)>\n",
-       "array([[[0.57808346, 0.57159167, 0.53605723, ..., 0.42380628,\n",
-       "         0.47128317, 0.53832381],\n",
-       "        [0.51796103, 0.5064675 , 0.47607245, ..., 0.41564899,\n",
-       "         0.43997698, 0.48980835],\n",
-       "        [0.47207293, 0.46880608, 0.45562155, ..., 0.41782065,\n",
-       "         0.41604955, 0.4486439 ],\n",
+       "array([[[0.54809688, 0.51879934, 0.45514536, ..., 0.54077783,\n",
+       "         0.54456105, 0.54726763],\n",
+       "        [0.51027425, 0.50829846, 0.47952886, ..., 0.50617368,\n",
+       "         0.49433087, 0.49501071],\n",
+       "        [0.46562662, 0.48901278, 0.49296147, ..., 0.48759978,\n",
+       "         0.45046558, 0.44113049],\n",
        "        ...,\n",
-       "        [0.61990063, 0.60268694, 0.56123414, ..., 0.53148674,\n",
-       "         0.56269448, 0.60187529],\n",
-       "        [0.63107469, 0.62990889, 0.59892897, ..., 0.49414191,\n",
-       "         0.53835709, 0.59487888],\n",
-       "        [0.62020502, 0.62145745, 0.5897504 , ..., 0.45245432,\n",
-       "         0.50589834, 0.57520595]],\n",
-       "\n",
-       "       [[0.59323122, 0.63647222, 0.62798396, ..., 0.44635778,\n",
-       "         0.46106912, 0.52004527],\n",
-       "        [0.55492442, 0.60076614, 0.59340881, ..., 0.41582369,\n",
-       "         0.41842523, 0.4777155 ],\n",
-       "        [0.51070179, 0.56796719, 0.57598255, ..., 0.38093767,\n",
-       "         0.37107501, 0.428035  ],\n",
+       "        [0.45416375, 0.50135563, 0.50022922, ..., 0.5021761 ,\n",
+       "         0.43741638, 0.41562048],\n",
+       "        [0.50440694, 0.50890034, 0.46730875, ..., 0.5304542 ,\n",
+       "         0.49895897, 0.4870923 ],\n",
+       "        [0.54747542, 0.51843947, 0.44854823, ..., 0.55195339,\n",
+       "         0.54888113, 0.54681858]],\n",
+       "\n",
+       "       [[0.40788693, 0.42562273, 0.45773465, ..., 0.52748649,\n",
+       "         0.47758809, 0.42671061],\n",
+       "        [0.36856905, 0.41450383, 0.45445759, ..., 0.48377584,\n",
+       "         0.4111449 , 0.36218142],\n",
+       "        [0.35718669, 0.42677321, 0.47436382, ..., 0.43942581,\n",
+       "         0.3617547 , 0.32560637],\n",
        "...\n",
-       "        [0.60047027, 0.60373236, 0.60937557, ..., 0.52570707,\n",
-       "         0.55535464, 0.58379885],\n",
-       "        [0.62778389, 0.63385731, 0.64214575, ..., 0.53296695,\n",
-       "         0.56432668, 0.60300261],\n",
-       "        [0.62063501, 0.61368449, 0.61866165, ..., 0.54534635,\n",
-       "         0.57696132, 0.60898905]],\n",
-       "\n",
-       "       [[0.56095996, 0.6143609 , 0.64004203, ..., 0.50187859,\n",
-       "         0.4754496 , 0.50218149],\n",
-       "        [0.61985048, 0.67251172, 0.68152816, ..., 0.500612  ,\n",
-       "         0.49494918, 0.54534882],\n",
-       "        [0.6329144 , 0.68407263, 0.6843784 , ..., 0.47396791,\n",
-       "         0.48464249, 0.54981035],\n",
+       "        [0.60642019, 0.62574808, 0.62237682, ..., 0.46241346,\n",
+       "         0.51060521, 0.56372545],\n",
+       "        [0.58849856, 0.6271481 , 0.63239052, ..., 0.44797544,\n",
+       "         0.48021383, 0.53201329],\n",
+       "        [0.54100755, 0.58573353, 0.59717044, ..., 0.46130668,\n",
+       "         0.46130901, 0.49061944]],\n",
+       "\n",
+       "       [[0.53729698, 0.52857762, 0.51383054, ..., 0.41468917,\n",
+       "         0.46738022, 0.5187807 ],\n",
+       "        [0.50018455, 0.53593744, 0.54907511, ..., 0.39134667,\n",
+       "         0.41190293, 0.45472288],\n",
+       "        [0.50622026, 0.57975014, 0.61671331, ..., 0.40862194,\n",
+       "         0.40055473, 0.43683165],\n",
        "        ...,\n",
-       "        [0.39009849, 0.4203935 , 0.44261993, ..., 0.42716515,\n",
-       "         0.38034792, 0.36774248],\n",
-       "        [0.41016413, 0.44657908, 0.48000503, ..., 0.44284947,\n",
-       "         0.39648523, 0.38594168],\n",
-       "        [0.47716668, 0.52459963, 0.56103944, ..., 0.47665114,\n",
-       "         0.43523139, 0.43823365]]])\n",
+       "        [0.57293942, 0.51371839, 0.51298786, ..., 0.50467932,\n",
+       "         0.57709032, 0.61065355],\n",
+       "        [0.60624125, 0.55069431, 0.53122392, ..., 0.49139126,\n",
+       "         0.57548905, 0.62723903],\n",
+       "        [0.58699326, 0.54542774, 0.51721811, ..., 0.45694501,\n",
+       "         0.53387825, 0.59084717]]])\n",
        "Dimensions without coordinates: time, y, x"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1401,22 +1417,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x2ba7ed13d450>"
+       "<matplotlib.collections.QuadMesh at 0x2b26e26e7990>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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pz6A7S8RpQFl5v3hHgY0K9nLeNRKpp0GhssSQBTIrnHxtI9Oy40G5pTQDt23Jo6sTLrZTfDRUtuO6nqBb2eEqlZhmsv2t7MDj3DOM9ZY0cs1jVGz6HKenaJXwSR/6MaQWldPscqE8eqknxeXAa6dSkwL4xdbRrSbEkQIaouYr7St8hVf465df4PGTJeys7AgGRb6SGgRAyIR3DhB6Q0iGeszfv0gcI/SPEJOyw59ohiJjiOrQ8JEGjdlr7FZjurH6vfC8Nl/xmrsB4HG/ZL2XSW8adWg4Ymy06QZLt3PoWrjD0QBBs+1z3mfJalUxvYHJBwN6SJjeYXqFn6hnBcRlgGkgRKnyF8uWM1eTqUCbhNdb2YHKDXR9Rqozyqea6gm4sXjnx7qabRP5KpDtxu14SPjKEpyRyWwk9bOrC97anlKXDq0SmsR5VcM9WBclfZtJqDE29QSkEQmlMM34Xg30nWbien5gcUHtczZNTnfhsI3CtBCzjCsnN681gSIf2J4M1GQMM4XdKcwgN1q/lOPGk4HFvCG3gW2Tk3qDbjW6H1MICWwWmOQ9S9cwNS2boRgbfmQB1n3CNIrdruCxTuhx0Wh7S+iNrGsO+qls27ulPEiSGR9iRZDrvDeYvZbXSs+uzVntKsLjksWbmuqpLJbBKZK2XJzMWLiWiJJFcZBGtm5V8PXyjBP3WeJIm/pHm9fY7QpMLywX0yj6XUadIHoN48LTLxKhkN8hSbqFIlDmPdZErk8yulOH9pI2aM+gvR/hpCcvB7RKxKTwWSSWsvjqQ2OQIu0y7JjeaWtDW+WkoFAK9s5x3U142sx45/EZ2TsFXsFP3VaYaiDc5OQ3mmSh2eU8mc4AGIKhvS2orhXZTh6IQ1AMg+FiO+O6nhwWcqMTRkU6LNumIDUWHSDmws8v5h0Pqy1j6x5FPrCrIihNmgQyE7gY5jxtZ7xzfYq+dZhGGFBESaPFDJJVJAuqV+ibTNhaCYYTwzZ7cQt6AoZPcA79I2v9V0r9WaXUhVLq55977f+glPpFpdTPKqX+H0qp5XM/+xNKqTeUUr+klPqDH9V5HXHEEUf8WpFIhA/59XHgo4zQ/xzw7wF/4bnX/hrwJ1JKXin1vwf+BPDHlVJfAn4M+E3Ay8D/Wyn1xZR+dcJnpiNfPLlkNSlphrETcdyC7wfH7a6i3eSonRVa1bTHqsib3X3+UfgMf/3pFxg+kFC6WiFP9JlENj5oQpQCZ7KJfg6xilQnexZ5K5IAvWzt7d6j20Cea6K1dFE6Cu+gTCQpoZV164KfevIZbvuKadayGUo2fU5uPJkNtAFsDfk6YttIyCWVkrREpyokdC/DooaAzjTRWYapwpeS9vG3OW/Fcx6XcyZ5z/mk5uVqzeem19wuJ7xfz7naTGlrRxo0Ko3nq4QHDGAG6Jaa3hsqM1CZgZNJw/vTKUNtJJ3lFX2dcZNV5M7TjZIE0UX6uSbkCuWFazycyDlX84bTao9Wic4bGheJTnjNyiv03tDrnBsF79gTfNLcdBWxN0QH3UIxTGQ8QmNZx+rAj1Y6okwiZpLmEo40DItIWgxkpWdSddyb7LA68nQ34/ZmQuwMKmj2N0J9LZ8oihuhXgKoIF2f9SbnkVuybxzqIqe8kIL3sLasmyV/s3F8/fSMyg48qWfE1kqqY6IIlbTFx85Arw+8fEximEvhWYWRSmkSzgROqz3pXHHTLYjGohJ0Z4HypZpXT1ZUdsBHTR9HeQjjcTrgxyLx+9sFF8MSe2FwK0jWEHIjHacZNI3my+EhwRuydwrmbyVUgP0mY5hmFDXkt5KuTCrn/XZsfOw103c1i7cjekjsXjH0S82wc/hVjt4LVz+U0ilcTHoyG2T34qLsWpNCn3S8dnrL/XzL1heH+yVpSTvZSc95UWNVYB8cvjeSYrRyjVVQhFzIDndpKbeRa2Jb2RmGUmPNC6QZJgif3AD9o4vQU0p/E7j5ptf+q5TSWDrn7wKvjt//EeAvpZS6lNJbwBvAj35U53bEEUcc8WvBnczQh/n6OPBx5tD/p8B/On7/CrLA3+G98bVfBqXUjwM/DrB4qeQHpk95rz3hspXuSqsizgQqO2B05BLogBQUKWre3S7ZDT/IRT3l8t1TqsfyTHMbKahqrwhRSXSOCF+lk4gtPQ+XG764uOQ0q/na7j6Mka2vLMZqQqkPke4dJU53mjhqg7iV0P72T075mdly1OWIuEnPrBpD41HoKBQKXxq6paJfSERl94ryMmM2RgjuYo9pPcq7gyiW6cBcGuJtSVsU7KeB+p6juj/wfZNLMhW5aiv6zqJvnHQsjuJGdw0uIPQ+PSgRPouaTEemrsOetHSpeFYs6zTdOqfXObQau9OHblPp1kuEIqGmUvSalx3TrKePBmsixgVCYYi9wTZg95q00gwzy7s7x+V8SkrSaesnsNdCQUxZwuwMbCxhzEcz8xgXpNEGnhPCStjCs5zueXm24TPVLUPS1IPjJk0xtUE3GttAtoGslkJfP5M54EtFdECn2dxOMFcZs7cVkycR7RPDRNOuNM12ypv3C+x0OHRHhkUguIgtB6xO9LWTzs/ts45cP0mEMoq2T1TgpUt1XrTM85bdSU4fShECWww8XGz4wfkFZ25HGzPqscgytw0L2xzula+4h6x2JagMt5MaTDQyx0KuMJ2hHSYQIb8R6p9K8nm1h2wH1WWQukZr6G7GZrkBZo8Ck3drktUM0wlNrUjKkt8qyqdghkR7Yti/omnOFb6UOM4UHjPpKfKBB7MtX5hfMjUdT9o5AE2bicaLTjjnOXF7Cj0QkzTehXKkadpE6jXeS1exGsNE5Z9Rl++Krp8/vQbgkPv9dUERvkEd7ZOFj2VBV0r9bwEP/Cff6d+mlH4C+AmA13/zNLUx463tKe/dLhlaizKJquwp3UA7WPp9htpZTK+Ie8Pj5pTHZgm1Jb80jFpWB0E4kiz+MUiFXttIlgVeXq750uIpD/M1F/2Mx7s5amdQCfqFJWaK5lQxTKUgd6empz2ojcHuFflK2s5REI0GpfEFdOcZ1/cd2snN4yvY31MMc2he8SwebJkVHTe7ipt3ZoCkl05qh+oD+m4PmKT7Tg3yeaJVhJ1l76d8BVgtCmJSvH+zhCcF1WNhCMRMFhbdP+sU9RWESuQBLroZbci42VcoBVSBmKQTN9voA9ffdLII6EEW82EGg4NYRqpK7rJZLu3ojc9o+0wWPiODn23lwUqSdvBmyGgS6DyAi3Rn4SBspgeFu9Gj0JrcYK0xJCtjqHvI9vKgGmYa31r6yuCjZhccm6HkyWqOeeqoHivcVhY8PSRJ5zhFP9WHsYgOEa/aWIqnivm7nvKDBjQM8xzTW1TUqGDpT7Q8rE1CTweWiz1nVU3jM95rTrG1orwY512UNFJ3Yoh5Ap2IraapHdd2QmFHWYuJB6/RNtIHSxMzwphaaWLGdTchphNO85oHudCj5rZlOW24mk8YJsJi0kHG927h060snlI81iQjReSYPVsYs1qiEz1y6ZOW8465JWaaaOThme0UxRXM3x0wXcD0Ob5StC6jH/9WZQk77ZgV8mBvQsYb/T1+6eY+AOGiJL9V+EoUM7dDQR8t720WhM6SsogpPTYL9E1GHDIGQEU1TnqFnozz73zgc69d8jtP3wTgJ7/TxeZbQIqixwX9AKXU/xj4HwC/Pz1zqH4feO25X3t1fO2II4444hMD4aEfF3QAlFJ/CPjfAL8npbR/7kc/CfzflFL/J6Qo+gXg73274zXR8dcff4HHj05xV5asl7TJdunYVZ40GMyNJb8ZaXZWEQqhYakgEcidxkhwYxQGqFYzmOwg+JySYtMWvGnO+Or2Hu9cn9K9P2Hyriarn9PWuA9+NhZ8Ro6yHjhQ15IWYTDtwe0S+TqiItRrw9Y7hnMPBvplol9CuNfzw59/xD937x/xfe6CX+xe4j+Z/ygfdC8DYNuSfB3oFppwF0X6kY14J3seIFsb9mnK19elRDBrS3kx7hi6hC8VQwW+FF40QHcC6azDqMRb6zOuNxP6dY7qNDqIRo3bPNtxhOwZ9/+uJyA66Qp1i44Hc4kaz4ua3ZBzW1fU65LUS4ejinKs8mrccShLe6bQLrBc7DEq0g4ZbTdKAF9k5CvItolu1Djvzp5pfj+/Q7J7RdxkbEzFe8C6F70X/96E+duK2XteotAIIdf4iZHux7t5O6ak9KBRg0T+WR3Q3UCsHDGT1Jv28hlMI2LdySXIIbeepbsTPZFdUb6+SwslktJEB4OG6ERbNnrDvnEEpzE64aoB3xvioHlyvWDTFCyqBq2SSB+vShEMm3heerAC4PX5DSflnqv7Lfu+wE+U7N7G6zPMR90Tm0hGM0wlteTnYdQjN2hvKJzw5Pv5KAc8geaeIXu1QgWR+vWlXPvxI5LUKD0cZBdgGhF+ixa6peHJYNi2OUqdsm9y/FOhD1ePNPlGdgm724KfK16i6y3Nkwl2p/HTSLb0lPlAjAqfWdlR6yj00ztd9jxwdr7ji4tLzAtmnMTfiBG6UuovAr8XOFdKvQf8SYTVkgN/TckF/7sppX81pfRlpdRfBn4BScX8a9+O4XLEEUcc8d3Gb9gIPaX0R7/Fy//Rr/L7/w7w73wn77HuSy6/fI/ZY0U25oK7pVCVkrLo2lBcKYpr0EMiZgpfjE1GuRRN+pMxCldSEFURbK0JQY1yuInQGi4by2VaSnT7RHHvSSJfB5KC5ky0SoYzj6kGojfEnYSId80nKCS/bu/ymIrqaSTbDiSV054Z+ntgFz1xIgWgV+6t+dGTt/i91dd53c74fPZVnj5Y8H/9fikg3fgpbm0ZpjAshBanG43O5H2SSehBCkbuxpDWck5m1J5JhrFrVDoUh9kYnQHuvOHlkw1GRR6vFgyXBfmtOajkCbUyHYqCcSljeie5O8wSw5mnXLY8XGz43FwKU3PbsupLdtsCfZMdDA6ik+ujEuhOio3RwXzR8I/de59l1rAaSt7anPHucIqK2aHT8zCHTCLPPYNO9Et7MMxAiTxy2GZsqGhaR7fJqa4U1WUkvx2kSWti8ZWWIqg9bNAkyhxkzFSUjs5hYkgPpvQLy/6elpqDe2aYogdF8oqoM3bTnF3h2PVSOL7LTYN0+d6NWdJCyUtZQiGdlzEpKtczyXu2bU69KknXGXtfsHNzKQ7vNZNLha1hmBke+1MApq7jfrljd77mfa8JRYZpZD4mm/BTUYrUNhIqQ/Aa5QLVpEMpqMuSmDm6kzG3fioDEs96jAvUrZWuTQCb0J2iazR1bzGd1AZiLnRM2ZUAEfq9oetKNpVsifXeUFzLIlncSi3DFwq7MazSHLMxzB7Ltaxf0Shg4nq63uJVkuuCIoJoD2URW3ihprYz3t+PQkL8l9/J8vItkVCET7Bz56e+U/SII4444ruJ35Apl+8KGs38DVGrixkMlWKYJuIkoGw6aFpEO+bP8zEqdRKN9vc8biHemCQYbu8s7KTJJRSJlEHyoJsMt1JUj2H6gSe/6SElhrlDhCWA0adRfCbvcujPKFUhBz+LI8tA018bTB+JmZybmQycLnYHj1SAD9oTftq9ymV2xSYuMSry2uktAO98QbFrsmf+lnuLGhLBCF1QLO40WSc1BJI0+UQ7aoY4Do0/vgK/9Mwe7gD4zfcf81p5y2qo2HU5TV4QszFC7yDfJNw2ikKglRxqEPE9Qp6IZwNn51temm64X2655+S4EU3rLWlvcVuJdvsiEqaJ7tTQrjRlfKaSaHTkzO25n20AyEZta5WemXDc1T7IErkbKPKBzX1FUzpUL1G/+FyKJEQfM1SrRTffwDCxxFzTnGr6uTpIENylXmMueeOYJ0iJbqnZvWIhSa2hO0mSL7/z3EyjZZ2HwWq63rLtc3Ztjm5GZtRk1LaZjNIEE9mloOVL6YTW4jE7L1rmrsPZinpTkG3EHjApRRibavJbcNuI9pp2K3On8RkT03O/2nE1mdDVltQnYGwkG3WLjIno4lnr/bToMDpiTWBrS+ozYY+VC6kDvHqyYulartqKp5sZXetICeKgaVRGtKJDdOeJqhIHn1h9x67pldQL7jx979hVhdyrvhxf6zXZbjTTSIj+f1JkWnRpmpHxpAeIgyKIIgDeWFZ1yWYv+vUvCglFfzCE/eThU72g3xUXhTOs6M4g3B9YnNQolVirCU10UuzJRu/COyGhuef+gzVfPL0EoA+WL7sHNP1M+OJeNE5SPhaNgsK0CreNoqUSk+hHaNA+YVqRLo1BwfCMi62eM1lONh2O13eK/T1NMo5+JtxqpUUUrO0zutpRrwsu11N+avpZFkWDHaVA70yR7y13hLmmHSx1XRBGSloyo0iRQm6iTrRZxmcNseQgDqW70ZhY6nhMC3nAff/kkh8qP+DSz2iCUORu3JR4m6G9JmSKkCt8qehnkr6641Enm3BVz73JjtN8T0yay17EwtqQsW5LKa4OYwOGBjUd6BLUjUElWfTcBq4vZ/yMe42TouG2LXm8nhPrDOKYOotjagzEYzMpZkVLdhKoK0fXZYTOQjt2/UaFSvLATQa6mcYXim6paM9hmEVZgHp1ECoLpaQmssLje0NrHL4yInQ2mikQgVbMmHWnMHeicHfFcZUYvDmkWwaRRZH3XEgRUg1STI9Kk7KI1okyG5i7jqXbC+V0pLbaRq71XddnyMH7Ucp2jCB7b6mDYzc4htaiWy1Svnfj5RWhsUSv0Vkky6Vb2eiIVZFp3mOWiW5iMTqyrITjvnQtVothhdEJY0ePUxfogWEQQxkpEI/zzj3T8+nniXA+kM/lwdE2js7KopuMpIT6k0Q67zAm0YecbNRkUgGGztD6sWptR42eO5/eUXuNoOh3DjpNdv3iljl5Lh1TLkccccQR3xP4DVkU/a4g3cniitt8f2/g/N6GL55c4nTg3WrJ48mCobdY58lNJARNjIpp1fGbzx/zj8/fBiQvFlH8gzrHd7m4iIM4rpsoHpRatoPDzMLUkozQuVQSuppu9MGj9C4KumvaQY1byDjS0nIR5EdJVKU99Nc561WObjVup8ZoLmdtp9zkEimmacDNJYqeVS1GJfrB4vcW02uRii0jVEFkU5N+1jFpx2iuSOImbxJ67O7Ug5z/vpfIZ0gGQ2SmWx4UW66mE3zQbPwUv5UiIEozTMBPpZinh9HXMZdI2UfNVTdh2+f4YA7jvGvuojG5hniRc+Wko/EFKmrytXSu2sc5b/UPeNvGZxFwEGW9UHBweAfpyu0GSzYJzCYdE9dza0t2qcR7SX2pQTxe73ZQfgK9VTQPE7zcMpu0tH1GX4vvKsByueel2QZN4rqZcJNXDAu5dRSSxqEWWt7d9v8QQY/qh7nxBwXCaJ7Z+Q2LABMPnUHvtKh1VolYKXI3MHUdhRkOJh7GRNltZvK5ox07It2zAnccO2WbPuOd7QmXmynpJifbqYOfaxyNS1SnYdDEKqCLgdx6rIoM0dB6iw96VNOMh9zxqi/oguV6N6GpHSkqdBYxJqJ0OugO3ekCDTMxS8EmcBE37/jMyYqXJxtiUry9OeXxsJTr0TkplJ8MvPrglpO84evFGXWYU1xKYTTuMm6LUlQ2TZTP45DPVHm0jaJoubfYrRbP3xeElNShoeuTiE/3gn7EEUcc8V1GPEboHx3ummJCmTCV5+Xphh+aPmFh97xUrPl6cY+brsTqiNOBvc9ofUZhB2mNNtLfNNMNX5o95t3TJZe7DO3FgJnaEDN9oHuFXNGcmVEjW6Ikof+NhchpAJ3wY7OL8hIR6tF2SzcaOiVaKOpZBG/3oEdHed0JNdB0I10uJYJTDFNNd6rpRuWfFJWYcWxzzNbK+U0j9qQlzz1N7YiZlaLeGNEO00SsJJKxWRQt9ZCJ0mGv2I/R8+N2wak9Z+1L3qrPuKontJ1E7yFPYqqc3xVD0y+TeQuD5nI3ZfBGHObHgqHNPUpBrAJDqzCdvG/oDOWsoz/vaGJOsmKCYHrgxkoxrRuVG+dCuSPJ79xRF02j8L1Fq3QwTFi1JSlKZK47JXrZYxRNlIaoYQbhvOcHXrrgfrHj0W7JB2mBGovNZ1XNa9WKiDrczH1paHvLflNirjLy21FZ8m5HFsdiYFCEoGl8RkySt4/5c4VckyBo9F70XaQBTRFJVG6gsgN777jyUnvwvUFl0gx2937RAs/tvlIpW5beG57czAlPS8qn0hTVLyFMxUQk9kbMrntFyCLWiF5PTIqbfcVuWxB7I7oqkwGjZOKlpNh1jqZ2hH2GShB8JNpI8kIrTGbcPRQSnWf3G6qyo8w8Z2XNZ6c3zG3LVT+lDwZqWYqy3WjDB5zkDd8/u8TqyH+7LfBNPu4kDV3tMFmUuogeCQATTzVrRet9l6N60eR/Tt7m1w0pir6YZXNstPx3AQP8hymlP/1NP/8zwO8b/1sB91NKy1/tmJ/uBX1cENFAVESvaYM9pAsq3TPNWvpoiEnJ1lHL1rH1GU/aBe/lwtl91d1wamtenm24ms5IG5FMNa2kWkwv1Xlfjn6cUw5bS5BFJt3rWC73ZDrQeRnats8YGkvcZtitwbbP+O7KyzHuFoC7os+d0050HH5Pjdt3FUC1kr4YtCNF4fGqQR4oZtFzb7nD6EjfW7xN+EqJpOw8oCrRwbA24jJP5yytV6hgpZN1NFK4aKfE9Arv1Qveuz5h2AmTQemEXwZioVF3jj3j+ScDwSaii+A123VJ2osw2Z1gVtCJvBzIpj1+0KikpRDYWMJkoCh79qeKRrmRCTF2VNbjA9DKw4A8EkIGN89u2GwHdW2p+5zKDrTe0vWW2Fn0XpNt1S93MrKyCLpq4H6x4zyXBb1vMhjH4omZ40zAqkgzZDjrKexAiNKdWVwpipvRI/Nk7JrM7tgc0K9yHscFobVYrw4CWYA82PcKt1LC0+ZZOgZgNzhWbclmVzK0ltQZjJGH0B1DiZFFEjPwk4idyMNMq0S7c1QXmupxIhlhxZBEq4i9IduI21d08lmtjmz7nO2mRF3kuFrYXv25os+loptnMulTEjaY8oo0KGKuRL64jHQnBl8Ke0efdJzNa5yVv/NJc91Nue0r3t2ecP1kQfmBzOnyauxYXlpu2oq6zMUNqvD4iUN3ipiNxiODhp0l22qSSQy5Riko3EBrM0kFebneLwovqiiqlDLAvw/8M4gY4U8rpX4ypfQLh/dK6V9/7vf/F8Bv/3bH/eQmg4444ogjPoEISX2or2+DHwXeSCm9mVLqgb+EyIj/SvijwF/8dgf9VEfoSQs/GDXqSGwy3rk+JSbF/XJHTJrNkNMM2aEgVfc5q7okeM2uc4dCz3ZWkKnANOsoqp62cNidIqufPeGjgW4uXZChGotKXrZ8ajHw8v0Vn5kJR3zVizbF9X7CipK+kZSI3cu5JnO3RR63zHpUwDsoJTIen9FzckzruHTQiWFrIKqx8w/iJDCbtBR2oO5zhlZUJkGiUDOTCBggjhLBRkd0HgjVaF82ju31fsL1fsLl9Qx1mWN7hZ8F3L2G5bQhJMVmV9JvHGYrBUGVRi66HemLjUTGKkrkDqCUcJ+1SaQskpSW3U+rGVqLHR3bh0kglgqVB5RKDC4j3NnFZRGCbKeL20S+ujOiMPTzjMupbONDVPRdBr3GNgq3kWJltNK1e9c1HPOEioqrbsJmKHjveon9ID9E/s16zlc2Ba4csDYwLzsWhdjooZLMjzFCHmbC52fQuLXGtJA/sYSVwUYlKaTnwiiz15hGuihNM+7KRt583TlWdcn+tsRsLTpBzKSg2VuhXiqPWAJ2cg5oyHOJ0DMbaILM4XwjphD9RhNyS1IWt5ZdjUT2msEb+mBohozYWMqNdJ96rwgTQzcWzPPRl1T64IWmmbTsPHTZo0qPzy1+byBLOBfogxELw5GznuUeoyNNnWOvLPlKxsNtheNras3lesrXzDl9sMJzrwJhAnY6YJ2n2+a4laa8kDTVHks3Fe/X6aRlvcjo++wbzGZ+vfgOO0XPlVI/89z/f2JUiwWRB3/03M/eA/6Jb3UQpdRngc8B//W3e8NP9YJ+xBFHHPHdRvzwLJerlNKPvIC3/DHgP/sw+laf6gU9OjHM1b0U19xKE9oJX78ueHPiyQpPnnmKbKB0A0MwrHYl/WWJaTTrMudnx6hj7zPul1txPC96mmkg1BJhmShRXb+A/iTARBop0qBAKygi88WelycbTtyeJmTEJInQMDazAKMSIAQtVDNfifkDNkEY9cW3Ct2B0qMO9ywdaI8gOfRD01J8zkjCRZQVl/TbpmKzKdE3jmwjkVQoFdErBm/wnSF2EvUom8YO0mcdigB15+g6C7cOtx4pfnNYTht+2/n7RBRfsQ94f3eG3SncWs6xXyhCedfAAxjp4k35s0Rm31tCZ9C1wTZjl1+m8L3B54botXTaBgWZQmWRVHlCNmpqDxp7Y5k+gvk7PWY/mmbHgn5hqMuCm9aiRuuxlI1Wfmrs2jVjsW4ZSS7K+PaGN6/O6JsM+27B7O1nZh/dQtFscoaFo5t50onCWS9dq2VgmNmD3V0oI6rypKAJbSZjs0Py18VoiTeTaBnGjtI7g3LGpjAlVMjtpiTVlvzSYhvJLffLJJRUjZg97wyqFrNmoxEtmrHLOLOBpJN08hbPbAyLK9mpuE1Ch0RzOhb8g6b1GT5olEn4KknkbYGoaHdSyR0GUX1MuwxbizFINNAXkBWeedmyczmNKkhBMbSW286SNhnZ2qC8FOfbkUCg8kS3HGnCRonlXZbwg+G6FrpsihpVelzhmU1aQtS0twVuDdXlaKZeKfYPLIUdOC9rntrAVTGlqZ+Tzvx1QsS5Xkim+juRDP8x4F/7MAf9VC/oykbsw4Zhn8FVRnGpKC8VwVm6E0t/5kknHZO8Jzee3lv6bU7xxJCvwJeGZpgA8Etec72YUNgBTcJUA8NMvCbDKMs7nHnMokephK8depQWSEWgzDyFGeij5aqd8nQnrYDbbUloDQyKOBYog0uEWUTPelwunX99k5E6h20gX41yvnbk75aRFIQZo8cOSxhNBszd94q0t9ShIgURNspvFGYvDz7dw9Ab+qhRa4tbj6mQQhYhiohyAedkccwzTwgan6UDm0c6MeX9NElcnXpNVkNxm0ZOuCI6LfVEk4hFItkk5h0jQmdhZ7A7jR1TWr5E0hfjA0V1wo9PG4OfRJh6bOVJEeLKUVzD9LEnu2lAP7vB9ABupfFdRigTatGTLzp6m+g7d2j391VCnXbkhWcYDKG1dE8q8mvD7J3E7NGA7uScs9qhoqEdlJhLqJKLpHCZcJ6HeUL5Z1IPvjNSHHSJUKpDEdZPoL8/MD+vmYwFxptdRWerbzSPSPL5k8/IVob8llHaF3n4m2eyzjooTANundBBegB2p8JUMkYcsboTgLGT0krPhG0Stk2EXCRzk4bQG1b7kpTAVAPhpYCPSnonBg1bWRjTSlyFTCPpHNPKuQ0LhTWRiesldaPk4ZuCAq9wN0aE8nro54rGaNRZh110tGeyFDX7kd9feaqqx5ooDxgdMQ6yLKBJNINBteYgmoaVa5C8JiTN3LU4I12vq6L8tSwv3xIJxfBiWv9/GviCUupzyEL+Y8C/9M2/pJT6QeAE+G8+zEE/1Qv6EUccccR3EynxQhqLUkpeKfXHgL+K0Bb/7Cgj/m8DP5NSujNY+jHEb/lDibp/6hf0Ih8kYr7NyHZQXkeGiWy/eg3OeSauozCe62DQG0t1AeWV/N5dhar1FU9qh6kGjImkqEhFYFggBa9SjBqsDTS7HL2yuI0ahb4U1gSsDgzRcNuVbLcSFYRNhur0IYILRSJMA+5U7MGMFipc8OZAj8xXkeiUdJLahMoCKRnhij8nFytytZIysbVCrwxEI0YLI4f9zlQjlBIlpyg6M24t7zVMoFciK2zzwNlMPPlemWzwSfO17JxNnJOtDdorVruKr+XnaJVY1eWBuqgCZPXYCZlJW2wsouwgdHxG07Nizea9Iu3MoZsyadAuMC079irRaIetpYjsJ5pGGcy0l/HaZePuRDEsS4aZREz7B0KVUx7cWuEHxTDTLKqGUHbctAt0L1M+TCPLRcNZVXPbVNy0M9zKMPkAJh943E3L3XYk5gbbiA6KaRRg6eoJbS5Ca2akmtpGCthES5gH4iTQZYl+KbowaT7w6ku3/K77b/PQrQD4av2Qv6G+j6GeYZtnNFXdSzpP9zyjhDpIVrRm6Ax2a4TuuIJ8I+eS7cyzneNSkU962vuaMDFieBIVdiuCJ8NEegn6xUif3WTsGouyYvN2clozz1u2fc715QyzGVM5W3WQFLZ7mWsyB54xO+5E6hilolVQB1OZbJ9AKYa5Jt5PfPbs5mAA0gbLbpDUzp12kTOOvYkM3pAS7NqctnaYVnYdw1Q6tpMB1Rgu1jNC1ISo2TQ5ff8ilzn1whqLUkp/Bfgr3/Tav/VN//9T38kxP/UL+hFHHHHEdwuJFxOhf1T4VC/oyWv2+5wUpUvQbRNuF+lnlv4kMb+/4+F8M3bbZWxrkR61+4QeIqbXuM2d+IrC1xnD1NLnURRxVRKNizxQlIM0atQOc+EonwpVrF9AHxRWRUoz4KPBPt/J4IXWdUc1DEUaZV6lWDsEQz8Y0uhO7wt1MFgIBVAGssLT9eYgw+ursUlnIrZbZq+xKzHysI1E7NGKeXI/h+48Yh80zKcNuyZnWIkOzfPFVqIiRkU5dlh+/+SC+27DvXzL3/DfTxumKK8Y6ozHZoHWkb61JJsYppITtV3CbUX9Uvdi9xcd+InCj3nfat5wNqmpFzkXZoEenNgDuoTNA8uiobCe96sCMFLs68VQwp8YbBkgSwwzqF8y1A8Ngwg50i+EgmcbMHvJRQ+NIaJwJkARCcWoyFd57k12PCzFGu9GT9EdZLuEbSR3nuxdXlsdLPWSlt2QuZHdXRztDN1W/lYMKxRhAcWypXCDFKK9wZiIMx49auQAnLqawg3UY51Cj9RV7e9MSiBUo5riPGCnAyRFqO1BRtftxvlQyE4rOZl/VdHjTGAFdHlGCpoUFb3T+Jl8tpjJ7kl3GndtML2MYXduGMqeybQnorgeKbowNtONSo/prklq/EpJWuNTUqPerewq0DIfQvHMkjHbwH7t2J86vm92BcDU9myGgvVQsvcZvTKA7Mxab0WJtM1IdSad3Fpks++aN7ONpksT3s9LoVS2+qD186JwNLg44ogjjvgeQEIdDS4+KigvOWqAopbcXLSK9gzcazt+5KV3yVTk/f2CJ5s5w3XBpJaoolsahkodzIClJX+MLHMzqvkl4slANe3IM89qXWE+KJi+C8UqHZQeVVB0weKjIdeeRd5yXUlicdtYUeMbnkVgIQh9cNMW7BtHv82hl9Z20YwW5kH7kufBvQ2ZCTweDDE3opY3lZDDLHqMifSpADS2SbiN0PD6uWaooDtPZC/tee3slmnW8wFzLssSP9EHHe2kQO81Iea8m50A8HK14b7bsMwaoXHaJPnyXtO3Mm3iYCRCn0f0oLGNJl9F3C5Jk5GT8e0HhZ9KVFO5gd968gEAP6Ve50lzRnYrx0lRxjEmhbLxoHdim4RbK/a3jv1goNUEB/uHo+1bdUdPlHM0ncg1kERjfNfkGB1JvT78ns09lR3IjRfVvvTMrs5XhugKopEbd5gZhqnIPYQqojai4Gf3z7R4TCtzaBh15VXlefVkxf1yx6oveff2hHpd8Nb2Po9XC87nIgHog2F9PaWowQzjOY9sITVSPgcztvSftbx8JvoAj8Ip6Uq0f6KF9kTTzRXtPTBz2WVN847ceIao8V7j21HjvQqw7JlMOlzm2e4L+icVdi8SBgB6MGzchLeTaNHQmoMl351RzF3tQ0xNRJkURFFT64h2gajHJrKo8EnRJCNmLo3sRLIby5P5gmUuXVyvVGvq4Hi6n4oOT0IYZHbAuEhKirZxMKpn3tE9iaPuzw5Mp0GNCqIdvKCUt8wdYHhBWi4fBT65Z/ZhoJCUhpfiUcygm2v2L0d+9KUP+G2zR7zdnvOknrF9PKN835CvZaHpltIteJcdsaLRJVs3NWqmBEAlKjd2V24cs/dh/sijfGJ/38rvR8WuzXnczFk6cWK/o6U1kww/KJQ3Uuga9S/6zgpd7iYnv5LioK8SfhLxE0gzz2dfu+J333uLmBR/V7/Ou/4M3xl0KbmXqhQKZZ9n+NLST2U1kQeWojuFeNpzNq85zRt8Gs0xRhOM6O5kWIXHrK8NXS35i78TPseT+zN81NyuJpi9aLfEXBEH6VCl0wfnIF+K+ztJi5hYPvKJR62au+16M4jWzondc1bWPJ3OCWM361BnPElzUpIu08P1CJJGya8McW0OW/5QJvwsHlIMahD+elLPJGXv+MxDsOhGxLxwkKJmNzhimnFZT2Evx/W5Yn/fEjN1cNEJGYfFPBaRMIxFOFFCPujuDEoW/WGemM0bXq7kgdiGTMwtrh35jQLleDIRWmvKEnktjjzpTpto7HxWo3lHzEQf5XTW8KXlE+ajLu27q4dkW33wyu2X4GfhYGC1bgpyG0QCd3wxeeGYu9zz8mLNeVHzpJjx9X1GuM6lsNok4o0iZhn7/QwU32CMMUyFkil0TH0Q4kpaHlC9t1gTycuBEEV+V+uIrwx+Zqgbi9lZbC1j6GvLk1rGQ6vEbnA8Wc8PTkPNpGc5baiyHqsj2kSCkqBBx7FLfOQ3RCOtIUnd3b+80E5RUEc99COOOOKI7wUkvqNO0e86PtULerKJVETYmWfbzhMwD/Z8tromU4En7ZzryxnVI8Ps3US2izTnRoqZ9weRtwX8VlIeoYritdjJ//UoK9oMGabWFLcJuwv0S0t7ougX0jizbxyPzJIbV6FUItzJxdqILwLBK5IWA4q7xpAwUs+Ka4km2nNFW0X0sufh+Ybfc/8N/sDs5xgwRDRNn3F9Oz10nu6bMScRFX6SaO8phplEUr4Cvwi4apDmir5g2xXSQVob2YoC2iDb1QayGux+PHaY8Es7ERYxNxnZWgpPfswfpqBEJyaMlDwrhh3hzhOygliMkbNXh67W9dWUv6tf595kx67P0Vkk5Em8P7eWuM6Edjj6oAYn9MQ7iWEVnxUMhR4pkTlI2ijbqYPxg7+zh0PSQ6ZX6ACpV/R7ywerBUol9qsSd2PG4iy0p4ph8axpy4y2cUQJ/UKRaM+l4Jy07HbuVP18CfF0YFZ09NFy0c24bitRsRyjRts+2xFGMyoCplFbZkxn3GmzRCuRehgkTZdrzyv5LZ+dLnh3fsYwzYWaWo6pn72GpgBgc5UTq4CdeKzzmDzgvYZBMfQWHzUz22Inkc15weXuFLs3qCTn5NaSvrhrSBomY0plImqX0Ss843VQMq/DYGiHMUJ3npTAmkimI856NIkhSgNTvS4klZOlg4fu3mf0QXavNEas5ICNTvhCi+VgAkYtpGikQxYgag7duNGKMFFSsgt6kThG6EccccQR3wNISR0j9I8K2opSYKoNoYQmh+5Uco1NcHylfpk3bs/Rt9IqXj2Vdu5+Vgi9baSAAQSdkRSYyYDNAv0+I3mNvTNu7jIxSIgJPzXUDwz7V8TsVulE6AybUFJnOdaGQ85SqYRxEV9EcZ8zCT0dmEw6ut7icydR2p1GdxmZzlo+M1vx2fyK+2ZPQPFafs2yfJnr1ZS0G1uwOw3CCJOC6slYHFRCgSSPBK+53oq8Qd9lxJUjH1Ukk3hviH7ISD+7MzF2G0jGkozQ9CSCTDAbKKY9Q28JwaFHXZnoEr0TmYBUBrJpz7TsGbyhWReYKzln975jtT7l5mSKmwxonQilJ6XRLmyjRJEyjDllC2H6zBDC7gH/LFLX/bObK9uJOiAJ0uTu0orBdxr0wdhCisCGxkpFWN9muJXsUIKDYQ79SwPYUXd7leFWorMzoImTwPDKgM09znlilEJxaC3KJoppR+8NX7s9Z986wpjDDg9a6mmG2RpsPe7gGuDOSq6Q4qJ6ThtfK2AAu9NsbiveWNwj154+WrSJJMuBsmc6sLfqYLmmoqJfaOrXNPnLPZNZzyoo4trha8tVPeHlasN5vuOLp5fUnaPp5pBGVchx5wajRvs41EnLsVVUJJcIuRTilUnEoOgGi1IDRqcDhVGphFERZwJZCqgx2m9zUUK1o+6OVonCDlRlz7Yz0BlSUHT7THYXiEQBKhHyhJ/c0Y6F3umnCT+XnZlxgcz5w7FfBKQo+kJa/z8SfLoX9LHsnvRzhZpFT0qKn7t9ibp3XF7NyRo1dkxqVEyHBczaSLzrbgvCFQ9kxFxL8ajXBJWxViW+teQefA4hMzQPINzryac9Xe1gb4lJ0gyxGg4SpncLu2zXgSwxmXS8ulzRess7g2E/FOhBMZwGqpM9p5Xsx99q76GRv3+/OxEGiNfYrUxsdys3XiigWybCIkIuK2EaxvPvchpy2RJHxHlpZAeokVERM1kwg3vODGCkESclbB9fQTj13Lu34eXZhk2f8ySf02xzGSudUDaS5YEiH5gWHVPX0QXL+12G9rIi59fgVopmcPT3IZ/2ZKWn9xoVjOjC3CT0IJz87kSJkNk0jnood92aozuPEd69zIOxazXefSlS0MK6aLR0NbayTU86oTPpCL6TKTadiFElDbrwZLkUn7vGQNJjmkTRTuH++YYvnT3lQb7hsp/y9c05l5spMSkyG9g2Bc2qwKwt0SXyl2q+/4F43b6zPuH2iRQBeZIdtHmigzD2GESnnnXQehFki9eOr1X38EnTeUuKo3FJPrpnjQ85t5VjuG3ENpphZggPNdO8oy4c3Vp0iLbbkovZlPN8x0vFhpvTil/c5XR9IZ91LPrezZHDfdfIw5EohWlmHjvOu+cRoqSJYtR0xrI3GTHq8TVZ6LVOojlz57eaFIXxnEz2xKTYb3NSa0mNxQ/innTHgY8uMUykZ+MuZeUXAbvsmE9b5nnLJOsPnZ2/wIvAJ9tT9CM7M6XUn1VKXSilfv65106VUn9NKfW18d+T8XWllPo/K6XeUEr9rFLqhz+q8zriiCOO+LVCiqLqQ319HPgoI/Q/B/x7wF947rV/E/j/pJT+tFLq3xz//8eBfxb4wvj1TwD/Ab+C2PvziEnU1bCJUAZM6bEusNkV3FxPYW/RrRR12jOIxmI6S3cCcSL84370yXTXhvwGotX4iT1EJyE3hIkZ/SGFdx6dyJi6apAIr7ZktwYUDICaJMoxQvdBEwaN3RhMoxiigjNYugabR+qTnKskxcblcs+9yY6YFO9sTnhzdUqefT+58YSo2XU5enR9v4MKo9qcBvJAVnqCl/fUrcY0z4qEMU8HalwQ6rrovOQS8kTHoRv1LmqPLkrRKxO39ofTLa9UK07zDGcCV8WEts8Oxa8iE+MCrRKNz/DhG7enOoDqpfjqe/mZMVFkfJEIurgJ2DowzAzRWekETYqUB8I0EjRycRSSdhhvnq60hNKITZmTLl+s8M+znT7o1/gKmHpevrciJcX7wynxiUOHUYWwEcnXOKZcknmmOGk6xKvSRF4tbnnJrQ5b8BDFJESMNSx2ZcmvpVBtX438psUTzrIt8HlW10IPvdPduZPNDaWkC4IGpaPIxq4t+bXGrRSdrXhLjdK4UY9zIcm11TI/73YqSY+F/Q66JqMuHX4w6F7mxZA53quWTLOeM1fjtBTRu3kmEsh3qRSvUIM6aLVkWzHlSBqSE8ORPBeKYgz6sHOOUdP3Vl4zkQ6LbzPYGVRUxDJgKo8dqZUA266gNVLI1kr469LtqcTasAooGyWtGBUxRdLYLxCqiF12vHq24pXpmtIMdMFy0U6/3VLyHeGT3Cn6kZ1ZSulvAjff9PIfAf78+P2fB/75517/C0nwd4GlUuqlj+rcjjjiiCN+LbjrFP2NGKF/KzxIKT0ev38CPBi//1Z2TK8Aj/kmKKV+HPhxAHO2hE5DHshnPWXeiynzNsfeWmyjxigburNEd4pQwSaB4nzsgFwJxSu/hsXbAZWgW2jRh9B3RTI9dsJJ84yfQFwO5M6z3+eYncZtnhXUymLgtJQ8+LotoTUUF2KB1jWa7bzkaj5hmolGRTnpqVzPw6noijzaLFldTsWRfczL69nAdNoyXzRsR9rj3uVkGyMaMPNAMe1xNtCSEe6KsqM9WjKjebMGrzTJjp+vEj2YZCUKulNzFAqd/EwNCDWyM1zux8hyjMJmriPTkT4YsZZTCR8kxyvqeGKswUgdC07y/tqL7VzfZFgXgCRUM6UwbSRbt2jv8KUmZHJu/cIQziOz5Z5p0aFVwuhIpiWi64JlvS9p2gytRNM9JcX+pnym2R4S7anGTQa+tHxKRHG5npKMw7QRNyTR81lahrGYpkzCTxKmk/GxO8PF7YxfmLzEZT7j0X7Jk9WcfpODicRCEQdN1ovej6/A6MjUSEPQps9hJ1G93XEwr0gGqALVomFa9Djr2XU5t/0cFTXZFkDTmpK+CtIM1alRBz2Rpp64jOymsoUbZga7l91YGjSrTUW4ySmvpPBsGkMdZvxsb1lOZb7GoKEMqHlgPm8oM8+2zanXJepWjnvXsBNKiHPPfNpiTWTfusN9GqOm92JWgpJ6lVIJ31oxSe8VyUrk7jJ/2MnV+/zwN9GLBnu2kbizd5BVA2XR0w+WVjtisuj4rAP2dL7nSydPeK24YecLfnH3kMeb+S9fiX4deBEm0R8VPraiaEopqbtKyHf2dz8B/ARA/tprSe8NMY9kVm7qobPovTjh2D2HAkqoEmkqaZnlrOG1+QqfNDd2XKAi2CYKi6VUhOw5ISL9rBvQTxPhxHN6b8uiaPjAG2GK3LFF8si06DgdW5kbL56W+Qqqi4D2hvbM8Wh6wqTs6AdLZgPnk5q5a3myn7FeVdgLh1uNAlNTTa+AacsrszXMpP37/emC9aoiBU1e9czLFnPXfh00QUHvJA2QiogpvGxTVQaIP2eaeXQWiLmlN+bQ0RmLCHmUVvq9FMH8kPOkN1zkM7SJGCsc/RgVfS9FOnN34/bm0FGaIqhxQR9mitSMTJNWEXYZQymuDmES6RaGbmnRvROpAyWSDqZT2L2ithnD3JCZQKYDVkdOc1mMFllDM3es+pJ2lBC43k9oQjXy7O9sgWSBndhOZAZ0Gv1eI24zEJymW2r21Xh7VJ5YRUJj0BvIttBeFHzZPGRaddSto1vn6NqQtGHojRh07IU1pAIM3nA7VMSkua4nmFYWBZXu0l5S5FM24rJANT7sd+TyoO2f8fBRhlAIb95tRvOSqaaJGfF0gMlYzDWJblBQRmw14DuLuzFMPkgUq4gvNc1a09xOuDwrYOJROmHywGK+53PLG5z2fD2ds/PVoRgNo+DbK3t+y/0Llq7hg/2cpsuIUeG9EfnaQa5fWfW8ulxR2YH3ywUXag6NQVXyMCiz4cDE8qscsxMpaa0TuhHXsDsW1qTqeG2+oo+GD+yCzTCRoA7AJE7KPa8VN9yzW66HGY82S9ZPZ9/pMvMrIiUY4nFBv8NTpdRLKaXHY0rlYnz9O7FjOuKII474WCApl+OCfoefBP5l4E+P//4Xz73+x5RSfwkphq6fS838itAB7E7RZ5aaUmzaaiPC92O6xDbS8aaipgNS4Tkp93x+ekVMmncXIkbVneTs79vxe9HG0P0zPjQjfS/MPNPTPZ9d3DK1Hbsu53Ja4VsjEVYWMfoZ7zWNok9SUIuYThzou31GQgqJ5+Wez02vqczAk/1MaIBR+MWJkZ8+8nvbYKlGidvCerY2EoJI34akscozLTpKN+Dnmra3hKgxOmJ0Yr/PCaOkb0wQg0LloHNPhAONUxnhb9udIb9VqEE4377PSDYjJgg20WVJ/FAbjY7gSylGqiBUQYIi2XTouhyWEV/dGR4ozFYTvILZgF707GMOaNqzUro9R8OKrJYvt1I084IncRSNAmZTSWW8NNswtUKk91FT9znbukCP0XA/lSKin4rgk4+GLlrRjhnvUd0OuI0l2zn0GPnFSknKahSkMp10ZPY7xw7x4hR6nxKjkRtNtoHqMonph9as1wVvbO9hdaQf7FiIhvZs5MYb6WhMg6be54fOyWbv0Ht96ES9i8pjDdlejFqybSCUGrc17B84hsWY3pp6iocNnzm9Ze46fvHyPj7mlDeR6tGOlBncpsA0ln0wtPdALftDdP6Z6oarbspqV5J/kFFejtdwAt1nB/7p17/KP3vyc1z7KX8tfYknG+Gwx6BIfuwmdoH7sy0/cvIur+S3vD0956fdZ7jaTXGZ5/5ESPN3Ebrei2nHXYEXxvsvitBaSjB3LVZF6sGxcwVJj8X1LFIYT0yaSz/jrfqMq5sp7urFLnO/ITtFlVJ/Efi9wLlS6j3gTyIL+V9WSv0rwDvAvzj++l8B/jDwBrAH/icf1XkdccQRR/xacUdb/KTiI1vQU0p/9Ff40e//Fr+b+JCu1t/4h2MjxUqjbpzoX8RRx2QmeVEdFG4lkbrymsY5+nPL3LYs7J7PnJwD8JX7U5Q3JCOUxJglTKswo+RocKLZorTk0USpT6LilEV8JYUcgua2rg6nuG1FMS466Ociw+rLhLYJZwPzsuUHFhf8yPRt9tHxdXeOyQPDcrS/GwugKOh2Oe/400OzUr93qLXF9ApfZKyCZrnYsygaTosGqyKbIee2qWi9pR8MoTW4tSZbQ7KKLlrRmbFJouZRc4VeYfea4koszu7UGVUU2qFp1aGRxHQcOk+7E9HeSEoaUEw3Gi8sRtOIxSDUydZgV6K4pwdFX2jKRQuTnnpWsN9bUhZRWYSdpXwiZhcqgNlY/FYMHkwL+4mM91fO55j5IGp8XhM7g9pZ7F4zTMXww09geLnns9Md5SjSMi07Nosp3YkhG7tw9fCsazb0GtWPxdwwUjrzhCkCVdmjVWKrE0OnKS4N1ePE7L2B/PEWQkKFE/YPHW+fnLKsGpGWPRExnWFioNdiUxhEz2ZoDH2WQCVUa3DNqCCZPzfvw10zVMSte1iBrTPydcb+vlyX3euGl17f8C+89A95JbvlP7e/g7/1lhQI9b4nKYWdZuhgSEqRishs3vB9y2t+0/wDcj3w5u6c/qLk7B2YXEhufveSZY/iteKW1+01fTKHNIS6251GaYkzNrLMWz5XXPID7jH37IaI5pey+/SjGUwb7KELVPdiep3G3Vl0iejlOttas76d8H654F5ZH+6LZBPJRWaTlsJ4LvoZV/2Ur9+eEbeObPhOF5ZfDceUyxFHHHHE9wxelKfoR4FP9YJ+l2O1reTJbS1Uqn4J8UTcAvrgsLUwXuxeosZmyBiSIVOBeSaRkpoPdIM0pJhlT1X0eG8YutGgYoyi9Naw76Z8bVtgXCB0BtWO0blO4BVN7Q6NEkMn1MN+hrAnTkWNb1L2uMwzdR1nWU2hB9ahog0WYwPqtGU66SisZ9Pk7FclamOJt5K/BrCdEmPiAUKu6KyjKQbOqpoTt6cce8o3XUEImq7LUDtLtuUQdYOij+aglXJnGKB7MZIurhFbv+moe50nCArDaIrcj3WKXSJko+FHBO5a1u+aZsYmndm8pXQDq7pk2Bv0SnLIQ6fJbODeZMe+aui9YZp3wozYLlixIF2K0bFp5XpWT6C4jQyV3GD12tKdWUIRISiyTh3a6v004aeiZPnS2YbPTW84yWoq03NvsuNmuaQ9MeS32TNDhHG3ogaF7vXBsDlmEKvAYtrw0myDVZEnKnKxzjEtTB57iq8+xb/zCGUM1exL5DczdptCzMSNUFUBUgVdlxFWOXoru6Kkn6kFKi+NYck+i9DvTCVErkGTrMbUPW4V0UMC5GLuH2hema7571Rf4/PW8P7iTf7GyRfpFhnFsiJlmvolx+4VRfuyZ3Fvx+vLWz47ueHE1lwNMx7v5riVId9ETDvSOAPQan5h9xK5Hvhq/ZBfvL7HfpeLZksWSUroZSkq9j5jFSr2yeFUYG4anAnctBXNkLFvHcNWzrlopfkrjmYwsZDxNi1kO4iXjkfuhO08Z986Ui+mL3Y68NJ8wyxr+aBZ8ub6lNXNBLwokb4oCMvlqOXy0cAk/KknraULkyS+kv7ewOn5lhAV687Q7+2hOzKZRDdYHrcLfDKs+uJwuJgnqDzLRc3DyRZnAnufcVlPubmaorcGt5YbLOSGUIDORplOm0j5qKWiZCEHZNuvxoeMS4SzgcXZDmcCQzSs25Kv7h5wPUx4VJ/w9Ytz+r2jmjd8bnnDWV7z9c0Zb20LTCMpoIPxgksMz1Fs3/6f/6++i4P/PYbf83GfwEeDP/OVPwDAOg4MyaBdoFs49i8X9HPN+vsU4fv3/ODDS+4XO6wO7Lzjy8MrPNovubyakfciTd2cyaLbPACyxM9fPuTnLx+yvpmirzOMF2elOJW+guQ1fdA8KWZ8uXoZQ0KryJN+zpN6xuPLBbEWWq9tn6XvlLRLHAxmYg6xE06/aRX92nEzSErNbMTX1pjINOsZouG93YLryxlqLemzMHmR4lxHC7ojjjjiiO8ZHFMuHxV0wswGvE40xorBwCKwON+xKBpu9hVJJ4ZJEn/LsbDZdZavb874wM75YL0AIDb20FTjTOB+ueXM7VkNJbteFAXtXmF3z1QKJQUxNuGUnnzaU7iBGDV1Pe6PB0nHDGced9ry+ukty7zluqm43E1puoy6c4T4gP2qRN9mKJuIU01leyZGOiIJCt3L7uBuCxnvd5yc1szz9mMZ/iM++fg7t9/HjZ9wnm35mfXrxMHgC2jODe05DK+3/FOvv8UPz99lGwq+snvIV1f3ua1L9usScylR7vZ1GB5Kmmh2uifXke2mhKcFkyeKfCMp0O7E0C+0mEpEKbZvs5K3q1PysQ3569tzHl8t4KLA1epgEgKSQr1Tz4xu7IC1gWTEwlG6mhMEjW5EhjhZRb/PuGwm3KiSq/UUtc6wtRZf4Cy8sPH8DctyOeKII474XsSR5fIRQSnIi57MefxMoxTM84Hcei62M+qbCrsS7YiYCxWRqBg2OY/TApsFup1E0mYnEYDXlvWsYDMtyVTksp1ysZqRXVuyjdTL/AS604RfemzlcTZgbWCS95RuYNeNehRwKJi6k5bf8cojfuv8PbqY8WVeHouVjq639PsMvc4wnWJwCZd5YlJiYbafQGsOlmR3OcHT05ofvv8e31dd/EpDdMRvcPzMm5/hq8tzzic1m7Yg9VoMrSfyVU46XilXnNodN37C43rOBxdLuHVi6lGPNODXWn7PF94A4DdNP+DLu5f5W5vvw60V5XXCbRMxE9qrHhShUEQjphMhaPpgue6m7Lzj3ZsT0lVOvpIC+jBLz2itNtG3Wu5Zl1CTAVd44kwRR4PrMgvEpOijIoy71tQbnq5nKMRs3Azq0BCoXmBAnZLCHxf0jwgK5mXHLBf+aT8WGW+2Ff1lSX4lehehGDnUQfisqTWEkItTTv+M/2pr0N5QZxO+qu8xyRdcrSfw9oTJe8Km6efQniX0K3teO91Q2oFVU7JtCrZNQTtkdL2FWobWNBo/iZzO9vzO5Zv8luIRb/f3eCc7ZZ63OCOTs84CjY0MQTOZt7yyWNOGjPc2C1bXU3Q3bh/zBKVsXWNSPG1mdOHTfRmP+Ohg3i9YN5bm1EnqTotZyZ2RSdc63tmfYoi83ZxxsZ2SaoutR0OQTu6fLPd8cfIUgB+p3iSg+AfTV2nKkqFSzzpZu0S2E3aRryT4MVnEjffnRT2lvSkpbuX4vgRfJbKRl++cp20cfpehwmhQEhXOeUwhxc/CikTzLu/ZFqU4RenE0I73QVKEIqKcktTPC3QsgmPK5YgjjjjiewLHHPpHCEViUTR8cXbJMtvztJvzs21Jt8nJbwy2Fg6rL8V/ULrQxB8zOgWTJDRDIBYa9hI1xGvLNszY6kR2bZm9A9XTQMwU/UwTXWJWdTyodmgSN01Fu8uh07TZyNUdxouuhM54VtbcsyKP+9TPuWhm1L3DmshJ0fDKbI27H1hkDaeupgkZ/+3Nq1w+WWKvrHQKziJ63pONRZ7ttuTnLqeSjoEPYQlyxG80lJfQRktncrJpj8oifhpRSVKBfpfxlesH3HQV67ak64SHLylKhdpLf8futuDnty8D8Kq7oVCelxdrfulBRTM4ohWfWu0TuudgiYdJWOcPO9F96zBbc1CJjA6hJo6c/66zhLWjuBilf52hX2bUc49yEaUT+9wzm7SclA2LsmXTFjRdRvCaFLXoElkt5jOILtGLxIta0JVSfwj4dwED/IcppT/9LX7nXwT+FPIs+UcppX/pVzvmp3pBP+KII474buJF8dCVUgb494F/BvF/+Gml1E+mlH7hud/5AvAngH8ypXSrlLr/7Y77qV7QU1L4qJnYjlNbc9lPqTuHrqWA2C9hWAbMsscA4ToXrZJRI91Vw8EqbmNLenLsRmN6ULcG5aG4geI6YptIn0kkrL1iVxc8yWc440XYvxXLtwiQB+JkLPIYjXKBiOKd/oy3unv8nevP80tP7uP3GSqLdCeWL5xc8dsW7/Kl4gMy5fnb2y9ysZ7hPhBH+v4EQuVZLvZ0g1y2/rJk+pZh8mSMQP7V7+boH/FpwOzdOGqvZwxeQRGJVWBA6ka60ayup+ybsVU4KfRkIGaRwWe4rXQMl+9afmr6OiDmJq8UK07zPdWyodlZbDveN6PZRDJSwL+rH0oR0xCCFm37RvLt0SlMowkbeX/VaqaPNIs3A8XNgC8Nu5cz2vNMOmWTRPXX5yXNgx2n0z1lNhCCFvtHFUSPPxiGxhJ7Ay+4s/MF8dB/FHgjpfQmwKg0+0f4Ri/r/xnw76eUbgFSSt+W/fDpXtCDGBg8nizoouWd+pTdpkB5hZ8l0nnH6w+veWW65qKZ8ka4j9/nKC9+htOy4+FE0iDzouWxXdDnBWanZbIPsm30lcKXlm6h6BeIANjWcWmmTKsOrROq8sRck1UDVdnR9sLf7TY5JMX76wV/R30ffTS8fX2Kvy6wW0PSiZu95ZeS4mGx5vPukl4Z3mtPaNcF07W01g/PafQPg0xQd2uYvx2Zf3X93R76Iz4lmH/lhnw9R3tH7S3dWUBVgVREkjfYWhO7jL60pDJgK8901qJUYp1m+JuM4joxeQyhKAH46ewz3NwXQbSU1IE3nowUOUMh83WYSroxBs22KzA6ErzB+LF4uk/4QvorwkhOMHtNfguTd/eYJzdkiwnJLFFRfH2zOhEt1A8Nu37G+6c52iRSlOJrVXY4E6g7Rx8dqjGHAvCLQEoizfwhca6U+pnn/v8To0EPfGuXtm9Omn4RQCn1t5G0zJ9KKf2Xv9obfqoX9COOOOKI7za+g5TLVUrpR34db2WBLyAy5K8Cf1Mp9VtSSqtf7Q8+1Ri8YdWX7L3j/fWCtMvQCcJi4HMvXfH77n+Nl90tXy0esu0KngxLsb/KIiFq+nE7Nsl6TmZ7rqMiKEeqDShFa6FbKGIGwyKSijiaGYhei5k03J9tGSZ7tEosXIvVkXfWYpzRrgp0bVj7KV8dLIUbJKopIrHT2J1CD5ZVmvP/059n4wty7XljfQ6dfqZBYwGv2dYFQy3Rf9mA7SKq6T+m0T/ik4705iPy+BrV9IR+ZhgWiqgTZBHtDcUVYi9YKrpTjX+QKJaee9WOlBT1zZLiVpHVifxajll/UPG1eI8sCzTbHNMJFzxaoSp2p4m49KhM3GF8b7jZVVgTCL0mC3fyxEkICnlCLUdjkolmXzuK24qyMAzTjPqhZZiK9Z9tAqaLJJ0RnabfFZLi0TAsAt29iCvHztA4yj3HF8dKeYFaLh/Gpe094KdSSgPwllLqq8gC/9O/0kE/uQz5I4444ohPIFJSH+rr2+CngS8opT6nlHLAjyHObc/j/4lE5yilzpEUzJu/2kE/1RG6MolXlyteKtesh5JusGJTpUHngdOioRj1U6em47XZimawbDcl0Ws2m5K2k2i3yAdSEmPakCViHok5YEShUeUBVw4onehqR+o1WidKN/D67Ia5bcl0xKrAVT/lzXgKgK4NbqXxg6LPM6Zlx8vLNfuJ47qc4p8UouB4YbmOJ/ydJqfMB5EGtYnuLIlkazE2hfSGNNrEhQL29wxqOP1Yxv+ITz50VRHLDF8o0R0qI8W0p+/EiLu4FsPoYSJ1o9plrGcFJ+WeedmyXnq6RYbyCiu9P7hrTU9JU0TwYiUYreTQhynEpadYtGgdaeqc2Br6QeNdIHktBicWYqYIDkIVeeme1IGWRcPbi1Men09xtxW+EB0kZRLZ04xkLfkqEu0o39xJwx9Ac8/QZAVay+4bLeboyb5g2uILKIqmlLxS6o8BfxXJj//ZlNKXlVL/NvAzKaWfHH/2B5RSvwAE4H+dUrr+1Y77qV7QjzjiiCO+m0jpxfHQU0p/BbHffP61f+u57xPwb4xfHwqf6gW9yAZ+19lb3M82/Hz9CiD5MhUhDJpHmyV9+H4K49Eq0UfDNO/ZZzmhscTa0tqRjVJm6CwSvSZFUHeRuYtoHVEmEYIm9YrUGVSviJlkrOa25ZV8RaYC++h4PyzpRpbLnYJj0qCzyDxveVht8dHgo+bm1qEHQ7YR2YFumNAtPEpHlAuE07FEbxLaSmOFKkcLunuKtbHs72ffzWE/4lOE9rd/jv2DTEws7kfcScvZrOZWlwy6xAxgmkBS4HaGcKFozIS3oiLLAkqLaUzIxfYOJJeN1vRz0VsJVQQldoMA9Jr+zg+gsehGi1H4qKsSykS3UIRc4UtILrIsGgB+ePmI37R4wlfOHvCknlFYz6vTNVpFvnz+kFW5pPxAYwYh14hRdkD7hIqWYWZpC4fNAyb34BRV1f2ycfm1Q0n0/wnFp3pB1ypR6Z4hGZ62c7ptjtsJjSquM572JzzlBFTCVJ6y6oV21BlUr1Fe3Ny/AaN7OwFUUiQ0JC1pjiDCQ3ktD40+KNanBU1wBBQhWW79hM1QHJ7iMY8MWhPnnnklUri7IWc3OOrWoQeFHj05VYRoNb01pApxQBrPT5uINhFjI2pcv0MWGcpAf++TO8GO+Hhx8TucUAjnkTTzmOd0TWKW6CcKyBgqRcjFFUg/0rTthHoRYBAHpeCAsfauo6Q6tJfuZVzEOwNr0U7SV4awK0gGrHhdEBXSuakTvkp054phEJqjMolmkEk9JMP9bEM3tWiV8ElTmIFTV9OfWf5R42h9hVuJa5XpE7YRN6VsZjCtYkiKwg3gIERN6V6oqeiHyY9/bPhUL+hHHHHEEd9NHLVcPkI0Q8b/68mXCEnz7vvnFG868lspFoKGtcY2I8VwllGfOBgLOZhEmgTyqWzHynwgRkW9zwmNdIOSFMknieKjQnuF3SnylUQnoNluS9ZnJfuQMyTDZTdl0+eibAcw9UTATUTWt+5zruoJbZ/R1Q7NKORvxXJLD0IjC4MW1/egRv9IhdKQUrrr4yAlMC6Ae3EC/kd8b6H+nIdsnDGdZn9b0jUZcTDYII1y7ZlimMmcLq4hv5X53w4WXyah7M4gjpkLFUaTl6Bk9+sCAUi1dIGaFlBS8Iw5+AKZrN0oKR3FpCXpRCwjWTkcJGlvhgldtLy5O+NrF/fotzm/VHhOljXOjN3XWs7BttKgpMJoA2nkXionHS/NN3TecrGdcrOpXtyAJvkon1R8qhf0I4444ojvNo4WdB8RUmN49x++gvKK+WOYPQqoKG3BIZcoItuCGRjd3w1+KoUcJp7Tsx0vTTeA5OMv91PquoBBNC5UGu3eJgFX9SLUbwuynSbbgltDt8u4aivO8gm1z3mvXnDbVIco2rgIKqFVoh0yfND0vQx7PulJ5cC+KAhPLdl2bIToFVrJ+6tBieO7gpQFfG9EnwIk4lFA9mL1no/4HoNXqE6TbTTKQ8wyjALTSg67P4uks57YGkyXkW0TtlHoHqiEVhitEoVSRiPnu93k3hAysUgEmb+2HaP4EvqMA23Q7LWonUYIRcIvInY6MJ10zJyE/12wXHcTvnZxD746ZfEEks3Y3C8ZlgGCIt8psj3YJmF6SEYxFJp+pvCLwOeWa35w/pR396e88+QM837xLYfl14J0LIp+dDAtLH5JUhLVZaC47AilRUUjC12SyrzuE8bIVjDkCspIMel5MN2yzKW6ftVO2DQ5fm+xo4wuiONKMWv50oOnOO352eJl+u2CfNRYMWvDk81cip19zs2uYujsQd9CoBiSFQ2WpEgJptOWHzi75OVyxRv37/Fl9wo8cugeTC+fSQXpwAs6iQxvUsTWYFdy2ezoxxiKT/Ae8IiPFeUjS8zGhXYvaZU7zjhIZ2eYBs5OaurW0V9lFNdjBDqK2CUFGJGiBjmWTrJom1bhzbP7Tfjl0rGYzMiQmUpQQyeSuLqXtGJ0hjgRswo7Cq74pLluK7p1zvwKph9IkGZrQ3tmiJnc9yQITtFPwZcWXyjaMzCLns9Ob3mtuOGDZknaZMzeebFj+klOuXwsjxql1L+ulPqyUurnlVJ/USlVjB1TP6WUekMp9Z+O3VNHHHHEEZ8ovKBO0Y8E3/UIXSn1CvC/BL6UUmqUUn8ZaXv9w8CfSSn9JaXU/wX4V4D/4Fc7lvYJ0yf6uaI5NSRd4AtFP5MowdZgWvE7VBF8qVAzwCYyG2i95dGwBOBiPaPd5Oi9kch41IEgKKyJvFre8jBfsxtyfm4xJeQG04BbK+qLCW82ThTj2jFaGY0zjJPIIyVQSHSuTWSS93xx+pTfWj2iNANfm94jGXmGpVF+NOmEshCLiMoiyWvM2lI+lsnitqPHaPHJzekd8fHi7MuBbqkPekQhFwpiMhI0BwfKRpwJ+MyzK5LcJ3GM4hMjtVaNRABByOUei3niLqUcXWKYya7R9KPq4iLgzhq0TjSmwHQZbkDunVtFrxy3eoIet7QTl7NpC9GAmUJzZjC9vIdtIQTRNepOxs8Qn+nIDMtIng+HY/XRYPaa4ubFpSRT+mTTFj+uZJAFSqWUBSrgMfBPA//Z+PM/D/zzH8+pHXHEEUf8yohJfaivjwPf9Qg9pfS+Uur/CLwLNMB/Bfx9YJVSuosB3kP0gn8ZlFI/Dvw4QF4uaU8V9avyRM62YyGzuDOshXwdcduAioZ+bkbjWcW+cTxqT/D7saNzZ1FJtB98HonOYPdyUXpvqEMOwNy1MPEME4MeJI+eXVlCo9F3zURlOETmRdlj9F2Urui9IXhN3TneqO/TpYyvrB/QrXPKXqKPMImEaUBp0W8xY7QfVjnFpWL6WD5vvg5EA7765BZpjvh4MfvyFdnrJ/jS0Z1CvxSDCwDV60OevO4cvRd9fl/JPPZVItmE6kZvgJEdGwrws0iaelQW5b6JiqTALxR+Z7A7ORYTz8OTDSd5w6NiyU1coKLF3Qo90rSari252I91oemAMREzGWg+H2keGkwjNS09CGXRTxJ+GVCVl7x9Z1AjQaDdO766vseQNFfNBN0roTW+QHySc+gfR8rlBHHm+BywAv7vwB/6sH8/CsT/BMD07LXUL4EHLdYFur0T5kdQ2I2RSrwoeBIzdTAu0Y0mNgV2p6m2z47d3k9kpy2n0z2ruqS5KcUMI2hu+4q1q3Dak097+qUTHm4aJ1qriVkSBk0RyZw8mwo3kOmIsx6jIrsu53Zbsbmd8Pc2n+Wn9WeIo4ei6aCfQ5gE3KwnyzzToqfKelZtyeo6J6vBbeTOstsBlMI2xwX9iG+NdHGFPZ8SjaM7jZQv77g33xGT4no7odnmEBS7TUGKCoUUSmOWCPMAeSRogwrmUOj380B23jKfNmgS+94RgqbIB5wJ3JYVPpSYRpO8zM2la2gnltWkImYSPGW7RLYDu1f0u1GC48TSnw7MT2vuPdxhdeTJdsbqyRx3ZSV1Oo2405ZF1TBEw2ZTEjtHtpZu1bf3D7i8P6XvLdqP0tMvajxRxCPL5Rvw3wPeSildAiil/nPgnwSWSik7RunfShv4iCOOOOJjxyc4QP9YFvR3gd+plKqQlMvvB34G+P8C/0PgLwH/MvBffLsD3aWp0uhjqLNAVAm8JmaaUCj254ZkDN1SCimxSOhOka8UxSXkG0mHdHNNdw5ns5rffv4el7MZP68e0mwLlErEpCj0wD0nEc6jswJShh6kGBSKJOYXLqJ0pG9H38/WYrLIfNpwfyIRx6Yp8FuLu9GYRmhYwnkfKYgKfG/IMs9ZVfNateL9bMGqnIkL+ly2GtF+coszR3wyoJZz/GT046wC9+Y7vm9+hVGJr+sz3u3OCLcOvEUhVNmQjztNF1EmkirwNkEu98pk2fDqckVlB67birpzGBM5KfecFg19MGxChVsDZDyZzzEqsukKQmux4645aUXWJGwbRYMJidZrY0knivvlDqcDt02F8kI7VgF0pRlay1YVDIMhbjPcraG8lGJrt7LsuxkpjxThBd8nx6LoNyKl9FNI8fMfAD83nsNPAH8c+DeUUm8AZ8B/9N0+tyOOOOKIb4v0Ib8+BnwsjUUppT8J/MlvevlNxAn7wx9HSfEz7S39XZRuRXbWR2i9pV8qhlmEk17kcRuLucowDeTbSFaPDQ2F5MMzEzixe2KuKPOBZlsQo0KrxLndgoWvV/d4Mp3ju1Gx0SUoAsqKPV1qLHotUbRtRPz/+qWMyWs9L1Vb1lXJZZqQ30J5lUhK9DR8JV11Zm3R3rKfZ1wXPd8/veK8qCkWLc1De6ApqiAGuOoo5XLEr4Dtb3+Z5twwzKSYV/eOvc9ZZA2VHaSLudeYvRItlCwdKI3srBQ2DVB57p1LV/UPnl7woNjytJ3xTndCs8vRWUTPE1PbkemAHqRLWwWo5yXvJYXvDHovzUH9iRRX40pRXiXcViaxHgy+0myXFW9k5wzRcPt4zuRdQ/U0kbQonrY+py0dKklzk91LTt5tE6AZZpphMZpuVC82ov4kR+if6k7RO5fxpEVn2ZUDy2lDlfVcFlPqTFzK5yc1L803ND7jg+sF0cmi2C00Ph+ZLHNFGn1G99Hhk6EbLLQaT4aPmko/8+6MXhgCySRSJtK2IBX3bGUon8hx81UiOsXGZtQPHItFw1lVc2FOsTUU18KYiUYRioTuFcWlwm2gXxguigVvVOfMs45Z2XL1MKM5Nc8GYWzrPuKIb4XH/5QGJGjQe8P15ZwQNa/NV/ikMSbiVUIlRTSJWESwCdVpadXvhKvuS8/LM1nQf2TxNoUaeNrO2NYFaZsRqkCIGq0i1kThqGdjQTIohlb0K1IZSPOBlAe6xhIeObJaka/l/snX4FaW/irjMiyh1VSPDdMPEuV1IGQKlCFpRb9QxDIS88QwVfSNcNKT5dDhGpwQDV4UEhBfoEfpi8anekE/4ogjjviuIvGsePcJxKd6QU9WKFS68GSl5958xw+dPGViOn7BPOStzhK9xo7Rc+8tYZBOzn4h0b0eRYXi2JE5BMPWF9TeMQwGszPETvO0nvHUzxmi5d31knST4zaa4BIBeWqrBLrVmFYd3F1URNzHg7QD59pTGOHPZvv0/2fvT2MsS9P8Puz3bme9Wyy5VGZVV/csPQv3ERcZtASJFA3CEkjCFAhChkEaBMYyTJqGLIukINMA/YWyAcoEREgYkBLGsOwhTRvg2BqIoCXPBxnwYBaO2ezu6em1tqzMyIyIu571XfzhORGZ3azuqh5mbY37BwKZsZ1749xz3vu8z/NfyNYDKjhMn8nvjcLPrZ4FbKsZ64zfsPdZLMVcppr1t9a8PmjafU4aP7kX2BEfL37nH/g6b2xOuHy8wF5ZVOtYhzkAdSY7zmgg5IlQR8xJT56P9F1GeJpjW43tYBz17XU31xLi2YSMsbXoQROySB8sXXAYHQkLT/PAEsqIOR1wmScmRe48n1ldc7fc8eb+hK93DxgfG0Ihu8ybAaYeFKExQjvW0jZRwciuvBKPGL8M2NOOPPe0h4zGFiStpoHr1I41Ur2/TBx56EccccQRPyg4LugfLtJoGIGukj9Hq0QfLP6QQWO4Gg37JmfsLWmdYUZFKCP+5AWPh6ggi7SD491mQeMdwz6j2CjQiourOf9k+SpdcDx9uqS80Ng9hEoxBEMsxLBfRYWvE615oTevYJxHrI700eKjhqRQMaG7EQcUayfDziSVRcikyi+uAF2wOXGoxUg1629jxJo2Q19l5M+OFfoR741/+8H/m380+x38l/1PMlzNsY0iri2brKIt5Ro3nXi3YBJVOXB/scVHzTt2RU8lCuxe8+5emtFfmj0kJMWj/YI0mNs2xLYteEuv2HU5pvQySF3uuVvv6YJl1xfUWc9r9TVn7sBVX5NcZKwM7ZnMhUIuoRu+jjD34ALdStOfO+xeo4IoWOPpyJ27G37y7Amn2YEvbe7zG+0D3M5Nbo4yLNWTc+nLw8dnvPVB8AOxoB9xxBFHfGQ4VugfEhJkV5MsGcflzvHLQbMsOx5dLjGXFndQ+MYx1OLj4vbi9xKzhKo8dopv84Mhec3hkPOtdErfW+xTR3EpbJruOuObp2cMwaA2dpIsAwpMDslNEVhVQJUeJlP/YdDQGwnSjZqdz8W4pwp0p47iToUOSZwjO0lB786hO9VoL9V6fgnKG3qTCOX4vId+cFTPFPW7n+Ar7IiPFX8g33GY/SZfPLvPly4r9ChyeL9z9FuHWxuyjcyjojM0TU5TZqzylrurHe/0Fu9zTKt5/HgFwP/Lfx6tEtfXNboVDxUVodnlNLucNBowidPzHb/9/F3uZHu+frjDdVtxeaj5jXSP3HoebZbo1hAKaO7d+MfAuJRA63LecX+5ZeYGrvuSy13NMFisjZzND/y208f81PwNCjVy0c9RRlxV9Sie66TJg+Zl5r9MvjWfVHyqF3QVoHwM2S6hAzRrwyau2J30hNaS+ecnXmw2JwvQKQ8xAc6J54o2kaGRrMXDpoS9ob5SZPvEWMvvjlETkyKZRDQyeCFN9Kg8wdyT1QOns4Z6SmDZdgXPrubE1rLZlVyUM1Z5x/LOju2PnBBdRrZNRCc89P4sMZ4EVBagsWSXBnuYrEyzSJE/TzBXk81uyD65F9gRHy8Cift2w+9YPuKde0u2aQ6D6CfsXlM8A7ef7HCNYlAF7/SG9aqlygZsFggmYfca/UjsnTfbFckKf115KY6SSaTOTlRHhZ9F4pliYTucCmyHnOurmrR3bNxM7KAHg/GKcZGIU/pBLCLJRpSCEDUpKQrjOSsatEochgxNonIDISn2oWBPwVVfQWtQI3J/T63Lm2Sll4tP7v32qV7QjzjiiCM+cnyCN8Sf6gVdRci3iXwtbZNhbjG9IkaFKT3DXcQNMQ8ok4h7R2ytRMc1iqG1jFPLxZgoSlIP6YbK6KBfKMYFpOXIeXXAR816VjPODWZEBAwWmHvmq4Zl1bLMutu2yLNQkyavCd9pntU196sdnz99xpeCYWvn5JcaPYqXi7878uCVa+5We54c5jyulwx7C7Xn7t0tD+cb9qOUM+3S0b2iGZZHYdER741f6lccYs7Stry+uuYbUdO1GaE3hNGRjGTWRjtl8G4Vocs4dIZuORCDQkXxUbGTubXpNMlOO9MyEauAnY2koIhjhhoVRMUwGi76OVeq5sluDtcZ+VoTMkOoRcAUy0hYRPRkEa1VIjQOtTUMe8u3GseT2ZzMedRUGPsEzw41hyHnqq/JdODRdoEepP0T3QshHgHU8F1Ozm8VxwX9iCOOOOIHAEdh0YeLaGCcGXwB3Sn4pWex6JgVPc4EcuPJdGAzFDxKK9LaoLzCHSAZyzj12ccigEmYLGDLgM8irc4Ylpowi5zd2XG/3NH4jLfqEV9lhN1NJZ/IqoG78x0zN+CjmOsDbK5q8gtDvobea/Z3CoZTy8x1nNQNh3mBbzPxfMkSOgtUbmDmeprccVhmsIQHyw2fnz8lN563mhMAmnlGV/YY9QkuGY74WPGzj/+7zF2HJmF15KRuGPKB3hs2uqZNGUMj8XQxSzKI9wrdakJuQE++Lunbe9FxirKLeSJf9jw8XWN15GIxY7upIGh8MHxre0pKit22FAohN3YZCcqAtgGbTWEuwNA4zM5QPFOYHnyVM6wympUnmw8U+cjoDX3j2ETNVV0xK3vaPiPpRCiF+hszWXe1efnr71FY9CEhaRiWil7DOIf+NGJKj1KJ3HjuVXuWrmVMmsY7mU7HKS90UmS6/WRF6wy+SoSzkaocWFYdhzKjazPyzDPPenzSRBRFNrKtIr4WDm4oI8uq5zRvAdiPGdu2kCe5t1O2qdwQYTA86yr2PuP6UEEjbSIVZHsYBsPj7YKL3ZymzYijppr3LFxPaQa2vmA9FLfn4H6942G1+cjP/RGfDvzSb36ObDawqlsy60lJUbmByoHRibWtxOrZJJSOjJOBVjI3WaEJTCJZMe+Cic1lxeo5zTxniwM/trzgzB14Mlvw5fweF+s5Q+N43C6Ft92KynOcJWIexcxuSvLyo7ltc7LOKCbmljtIvmnbKA7aEusRpRLjaGCdYQZFP2iMjjgbGOaecXToQYgLKqjb5/tS8ZJYLkqpPwr8TcT+7G+nlP76d3z/zwL/e55nQ/zHKaW//b2O+ale0I844ogjPmq8jA2xUsoAfwv4I0jk5i8rpX4+pfSl7/jRv5tS+vMf9Lif6gU9aWmzxHwKmLCJtMnYbjO2VcXlqmZRdnTecr2u4TrDDM/TzG0L9vLmYKLqPGhHVzvqfKDIRnwQ6tS2l6ALqyOF8+xPBrqUi2fL3FO6kcjzcFhrZMiT8kioDOOUsI7XvLteEoJmvM5xa4MepkFOKXyrw7ZAbRzZtTg6Hs4yvpjg3dmcfZ+z20uFrlQiLLXknB5xxHsgfyNjXFmenlnKuseaiNYJN5kN5cXIaIQmqFRiZCIFTLtZJkvdG1dTmKrzKhFmgWw2MMt6nIqMydAGR+ctY+PQa1FtJi3EgWSSHEMjFXs08hiJ23ZMfq0oL6C8DJg2YjuNLyy6V8SgGEaL3zuKaz3dN/KkFmVHCJpu0LA1mEGhJh1HdC/xhL48r/PfD3wtpfQNAKXUzyHRnN+5oH9fONIjjjjiiCM+MCZf3g/yAedKqV954eOnXzjQQ+CtFz5/e/rad+JPKqX+iVLq7yulXnu/Z/fprtANDCcRXISoMAdNfi1m9yE3dIucw+QxnjVghqm6yGVYQg+2k7dbFRKhEHWmHwy7Lmf0huHgICrWgyFExXl94KQUkcNVFgijocg8IWou2wqjI4Xx3J9L+vToDc0ww62lh6j2hv5QSwxeI0q2kMNwHijuNNRlz3pboQ455RN5fm6nadsFb1cztFeo4Tmt8nHn2Lb5x/USHPEJR74GlKYvLb2N9MichjSFwejnQ74UFLGzmINBD4pYaPFHVxDqeBusErMEMxHRzesOHzVf2txj2xVcbWvCVU52bbB7pohGUYD6CpQG1apvcyQlym4ZINtAsY7oXvrrNwNNFSGOhs4b3DNH8Uy+PiwVSonQqM0drS3QXmFamUklI0EaLxUfvEJ/llL6vf8cj/T/AP4vKaVeKfU/AX4W+EPf6xc+1Qs6NqFPexlMthYVDLaRUImkwe0UKilsK5LgYa7ozsHPZJE37ZRUhNh2tndgPPWU5UiMiqFxsLeSsxgVQ2HRKrFwPdl0NR76jBAVm6ZgnUrqsueHllfcKWRBz3Tgy4PF+xJ70GRrCQ3Q/ZQjWsG4iNT39/zOe4+o7cA/5iHXWQnIpD9fi9I1lDLdubnIYwY+OJr9y576HPGDAtNPmbWdJuSW5BVmN7Uw8kSoAthESsJuMQdDtpaiKDrFuDCEKkrbpJBrXtWe+aJlUXZYFdn3OVebGfFZTnatyScCgPKgJ7Vm0oASozrTT9L8iTN+I9cHsL2sluPMEDPFWCmGxZS1GxU0hvwa8k3CF+q2nx2TYvQG1WlsI7Yc0cr9NaxepvYfeDmHewd4seJ+lefDTwBSSpcvfPq3gf/d+x302HI54ogjjviguOGhf7CWy/fCLwM/qpT6nFIqA/408PMv/oBS6pUXPv1jwJff76Cf6grdusDd0x2dtzRZxhAU3WCJRrZzKoDdC/0p5IphDt29gJqNhINDeXM7MBnnMD4cuHd3Q+UGrpqK1mtMJ74XKBgqx6Yr8VHTecehz+hHCc0IvSF5RQiauFScuQMAbeHIsjOayaxLbD1B+6n9k0GsA6uqZelk36mRAa8vFdorMetPE60xfz7kiQ6IYJrj+/IR3wVJqmF70IzaYgJka4VpIJSKMRhCnoQH/oIHiumlDaI9jIMmFOCNXMM2k+v1Xim2uNdtiT9Ysp3sPqMV1fNNNW766blEpiGrXMehSsQsokdF0nINq6DwhSJk0irxFQzLRDwZUS7C3kzGW0w/k7Am0o4Z7SHDbaXVo5KEYAzngfxu81JP6ctguaSUvFLqzwP/EKEt/mcppS8qpf4a8CsppZ8H/udKqT8GeOAK+LPvd9xP9YJ+xBFHHPGR4yUJi1JKvwD8wnd87a++8P+/AvyV7+eY77ugK6X+AvB/Sildfz8H/ihQmpHPLS/ZDgWbvODSRFpX4ufSI7QN3DijDQtF+yBy9vo159WBR5slWzNj7KQySAvP6fmOk7Kh91YCohuD3UsfO/SaIeVcdAZ0Io0a5TVMCjfVabRXjBou24p1UQGwHwt8mMRLWcJPWzE9ThVGmVBGXOS+srnLYch5+nSB7RQxF+fdZJ//rK8jlFMTTyXoDPoYEn3Ed4Ev5DKxB1BRTzs6IQgAJKNQXlTKMY+EOjIkPVlNSy/aDOBzbhU6fm4wKlLZAa0SuQ2oLOLnET+DNAtk8x6Solvn2LVYV4diCqEuhO54d95Q2JGn+xmHUpTVfiY/G7NEdImUR/RsZLlo8cFw2DmShXGm6E+B04HTqqHzjtBZ8oPsKkIBw2mkfmXP58+fAvCbH8P5/6jxQVaCewjp/e8ppf6oUup9m0NHHHHEET+oUOmDfXwceN8KPaX0Hyil/tfAfw/4HwP/sVLq7wF/J6X09Q/7CX4vGBUpzMhgLV3wOBtoTSS6CEkTvQRGoCTWKi1HXp1vuFfssCrylkp0gzSkrQnEpHi0WXLY56TLnPJCU1yB6RIxU7idxteZeER4mdxLYG0U/4tBERvDxW7Gb5i7AKzb8pb6GF2aihyFtpOEOpPe5XZTsr6sUVt3y4SJDvxCjp+KiK5HFvOOYvJwbwfHbl0Sw8tUThzxg4T+bJrZDDKDuSnhbkRCN98LhWLIQc8HQqnpdAZKkW2lStcDt57l4yCVem0nO4oqp106mixgXeDOYs/DeksXLN/Iz9jZGkYFRaScd7x6sua3r97lx8t36ZLjVzaf5YvuPgC7lXAMjUoQNEolZnXPvdmO/ZCzzypCbkRUeCfymftX/OTJY95pVjx2S2F+lTITi6uRu/Md94rtyzuhiZcm/f8w8IF66CmlpJR6DDxGGvQnwN9XSv2jlNK/92E+we+FIVoetwsOY8amLdiuK/R1ht09pzMlA7frXWv45vUp11UJwLzomRcysRmDYX0oGa4K3DNL8QzKS7HmVRHGmZbBzXRcHcQYLFoZvmASaNCjotmWvBnljhl7C42V9HIlN5UZhLZ4w49NQRH3DrsxZNcK28lz7mdCo7TzgVndcVo13C0P+Olu/NbmBKK6VdkdccR3YngwYq4t2bWEuyTEWCtO0gU9ytDyRsFZ1gPWBLY60cccksLdBLlM7FhlEoX1nNgGpwNtyNhVksRldLxVoVodqfOBfm4J3mAzz+ms4XOzK36q/hY/nF3wrfEOVgdKJ7zFfOmZZT0+ai4PNf1oyUxg5gaGYG4zd5MBZp4fXjzj986+xd3sjIt7Mx71Z5i9IeYRW3jGaHi3Xb7ck/oJNud635aLUuovKqV+FeFA/n+A35FS+p8C/wLwJ38rD6qUWk3Kp99QSn1ZKfXfUUqdKqX+kVLqq9O/J7+VYx9xxBFHfJj4VLdcgFPgf5BSeuPFL6aUolLq3/gtPu7fBP6rlNK/OXEwK+DfB/7rlNJfV0r9ZeAvA3/pex2k85a31ytCVHRtBluH24gZf3RShfgKtEPyR59aDvsV22IBM8/y9HCr6IxJsW0KGESY4PaQ7SJ6EAXpMNP0K6Fj3VDBVJLHSRqSSigvrok0hp5pf4qSIaqWGDt7UGQb+f2B6YVXiAukFyfIaKTqD1VEF56qHDgpWx7UW5au5bKfATCMFlqDbY4V+hHvjYevXvJuvmSgwB5uRHSQbmi0vboNV9HzgfuLLYus5x0beAq0WcY45fCOcxnG55P7Z649TntyLS6OXecIvWW/K3hcLsicfN3agNaJmBTXh5Kv2zNq+1neHM75p7sH/NqjV+n3smXI6oF8JS3F0RvG3tI5S+MdQ7CozuD2SJXcGHw0rMyBuui5PJ/xy0lxua1h1MSgeXy14KmdvdyT+mmu0FNK/5vvXMxf+N77Et2/E0qpJfAvA39nOsaQUlojxjQ/O/3YzwJ/4vs99hFHHHHEh470AT8+BnwcPPTPAU+B/1wp9buAXwX+InAvpfTu9DOPEXbNP4PJ4OanAczpit26QpkoNMLJWS1Z8HUi1AF0QvUac9C4g8JdKJIxdHc0w7xnNTkVzp38+62g6VIJSpOswXSacaZo78Jw16MqTwoa9gZzk3j+YorJTRiAk2qmKAfiTDMOlrB1sLXoQfroKk59dRvBJHFkrKcqagqFxmsOhxylEqUbsSoyRGlmhsmpLh1Zi0d8F/xL977OL9vP8I10h+EqQ/cK9BTsnIlPS9IJNx/40XvP+F2rd3AqUNkBZwJXdcXQO2JQuFwq52XVMUTDm90pYzS8fVjy5HpOvCjI13IxDmVBuwyYxUBd9WAih0NBf13wtcuKb9XnoBLpSUH9pqaYaJTt/Yw3XrcU1UB3yIidZQ88s559l+N2muIqYYZEf2r4wrNX+Gz1Wc7djtx47lR7Om/ZbkriNiMNivBdzs1vBR9nO+WD4ONY0C3wU8BfSCn9klLqbyLtlVtMQ9j3PG0ppZ8BfgagePW1pNeWaJ//qJ9HYhGxs5FZKQOeYbS0u5x0neGUqD5jFTibH/hcLS4/527HebbnbrnnjZMT3r2zpHtaYBpNzBPxZGC+aincSO8te1sQdIbuNGqUIazyiqTlRjlZiVL08ydPKczI43bBN7IzxsOMfBpQiYeFwnuNzgPu7sCs7MlMYNflHK5L9MahvGM7d/ig4RSskjcLZwOUkTAeV/Qj3hs/Ujzhal7zbFmzbi16MFMAhFg7l4tO7oP5FT8+e8yJPXDta0ozclo0ZMYzBMsYDH4a9Pfe8JWnd/DhPn4whNZiry3VM0V+DdonKYIGy5AHqtVI6QaG0RLbnGytUd5hW5g9Ssy/ebitaNc/XnGV57R3lLBcek3AcW0qwmDIW3BNxB4C1ZOMqzeW/IL+SU7LhtY7rg+V2E+vHflaS/v1Za9yn2CWy8exErwNvJ1S+qXp87+PLPBPbrwLpn8vPobndsQRRxzxPfFpH4q+VKSUHiul3lJK/VhK6SvAH0ZM3b8E/Bngr0///oP3O5YK4NZ62jbehERE1BSnlRIylDGRrB4ZUPSFgSJw996Gf/HOG/xI8QSAkDQ4OLUHfrS+4OvzO/zG4i5X2xqiIs8l2m4IhhA1SiNURcSc/6biDrlCucj9Woatv3PxNqfmwNezu+yGnLeriuAMmU9kGzHxGRrHcKqxdc9PnD3hPNvzG9t7fOW6xG1E8Tr2lrbK6RaW00I8X6psZJuFW5P/I474Trw9nHII2e3nZlJQ61HuhezM89pszWerS5wKfKO7y1d3d3i0W9B7i1IJoxMhKtpejjNsc8y1xe0UxQg3eaM3RIKbdmK/lN3wnWrPZ+srZm7gC4cM1jnZFoqrRP2oxz7bkzJpI9quRAWNycSmMSDHD6MhjZJxOlbSXiWC2xiePVpy6eakUaMbQ7bRZFt5Pip+rPa5Hzk+Li+XvwD8FxPD5RuIYEkDf08p9eeAN4A/9TE9tyOOOOKI98axh/7PIqX068B7Gb//4e/vQM+N8UHEBn7QhFHhG4O3cvZfHBqqMrA62/NTd97ih4oLrrxQmr58uM9VX7NwHafZQcQO2YhzgaGzDI2jj5kMQSdnuqSTDF3jVKGHm36dwk4BuIXyOBXkQweSi6AMtk1ku0C6UAxzzeG+YZdXPDupqc3AYcygM7dKPpI8bmVHCiMiDK0SKSj0sYd+xHfBf/XOT9KOlkOT3w7hiRPtdlD0g6PxGe/2S/5p/4DffHaHw+MZZic73xuVstIJBrnO7MaQP1PkWzlWKCaacCb5AklDcIpkwbjIKmv5ifoR9/MNuyHnW+099GCxraI/cSSzwldSoe/va/ydkVfP19ST66lkDmiGBOPccriv6AbDOJ+8kKKSe6U1uI308bNtwnaJZBRJv+Se93FB/5AwSe+TlsVUe1ngTa9IRl5EFbl9AWImZvdhpYlJ82Z/xq9eicf8V9+8j15bYhExywHrAkPriK1F9bLF0wmiTaQqoLOAzgNh8j5WUYmZfwIi7EfZnr47LNmYkifDgpA0yiZCDkkrTB/RY8R0hqQtw8LxtfquDLC2Fbq9uanAVwmbB7RKdJP09TBk0NpbfvERR3wnnnz1nOQS5AHyyHgaCKUszLGMKJXY9AXXfcm7V0viGxWLdxTuIMZe48IwzA2xjN9m8X0jsVdRjLvCZAIW7cRrL4Vppk2kC44+Ou65DT++esLF3RldNwc0vjLo0TCKlx3tg8TifM+PLp/yIN/QrxxP+xnPupp3dkvWUbHPnTxWEdGlx5hE9IoYhcGGYgrPUIRMvfSWi3rJeRkvE8fS7ogjjjjiBwSf6go9WuhfHcEKD91sLNlGouUAEWl6MSAywxR35TW7RcVv1HfRJL75hphoLb7oqB9HQm5ozyrGOTjD8+2VhpAlyBI6DxTlgFIwlp4hc4zGYQ6aNA1KD4Mo395ozgDYjjljMGTVwHBmObSakDv0KDuMsRbqY9g5rmNNHAxawTibTLzKSIqKR/sFYaKPba4rdKNv47uOOOI7UT7WEhJxAno5kM17lEqkpHBW2opjNGzbgvGqoH6qKC8TekwkpfH+uV4i5VKa+gJCofF7LS3PhHDbFYw1oCbTulmAqHhrt+JXzOu8Vl4Tk6bOBw51YOwVMZNYupjLfROrQEqKIVqWtuXV7B1CpURVmj3gW+6U9syhVUKpJLm/o8VrjS80vtJyXCvHld3tSz6px5bLEUccccQPAI5D0Q8PKouc3d9QupFdl7NRc2Lr0MONNe1UXWhxR9QDuB2Ml463M/H+ck+lH109Tcze7kla4fYZ7blmnElUVrJSfSQLVIGyGm5dGkNUHEygAUJyqKBIQbE+iKNj5y2jN8QoFVFVDuzvK/Z5QXv/uSgp2kSYiUWuKzzRRUaTRDQURY46HhyXBwfTEFS3WuYFx8bZEd8FegCjwRw0oTS4Wc9J3WBUZIwGHwzt6Gg7h+5ktxcN+FwzLGFYga9lMMoUEm2c7GSDd7idwjUQ9eQ/VMi8J8wilIEUFBdXc7ZtzjvzJc4EmiGTQSaTa2ISGiWAXRt2acYX1CvUZuAVd81n3BW17glJc5JJnFxMineaFd+4OqPbZ6IUH/Rt8PqwSIQ6Qh0w2cvUinKs0I844ogjfmBwXNA/HFgdmGc9zgQGa8FEcT60UwTVKoBL6FbjrzRuKwNwt1N0eU4qxAUOYJgr+tMMFSWcORQyqZ8soaXidwntAkZH2tHeRsuFqIXpEpR4ZShLF6cKPVboTlKe29XI8vTA6aLhkHu6NsNP4dJKg60HTuYNq1KGAM2YiQXAocDvHWpn0L3C3PifR0RUZT7qM3/EpwW+lN2p2ylQjp2WhrIxka53jIMlBkXsDdZPTLClYqygP0/4RZBw5hu6LhCDgtaQrRXVhYSwj7WiKRS+TIR5QFUeZRKxN9AYmm3Gm22Gyz39IUMfDKYVRoz2EzUXUEkxbi1bv+DX3UNOswOZCjjleZBdc89tmJuOXSi4HmraQ4Z5mmHa6Z5QEhwdTj3zswNn9YEbF5FvvITzqfhks1w+1Qs6CHVPKfGXAGldRKeEMrUaKOuBcTR0eUkyhmwzDUk7RagT/o5MFLfG0S8NZpA2yzgTjis6oUYxwUIlUlQ0bYbvLak3kzEXmL2EU+hB0tTjXk6t6cHuIVlFEzKa0lMuDuTO03Vu4s9qkk3EXJM7z3lxINOB9VAyeMM+IgZjjRYVnngkyYWljuZcR3x3+FqovLoHt1fEzLKjBBTspzxaK7m2ych172sYZ4l4MmJLD0kRvRJTOoBO464M5VMoL2V1a880w0kinHnU1OKIvUHtLKYR+q2PGX1hUXt5M3DbibQwSioYTK3RUTHODJebmi9UD4hJce72zEzHfbvmjtnxiBN80sSDo1yL+jWZiS5ZgalG7i+23C937H3+8k7osYd+xBFHHPEDhOOC/uEgJSWWmpOBvis948yC1kSbMFocCY2ODJXDl1q2ZgqSSxSLnrO5uCLuzzM2d2o4WHnBTJI2yiCCodvHDBrvNWprsa1ULCpOPhYbbilcTDtAPYDtpHqwB8XQOnZZTggaf3BkV4ZsK5mOXeZoTxxdcAzRct2XrPcVcZPhdhM9Mb1wbC87gCNt8YjvhqQT0SjIIGSQsoTSidhr3EHLTrUAv0iEuScWU8xiEbHViLGRGDQpatLNfeAlRMb0iaSgX2raexAe9NSzXoIuthlmZ7AHdZtHGgtFVBrdK+wBsp04M2oPZpjaOU5NqtOESorHhzlDNJwXB14rr8lKUV4/9ksu2wrVy31x0wZR8XkFbXVEq3TrEvnyTurLPdzLxKd6QT/iiCOO+KhxbLl8SIhJEaImU546GzA6ctlZ0uCk8rjMWfdGIuB6cWoLpVQq8WTkc+eX/PhC3BYPPufr9RlP9zMZFnWWdHBTRJcSUZFNEqbhJ4dHIz4x2sNN2RwzEVf4hZQMuhLxhAoibKLXNPucFBWqlZ69HqfvJYUPmu2Q04wZT9cz/LOC7MrcCqNC8bwauRFNZftP8BV2xMeK4qm6JQmMy4A77SiLgf2uIDoJW4kOKD15NZKSInipaFNS+MGSEigN2klvPGSa6MCXik5pulNFf89z53RHZgOPO4duxFflRniU7OQjM/Xqb+Y+NxV1dHL/DHNFfwLxdKTMR9re8Xa34jKv2c4K9iFnYTveaVdc7GaooIgvpD2iJJfA94Z1V5LpcGvD8dLwCb7dPtULekIuPm9foHkkhWn01P5QhCLDl9JiARinreX5+Y7X6yvuZlsANrriUGVYHbluK65Txbh3qCg875gnVOXJylEeU0EAtA343kJ0qBGSg3EZ4UTG9gHwS4uajI0YFWnjICm0V7INXsrzMqueWT7QB8vlrsZfFuSXBnuYUpjKRJg/31NGayYe+9HL5Yj3xulXPN2p4fBAgQHnPIXzdFlgcEkUlSahbaTIR5RKdIMUNKGbBBgmYXKPtVJJxEzjZ4b+RDGOimEFqvaU2UhuPFnmaW0CJYWMhL/IvymLxBkMK4uKYDv5mRum1rCE/jxQLjryzNO0GUOT0R0yusGy7kucDmz7gmZXoHRinE9/bFToG8p5L+pXZwKDf4nLXDqyXI444ogjfnBwrNA/HKSoCI2jDYoQJLdTry35lZjnaw8+V4yziVs7l5zRfNlTZwObseRL/gEATcjopnfywo0YExlclEGOARYj9bzH2UCvLFon8sxT5wObpqDfGVAaNUqSepiUcFk1ErNAGAyxN5i9xTRTe8YlQpkYs4g+GXjlbMNJ3vK0mTEcMtxaaJYqwJgJjdIsB4yVMmQoHYfS0bXHCv2I98bsK1eY11cM8wxz0DS7gnG0jK1Fj2L7nHpF6C1DYXE2kKIienNrl4uJGBNveejKJGIR6U9FmRmqiMsCRkVO8xZO4FveMIzVbaCGbWHsNHEBqvKMZxCdwbZKaLg3G9h5gpknz4Sb6wcDrSElQxM14yihG2NnobFCh1wFVOlBIX9XJwcbR8O+z+nHl7vMfZJ76EcG8xFHHHHE94P0AT/eB0qpP6qU+opS6mtKqb/8PX7uTyqlklLqvTIkvg2f6godrzDXVhwSc/GiKJ5J/zzbJVRIk0eEnpSeiliL0m3dlGzagmF6945JkTtPlQkHUClxVYwuYYuRxayjdCP7PrtNQc8zT+kGWmfpk3hIZ7uE7RWHIGKG/o7G1iMmCySvUUGohkI/VPgiwtxzttrz2mxNpgNPm5mINw5gm+lPrSZfmsiturWc9YRqJH2CQ2uP+JgRovSwI5hWETeOsTUQpDJWAWyriHtDZzJ84ae4N6H36tJTzXpy528r3YGpF55HlAtkhWdW9czcwN18x/1ig1aJr7SvENYZ2WbKKjiA7ww48YUJSRFzNc2pnrst5uWI0VE8kLzQHNWgiKNi7DVJiY+R7STsOiwC9+9uOC0anjYzLtczwqAJQbNvc4bGvbzz+QEX6/eDUsoAfwv4I0jO8i8rpX4+pfSl7/i5OfAXgV/6Z4/yz+JTvaBrD/mVYpiLks0eFG4HrkmTKZcYX7lWOK0yzLCMSbHtLKBIfgrC0AlfiJEWyHZNmURW9ZzULfO8o/WOQ5MTrsRcqLGRUGsyE0g6YVuo3x0prjQqyKndOUvMA67wzyf80wAoukTKI3k9cLfe87DcEJKisCPJJKIRi2Al8YqYRuNtRjfIAXQWsFnAmE/wlOaIjxXtD5+xf2DpT6Rll3QimYTKIyL81JhhYnL1Bh+VFB5eQRVYrhpeX16jVeLt7VKOqUSdbUrPctGwLFoK65m5ntx4ZqbjNG/EFGuysFYhYRslJmFaWiXEiSmWR5iseV05UpUDhfX4IMZ0ptG4HSSjCIUmaTCtaD9CDk1lyY3nh2aXrPIWHzWbbUUYDP7gsOuXt8wpXlrL5fcDX0spfQNAKfVzwB9HspVfxP8W+A+B/9UHOeix5XLEEUcc8X1ApQ/2AZwrpX7lhY+ffuEwD4G3Xvj87elrzx9HqZ8CXksp/Zcf9Ll9qit05cE0wPyGE/6cJhUyCLlQDvUoaeS2E6pgg2E8S1AElHv+dhu9oh1y0iB0QGxiBIbCME42o75z2MMU4RUUy6zjTnng2cmcsSrQQ8QePPlKquhDL7Sv3HmCMwQX8eXUAqrELrcuBmZuoNQDMSkxHJsP9OeG6LTw3KdKx24NaVKoRmcZnPjNHHHEe+HyJx3DCvqzIFayeaCuOxZlRz9aLq9nDJvseUZuVLeRi4nEqmj5THXNmDQXjeTvxqCh1wRtCFFRWE9hPF1wvNMusWrORTsj9IZ8BBUTKt20XRQqGuGhK9mlxiLiSml11lXPouhwOtCOjhQksCZfA2kyzLMyZM12k2/TzPB0P2M9K4kThTeMGvYWtzUUly/5pH7w2+1ZSul9+97vBaWUBv4G8Ge/n987VuhHHHHEEd8PXs5Q9B3gtRc+f3X62g3mwG8HflEp9S3gXwR+/v0Go5/uCj2Kys0vA2Y1MNqMcWswg4TDjjNAg9tCeZlw+0g0mmGuGM8hnw1kEwWw6x3DLsNeWbKtQvci5hkWlqtTx/4kn3rViVCIQnQx7/ixxQV33Zanr9Q8vvuA/sSRX4/f/oKqRIiKMGi0VxLXlUcoPTYLxKRYDwVvdyvMtFc7mTfsbGQ4t2JB2ooz3s0gC8CM4mNx9HI54rth/9lILCOmHslyz6LqeH1xzev1FU1w/NPsFd51S4LXWBcI3hBGjerFXbEZM9ZjiU9aQskBWoNbG9LGsOkXdIOjLgZ80LczqKF3qJ0V0ZCWODgVJ+dHPw0zM6nQlY3kudAUZ/lAaZ8TE258i0hy3av4gsuoEfWpHuCwLfhaeY5WiX2bk3qDnQSG+folntCX57b4y8CPKqU+hyzkfxr4t24fJqUNcH7zuVLqF4F/N6X0K9/roMcK/Ygjjjji+8FLqNBTSh7488A/BL4M/L2U0heVUn9NKfXHfqtP7VNdoScF4wKyOy0PT9a8my3pm5lMw8sp4EJBnhupZn28fYdPOlFkI3ZiiBz2OfbaUr2rKK4TthWmjC8U7bnl8JmacK8jq0eGyex/VbWcuR3ndsfDesObZ/dozw06PH81TQfjOqfRGXZtcFupTpJVxKTwg2E7lrS941lTU1ipVMpsZFF0xKTY9zmbpmQ4ZNBruInrOmjcXr3cCuSIHyi4VxqUTmiVsCaSWU9hRnI1MipNaUfqqiczgbPqQOctb6pTwmUOnebZ9YzeG1JS7LYS2qIbQ7YGdwB/aek2M67mEYLC9JIdkIz4nEc7UW4neb8egSieR+SQbEK7iDXPY+Ja7259mnQWGFbCSNMjtz4wMRcvGbHEADrDxfUcrZOIkUB8XdLkIfMS8bKk/ymlXwB+4Tu+9le/y8/+Kx/kmJ/uBd2An0fuzQ/88OKSlBTfXBWQLKGK6NUACcahYNyob8vfVF7T9s9Ne+Iuo9hPF42Wj2wfKZ4Fsr1w3ZuVIS8GUqEIo2bdlPza+nXuFDuedTUpi/RLg2sMKsqinl8rVDKQZOtnm8Q4U4RcE/Npe+sVvXEMpSOrRopspMpGjIqk6Wq0JkA1QMXtBRtCjh4V+eZIWzzivfHwdE3nHc3giFHTDBlvH5Zc9RWNd1w1FSkp7sz3/Lblu4zJcBhyLjYZZmtIXcH2WU7SL5jC9UI+cIeE24sZ1tgY1MQ1Bym0fCVhGclOXi7xebswaSEyoIHErR5k9x2rb1EP9DrR1WL4ZVolRnUaYgkhTyQrvPTYF4Q8Qh7QpcfrRO/d7WO+LByVou8BpZRRSv1jpdT/c/r8c0qpX5pUU39XKfWSLdKOOOKII/458UHbLR/Tov9xVuh/EekdLabP/0PgP0op/ZxS6j8F/hzwn3yvA9zmfE5vmUZH1GSheQOlIZpEKBS+ULfOb2anGXRx+3O6E0vQ5hUZtJpOU7+rmb8l5vvuAOwtrclJrUXvDbvLnF9eVxS10A1JinEBXavI9nJc2wL6+fDm5nnf7hSCQo3q9vXXKpGSYtsWXI41fjBEb1A64kpPmQ8MRl621grdTI+f4JLhiI8VhfWMcRpUekPXO7b7ghg0cZA8W1N5upkl154cL/dRr8mvJMhCoaR1UssxQw5+BsM47WinVUR7CXO5sYqWCj0SKiQsZpToRz0yVeaiAA2No50sezuTUCpJxm7myZ3HzQONjfhUYA/iPqqi2FSjFHRgpl2Dn2n6u1CeNdh5ZGcrOvUSlaLwiTbn+lgqdKXUq8C/Dvzt6XMF/CHg708/8rPAn/g4ntsRRxxxxHfDjVL0AwqLPnJ8XBX6/wH49xCuJcAZsJ4mv/AeqqkbTGqrnwawJyegoPOWzVCy7krU3kjCedLEucIWHl8FfKUxDbgWXAM8U/jWEqbGTjKJ4SSQ32v4zIn0Hd/5xh2is+TXQp+ye00ccvK1It8IHatf5fQnjliLommcJ0z3fJuQDPTL59UNSRHLSFx4dBaI3hCtQueBxaqhykYOfcZhU6IvHfYgnhrjIuJ1Ijp9K54gCgUy5EcvlyPeG29cneCDkZ3eaKDXqE78UbJBrptxbngrO+GfZj2FGbneV7idpriCfBPRY8KXmvaO/HxzD/rTyDhTqKAIZSS5hNlrVBB3RRWn4JZCsgTIAilCOhjMQYRLsruchEaTQ2LSEmuHhlAYfGEwNpKiFgHdRH/Ug1jCpPZGOJhQAfqVwleGdKpYVi1KJTbD/Lucnd8abuZjn0R85Au6UurfAC5SSr+qlPpXvt/fTyn9DPAzAPlnXkvohA+a9VCwOxS4jXBPoxWl59niwD7z7IY5tjG4Rl580ynCAfzUdRnnirBI3Fvu+JfufB2AXwiGy8M5Ppdpuh7BNoryGWTbJNmHRgacySSYhutJc/tG4WfQvuY5e7BhWbSM0eCD/GDnLYcmJ2aauu64P98Rk+LZZoa5cJRPFGaUKX7I5Q1o5zV08vt2L0ZFw+LIPj3ivdG+9Xwx00GhhykPdGqNqASm1fSh5gvhFWZ1T986sjAZd3UJ00V0gH4p110yibT0kHu0jcyKgcwErrYVjakonsrg0h6ApBmXkVQksd11GuXSlFKELOoDqDBdw+mFwak1hNIxFDLoJA/09xK+sridvHGYXtqappd80rhXZBtFt88YKktuPSp/iVPRj7E//kHwcVTofxD4Y0qp/z5QID30vwmslFJ2qtK/UzV1xBFHHPGJwCeZ5fKRL+gppb8C/BWAqUL/d1NK/0Ol1P8V+DeBnwP+DPAP3vdgU66nUjAGgx8N2ThxXjVUVc+PLJ+xrQq+cMgJT8vbIaIeE2acMg+RoUoylkerJV+uXmHuOgD8ItBNQyWVwAzqVqkWjbr1WDGdWOO6raK4eq7e9DOw84Gfuvs2n6+ecOVr3mhOefew4NBn4osBOBvQKrHtC4ZtRn0tzy3kMCzEKU+3BvPMke3k2HqQlk57zhFHvCfyZ+IbhMzspV0xeQOhbnadYqF7oGL/ALJypL/jML0BZXCNJlq5FkGGoNoFZnXHshQvo5nteVQs+HrQDL4gv1TYbnosrRm0lSi7VtTSoUjEMkIAPRrMzX3YgRmmKl1PATVLw3AnMb+35/5ii4+ad65XHB5X5FeaMOWb6hvL3wHU1rGuS3LnRXH6MvEJXtA/SXv1vwT8O0qpryE99b/zMT+fI4444oh/Bseh6HdBSukXgV+c/v8NxCP4g2MKochMILeeLPeMiwRKMS4D96qWlWsZokWbKP4ROYxR39IGzUT5yzcJHRSHVPNLzedw9fhcwLMUv3PVa3RvpO8eJW38xq/cNFJRF8+gvghoPxn2O0u7yXinWVLqkcfdgm9sTllvK/zBoQZNcpF9lmNUYtsUmL2ksYcM2rvgX+nRNsKTgvodqJ6JwmOsFIcHiu7OUVh0xHvjRd8TtFyvoRRffj0osmvINgnXwDhTjK8oHqw27MuOp+WS/kQG8zdURDkohMayS+Wtd4suEzM3sFo2XDYW3TvUBumJe5k96UFLX12JUjS5iJqCpG+CXNwBTJ/QQZ4rUVTfACd1wx88/wYn9sAXFw/5/2avsylnqF580/WgcHs5nu4VwyEjlerbaMwvBZ/gCv1TrRRVJlHOeuZ5xyrrGFYb3v6MpmscWT3gdOBxt+BJOyMMhpQlxoWYdkUn76L2MGV/bkX5Vr+rMH3GOM9QuQQBUAbJUwwyHA0ZclE7CMXzAWic+LUqJkwjg5jiWlO8a/ly+QrfqM/oDxnsLLrX2JvWTabos4wNMLRO2jUKQinGY/NVy+AN6aCYvx0on0g7qHlQsntdoc76j/rUH/EpQciRhdwlKUAKuZ5RiXCw2IPBjGA6CaAYouK8aHhQb8ls4OlsRt84MYc73AzjFdm1AxxDWfLmasbj8wVn8wNVNtCdNRyoCIVFBUVyCaIMSYsruV9uGDJ44aXrid+mkgRZ+OneGmshBSSd6EbH9VixNC0r1/DKYovWiZTA6MS+yemflriNKLPTqKBEwmVeFtLLk/5/GPhUL+hHHHHEER8lXmJi0YeCT/WCbnRkWXVYLW+Z96sdlR1Z9yWDN2z7gqumou0zUtSEMtEjL0jMZKCq+8kQv1Dka8lZvMlAHGeKUSui1dLe6TWkqXKuZevq6whVQNnIOBh87QiZpXw28WqNwm0hvJPjXYYbJGk9ZAgf3U50x6gYe0sKWrbIWgZDelC0ncP3ltkWissBeyWGGfpOTsg0ZT18HKf/iE8BQjHFHrpELAOmktZkjIqhsZP9ckKHhPIQO8vTtqZ2A0ol5lXH4DwHk6P2UqEXl1BdCJ3Rl5r23NA8qLl4zfDwzjWvnax5lo+sZxV+MCiVSI0l7qy0J28q8kGjXwikAdlRpGkA68tEqCJYcdi6eLrgvxk+z935jsJ4fNSsipbc+lu1+GWey/0KkBTaRGblS97Bpk/uiv6pXtCPOOKIIz5qHCv0DwsKmsGxbQueZSOromXmBio3sG0X7LcFaTRgEspE0swTk72tylMe8aW8OslYVFTk18/9V0IhTnK6FQWcHhTRJRm8zj35rOek7FiVLYusp/OWb52dsi3njLVUCbadIrMaecJiyQt+HlDLEWOSxGUFdeutgQKS/G5xoWlViULoXEkrYi38sWFh8LPIvar9yE/9EZ8OhHqqcLOIzQM2k37y0DrMTmN6EeGFfBo+esW7m4VkOCeFNQFrIko/F/zYBvJrj20CMdPoYIlWs59ndCvHvXKPrWXX3A0ySW1NwtcWX06CJs+t1W7IwFdyH/oqkYqAzgOu9BQ20PcWf1lgr3KaJxlfX8zITjuWdcssl+r7MGbs21xUsF5NO1x1Swt+aTgKi4444ogjfnBwHIp+SPBBs76Yow+Gg01cr2pWy0ZCIXYFaZPJ1HwxUtY9MWq6QaN3FtXDYDVqLhVLLCPRGcyQsF0i3fThlPhN3LBh+rPI/NUdP3nnCfeLDbmW/p0hsvUlXbB8fVXQT17roRGHRxE0TbYAhVT4i2VzGxyQGisT/zTtCjxkexE/hUzjZ4lhDtvP5uhJ4bH5nCK7f+Az8+uP/Nwf8emAO+/QJt46kYagGToLO4ttxUWxuTu5hN4NmPmIHw2hn5aGaiBzUtn3UxXdLxVmsNjOkJTYUmgPZq9Z70sqN9AHy64p8IPBOmGJxSISco1thJ6YjFB/Qx2JK7kP62XLvOgp7Mg864lJ8eb6hL0vKZ5JVd+fWDpV0GWeMhvZD5arfUW/ybGNCPySArxibB2bl1xRHxf0DwujJrtw2MNkguVz1gmMi6RRy2JuE1k1cm+xIyXFm50lrQ2qnxbaKbEoZYqkDdqDHiQz1JcQq4BujFjfKsAlXl2t+X2rb7IyDU/GJe/0K66Hiqu+4t3NQrxWJu7rDedXBSbTLkhZwji5wUavSV6jO31rr2t6WfxNnyaalCLUkXaWGFbPjx3vdXz+/JK5PdIWj3hvfP7eBVolumBZtyWbpiQOBhUUvkziE1RH7FnHw5MdmfFcNRVbX5GCwphInQ0U1vP0XIaiBwr6Uz0Za0krkCjX93BZ8taUS8pOaIt9LS2UZIU6qfbStkkKhpUUU/VS2oZ35zsK6ymMZ+EksevCzTgkuS/cPhGdohvEpC4mRTs6uiZDtZNupEjEbFL3NAbfmJd3QhPHoegRHw1+4q/+R/QnCfuZA2fzA9u24HBdonYW02oxZEownETcqwdeWW65PNTs31hQva2x/STmQLysxxn4E49ZDGSZZxgs4SqnesdQPJWf685gWMpNXV5AcRUnFo/0Mc2YMH0SszSgO9F0Z3J804sQq7iWN9X2XLP94cTJj13yB+69QUyKL1w94HJXc3+55Y8/+Cf8a7MvAfBr3Wf4xfWP8auPX2P7lljq55dSMfpZItmEaWVnFS30r4zcfbDmtGp4ephxfV2jVOLsZM/des9hzLjYzei7jDBo1MZRvyW7tNkjsYo43NO09yUlJ1uLSZseEmOt6E9gXCZCLsZTulOYTt2maqW5J42a/Ill9ibM3xZvCLcbxbXzLGP7umH/WiLOpIgoHynqxwkzJNozzeFVGM88uIiykWrec1I3bJqS3dtziqeG6GD8jOgUfvfn3ubWMe6Il4bjUPRDgtD6JjEC0xBkNCgNmESc6IR55llkPYXx7E5ynjUOczDEKlBVUhaHQjMsLf1SEZymX8F4NuLmA94X4jfRw7A1PNnP+Vp9F6ciX9uf82i7oO0ysSg9OPTe3A5OfJVIZUB5RXQS0xVtQicYRoP3RmxwVSIpEVvcpJuDDKx8Cdl5y7Jq6UZ3a597NjtQGM+vP3vIsy+fk3/kr8ARn3T8xPIJmsg73YpNV4r6edQkm/BlxFQjq2XL68trPlNd00fLb6S7HJqcgFAOlUoUdmQ5lyp6byL+1BCB6DUcLHYru1iz0wSfo6Jk3iYFqYgYFwgLGA5aYuR6RDxXJHQ9UmVyH3bese0LjEr4WrPIOqyJRHMTDDPFSJqE0REfDN1gSV7sdUOdoIhgZZdu9gbdfQiD0U8oPtUL+hFHHHHER4mjsOjDRBJqoZ9JzzvZRPKKaBTaRpKW0r3rHc/amgf1ltOyYXdSMNgMW3pWtVQdzgTe7g2HrsQdFN15ojzpmJcdF/sMFQ3ZNpEeKa6KE/6bJgcFwy6Dw3QajUicMem2dZHKgCk90WtiUGgtoRQpKMbRSjvORkINKteoUaGiFpfFmWacgz/1fO5kzYN6y3Yo2I8ycNUqcd2XrPclmISvFLGIpKjYNAXtIYdhqsYWgVAq2SnkEtvnTGBRduxPC9qYo7vnvhdJS/guQRFHTbAaYyKhCvQnkqmngrROkk0w3AR6KLwFXylCJrsmHZ4LR/oTGSwnk3AbIx4jTAHCU4jwMFquh4ohWq4PJd0u522/4hfzz9MlS6E87wwnXLRzusGhR6nA9DhF/fUKJu9600GqJ5uIbKSy460QLQZNNzoa7/BJT/GFCYLGtPrWX8T0Erqg0vNZiOmk3aKitKnGeSKcD2T1yNhZ0rMcvQPdAUozKotOIqjRPt3uwJLVDEvH/oHh8CARzwZ5DfYG24sf+a27Z5agCJgsYEwkd54QNV3vsDtDtpbzPByEKrgdcqwKGCJdcOzanLh3qE6TXELlgazwFJMwJ6CIKELUhMEQe0NLzkYnMucJcQost4E88xRO2ka7uqB1BWZrZdcckCAXm0iZVOD3TnYolXjXrjjYArcXx8VwPrJctHLugWebGcMmB5XYnhTcXe5oRwcmiY1BgnEOVEKn7Lyl7zKh+2YRXQSKSiIhu+sCc9ASH/mykNIx4OLDgkqSWch8lLZFY9CtbAVNKbaZoXWMO8ej3jCcGcpsxJrAYL79RcmNp6gGmmVGMoZYRDInmYam8PjSgQK3h+qRpm9r0OCmhSyUiVAElBVeuQo3KyPCLw8KHRQEhR4gtpYx6OntXqFcAudJuWJUFhU1voJhmcjPWh7UW5aupQtOWArAYchoe8dwyFBazkVyibF1jOscvTfoJBbAbiGDU984UlAMg6UZM1Z5S/aKZ3NS0nQZw8RuiHtpHdmdJowZ/WDQeZBt7TzQaSOGTbmkyMRR4QsZ4EYnHhwh5zaZ5sZgabgzUp/JStmYGePW4G7MnybDqN2m5MvmHv1gaS9q3JUhWcf/r3mNb56dUucDIWoOfcZwyDCTVbH03aYFZVSYdspxrZHWm5k42MEQO4PqDDuvaTuHUuAHQxrMlHoliykIM2mspfWVFLctseikPz+cQLzf8xOfecz9csvXt+e82dxFX1jcYeJvJ3lj1YM8v5tFIWSa9lSzfxX06w2ns4bNoSSkDOJNWIqc21BEsnIkzzzOBmZ5jyYRg8a1YjAXjdjNArx9vWLmpJXxrfUJzVWJ3Ri5bzQQFUNnuQw1QzD4qMXCuS1IO4fba0Jh2AVFVo1oLc9Za7k3FkVHZUdmec+7QJtKdKelkNIJcqAMnJ0c+PzqgjvZnm9W53ylvsN+V6Bt5O6i4aw6cN1W8tpsM4pHFu2h31rePMtl4Dq1b3wNwypSzjty61kfSnxjUZ2BLMo9HzXDweGeOaonMqt5qfjkruef7gX9iCOOOOKjxrHl8mEhSUtjtuxETdYZ1DANFm9o5L0mW2vCQfM0Ksp5z9A7Um8IXnPlpDJoMkffZegb97dB0Q2OVdWyWLasH2SAud2G21bdWvDKsCY9b7CphBqmNkBjxXVeJbH49IBXEMxzrvvNn+MSyUXII8NKqsA0C6xK4ePuxoJ1X7DrZPx5OBRSnbSTu5wVhoXaWtxatpqhgDCHuurJbeBZmJGe5cTG8Mhr3P3A55dPKU8Groaar1zfBeBJu8LtFNkaklUMS824MODS7WMlBymLoMAnZFdRc2tTnHQSaluYuPeAmw88XG0ojOdrSdF2c5JR6F5+T49gnmastw49KKpLhdtJK6dvM/ZbyzafKsDp9VVTKyDksmOImbRdkpZjRictlzEY1rHg0OSYg8FtNFxpknEkBXZS6JpBeNI3zJzDvYnFspDX2DRKHiuTllP3iuf1V674l8+/yuvZJQv7Qzy6XBJyqdD1MOVrqhesXG8WhYnHHerIvBhkpzBOVXQJzR1NdLILSPnUKkoKqyMneUthPFd1RVOVBKcwY5JMXeDwuOIL/QP5nb20ZVSQllvKhTYbe0toYZtgkXfUbsAHodG6nRIbWmsZTbp1LcxtYJ71nBcNle0pTMG+zOkLR4oWkpLgGZOwpSi4Xy3WfC5/yt1syzJreWe5BOA8P5Abz2FqIyqvcXvIduD2ivFKtCS2kZ1Ofwpp6Tmby+9dhhp9MJhGk6widhofFcVaUb8D9WN/+zq+FCTg2HI54ogjjvgBwSd3Pf/0L+g6D5zUDXubs26cvHmWgarqGb0hpnwS6ihi4WhRpFH8WZJNDE4GSMFrQmuxnUaPoAZFDIq563lYb3gr73k0X9Ff5TJ0m/q1N8If0yn0YEn6JpJOqgIVJ+e4mdAXY1Ay+AwSmaUHhT1Iny8ZGGcGP0tEF0l5AhPpBsdb+xVaJfZ9TttNKtROPKr1IHznZGUXoLyE9Jp+UsyNipQUaernF5cSpN1fF7xlTnk423Av39KGjGEKsDY7K6nv12kKNhALyJgxUSyRCj0oMEl69/P4fDuaFGpy1VNedjwgNDerI+fFnuHU8M2oOcxydGNkENlCfjmdnwFcK78fiql6bzS6l78Tvn37G6ok3iVZJB0MoZfqNhQSU3gYMiLi75FkritBw1NUWpqocTee14PQ2+nuJPydEXRCbRw2qdvq3K885WnLvXLPqTlwx2x5rbjifHng8VmJSvp2eB8z2bFEA3p8Lje82RHudwW7qEibDDeKenM4Ed57LGQnNBwyBpUIM829esf9YoM/0/zaw5L9MA0bJ/6qPWjiUMiuY9pV+aUnX/YsyoEQNId9ThwMWidKN7LKW8p8pJscDnWY7p2gbxcyayLzrGfpWkozMESLudmhJgUBFHJdaJOo7EhleuamxSnPvijQJMakWTkhJZR2GoRkotgmSvBGtpmCqvuELzXjXKF0pHbDrcOiChIuoweFGeT/+SZRPBtxu5Fhmf1zrTHfiWPL5UNCMlDWPa9UO7ZuoOsdQ2Yp64Fl1bLrcrqbrflkRRsag/bqVkV6u43MPE1S+JkmabHarXPPK9WWz1dPeL264gvZA75WnNNdF9JSUcjAptFkW1mYldwHt+wNX8qw0t1vOFsc8EGzOZQMjYPeoNYyFKzfjZgh0Z1omnuKYSXPIZpEe8gYvcGaQIyaGG8GrmpiXtxQMJAbQiXG0UyrOehBs98VdFlA7Sz5FczfCQzXmqui5J/O7rNelDxtZqwvJCU+38iCmjT4QhEKsTUVJoq0M6JK6KSfM2NMIrrpfI+glJIhop5aUsj/C+M5yxpy7bEqcjmrWR9K2nWBeuKwe57nUU6L4bCE/jQRK8mhFKGUKBVvzrXYxIroJuUKX8n3YxlxJjIEg1JQ1x195ukXGX7tyC5lm8/02qkEUYuwCkTMszht6HpHuM7E0MpMA+EykDlP4x1v9mcYFYlJ83C+4fqVkraYrhU7DUF7C+r5UJSUUCmhvCLsnbQ6tnpqucgbVHKTWKmR1oIK0K0sj8oFn62v+OH6KcNnDF8t73DY56Sp3acGhe61CL2KhDrv+aF7l/z21WNq2/NWe8JvuLtsdiXOBfS0YufWE8uIr/Q01FakQTMaWS465+iCZUyaPGk0wgnXNhJUQkUNAZKSwkerhJucvcZkCUnLG2vS9NHe6ioAdO4ZFk5SjCY2kWpFXJW02F2n0dB6R+0GnAsMRSQZg22hvExk24AOkJymP8/pVi9XXPVJZrl8kjJFjzjiiCM+2Ujfx8f7QCn1R5VSX1FKfU0p9Zff4/v/tlLqC0qpX1dK/bdKqZ98v2N+uit0C8uq4yRryIxnU5fsTE6dD1glKjIVpEpQCdSo0N1k3uMSqvTcXe0AeFhvabzjW+Up+22B1olF2VHqkVyPzI1QtPQL+63kIsokqZg3CtcINzkUimGq7nwN+k7Pv/DqW/yexVvsQsGXdq/waL9g2xbsVU28sGT7SHbZY7qM6Bwhl239bZWtEkYnrHmeYt6Nmug0hCRvzTqhsoCuIj6zROtwe5G/j5c5g0u4vZZ2TBvJIxTPDJtHC7abitha7OZ5NdOfQH+qJAZsJtxxPWiUl3OfrHCkdSeVXCimwa6R3ULQ0mZIGqGWAg/PNvzY/Ak/UjxhF0pKM3KRz3mczXkrnjAeDLaV4yWNDFwL6E8S6U7PfNHhg6bd5cSNw7TPWwGSX6nAKJKewhFMQs9GssxjdCIzgWXRsnA9XbB86/qUbTVjXBtpgfmpDTP56YAcc/SGGPREQXzxIoR+tFwcZvwT9ZAnw4JMewozirWCDXS9I0bh88fMEK0iZlJLiSpZ4U88qvKkIRNaYwBtFdGr27zMbKPIr2T30q8Mz9yKr9Xn/K7VO/zu1ds8rNY86RY8Psgu6+l6ht/kxFHB3PP63Sv+1btf5fdU3yKicepzPDos2B0Kujbjm+mUIvM0XYayET+LQkOdXufYy7XRqowLMyPTAcodufHcrfYM3nAZFXGbiTqz14ydZT9m7EPBLpRsQsXlWIvOIBi2Y4GPmk0nvFalwa8Cob7ZXSqya01xqTHDNPTfGy73NW4ROJsdCHc1HRWmNbd6hmEudFBfyT34siC8h3/+Cl0pZYC/BfwR4G3gl5VSP59S+tILP/Z/Tin9p9PP/zHgbwB/9Hsd91ihH3HEEUd8P4gf8ON74/cDX0spfSOlNAA/B/zxF38gpbR94dOaD1D3f6ordHQS+1mfM0y9uJSYBnsZfS9ubyohve5BBjwqyUALk7hX7QH4bfNHRBSVHfmqPaftHSFqLvo5Y9JsxpJvbE5pNwV2LVFafgZqMZIWnmEQmp3tRCE5TgM1f+J5eLbh9y+/xR+ovsZjv2Q/Ta1mWc+bQTMu5oylxrkbHuTUizcJXXoWy5aTsqGwErvVTBSvrYnsFURjpU87VfNZ5vE6MbYGtZ1EMo2WcIEoff3u3N4OBs3OkDqNHZ/T6vo7QTwx9M32BlGN3pQAlSgWQ2cgOem3myTiDp2kvLYQbcRUnrOVnOffdfYOv7/+Oq+5a9ahxCl/2189DDlPOkufMqKThHgzcLuFVUZ2TYUdWRcl67xi3DtJfUeG0wQFg/h6UERM6ZnNWma5CGyUSlgVqexAYUbO6gP9yjKYnDAqdGumavh5hR5KS+cKCUpxCf9CknwaDEPrWAdNM2Q8zubU2UBuPUZHymwkJoUPGg+ETMy82nMZxg9zzeEzkTuvXlNmI2/GM+I2x/ZCndSjzChMJ9Fv9WOPOwTac8c4s3zj9Izz/MBnyitWrqUNGZemmv7W6TXRibwcWeYdhR7ZxZIrX/Nuv2TbFwyHDL2xDH1BP+2qbgbdSUfZienng+jQWbap4q2k8EnzWr3m1XLNzPZ8wwYexRV0OabRBJXxdrXiC/lD9nVBExzvNCuetTVjMGiVGIJh38o9EUYNlaeY9dxZ7NEkHl0v2b5ZUz4WCqzbaQ7bgjDb87n5Fa/PrvlicZ9Nc4q/EErxMNO090SElOzL7Xm/jAodeAi89cLnbwN/4J95LKX+Z8C/A2TAH3q/gx4r9COOOOKID4rvr4d+rpT6lRc+fvr7friU/lZK6YeBvwT8B+/385/uCj3B5bYmRMUYDbt9QRgMQ+7JMk+KUqlFeyMWek45CpkiRoWfSs6IQpPQk8nGOBo2qeCbnPLEzTgMGdfrGr1xuO0Nu0IT55DVAwPQ4TCNItnJkgBQlWeRd8xNiyFxiDnrsWTdF4SoyWzgME90pxrtM3w5MUqm6tllgZOy4UG9RZMYoqWaKF6VG1i7kSszI2wy1KhIgyHk+rbPrgexKwCpOMeZiDPGuTBQQjF9rxMbgvFEquXlvR13ZnuaMeN6X9G3juQn+XrhmS9b6nxg0xQcoiL2GoqIygKxN5i9kQAFp/Fes8vlgS77GVdhxn27IVOBU3ugiTljMgxz2WU9MzNGckwnEWmmg+QUTZnz1M1Y1i1GJeazia3STtTTxomwrNdSYeYRbSKl88wy0X+33nHVVVx11a19QAgalQVwUoTGzKISmEbOYbZW+MoSZgFswtfpOR2z1UQso9eMraPROdtqZFF24rWS5DpTgHOBsBhp7+YkLdedn4G62/PZ5TU+ad5xJ0Iz7EBHMNMcwQyQ7SLZxmMOI1mmcTvNfpfz1n5FFxzroeDNqxP6p1Kh263GJYWvI74yXDQzfll/ln+sX+OinXGxm7Nbl+i1o3iiKK7lnuqXiu5OIiwDqvTYLIh3/2Q5QWPhYNjuHPt9QXvX8ePLC87zPduy4CKbE4Ncd7bRDH7GP+5f5ZvLU4yK7LuccRTGkTaRGOTcAdBryAPzsucnV49ZuZYvZq/whf2rhOuMbAt2D0NjiSg+Vz3jFbdGq8QvLpYkbTFdxHaT/cZL1BQJvi8vl2cppd/7Xb73DvDaC5+/On3tu+HngP/k/R7w072gB8V4WfC0dRAU6mDQQTHWBrUE4wL9LDCOCtsolJdhU7RCOTMu0Hi5kL56uEsXHG9tV6w3FbGzeBvZAr7QhCgJ4r6IhEKCMG7YVtYEYjHiawNMlqGTV4wC2tHxaDjBqcCvHz7DFy9f4WpbSYLMqG+56mOtCZks5noylxr3GVdlhVbp1lSqmDxJ7pZ7KjvSjY7d1qFGTeo1sVZoM22bDRNNDkiibhwXgZTd0AsVptETD16hrDzGadVwXjS8Gw3ea2IvA2aVRbJqZF70ZMaz1znKJhIRU3hZjHaW2VuK8qm0avqlob0rg7pf2n2Oi9dqft/ZmzzMr+VlRFHpgbN8zzAzdKNle52hPNhWlKlxr8ivNEOseDrPsNVIWYyU+UiaXohuMOi9Ew1AgphrhqjY2MA871hlEphwua85bAtSb0TV6xIm9zgX8FmgHxWmN7eKyxvDr2Qm9e8LOoMwLRoRpFpwGgWU2UhpR/zE61cqUeYjzgZ2QdGaaQHTkCI8Oiw4DBnhOqPYT60mQLmJBqvFO8bPLNFphqURfxwFzZjxdrA8uVxgv1FyOm3kTZ8YltDc1wyF5UItZFDaWWgtalCYKY3LtmAbeb2GxWTgNhspq4Eik3O8iTK4jBtHfiX++r4qeePgaB867s92XPclY2dx/cQNv7mOdyXreSHtj0nDEauArfxkiDbdTIOGqFjvS96qTjjkOVddBZ3YV5vJs18NYiJW6YG56SjNIG/CfSLbjKAV7dbiSzEie6l4OS2XXwZ+VCn1OWQh/9PAv/XiDyilfjSl9NXp038d+Crvg498QVdKvQb8H4F7yEv7Mymlv6mUOgX+LvBZ4FvAn0opXX/Uz++II4444rtiEp39cx8mJa+U+vPAP0RSSP6zlNIXlVJ/DfiVlNLPA39eKfWvASNwDfyZ9zvux1Ghe+B/mVL6NaXUHPhVpdQ/Av4s8F+nlP76xMn8y0jf6LtCJdnyJi/KQju59oEh1Jr5vMWcRFpdkOzUDvESOhFPB+4uD7c0xG9tT3m2q+k3BeogXhqxVIyZIeaKedEzL3p2Vc9+WTL2BmUjRTVMlbZB9wrTTJXb1MrxueGqqfjy/j6PhwVf3d7h6bM5XGe3f4PbqIkql0CJoMd0AIqkLOuwYFeVGBfJMs/duVAtF67D6ogPGtWL0CbmYG2kKgbWM8OwNKgouxOhcEXUcqS6yVjd5qitwe4npepOLomL3YzOO672FeMuQ40acqnCi2yUgXEzv01EIktQQPSG4lqxeCNQf2OHipHxtKJ5ZRrk7jO+2b7C1asVn1muWWSSriNxYpohGvl7JtvdaET5OM6kMtODIm0cftA0C01RDs+FKYPGHhRuL+2QZBRjY2lTxVUxcJq3VHZk9AZ97cRJMk/4E4+dBVZ1S2Y918XIzs1wz+RcmOFmoK7RYWqHDOIRkzR4nVBZRLtAWQ189uSKzy8uMCrx9f25OBkGTWYCmQk0RU6yUqHbvcI/KXhn78ArsisJQQn55E3jEAdJL+fCF/Kc+iX055GsHqjcQESRgvzt1VNpm+kxEXKxtFW9JgwZptXkB3GiBKGfkuS1HxbiKNk8TLgHDQ9WG/JpEH8Y8ts2nopgWsjXkG1AecvTdMLmRAI01No9dzhMYFuprLNrRTJTilMFvQI1GyiLkckiidBrdKMZx4ovtg/IypGhyXDXUqHfWAkDDN7wTr9iFwq+ur2D2UkmMEy755vFN3yvVeS3gJcUQZdS+gXgF77ja3/1hf//xe/3mB/5UDSl9G5K6dem/++ALyMT3z8O/Oz0Yz8L/ImP+rkdccQRR7wvXpKw6MPAx9pDV0p9Fvg9wC8B91JK707feoy0ZN7rd34a+GkAuzq5pSQy9YhJ0idPIFS1fOBp1Ay9QffilR5mkbM7O3509ZRhSqJ4tFnSX1S4tbkNSgijwmtH5wKrouVOeeD1+TXdqYQixKQYguHyUBNbS7ERj5SkYeDGJ13TdhnvHJZsh4KrtiKNBjNMXi7j5CzXRMwooqSYTdWZlZRz1obYasYsERYDbSHV7nooueoqmuuSYi29+NElzuYH7lZ7rI5ceE2bOZHrT7F8ee6ZFQMpwTjYSSAkohq3k/f4w2VFkxXQSYRXMglsvBXo7Lqcw1WFeyLV2LBMxFKL3/sIpovoXoa3KqbbC1wH0L1mty352ijn3ntDSmBslEDjJhP/EAv9Cvoz8VHXRSANBlp5nNAbOjKhuiGDXT1O3ige6KWyVslymQud0KjI2Frya3mtxloRSulz11nP/WrHnfLA13RkE5Zy3AtDtpHK3AygQiJmin4Fvk4w95SznjIfuTfb8btXb/O76zeIkx3ndshZdyUxKXpvCK0l38r1UVxCupyGrpMHy7ASf/04Sf7VKNeKLybXRSNCr7j0WBMwOnKS9WxPCnZnOc0U5mz7RL+UHSlJYffyN9uG22COAKBvZjgwnCbca3t++/3H3Cu27MaCR82CZnCE4SaNZNpBZNM8YRBbgt7kqE6T7UTsNc64HfDa6ePWqkHBEGVQfFYfbsMynvYGtc/Ei/2QM1YOHcSbCCU7ljg9jUOf8bXdHYZo+Oa75+TX4tvQ3ZFzMCyfu3y+TKj4EnouHxI+tgVdKTUD/m/A/yKltFU3kSVASimpm/3ddyCl9DPAzwAUD19LahS2Bnryq4hTEEAWyKbhoVIJNcqQhghjgNKNnOd7nvUi6ZTUF7ngb7Z2wSmGxtEFxYWOOBNk224GZrbHJ826L3mWxHBLDzxXON7sfQzEqNj3OWMwjN6AicQs3apYE+BLxVhpunNoX4mEWZAhZK9RXqGiIoVEiurWQOvJYc7Tyzn5I0dxKTckeeR+vePV8hofNbu5+NnEqQWkp8FqSIrMBIpy4LBwDK19buYFEhgwanSvUaOwTMKgxSMGGAYLjbk1tiKBdhFcZFg6Dq9Y0CdEq2juGA6vyHG7VwLZnZYiG2naDH9ZkF0ZzCj8+H4eYLKhGefymqYHHT9075JF1svfvJ7hDzIID52RPMkJvpxaMwHsQRav4hKiy3nLnOIKL+ZXGzEeU14xLhR+EIZNaUZKM5LblahOgWwN9UUi28nefZgbDksx7eJex+myITOBECWB/nKs2YSKpWm467bcrxaM0bDtCna7EnNtydfyfPP1NDiO8gY2LhN+5XGzAZ0Ufu8we0tMCTKITlKAkhMVZ7MteSdq+sWezAT8KtDek9ta90rCN/KIHjVuB24nbb6xEoZNMlIA3ZIFXCSzgUzLvbP3OY+3Cw7XJTTy2utJx3GT4DTOIcw8OgukQUv+ZwmhikSbMK0m2yjsHsxULL1g3yLJWYW03jZVic8cNLKIx0yJqVihMDnYOD2uV3hvuOoqCeS4yjEdDLWmPYXuXIoM9JRg9bJwU0B+QvGx8NCVUg5ZzP+LlNL/ffryE6XUK9P3XwEuPo7ndsQRRxzx3aCYzNQ+wMfHgY+D5aKAvwN8OaX0N1741s8jU9y/Pv37D973WFG4rqFQskXNpHpR9UiZD6SkaMaMoXWYg54GOBAzw7PtjEf1ivUg/GjfG+wUbuH2kO0jykO/1By8paHmzai5LGrsVK0rlWhHR9Nm3MSsJSvbwnEub+PJRsJgWG8qtInCjY8v7Ea0qErHpWJYJNQrHa/fvWTmBp42M6lGdxlqUFK5RsVhss8de4t+nFM9AbdPhEwqfh81bcjogiUlhXYRc5MbGTQhaHaHgjyTr6nKMy416aCJk6pOJcCLBa5tFeogPG/fGvzCo3QUTnYp1XAsIkXuKfKR9X3NJua055ZkxSUxvSIV2I++8pTPza44hIx/8uQBTVtRXkC2SwwzRXvXMJwGYh0YKoWqRx6cb/ix5QUzO5DpQOct68EIH9qrm6wLopWMSuUkW9ZeWarHCneA/BJCntPPLbZT6JtKL/FtfjkAbXDsuwy3lXqnuBYrVjNEhoWlXyqaVxPus3teP7vCqsjjw5zrdc3TwfDoeskbd0/5Xat3OHc7XiuvhSfelISDozjIkFqeswxvhUoLYR7Ilz1lPtD2GSHeDPqZ3CQnNS6gDga713id8faiIrmI2ZkX8krl+lJBhvW2kddqrKG7K8NgpUDvDG4t1sXq0rBzM76k73FaNVw1FfunNdlTe6ucjU58fHw5DThPPLPzhiIbWbsKTy6VbO3FgdE5Ri/q6tTfqKClyu4OGZd5TW7lhGidiHkSLYZJxFmAPOK1xe01eg9MdtgpKdzUcko6EXPxHxrnohAFsRC+0WG8NHxMi/UHwcfRcvmDwP8I+IJS6tenr/37yEL+95RSfw54A/hTH8NzO+KII4743jgu6M+RUvpv+e76rT/8/RxLRaFECZVJEfIElSerpJTY9gVt70iDCIH0AO6QSFaxe1Tz6zy4fSJxMCSbCLlUudk6kG1H3N4Rcsc4M/R5jh/s9HdMf08Qf2Y0DKuplNLP/0LVa/TeSh96+p6JMuzUfhqgLhPxZOT07o7fdvaYz1aXbH1BFyzXriTYCIPE6yUs3TQEVJ2m2Crs5BdtOoVeO75ycZdHpbg59ocMPdEYF0XHvs9Zryv6XUGvE8om6PWt97Q28sT95OmuR/F5d4fpubaaDgurAVWP+CRDTrRQDzMTWJ0d2LrI4WySXlaeuydSJv3w/Bk/Vj1hFwoez+d8fTYj5JbYiPpWJUh5JFsMZJmnzgfu1zty7Rmj+GjLiRdxiWle6J/PInY2crqQmPdn2ZzOT1JYJZTH6JWEccwUSSnGmYRony4a7lc7atNzPVR0bUY2cPu748wwGEt7ptm/Bvaze37Pg7c5zw683a7Ei+RpTnGpSTbjS9scfgT+1fPf5DP5Jc+GGaM3mIMM3W8UuqGQ6jwUEmSRlIRV78eS0FpUJ39fsogIyiuSElWvHiQi0B0gOkNwcmw7UQZ9DrqCmIt//Q0Nsj+BcHdgdXLAB8M+1GRXmnw9URI7yyYsac8zwvSc3e65t42/OaaSSp0iSFRj3hGilt1TUGgbSVG8dczAt+9KtNwD49ax1hVlfXOygSIQRnmd9GzEukA/aFBT+EyYnotOzF2PrhK7RUnfCt3VzwOUAVo5H/plhkR/wnvon2ql6E12JSAnWafbi2h/KORiAjCRcREZdxrTywJVPtZ0fiZJMExitTIxRNmiJ6tQPmBbjW0t2iuijuTFQIyacbCEwZAme1NVBJSLaJMIg4a9nFq3Nbjt9MaTbgZP3KrlfCXtinzRc1bJQvQbu/u8sT3h2fWMuHcwaPQgFqo03Fqv3kz9+4UiaXmDKB8runHG07p6bqk7jyyKjof1hsdqzlWYCa+3ky2zHiC/lrZHyCbV5bmiX6XbFB8Vn6cPJZ3ISjGfaoOGVmN2mkEVrIFZ2bNYtLS5lzdAlegmRsu77ZKF7ajMwKv1hsuHNWsW9JeyJR8Xspi/crrhXrmnsgO17YlJs/UF2yEnhOdmXLZ5rqrUQTPMDZkNzLKekDRXoyFpNylh5V042sQ4YzJRS+R3G37s9IIfrS/o4sRg8vp20d0/VPDQiKVDlfB3R15d7KntwD5kXHYVYzcpLycmxzizt0n2hRppg6PdFRIc0j9f0H15w/oQm2HdalKXw6iwgwKdZDBsxbrYHGShC5UM1kMp50ASe6b7Yro8QiXnM61GkkoczsSsjiKQTwvo6M3tQN82CdslSFrewGqHzT0hj4TS3AaJxGk4ezvZ9JpdlzN4w6GRgA01irpYt5riUpFfyyIccrnmb46lvSL655bNVSFJSuNUMCklpIIbskF0Nzc/xKCIKEo3UtQDzXL6+yqPzT0eGGcvVFcvCUeWyxFHHHHEDwTSseXyYSE66M7TZAKVJOYrwdBksJ+4b3NPPusZXaQNBSQJojCNKNd8JdVBqCOxDCSd6BtDd2rQ4/PtelLgSs/D1QatEldNxeZQ3hoW2TxQ5LIn3Yfi1pvixn9iYoHd8oqim3YYhdiUxqB5Z73kjWen9Jscd+nIGnnskE2q2MlK1k8UT78I9IvIcGLIrzTZtdDS9KAYVoZxkQh1QJt4a+x1GHLYW/IrqeySFn5wdRHIr0bG+cQNLy3dHfC1J5SaUEi4w7BK2POO+6stMSneabJbu9nQWPqxYnOuqaueIhvpgaG37HdyLr8y3mXTFzycbZjbjt9x/i6PqgPv3l0I/1zDvO64Ux54UK4pjdjPypDX0QeLUgmTRYKL6GDIJtdo04OvMq7mFdnSU2UD+0XP0Gr0KGZhejRT+2V6HfLIsuq4X2zJ9cjb3QmPtgvSqBmnFtr4IODKkRgVYTBoG9l1Ob+5uUM3OrbNNFhfBTotiuFYRJRKNDHj3XHFG7sT9JUjW0+7wWp6/CkA5KbdpEaFaSe1a5jUm/UU1NErsu1EAqiBk4Eut/jCYrsXPF9yWXDGk8Dq/pYfOrliZnuakPG0rXm2q2kPOf1liW412VZaIjeVvRmStEOiEpO7k55e5TKYZ2qzaGl56VGht5ZttxDOeavJX8jTdTsonyaKdSQaaM8M40J2w6GYdBH1cKt+nrmBZ9bzjBm+N9IiixNFNReFrMRHgu8cF4cZpRvROqHyAF7L9W4SthrxOtEtXiKZL3Fc0I844ogjfmDwye24fLoXdOUi8XRk3EpYA3lAaaDT2J0hmURYJE7qFmq4SNCmAr+TfjPquZ1uMuLHgU2MS01zV5G0lZ4i0qf1XpPpwGJy7RuCVHtKJYpspHSedrSkqNBThR6NBBzfzvKmAIE4Rbgll0Anxn3G2BXYnaHechta7EturXS159suJr0YuHsmlc3jiyVJ55QX3A6OoovoQiLrLnYzHm8WtOuC8sLIAMxLP1SPMlTVfUDd7FgyiCcjZ+c7+tHSnOSkqCnnHT9y/owfmj1jPVZcHyraLEd7hdkAaIZUsFtpskpc+qLX0Mpxu73jzd5yGDJeXWxYuI771Q6tEhd2RttndIPlSTNjCAarowRERE3jHYO3WBOp646dV/i1Ib+S82EbcFtFu8vZFgVGiRBL95r8UhS5N3OXaKZoMiXCljY4vrR7wK8/ecjunTmm08RT2XF95uEzXputuWhnvHF5ytha9oeCtpOhYYrgCk896+mWjvHgpPcdNW+0pwzRcrGZi9dQknN7M6tN7rnTYHRTH30QWqO5Vb0q8OpWGISC5CJnp3vSiWIzr+i6ydXRxltSwIPljh9fXvAj1QW5Hnk2zvkSr/D4eoF+klNcqOdiMiXiNh0mssEBOBjiXFMUI90K4o0i18hOODQOPRiya4VpzeR3I9VzyOQ42RaK64DbBXEjVfK3+0UUenE1cn+55YcXlwDUpqey4hW0VrIDTqPYD/tZJBSyK0g6wcGwzmqGqicl0DZKX300eAU2C1SLDqNfbkX9cXHMPwg+1Qv6EUccccRHjuOC/uFAq4SyUaKybMIVHmsjITfEUmTH5aznzhQz13nLVkG3FDqYvokqA1IWMRNDJtSR7tyQjJJec5/Ir2G4KHirWnFWH+i8Exk/YHQkM9Jv7QcHjb31y04WxlmUnmoCxqlUdwncVG57jWo19qBvXfy6s5tqUpgmphPTbe2f23cqkzgrDxTWc+gzDnOH30mvOxTcxsT5wTBcF+i9oVzfMA6EoukLSFoiuyCnuTNV0ncTq7M9D+cbdkPO0+mc319s+YnFYz5fPmYdKq76ii9sSsZ9RrZhim7TjG1Ov7RQRNIgFgIgzJRgEtu84G3A6AUhKrpJoBUax+AVh6uKtxBRTFKgsojJAsYFynxgXvRonVgfHHY/eZd0N31gCXUegbFxFGtF/SRSXHp8bWjuGPxKBChqNuJ04J1mxdcvz+i/tmDxSBEcHGbynJdZx918R+MzrAkEa259Z4JKKK3InWdRdjgbWI+aOBo2TcFX7R18MAwHhzPi0zLOEn753ALQNJqkFbEWf/CxsoDDTbMBu5frIl+LP7yvFcok6mygtCNKJfZZTooK5wIntXgXPqw31LbnYlxwOVQ8apa8eXXC+Liifqwon6UpUFmCwJMGMwgN1h2EodUvHHklPeo03StqquhvaJRuJ+Ird5Cd5zCb5P96uoYzjarF718CxxNqNlLWPYuy56xsOHXC8KrMQEyapnaEpFiHijgYMOJtAxB7YavpQeMbS28DzsmsKGJg0KLdywJlPt7emy8FKUH45PZcPtULekoQO0lrxySMjSyqjjwbaWcZRTbycLlhkXVsh4I6G8hOApzAvstotiVpmBYaI9vzFBTJRvwcSAbbQr5LVBdyYW7dgu7coXXCe02Kkg4Ukmb0ir5xkhQjnRBRvGURU4+yZR2FWpWseHgQ1a31LUlodPF0pFq0FJmXdscuJzzNydIU0jENWENveNqIF81hn0tikZU2SigS3ND0BoPZGvHTaOQm61dKKJNWWhV61PQLTfNgOrcPWs6qA/sx49F6ybAVI41dPtBHi1OBB27Njy0ueOtsxWazwjbCZc624LeKvrEMK1kIVHg+UFOZ+IX03nJockJrYdSi+pzOxU3S0o2R1E3S0nDqSSeKKhtZFB2H05yul+AF3Wr8IoilbDbSeSseM36yn8003Ynm8BD6+x636nmw2rHMOy6aGc2TGcs3FfN3Av1C092VN4qnzYyZ69kOOUYn5nM5N1ZHnh5mHLoMH4S617S5UE1HTQ88RdS9aZyseutEWo7ktbRFhoODg4EoLcQ7JzvMWeRxtaC9KHA7jWnlnOabG0kspFGz7QpGJ9a8KSmhcyoJVAExb2t8xrv7xa1ls2k1eSPXkC+EtjrOhEqoBwiT1a1K0j6Jg2EwiThq0vjCcFFNGospn+JWnarlGgy5KF/FaE5jOglvGefSWtJK8oDD5E10k7N7o9YtjCeb1NgqKGlL6XT7kZS6tQUe+0kbEp/n6qISzgZK9zwA5aXhWKEfccQRR/yA4LigfziIUWH2Ft0pvIaUFHXW83DeYVWkMCO58Vz2NU+nIdsi71jmHdeu5N3RMgbxRUle31aJSiFbvOJ5HqntAr4wjAvDUGVktQRbxATBa/rRStXhpcK0N479iufxWlG2iXqEoDTRSPWhJ/pXtBCXnlcfXPL7zt9kaVu+2Zzzj/VDtpuMaKWKfy6uUFxtK/whwz51Qt+L3PpgkIRmx6Bv7VLH+STuqCMpj6gXFHi+gvZVqRxfv3tNZgJfe3KH/3975xZja3Ld9d+qqu+6L307fXrGM/aMnVjKjVys3EAhQQjI5QGDhESEQvIQFAlhCYR4SJSXCIEiIoEQUoQAESkgIC+A8EMgISESD5DEJrEdj43tsTOe6zl9+rpv37WqeFhfd5+M5sxMxmfmnG6+n7R1unfvvU/Vrm/Xrqq11v8fXygpz3RFfxi3+Fz+BHNX82R6Ria6Uj7LA9EYtQBbBMJaQAwhEbpZJKTDEq4IFNOGeVFT9+4qYBo0Qh2trr7UQxOKex7bRtq5GnVEa2ldypkrmOYNedaxvjWYifSGfNry5PY5u3nFpk+omoRmN2H1lIFo2DwJPLvmA3vnbKW1KhQGQ9WpH+nFkZbtwK113A5PZpe+tcYEDqZLvm52RB8sVZ+wXGtFLkG0OrFST9MQoe8soddCG8ywQ7ERf6EQWTmShY5rPbMUScuH50c8MVnyf/PbrF+dkrda8Xgx9hLBrixnx1NWeYd1miJpTCR4oWr0AjliQhcsZ0dT0pdT0jO9HvsJ1Lf1Gol2SEOMomYbpRbVdVPVQzGp1wK9xmKri4qlIS3Ra5v6EirRa/gy6FlCP9PdWdNeWUAGp9XHYZlStZamTugu9HCBg2KJj8KmT1g3KX2VYCpVHA1+SCKI+vmMQbRydpXQbpy+/xHIAvmQCjlPG47r8qHMN/qZQz/0jynXekIfGRkZeW+JEMcz9HeHILilrqCjVe3y9SRjN6/YSXWJfLee8ZWTPZbnBcYGZCcySVoMEWPDZd6i9EYNElotUgrFoOA2aJtIHwdzAzDOMytrut6yWuX0jcOYiHNeV2H3H9kNxhsyaLZfFCmpEYcg7RDgudCJHq6VzPTsuDWnSalKdEmgL42qM97SVXQ2belbiz12FHd0VdlNtbAk2gi1IQartm0yWO/lkTjvKOcawFsuC/o2H3TBI9Nb+r5dpOl1JznzV4XsPNJsC75IeKHYw0jkmclcS9pbXRGGBHwmqmF9sSlxEIqApIMt2rCarHunZecmEkt/KdsQOktvLRIspgHbGFwd6fOhGEtAWkO1yvDB4KwnK/T9SJxnt9zwgekZB9mCLlqcBD7XWZZprgUpey378+HaWM9ovSUEoW4SYhKpb0E0VoOrQx/8OuHETLA2UOSq+GiJLH2i59irFFnpDoKoqYhx1pPNGpwN1FWKHwKKpjWEs5Q4xOmyM0N2Oujk7OhZ+DPFMd84eY2pa/jd8AHqforpjeq+DPZtphHiuaP3gt2q2ZlUWsjUXgXr6y6h6dzlDk0L2aDZDcheQzqktPa9pVsn9DFBgtA46HY96a1KVR/rlHbjLvXhTTv004AvI93WkG7pB+3xIPgyELc6XN7T1454mpKeqKyGqwWfWqK1hDRytpXQDBpJ9Y6jdB3LLqNuE6hVw0i8IBefLauKjEjQuEt1FYPyRSSUPTvTDc/ONJ/1cIgzPRQiY1D0XWPQXZEeMEI4SzhyU2KERZFR9Ql3Tub4uwXJ2tBPAmcGEhOwJpCnHWGi28guCrI26oUYhVDoVjSkmp8rwdCVQj+JFJOWWdpw3E3wa90SNq3BT/pLjZYL1DxAjxNM4gm5RYxuTenM4EajfbAR7MJx52TOc9mTrCcZZ12hglRpoJ9ptsxkTyeknUnFvfMptEJSoRf0RUDUgKkstpIrd5oiEGc95bzmYL4kdz2vAufnKaa1+DxSDopUTgKdV50P3UZrpR4R2mXKH5o9Tja6lT1fF2pIMY9sRI06jId2Dv3Mk8w1IwWgqx3rk5I1w5ecC6TTlllZY4icbwqaNscXkWZXNKPDCz6HbisQp/1lZpLvLCKR1OnsmDhPYj1GAqVtKU1LP7Gc7hW8FtWgw7rA8fmEfpXgznSSCnnUKmEXqW8HuqkG+/xQcSkBfGuR4ffaO16tt7hXTTg/KzELh1urAFY/CbDTsr+7ZLfc0PSOwzhl0xpCEExtSM+N5nmjeeW2hXYGMY1sZTVPpyfsuwVGAps+5bM8wXpSIJUd5H41W0i8EHvBmsB+uaJ0HUd1ydF6ou1sEz3aSQLtdlC52wTivKectOxMNiTGs2oyjrsp0TpColLUZtZeeqzGKHSFw18Eto1RTZ80ErZ6ZjubyyO0s0WJ3yRgA8WsIU16Fq3FrYXiSPViQqLZVfo5EfoTR1XNAPiqN+xvaVaas5628HivufhqZKPmHibXjCffWuJZivSDB22mRivzrGZqWxZ9zqq+EHx6SIxn6CMjIyM3hHFCf3e4lNEM+q9bGzqXcsyUZZXTVAlymFEeDilOwdBOHesyZausuD1d0RVqf37HzmnWE9gMq+dM9TPaLUN1S2hnlnoP/I5qhGy6lOVJSfGSI1lCNze0uxYTVYcjXQ4pg4nQrgz9jsFlnpB5Yu+Gijy5tP66wPTQbxLurmeUrqMdAkYm9YSJYLOePL2y1vPeYIcdoE8HJbtZDxc7jnr4WxYJE9XNmOYtqfWEqCYBDEdAxsOy0hLGw3pK3SeE0rM50Hz9fhYg9wjQLjLurdTYI/Yq5+pvdfhbUK8sbm00gDfrmE4a2gvruk1Odui08raA7lZPvr3hVrmm6hOOz6bYlSpBhjRqYC0LSNkzm1fMC5Vovf9owQ+qmps6pe0cVZ9Q+4Qn8gUeYZK0ZHlLHVN8Y5FFwuSOIT8C00faudDsOA3eZoF+7v/ITisakOG9CsGw6VJt63JCXDuStQbBQ6IBx7xsed9sQW577vZTrImkkw6fBrWUqxxWLztsq+PW7kB6q+ID5Sm5dHTRYQk8kS9o9y1H0wmrJqVqUrrKETYOUxtoDXWVclKXkG/ogqUdlC3bTaKpfAKh9ESnwUXWlrVoqucsb+iCJfQWt1EzCNMJjcs4NpDlGvzPyo52SIP1qdMgbxqYbFd8/d4RTxbnnLYlX5ZbnEh5eX1WdYqcpJSvwfRV3UlVe4bgtGo2XUbSxZVN3JoJ94DtacXORFN3V5NM+9LYy6OXJO/ZnlTECMdmSu9z7KDpZEyk9ZY79ZyjurzUEXo4jOJcIyMjIzeDCIzyue8eF9rKPhvOPIfVpveG2FqSjepPY4YqQhMxJlC4jieK5WUhQ+MdryW6sog2YvKeomxZAyubaPxlu2eysyEgnBxPyV9I2fliID33NDuW9YGuSvNTyE8GM+ZMaLYNXeXwQyqh6QVTa6FEyCLdNOi5cBSi1dXcJG1wxtMGi5WIyzy96LnzqtIzwdUmwy9Skn7Q9p6o4l8+b+h7g19ptWtI1CZs52DJU7NzStdRe8fd9YzleYE7t8PKzFAXunL7qtlBBGzR45/25GXLrbKmC4az8wn+NNUKxmYoTtnrmd9esTdZc1qVnB1PIAh52TFJW9puKP6pNQjoKmi2odsRDcwFw3mVE04yynua4tZuC34akKInL1v2pys+ODuhMB1nXcFhPeW0Ki/VDut1SmwNS1dyPJ/w9M6E3azCSCRPe3pv6QZj7stgdbgqXnIboZtZulkglF7NPxji5kELuWqjAWCRqEbZnVZxurUG7HxmaFvHaVPQecvR+ZSuciRFz9Z8Q5UlVO2EdKG7i9ho8U03C+yWNR7hs9XT3G3m3Gum9MGQWs+tQg/dqyYldlaL0dZGx35d8Moi5bVZq6vxQQGUjR2CoRFBjUiSlQwpqpZVL/htQ4gCG0u6hOxE34vs1NAeFdQ7GWGno5g2ZLkGn+sgqlFuIjHCpk+4V884a3PWTUroNbhb94awTCnvGoqjgOkj69uWxbNCu+8xjVC+ZCgPI/nZsPrPhU1esHKeg/mS7axikyccJVOWZwVUajvoe4ORSJr0pHlPnQdk0Mn3jeO1sy2O3JSqTojLizzfh8S4Qn93iAbq25pPTaqTYpL3zKcVRdJxZKc0a4vpNDuknwZcoSJaqfEEVPQJoOkd0g3+jYOwz950TZb0LPIcYyLbE81bPlmVmLsZ05cj0xcr7LLGbUogo5sYbBsvpUijvUiVGESqGoNb65dMyIR+FrA7DfnwYTESmRc187Rh06ccbqasmxSRSJL19J2lXWnuPJXFrrTUvy+uStnnZU3VJiyKjK4XQhHYOVjyA+97nm+bvEQXLZ9YfpAXTnfhNCU7Udcbn0JI9ZJYywST95hBPuGJ+YLtrOakLjiTchC8EtKl5h13W8L+dMW37rzKnXrO5+IBVZMyKRoS4y+r9VRylcv3GVGThdOqZHFWkp4a0oVOjv1E5WRj5ai84dAGbhcrDsoFhW0JCOsu1QkJiI3FrixE2HSGOzaQbntSoxWDTecIqdDPemqf4AsZSsj1CyY70SrJ4AxxqycdTCB8Z+nXDtlYutrSFQ6benxjMV6fk6zAeA34rbcyXmEbXznc3ZS0g/bA4mYbnt4546vB0Kw080KD8HrksFgVfNo9xapJOT+ZaIbHpGd/b0mZtJysStq7Bfk9dRC6kGZWETdLNy/uCzYOAfl4nyxucyX6duE1GtFKVoYvOtOrn25xDP09YbNvWMeUNgnqIwuEymGXFsSyaQ1f2qSDMJZR5y+vk30Igq00gNpNhHrXsfi6yNY3HPPhnSNeXG5zx+xj+ivfT9uAXRqqScZiKNtPrSdPOjZZSt8ZpDf42nG8mGBsoFmlmEY0wSBCWDjqtaUejDHMfR6+Xztj6f/IyMjIzSBCHPPQ3yUMxK2OtOzI0w5nNV3pmdkpu+mal8sdPh3fR0OJdEIoPNmQB73uUtZdyrLV44uT46m6ivfolhwwRFLrKfIOa1WAa9Mm1CcFkyMhWQc90shToh22e5mKHVW7uqUOiR4txCRornulOi+21lV1PzFEL5hBe0IkEqLw2mrO2bqgOc80337WMp3UNEC/1i2krQ2ml+G4SXOCZQgItb0djAAilJ6D6ZJvm7zEnym/TB0NJ37C78oHMPflwN9v/ODOLaE29IWnMYHTqmTdZixr1V5JKg0EJivN1Y9Z4MPze3zX9A953h1wVE84NhOKRHce/RDANL0GYX02VLS6QN9bzpuEeJ7ihiCuaoDoWNilxbSO1dLxKW9Y7OWk1nOvmnC8nNBuhmOQwYaQYWXW+ysP0ra3mg8+CLKFnY5mS4gBzMaS39MgqW0GydrEsz3RyOWqTvHnKempHXRlLH4y5NUPK3zbRkwfcY36nHqX4s4sk1d19b8KjvO9nGfmp7B3wpeGXVa7SVUWdyU0dwteXqS4c8fkUKtWqwPLsQs0E0t1nlO+bNl6IZCeeR3fYdx8bujONLU2vO5TfZFTL/4+XZy9QLm/5tZszXmVc1akmq7Z6hOy84CrAq62SIe+b0OA3p2pLhBAXzn8xtK7QTvIDj61Bl2ll576wGoK6syz/cw5f/rJL/NUdoaRwGtb27Rb2VXO/5BhGBrLcq1HaZO0JUt6tmYV68RrgLSztIsU6cxVHrpAGHYebnmVENA/xEJRbdx45DIyMjJyMxjP0N8lItAbfGdpJeJsS5F07Gcrns3uMbUNd6spL65SWDikNbS142xI2WqbhH6lqzt3bi/1V6JRfZaTTUlVa5qY2MjSRvq1I7vrSDbQlcLiQ1pU41OhnUOzB93cqx0eaKDTBcRGqC3JajAqWKt1nkSh7nKW8wRyj0kCItBvHOlhwvRcVxhN6sm2PCJQ22EZY+KVbgvDary1LM7VMd6urJ6vt4ZFk3O3n3MWEhIJJOJxNhDTSDcfDBYclyslWwm2Fnwj9K3heJFdyv+aoWLQZ3o22s0g22741unLfHv2MpbAF4oDNp2uQus+oW+H1R3DWX2iMrKSBLw3+GYw4k7UEKSdaSAXAbN2alBxbqjbGc8tcx38ymEqc+Hqp4VgWQQTIAuqiBkM6y7l+HSK3Mlx3VDFOO9Jpi1l0RCjsJhNCInqnYgfVAa9trnvNVZR3NMdTLMttL2aJtvqyiylz7VgJqTxcvxtC9lZICSG09sl97Ym7BdrdvdVjvOk2iYaXfnbtQY6sxMo7+nz+1KoGkedaNVkuoDy1Yb0cEVMHd12TreV4DMtbLJNJBmuYwlXK/gomjzQzoXqIFJ+YMl3v++rFLbj83LAsijo5pZo1Ry7L7Q4rN7TQHtWdrRrHU/Ta8phSLQqOSR6HUlyVXmNaFWwK1vsfsDZQJ503JqsOWknHDYzvni6Dxs1p+m0FgpfQMg1uaFvLRubkpjAXrHm/dMz+mC5V0147XxOfZZjaq20ji5qUdfUEzvBVsllsPvyAnkYxPhYZ7k8zK6OjIyM3HxifHu3t0BEfkhEviAiz4vIT7/B3/+uiHxORD4jIr8pIs+81Wte6xW6BDALR1hZ6jSlLlN8EKauxYnaioWo0XtbC+INvs2pCl2Vm40lW+lq09VcZouENCK9YXFWIueJmlA7CC6Srg3pORCg3hParcHoeRDgl+2Wra0Nbqj22dQpTZVoxsNGS75dHfXWREwnuEpo5452y+IHQ2C3tLoqXV1ovwyrYq+ZMoCWraeROFEtlOgFeiE0CXatuwGA6Cx3j+b8uvtG7uxsMXc1X1wdsKoygou0O+HSPMBu9LWTQSPH9IJtNHPEtICBbqJFRiETupWWik+yllw6cgmUpqGwena+aVOazhGHlLLgIv1UdJU+8dh0WEYO8gh9LsRpxM89ZtKpucGQfSEtJOeC+ATp1TDZ1lfnrs2u0G/3kAbEBkIQVm3Gqs4IpxmTIR2y2TO0EyFJep6en/PM9IS7e3N+L3k/fCXXIqHXUs6qLb1OWmHyqjB9JSAhEo3FF5qu6Ta6Cg9OdyvtFpohU7a0vdBsXRQeRfI7lq/O9uAJ2Cs1DbF7n2WRTFQ1tNUVv6uG17SDrEWjJt3YOMRdHC5LwBm6rYTlU45mW8dG4xr6ftgmagFbH4drW+gz8Ls937B/yDdPX2Xlc75sbw0yDFHlIYyobkwC/UHLk0+cUSQtr8g2AO3MqVH11JNuNeRpj5FI11uaKiGudTfsS89k0vDszgml61h0GcebCS+e7tC2jnaR4pZGbfmGMeynatYuTj8/Maq0wXZW8f7ilNK0vJptERBeqpJBD0ZlLZJbNbNJzWqT0S8diMZSLvwDHg6R6L92wwwRscAvAn8eeBn4hIh8PMb4ufse9vvAd8YYNyLyN4FfAP7qm73utZ7Qo4B04Fqj2USZ4Xzj+P1NxguzHayJnG9yzRXuBLfWicpnTreEHZqjju4U9cLQIKKxkb7R6jnbAIM66oWQf0hUq6Q56HHTDgGcCUwnDfuT1WV++70oNHWC9KrbQoTgNJApYfhSarUdF8YXpujxQFs5zfGeaZCu9ZbVMsed6rC5jTrgRBtweU8MhtALoXZXmh9eJwl/lPGV+oAXD/ewiboYhZWqXfmJx+Se2BtiPfhG9oPRQRgqctvBVzWHsBdJntB9fXOvwG4M5ycTfu34W+iiZRlyztuCqkvY1Cl9by69UGMa6YNcCoiFXnSyHyRSo1WJ1CgQ+kH6d/jAR6d6Mb4MWiW5kMs2AvQN9OGq8tV7c3lsgo3qc5mo3koybdmdbnhmesL3zb+Enwl17/j80bPk94TsDLrDIZAboDwMZCcdvlRfzGi59HmVHqIMX1JZRGzA2oCZdNT7asCSbCBZQP9Kzotml6dvnwLw9PYZh0nP8dEMjlLS5uJ9j+CGCufa4AsLuWfztEViQrm3hekj1a5h/TS0+x0I2HNHdjosUjb6pZysIdlcHMuBpJ7cdjQh4bidsmhyfGsuRbCigy4LxK2eJ5845Zt37+CjsGp01j3acmAit3bWPDHRWo7zNufeYkrcONJDh9to9fS6yOiHXPfTquTodEqoHTGoIF5MBtG4YSYKaVRfYABRfZ7U9oQonLQTjphyt5pxXuXE3mhK4iCna2zASiBGuTxuCol+rh8aD08+97uB52OMXwEQkV8BPgpcTugxxt+67/G/DfzYW73oY3fk8lbbkJGRkZFHSgxv7wa3ROST991+6r5XeQp46b7fXx7uexA/CfzXt2raY7VCf5vbkCtcxG954krV3NxGcJXFn084Kgs9inABXKQvIm6t6ozJWrfI8aJ6lEGHo1Q38nTekKcdq5jTTywh05RH0kCbOKQ3uEGLQ3rBd2pDJ9bottM77LBsFFFrvJB5fKkBRgS6Vp3MowyVglPo5558t2J/vqL3lsPpjPY8hSwwGYpcQuUoBq9JW2llXQCKvCNxqs+yqVMa0SWtaXXFahrBNI544vBDGpsxEPKALXpcpulglzEtr6tPhi3rhfFDSIHtlg/fvkcfDV9YP0lyx5KdZvzO5ut5/pk9dosNyyanahKt2L3Qi+HiPY/6uq0h9roytBs12cCocYlajtlh9Tt4cW57ioM1+/MVizrndDYnu+P0eehKjyxg3NWWODGB2WRNd9tSmwKikOzWHOws2C/WZEb343Nbc7tY8lzhAUe6jJdjHAVMG/GZ2vQ129BuBYwHvzSXOwKJejzj147Kq4wseaTeF/q1rrzTc6iznHu5FhZt3VIzi1WV0R2luAqSaqiaTETT/3oheENSdshTHcvtlPVJQrIabN1udRQ7NdYGNllGVQ5pnK0W9mQnQjyRoZJV0wlPmpLP8SRH9YSzdUFsLcbrkVR0EJOIzXrKQWq6Ce4yBVQGu0crkT4a2t6yqHPqTYpZaeA2Wev1st5KebHcIXGexXlBWKYgEckDknWEzOB7c3ndAdAaMAIuUKQdu3lFHyyfOzvg8GxGs8gwG4ur5FIDJhpL7QajkZUjW2ngti+h3Xl4QUwtxHrbK/SjGON3fq3/p4j8GPCdwA+81WMfqwmdt7ENGRkZGXlkxMhDMrh4BXj/fb8/Pdz3RxCRPwf8LPADMcbmrV70cZvQ32gb8j33P2DYtvwUQHp7zu5T55ydl7SnKcnCqqFuDb42dF4IOy3JtKWTSD8Ucbh6sMkqtLgFdOXZTwMy7didbtgpNpxlLcfpBN8b8sRjbaBKU7qhvtp0kB5b/MoQLYQssAkaxMkTXfnFKKSpGgm0Ai0On2pK2EVKWXBRNajnLfvzFR/euoeVyPOu4042x9rA7ZmmuZ3nJT7XYZOghrs282yVFfvFmtR4Vl3KS+k2i6TE18Nhb9CVnmn1XDam4Cca1JqUjZ43c5/mRRwULAfrM7h6v8pZwzPTEyqf8EV7QLKG4iiSrCxn6z2O9+ZIEhATcYnH2oi/WILFQds6AFZT7Uwnl2bDcYgp2GHlFRItmPKznu3bS77riZf49umLbELG/97+EM/tPEG91ENScYFi0qra3mCYIBLZKzZYE3gZ1WNPkh4fDPeqCYs247CZMXM1r262IA00O6hozn27ir60mM7SzqDZizDv8J2hnxraWpUqgxt2NmsLlaaMRgFfBnwhwy4SkoWwOdXU2XvllEnaELym312W8udCOxvS+WwkdobgDWXZUOQtmzKjXqoOuCRaZi8iJHkPuV57RiJNlVC7TM03gH6qq+vTquR4M2HdpBrjiVxZ0qUR0kAMwtF6QoiCj+ZSQyjUDh/gsHYcJ1NigOAN9AZcpJvpuIZUx3Z9Vug1tB5SU7OrgCeiK/44aK2byuDWg1RHEtgpNnzD9A6nfckXjvfpX5lQHl9p/F8UTdlakKApkLpTZ4g/Rcytt5wH/1g8jKAo8AngwyLyQXQi/1Hgr93/ABH5DuBfAD8UYzx8Oy8q8TFKkheRv4I2/m8Mv/914HtijB97wOPvAWvg6L1r5bvOLcb+PO7ctD79/9KfZ2KM+1/LC4vIfxte/+1wFGP8oTd5rR8B/ilggV+KMf5DEfn7wCdjjB8Xkd8A/gTw2vCUF2OMf/FN2/eYTeh/Evi5GOMPDr//DECM8eff5DmffBjnVI8LY38ef25an8b+3BwetyyXy22IiKToNuTjj7hNIyMjI9eCx+oMPcbYi8jHgF/jahvy3CNu1sjIyMi14LGa0AFijL8K/Oof4yn/8t1qyyNi7M/jz03r09ifG8JjdYY+MjIyMvLOedzO0EdGRkZG3iHjhD4yMjJyQ7i2E/pN0XwRkRdE5A9E5FMi8snhvl0R+e8i8qXh351H3c4HISK/JCKHIvLZ++57w/aL8s+GMfuMiHzk0bX8jXlAf35ORF4ZxuhTQ/7wxd9+ZujPF0TkBx9Nqx+MiLxfRH5rkGF9TkT+9nD/dR6jB/Xp2o7TQyPGeO1uaAbMl4EPASnwaeCbHnW73mFfXgBuve6+XwB+evj5p4F/9Kjb+Sbt/37gI8Bn36r9wI+gAkMCfC/wO4+6/W+zPz8H/L03eOw3DddeBnxwuCbto+7D69r4JPCR4ecZ8MWh3dd5jB7Up2s7Tg/rdl1X6JeaLzHGFrjQfLkpfBT45eHnXwb+0qNrypsTY/yfwMnr7n5Q+z8K/Juo/DawLSJPvicNfZs8oD8P4qPAr8QYmxjjHwLPo9fmY0OM8bUY4+8NPy+Bz6MSG9d5jB7Upwfx2I/Tw+K6Tuh/XOnJx5kI/LqI/J/75DUPYowX5b53gINH07R3zIPaf53H7WPDEcQv3XcEdq36IyLPAt8B/A43ZIxe1ye4AeP0tXBdJ/SbxPfFGD8C/DDwt0Tk++//Y9Q947XNLb3u7R/458DXAd+O6mr840famneAiEyB/wj8nRjj4v6/XdcxeoM+Xftx+lq5rhP625KevA7EGF8Z/j0E/jO6Fbx7sc0d/n1bSmuPEQ9q/7Uctxjj3RijjzEG4F9xtV2/Fv0RkQSd+P5djPE/DXdf6zF6oz5d93F6GFzXCf1GaL6IyEREZhc/A38B+Czal58YHvYTwH95NC18xzyo/R8HfnzIpPhe4Py+bf9jy+vOkP8yOkag/flREclEZVA/DPzue92+N0NEBPjXwOdjjP/kvj9d2zF6UJ+u8zg9NB51VPad3tBo/BfRiPXPPur2vMM+fAiNvn8aeO6iH8Ae8JvAl4DfAHYfdVvfpA//Ad3edujZ5E8+qP1o5sQvDmP2B6gB7iPvw9voz78d2vsZdHJ48r7H/+zQny8AP/yo2/8G/fk+9DjlM8CnhtuPXPMxelCfru04PazbWPo/MjIyckO4rkcuIyMjIyOvY5zQR0ZGRm4I44Q+MjIyckMYJ/SRkZGRG8I4oY+MjIzcEMYJfWRkZOSGME7oIyMjIzeEcUIfuRGIyHcNokz5UIH7nIh8y6Nu18jIe8lYWDRyYxCRfwDkQAG8HGP8+UfcpJGR95RxQh+5MQy6Pp8AauBPxRj9I27SyMh7ynjkMnKT2AOmqItN/ojbMjLynjOu0EduDCLycdS96oOoMNPHHnGTRkbeU9yjbsDIyMNARH4c6GKM/15ELPC/ROTPxhj/x6Nu28jIe8W4Qh8ZGRm5IYxn6CMjIyM3hHFCHxkZGbkhjBP6yMjIyA1hnNBHRkZGbgjjhD4yMjJyQxgn9JGRkZEbwjihj4yMjNwQ/h9ZO9JUYAO0tQAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -1442,16 +1458,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x2ba7ed1fdad0>"
+       "<matplotlib.collections.QuadMesh at 0x2b26e27b6150>"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1474,6 +1490,7 @@
     "    dx_min=1,\n",
     "    filter_shape=gcm_filters.FilterShape.TAPER,\n",
     "    grid_type=gcm_filters.GridType.REGULAR,\n",
+    "    grid_vars={}\n",
     ")\n",
     "\n",
     "mask_filtered = filter_noland.apply(wet_mask, dims=['y', 'x'])\n",
@@ -1488,13 +1505,13 @@
     "\n",
     "Up to now, we have operated \"eagerly\"; when we called `.apply`, the results were computed immediately and stored in memory.\n",
     "\n",
-    "Gcm-filters is also designed to work seamlessly with Dask array inputs, deferring its computationg and possibly executing it in parallel.\n",
+    "Gcm-filters is also designed to work seamlessly with Dask array inputs, deferring its computations and possibly executing it in parallel.\n",
     "We can do this with our synthetic data by converting it to dask."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1853,7 +1870,7 @@
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 10, y: 128, x: 256)&gt;\n",
        "dask.array&lt;xarray-&lt;this-array&gt;, shape=(10, 128, 256), dtype=float64, chunksize=(2, 128, 256), chunktype=numpy.ndarray&gt;\n",
-       "Dimensions without coordinates: time, y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>time</span>: 10</li><li><span>y</span>: 128</li><li><span>x</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c82f8a4a-a30f-4ffb-b449-a6549815e0fd' class='xr-array-in' type='checkbox' checked><label for='section-c82f8a4a-a30f-4ffb-b449-a6549815e0fd' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2, 128, 256), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: time, y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>time</span>: 10</li><li><span>y</span>: 128</li><li><span>x</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7d98e3e7-8e7e-4f2f-979f-a14cad662f0f' class='xr-array-in' type='checkbox' checked><label for='section-7d98e3e7-8e7e-4f2f-979f-a14cad662f0f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2, 128, 256), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1919,7 +1936,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-d84b2201-d366-42cf-89fd-8d873c934ad8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d84b2201-d366-42cf-89fd-8d873c934ad8' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-6af75eba-596a-48a0-b7f8-75a87c3dbb47' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6af75eba-596a-48a0-b7f8-75a87c3dbb47' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</table></div></div></li><li class='xr-section-item'><input id='section-952b2dc5-c7c0-415c-820e-a7c758677b9d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-952b2dc5-c7c0-415c-820e-a7c758677b9d' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b004e073-6a49-43f4-97b2-8c85891deaf4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b004e073-6a49-43f4-97b2-8c85891deaf4' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (time: 10, y: 128, x: 256)>\n",
@@ -1927,7 +1944,7 @@
        "Dimensions without coordinates: time, y, x"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1939,7 +1956,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -2298,7 +2315,7 @@
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 10, y: 128, x: 256)&gt;\n",
        "dask.array&lt;transpose, shape=(10, 128, 256), dtype=float64, chunksize=(2, 128, 256), chunktype=numpy.ndarray&gt;\n",
-       "Dimensions without coordinates: time, y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>time</span>: 10</li><li><span>y</span>: 128</li><li><span>x</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2844475f-9c7e-42fa-bb9a-a658b6873813' class='xr-array-in' type='checkbox' checked><label for='section-2844475f-9c7e-42fa-bb9a-a658b6873813' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2, 128, 256), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: time, y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>time</span>: 10</li><li><span>y</span>: 128</li><li><span>x</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-dbfa5732-4913-4944-95e5-cbfd6cf74882' class='xr-array-in' type='checkbox' checked><label for='section-dbfa5732-4913-4944-95e5-cbfd6cf74882' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2, 128, 256), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2364,7 +2381,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-fb0f6f7e-4fe8-435b-bb58-228245567369' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fb0f6f7e-4fe8-435b-bb58-228245567369' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-db351893-fe44-4726-a7d3-2cd9f76a3694' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-db351893-fe44-4726-a7d3-2cd9f76a3694' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</table></div></div></li><li class='xr-section-item'><input id='section-7c8ce2a2-54be-48b9-a523-d77155434abc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7c8ce2a2-54be-48b9-a523-d77155434abc' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-0d460dc8-6c8a-4e96-b407-218371c9fded' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0d460dc8-6c8a-4e96-b407-218371c9fded' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (time: 10, y: 128, x: 256)>\n",
@@ -2372,7 +2389,7 @@
        "Dimensions without coordinates: time, y, x"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2392,15 +2409,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 79.3 ms, sys: 3.04 ms, total: 82.4 ms\n",
-      "Wall time: 88.1 ms\n"
+      "CPU times: user 77.9 ms, sys: 3.74 ms, total: 81.7 ms\n",
+      "Wall time: 86 ms\n"
      ]
     }
    ],
@@ -2416,24 +2433,6 @@
     "Our example data are not big enough, and our computer not powerful enough, to really see a big performance benefit here.\n",
     "But it works!"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Real Data\n",
-    "\n",
-    "TODO once other filters are implemented.\n",
-    "\n",
-    "Or could we do an example with SST or SSH now?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -2452,7 +2451,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.2"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,
diff --git a/docs/tutorial_GPU.ipynb b/docs/tutorial_GPU.ipynb
index d3d7b10..a2d3482 100644
--- a/docs/tutorial_GPU.ipynb
+++ b/docs/tutorial_GPU.ipynb
@@ -435,7 +435,7 @@
        "    cell_methods:    cell_methods = time: mean ==&gt; the variable values are av...\n",
        "    nsteps_total:    9618241\n",
        "    tavg_sum:        431999.9999999717\n",
-       "    tavg_sum_qflux:  432000.00000000006</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-523308c1-68fe-4e44-85da-90a8e59c96fa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-523308c1-68fe-4e44-85da-90a8e59c96fa' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>z_t</span>: 62</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eeaa5a7d-88c3-4a7b-9ed3-38803f2719ff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eeaa5a7d-88c3-4a7b-9ed3-38803f2719ff' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-28b88258-df59-4fdc-a9e0-b92761ac2a4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28b88258-df59-4fdc-a9e0-b92761ac2a4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-000ef6a4-e057-427e-91d5-8da233b25868' class='xr-var-data-in' type='checkbox'><label for='data-000ef6a4-e057-427e-91d5-8da233b25868' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_t</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 1.5e+03 ... 5.875e+05</div><input id='attrs-6d729bdb-97af-4ea0-a683-2f0b49456ee6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d729bdb-97af-4ea0-a683-2f0b49456ee6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bff8ce6c-be9e-4ba7-895e-b4e98c5ef5ac' class='xr-var-data-in' type='checkbox'><label for='data-bff8ce6c-be9e-4ba7-895e-b4e98c5ef5ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>depth from surface to midpoint of layer</dd><dt><span>units :</span></dt><dd>centimeters</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>500.0</dd><dt><span>valid_max :</span></dt><dd>587499.06</dd></dl></div><div class='xr-var-data'><pre>array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,\n",
+       "    tavg_sum_qflux:  432000.00000000006</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-76128801-847c-48f7-91b5-ed628b836250' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-76128801-847c-48f7-91b5-ed628b836250' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>z_t</span>: 62</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-56822475-c710-43c0-bc8b-2ff9f330cc86' class='xr-section-summary-in' type='checkbox'  checked><label for='section-56822475-c710-43c0-bc8b-2ff9f330cc86' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-3551959b-c46b-4005-a9ce-6122a00318a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3551959b-c46b-4005-a9ce-6122a00318a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a37619dd-5397-4945-92a0-58ded58195e1' class='xr-var-data-in' type='checkbox'><label for='data-a37619dd-5397-4945-92a0-58ded58195e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_t</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 1.5e+03 ... 5.875e+05</div><input id='attrs-d0994341-0414-42c8-bf55-2291a8e4da49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0994341-0414-42c8-bf55-2291a8e4da49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb0917da-4ce7-4f55-bd5c-4108de833d92' class='xr-var-data-in' type='checkbox'><label for='data-cb0917da-4ce7-4f55-bd5c-4108de833d92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>depth from surface to midpoint of layer</dd><dt><span>units :</span></dt><dd>centimeters</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>500.0</dd><dt><span>valid_max :</span></dt><dd>587499.06</dd></dl></div><div class='xr-var-data'><pre>array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,\n",
        "       5.500000e+03, 6.500000e+03, 7.500000e+03, 8.500000e+03, 9.500000e+03,\n",
        "       1.050000e+04, 1.150000e+04, 1.250000e+04, 1.350000e+04, 1.450000e+04,\n",
        "       1.550000e+04, 1.650984e+04, 1.754790e+04, 1.862913e+04, 1.976603e+04,\n",
@@ -447,7 +447,7 @@
        "       1.968944e+05, 2.186457e+05, 2.413972e+05, 2.649001e+05, 2.889385e+05,\n",
        "       3.133405e+05, 3.379793e+05, 3.627670e+05, 3.876452e+05, 4.125768e+05,\n",
        "       4.375392e+05, 4.625190e+05, 4.875083e+05, 5.125028e+05, 5.375000e+05,\n",
-       "       5.624991e+05, 5.874991e+05], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f43dc828-bcef-4404-9e9a-371da1562d49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f43dc828-bcef-4404-9e9a-371da1562d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f915a29-3c70-46c8-a403-7ca70c88abed' class='xr-var-data-in' type='checkbox'><label for='data-4f915a29-3c70-46c8-a403-7ca70c88abed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-233bdced-20ef-4781-b3e3-2aeb812b8546' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-233bdced-20ef-4781-b3e3-2aeb812b8546' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc585261-3b36-4016-be0c-eaaff71443ae' class='xr-var-data-in' type='checkbox'><label for='data-fc585261-3b36-4016-be0c-eaaff71443ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6b719bdf-c6ff-4e75-9fdd-b64ade4a7ebd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b719bdf-c6ff-4e75-9fdd-b64ade4a7ebd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1861674a-7be8-47e8-82a5-2f6f23f565aa' class='xr-var-data-in' type='checkbox'><label for='data-1861674a-7be8-47e8-82a5-2f6f23f565aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dc5549f3-b3b7-46a1-a531-fdfc18e5ff9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc5549f3-b3b7-46a1-a531-fdfc18e5ff9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d9e9221-593d-45b8-a0f9-6e0885b4500f' class='xr-var-data-in' type='checkbox'><label for='data-3d9e9221-593d-45b8-a0f9-6e0885b4500f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cda266d5-a1c4-4fb6-966d-4e94a06862e5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cda266d5-a1c4-4fb6-966d-4e94a06862e5' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>KMT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-30d2b56c-d29b-4cd4-8fbb-83d48b3547d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30d2b56c-d29b-4cd4-8fbb-83d48b3547d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfd5389e-f824-4d7c-b39e-7e37af0b61d4' class='xr-var-data-in' type='checkbox'><label for='data-cfd5389e-f824-4d7c-b39e-7e37af0b61d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>k Index of Deepest Grid Cell on T Grid</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAREA</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c968c20-7559-4994-86a1-6ad2ff88e500' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c968c20-7559-4994-86a1-6ad2ff88e500' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd13a4c9-44a2-4db7-83a1-5442c18f710e' class='xr-var-data-in' type='checkbox'><label for='data-cd13a4c9-44a2-4db7-83a1-5442c18f710e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of T cells</dd><dt><span>units :</span></dt><dd>centimeter^2</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTN</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-33635777-c86e-4c1b-8556-658868e8d77d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33635777-c86e-4c1b-8556-658868e8d77d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdfa812f-c621-418c-acb5-d5e8f6ae50c1' class='xr-var-data-in' type='checkbox'><label for='data-fdfa812f-c621-418c-acb5-d5e8f6ae50c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on North sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTE</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c2c02fd7-3992-4989-92cf-8695cd2a3d49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2c02fd7-3992-4989-92cf-8695cd2a3d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5408c705-caa0-4a6e-853a-472e8f7f2d58' class='xr-var-data-in' type='checkbox'><label for='data-5408c705-caa0-4a6e-853a-472e8f7f2d58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on East sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUS</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c98f5c23-faba-43c5-a407-c102e6476ce5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c98f5c23-faba-43c5-a407-c102e6476ce5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd759e14-3d4e-4c2d-83ef-88768bbf40f8' class='xr-var-data-in' type='checkbox'><label for='data-fd759e14-3d4e-4c2d-83ef-88768bbf40f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on South sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUW</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f35a78b8-0c7c-4974-b3c3-3e4bd54bb56b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f35a78b8-0c7c-4974-b3c3-3e4bd54bb56b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59a892e7-2edc-4435-82cf-4697f4730f97' class='xr-var-data-in' type='checkbox'><label for='data-59a892e7-2edc-4435-82cf-4697f4730f97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on West sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST</span></div><div class='xr-var-dims'>(time, nlat, nlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a5a5aaaa-458d-45ac-9c1e-0496634dd44e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5a5aaaa-458d-45ac-9c1e-0496634dd44e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f55734b-2ee8-41af-a2e2-2d5e0b07e940' class='xr-var-data-in' type='checkbox'><label for='data-3f55734b-2ee8-41af-a2e2-2d5e0b07e940' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f90c877b-e316-448c-a698-642d5a678775' class='xr-section-summary-in' type='checkbox'  ><label for='section-f90c877b-e316-448c-a698-642d5a678775' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>g.e01.GIAF.T62_t12.003</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>Conventions :</span></dt><dd>CF-1.0; http://www.cgd.ucar.edu/cms/eaton/netcdf/CF-current.htm</dd><dt><span>contents :</span></dt><dd>Diagnostic and Prognostic Variables</dd><dt><span>source :</span></dt><dd>CCSM POP2, the CCSM Ocean Component</dd><dt><span>revision :</span></dt><dd>$Id: tavg.F90 46405 2013-04-26 05:24:34Z mlevy@ucar.edu $</dd><dt><span>calendar :</span></dt><dd>All years have exactly  365 days.</dd><dt><span>start_time :</span></dt><dd>This dataset was created on 2014-07-19 at 17:28:03.3</dd><dt><span>cell_methods :</span></dt><dd>cell_methods = time: mean ==&gt; the variable values are averaged over the time interval between the previous time coordinate and the current one.          cell_methods  absent  ==&gt; the variable values are at the time given by the current time coordinate.</dd><dt><span>nsteps_total :</span></dt><dd>9618241</dd><dt><span>tavg_sum :</span></dt><dd>431999.9999999717</dd><dt><span>tavg_sum_qflux :</span></dt><dd>432000.00000000006</dd></dl></div></li></ul></div></div>"
+       "       5.624991e+05, 5.874991e+05], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-47e5b557-46b0-4b9d-b829-198466ce01a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47e5b557-46b0-4b9d-b829-198466ce01a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dea1af98-40d8-436e-8993-3a29e8635445' class='xr-var-data-in' type='checkbox'><label for='data-dea1af98-40d8-436e-8993-3a29e8635445' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bbdc6333-4919-4ae3-a8b6-25701d0931db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbdc6333-4919-4ae3-a8b6-25701d0931db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca224530-c0b5-4a1a-b5b8-e4054c650e33' class='xr-var-data-in' type='checkbox'><label for='data-ca224530-c0b5-4a1a-b5b8-e4054c650e33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-925bba4f-3aeb-493a-bc99-984cd788d0ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-925bba4f-3aeb-493a-bc99-984cd788d0ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2a2ca33-9f58-4cb4-9535-9b3e0bd8618e' class='xr-var-data-in' type='checkbox'><label for='data-c2a2ca33-9f58-4cb4-9535-9b3e0bd8618e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b20433ae-2dc8-4c51-b094-b2601a487432' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b20433ae-2dc8-4c51-b094-b2601a487432' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc9339f7-aab0-4aa3-8bd9-032629113de8' class='xr-var-data-in' type='checkbox'><label for='data-bc9339f7-aab0-4aa3-8bd9-032629113de8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-efa64805-db7c-4e85-b38c-d02d38b42aa6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-efa64805-db7c-4e85-b38c-d02d38b42aa6' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>KMT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a2519c26-659b-4f4e-953e-51cc8fc5dce7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2519c26-659b-4f4e-953e-51cc8fc5dce7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b05312f8-3177-4165-b726-d3e131f5ec4e' class='xr-var-data-in' type='checkbox'><label for='data-b05312f8-3177-4165-b726-d3e131f5ec4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>k Index of Deepest Grid Cell on T Grid</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAREA</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2ffffb1b-c4ec-450b-aecc-d051e827605f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ffffb1b-c4ec-450b-aecc-d051e827605f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f58e9f98-f3c9-4f46-9a61-2c1bc5d58e7c' class='xr-var-data-in' type='checkbox'><label for='data-f58e9f98-f3c9-4f46-9a61-2c1bc5d58e7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of T cells</dd><dt><span>units :</span></dt><dd>centimeter^2</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTN</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-28059202-a334-4fda-9172-be1758faeb66' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28059202-a334-4fda-9172-be1758faeb66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c8521a7-66bd-4c20-a37f-814659c8d446' class='xr-var-data-in' type='checkbox'><label for='data-0c8521a7-66bd-4c20-a37f-814659c8d446' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on North sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTE</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7386d72b-37d1-4cd0-a94d-66ec0ec271e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7386d72b-37d1-4cd0-a94d-66ec0ec271e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1a56fe8-f976-4153-b4f2-58560d4bd76e' class='xr-var-data-in' type='checkbox'><label for='data-b1a56fe8-f976-4153-b4f2-58560d4bd76e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on East sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUS</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0ddc9230-fb16-4b55-bce7-fc5ff06693fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ddc9230-fb16-4b55-bce7-fc5ff06693fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63c00b51-2f35-45ec-a38d-211b2b68d8a7' class='xr-var-data-in' type='checkbox'><label for='data-63c00b51-2f35-45ec-a38d-211b2b68d8a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on South sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUW</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b92f0d2c-b932-4c24-84bd-09287efac14f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b92f0d2c-b932-4c24-84bd-09287efac14f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0bdb629-5a0e-4ecf-8c85-fc2b80bfe152' class='xr-var-data-in' type='checkbox'><label for='data-f0bdb629-5a0e-4ecf-8c85-fc2b80bfe152' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on West sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST</span></div><div class='xr-var-dims'>(time, nlat, nlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-58cec8fa-b54b-4b0f-a292-b486134870e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58cec8fa-b54b-4b0f-a292-b486134870e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba4a17f9-d055-430f-9b8b-ee1816a0e289' class='xr-var-data-in' type='checkbox'><label for='data-ba4a17f9-d055-430f-9b8b-ee1816a0e289' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-23460d7a-ffb7-4af7-a4dd-cff73ff5a658' class='xr-section-summary-in' type='checkbox'  ><label for='section-23460d7a-ffb7-4af7-a4dd-cff73ff5a658' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>g.e01.GIAF.T62_t12.003</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>Conventions :</span></dt><dd>CF-1.0; http://www.cgd.ucar.edu/cms/eaton/netcdf/CF-current.htm</dd><dt><span>contents :</span></dt><dd>Diagnostic and Prognostic Variables</dd><dt><span>source :</span></dt><dd>CCSM POP2, the CCSM Ocean Component</dd><dt><span>revision :</span></dt><dd>$Id: tavg.F90 46405 2013-04-26 05:24:34Z mlevy@ucar.edu $</dd><dt><span>calendar :</span></dt><dd>All years have exactly  365 days.</dd><dt><span>start_time :</span></dt><dd>This dataset was created on 2014-07-19 at 17:28:03.3</dd><dt><span>cell_methods :</span></dt><dd>cell_methods = time: mean ==&gt; the variable values are averaged over the time interval between the previous time coordinate and the current one.          cell_methods  absent  ==&gt; the variable values are at the time given by the current time coordinate.</dd><dt><span>nsteps_total :</span></dt><dd>9618241</dd><dt><span>tavg_sum :</span></dt><dd>431999.9999999717</dd><dt><span>tavg_sum_qflux :</span></dt><dd>432000.00000000006</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -499,7 +499,7 @@
    "source": [
     "In this example, we want to **filter** SST **with a fixed factor of 10**, i.e., to nominally 1 degree resolution.\n",
     "\n",
-    "To keep things simple, we will filter with the **simple fixed factor filter**. The `TRIPOLAR_REGULAR_WITH_LAND` Laplacian is suitable for this filter and our data on a tripole grid. This Laplacian only needs a `wet_mask` as a grid variable:"
+    "To keep things simple, we will filter with the **simple fixed factor filter**. The `TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND` Laplacian is suitable for this filter and our data on a tripole grid. This Laplacian only needs the grid cell `area` and `wet_mask` as grid input variables."
    ]
   },
   {
@@ -510,7 +510,7 @@
     {
      "data": {
       "text/plain": [
-       "['wet_mask']"
+       "['area', 'wet_mask']"
       ]
      },
      "execution_count": 4,
@@ -519,7 +519,7 @@
     }
    ],
    "source": [
-    "gcm_filters.required_grid_vars(gcm_filters.GridType.TRIPOLAR_REGULAR_WITH_LAND)"
+    "gcm_filters.required_grid_vars(gcm_filters.GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND)"
    ]
   },
   {
@@ -556,7 +556,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We also need the area of the T-cells."
+    "The area of the T-cells is"
    ]
   },
   {
@@ -565,7 +565,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "area = ds.TAREA.where(wet_mask) / 10000  # convert units from cm2 to m2"
+    "area = ds.TAREA / 10000  # convert units from cm2 to m2"
    ]
   },
   {
@@ -943,7 +943,7 @@
        "    ULAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLONG    (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
-       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KMT'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-af3b8ae7-1a5f-4a4a-99d7-2aa53782da60' class='xr-array-in' type='checkbox' checked><label for='section-af3b8ae7-1a5f-4a4a-99d7-2aa53782da60' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KMT'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5a5da80d-b4c9-4c9d-a5b3-bb4c23256097' class='xr-array-in' type='checkbox' checked><label for='section-5a5da80d-b4c9-4c9d-a5b3-bb4c23256097' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -978,7 +978,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-5c295d05-d553-4980-84b6-dd0a6f05992f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c295d05-d553-4980-84b6-dd0a6f05992f' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-8c630b3c-4ff0-4105-b8c0-79122ff068d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c630b3c-4ff0-4105-b8c0-79122ff068d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47a11c74-938b-4aa2-a654-df91eca12b4e' class='xr-var-data-in' type='checkbox'><label for='data-47a11c74-938b-4aa2-a654-df91eca12b4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-0645adf4-b6c4-4ceb-b3db-a814dea6fd41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0645adf4-b6c4-4ceb-b3db-a814dea6fd41' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-67c8455b-9e28-4816-8dd9-2b0211af2dba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67c8455b-9e28-4816-8dd9-2b0211af2dba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14bee73d-ba50-4c02-b00d-f39a99a1b691' class='xr-var-data-in' type='checkbox'><label for='data-14bee73d-ba50-4c02-b00d-f39a99a1b691' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1013,7 +1013,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-ef828d6a-dcce-43c5-88da-3df3d19b2746' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef828d6a-dcce-43c5-88da-3df3d19b2746' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f88e236-ae6e-4fa8-9222-668ecd9b32e5' class='xr-var-data-in' type='checkbox'><label for='data-7f88e236-ae6e-4fa8-9222-668ecd9b32e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-e381e4f4-c692-47c3-bab5-a733a2b177d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e381e4f4-c692-47c3-bab5-a733a2b177d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ebc09f7-db84-44cc-afc3-4647e93f969e' class='xr-var-data-in' type='checkbox'><label for='data-3ebc09f7-db84-44cc-afc3-4647e93f969e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1048,7 +1048,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-720a1675-2ef1-44cc-ac4f-8534e0fa5c53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-720a1675-2ef1-44cc-ac4f-8534e0fa5c53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc68c45a-eefa-4ae3-9414-474b595042ad' class='xr-var-data-in' type='checkbox'><label for='data-bc68c45a-eefa-4ae3-9414-474b595042ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-91c2e397-62ae-460b-9e3a-0959c93895bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91c2e397-62ae-460b-9e3a-0959c93895bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62c96a28-f670-4fde-8667-366eba774c67' class='xr-var-data-in' type='checkbox'><label for='data-62c96a28-f670-4fde-8667-366eba774c67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1083,7 +1083,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-8d602961-ccbb-4200-9beb-47877c1f1d4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d602961-ccbb-4200-9beb-47877c1f1d4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a13c332-c590-4296-91c1-e65d12e9d5fc' class='xr-var-data-in' type='checkbox'><label for='data-7a13c332-c590-4296-91c1-e65d12e9d5fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-6555f496-cefb-40d0-ba9b-e4a97027c15d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6555f496-cefb-40d0-ba9b-e4a97027c15d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cccd585e-79a4-425a-a322-d6433732d1ec' class='xr-var-data-in' type='checkbox'><label for='data-cccd585e-79a4-425a-a322-d6433732d1ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1118,7 +1118,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b1893ae-0905-47b5-85c7-ea63d8381ee7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4b1893ae-0905-47b5-85c7-ea63d8381ee7' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-734aa0e2-b8d2-4230-87f9-c0d317c4c3bd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-734aa0e2-b8d2-4230-87f9-c0d317c4c3bd' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'KMT' (nlat: 2400, nlon: 3600)>\n",
@@ -1500,18 +1500,14 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;SST&#x27; (time: 1, nlat: 2400, nlon: 3600)&gt;\n",
-       "dask.array&lt;where, shape=(1, 2400, 3600), dtype=float32, chunksize=(1, 2400, 3600), chunktype=numpy.ndarray&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;TAREA&#x27; (nlat: 2400, nlon: 3600)&gt;\n",
+       "dask.array&lt;xarray-&lt;this-array&gt;, shape=(2400, 3600), dtype=float64, chunksize=(2400, 3600), chunktype=numpy.ndarray&gt;\n",
        "Coordinates:\n",
-       "  * time     (time) object 0033-11-27 00:00:00\n",
        "    ULONG    (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    ULAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLONG    (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
-       "Dimensions without coordinates: nlat, nlon\n",
-       "Attributes:\n",
-       "    units:      degC\n",
-       "    long_name:  Surface Potential Temperature</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'SST'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-47f4fcae-bb12-4a10-96c9-d89dade66b48' class='xr-array-in' type='checkbox' checked><label for='section-47f4fcae-bb12-4a10-96c9-d89dade66b48' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'TAREA'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6dab898b-12b0-4704-9b08-44c2a95a53fc' class='xr-array-in' type='checkbox' checked><label for='section-6dab898b-12b0-4704-9b08-44c2a95a53fc' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1519,57 +1515,34 @@
        "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><th> Bytes </th><td> 34.56 MB </td> <td> 34.56 MB </td></tr>\n",
-       "    <tr><th> Shape </th><td> (1, 2400, 3600) </td> <td> (1, 2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 3 Tasks </td><td> 1 Chunks </td></tr>\n",
-       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
+       "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
+       "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
+       "    <tr><th> Count </th><td> 1 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</td>\n",
        "<td>\n",
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-       "\n",
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+       "<svg width=\"170\" height=\"130\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
        "\n",
        "  <!-- Horizontal lines -->\n",
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+       "  <text x=\"60.000000\" y=\"100.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3600</text>\n",
+       "  <text x=\"140.000000\" y=\"40.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,40.000000)\">2400</text>\n",
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-d2fe3be3-ce0b-4b2a-b8a7-b7ee83a70f9c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d2fe3be3-ce0b-4b2a-b8a7-b7ee83a70f9c' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-25e06863-04df-4cdb-b929-cd114174d92c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25e06863-04df-4cdb-b929-cd114174d92c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0fee957-0493-44e3-b5e9-e81276bd95a3' class='xr-var-data-in' type='checkbox'><label for='data-e0fee957-0493-44e3-b5e9-e81276bd95a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-fd7acd90-c06e-406d-9def-5c4c56a1873f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd7acd90-c06e-406d-9def-5c4c56a1873f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71878007-4aaa-4ae9-821c-9ecb4f97f5e2' class='xr-var-data-in' type='checkbox'><label for='data-71878007-4aaa-4ae9-821c-9ecb4f97f5e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-ff7c6744-b479-4b58-8046-ef10919ce592' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ff7c6744-b479-4b58-8046-ef10919ce592' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-e5c2735b-6d48-4edb-9ebe-42862da0a372' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5c2735b-6d48-4edb-9ebe-42862da0a372' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94d861cb-96cc-492b-9123-1b5898866ce7' class='xr-var-data-in' type='checkbox'><label for='data-94d861cb-96cc-492b-9123-1b5898866ce7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1579,7 +1552,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 1 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1604,7 +1577,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-bd0d3f9d-3b8e-46e9-946e-ebc805a88ae7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd0d3f9d-3b8e-46e9-946e-ebc805a88ae7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0413267-a06f-4c68-9a30-1a32bbbef0d0' class='xr-var-data-in' type='checkbox'><label for='data-c0413267-a06f-4c68-9a30-1a32bbbef0d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-aee8f07a-77d1-4556-a1e5-c10d0f226dcb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aee8f07a-77d1-4556-a1e5-c10d0f226dcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7647722d-525b-401d-b30c-f588f85c7e85' class='xr-var-data-in' type='checkbox'><label for='data-7647722d-525b-401d-b30c-f588f85c7e85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1614,7 +1587,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 1 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1639,7 +1612,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-3ddacd78-a539-4021-82f4-383f6650a27a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ddacd78-a539-4021-82f4-383f6650a27a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b90f9b92-28cb-4f13-871c-4485f62cd11b' class='xr-var-data-in' type='checkbox'><label for='data-b90f9b92-28cb-4f13-871c-4485f62cd11b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-170b1d93-d606-42d9-b977-e6997b7a5099' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-170b1d93-d606-42d9-b977-e6997b7a5099' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d96c467c-6f8d-43a6-9ae0-e7b862b27a1f' class='xr-var-data-in' type='checkbox'><label for='data-d96c467c-6f8d-43a6-9ae0-e7b862b27a1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1649,7 +1622,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 1 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1674,7 +1647,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-fdbe6d51-86eb-4db8-9d1e-085185b94072' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdbe6d51-86eb-4db8-9d1e-085185b94072' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8000e3dd-4553-4a49-b96e-3e8b8d833137' class='xr-var-data-in' type='checkbox'><label for='data-8000e3dd-4553-4a49-b96e-3e8b8d833137' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-bbf55e8c-0650-4dbe-a0cd-67b67960ea79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbf55e8c-0650-4dbe-a0cd-67b67960ea79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f8542b7-6cb3-4308-9dfa-522f13320543' class='xr-var-data-in' type='checkbox'><label for='data-2f8542b7-6cb3-4308-9dfa-522f13320543' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1684,7 +1657,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 1 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1709,21 +1682,17 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-47cb3548-5dcd-4bd9-9e3a-fc66eed75864' class='xr-section-summary-in' type='checkbox'  checked><label for='section-47cb3548-5dcd-4bd9-9e3a-fc66eed75864' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-bf38e906-126b-49cf-a01e-b91d8603982a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bf38e906-126b-49cf-a01e-b91d8603982a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'SST' (time: 1, nlat: 2400, nlon: 3600)>\n",
-       "dask.array<where, shape=(1, 2400, 3600), dtype=float32, chunksize=(1, 2400, 3600), chunktype=numpy.ndarray>\n",
+       "<xarray.DataArray 'TAREA' (nlat: 2400, nlon: 3600)>\n",
+       "dask.array<xarray-<this-array>, shape=(2400, 3600), dtype=float64, chunksize=(2400, 3600), chunktype=numpy.ndarray>\n",
        "Coordinates:\n",
-       "  * time     (time) object 0033-11-27 00:00:00\n",
        "    ULONG    (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
        "    ULAT     (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
        "    TLONG    (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
        "    TLAT     (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
-       "Dimensions without coordinates: nlat, nlon\n",
-       "Attributes:\n",
-       "    units:      degC\n",
-       "    long_name:  Surface Potential Temperature"
+       "Dimensions without coordinates: nlat, nlon"
       ]
      },
      "execution_count": 8,
@@ -1732,9 +1701,8 @@
     }
    ],
    "source": [
-    "sst = ds.SST.where(wet_mask)\n",
-    "sst = sst.chunk({'nlat': len(ds.nlat), 'nlon': len(ds.nlon)})  # 1 chunk\n",
-    "sst"
+    "area = area.chunk({'nlat': len(ds.nlat), 'nlon': len(ds.nlon)})  # 1 chunk\n",
+    "area"
    ]
   },
   {
@@ -2096,14 +2064,18 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;TAREA&#x27; (nlat: 2400, nlon: 3600)&gt;\n",
-       "dask.array&lt;xarray-&lt;this-array&gt;, shape=(2400, 3600), dtype=float64, chunksize=(2400, 3600), chunktype=numpy.ndarray&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;SST&#x27; (time: 1, nlat: 2400, nlon: 3600)&gt;\n",
+       "dask.array&lt;where, shape=(1, 2400, 3600), dtype=float32, chunksize=(1, 2400, 3600), chunktype=numpy.ndarray&gt;\n",
        "Coordinates:\n",
+       "  * time     (time) object 0033-11-27 00:00:00\n",
        "    ULONG    (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    ULAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLONG    (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
-       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'TAREA'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-bf58e1ca-2b9c-44a8-80f5-7bf193937792' class='xr-array-in' type='checkbox' checked><label for='section-bf58e1ca-2b9c-44a8-80f5-7bf193937792' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon\n",
+       "Attributes:\n",
+       "    units:      degC\n",
+       "    long_name:  Surface Potential Temperature</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'SST'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4d24693f-5ecf-461c-a0a7-c463395346a0' class='xr-array-in' type='checkbox' checked><label for='section-4d24693f-5ecf-461c-a0a7-c463395346a0' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2111,34 +2083,57 @@
        "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
-       "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 1 Tasks </td><td> 1 Chunks </td></tr>\n",
-       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
+       "    <tr><th> Bytes </th><td> 34.56 MB </td> <td> 34.56 MB </td></tr>\n",
+       "    <tr><th> Shape </th><td> (1, 2400, 3600) </td> <td> (1, 2400, 3600) </td></tr>\n",
+       "    <tr><th> Count </th><td> 3 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</td>\n",
        "<td>\n",
-       "<svg width=\"170\" height=\"130\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "<svg width=\"194\" height=\"144\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
        "\n",
        "  <!-- Horizontal lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"0\" y1=\"80\" x2=\"120\" y2=\"80\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"80\" x2=\"24\" y2=\"94\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Vertical lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"80\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"80\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"80\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"94\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Colored Rectangle -->\n",
-       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,80.0 0.0,80.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,94.9485979497544 10.0,80.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"94\" x2=\"144\" y2=\"94\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"94\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"94\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,94.9485979497544 24.9485979497544,94.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
        "\n",
        "  <!-- Text -->\n",
-       "  <text x=\"60.000000\" y=\"100.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3600</text>\n",
-       "  <text x=\"140.000000\" y=\"40.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,40.000000)\">2400</text>\n",
+       "  <text x=\"84.948598\" y=\"114.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3600</text>\n",
+       "  <text x=\"164.948598\" y=\"54.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,54.948598)\">2400</text>\n",
+       "  <text x=\"7.474299\" y=\"107.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,107.474299)\">1</text>\n",
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-8514e316-75d5-4f0c-b1cc-de3030a63753' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8514e316-75d5-4f0c-b1cc-de3030a63753' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-642c3730-c75f-40dd-8434-98877fadd6bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-642c3730-c75f-40dd-8434-98877fadd6bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e5cccd7-30a9-4a6e-b5b4-9236c2ee8402' class='xr-var-data-in' type='checkbox'><label for='data-2e5cccd7-30a9-4a6e-b5b4-9236c2ee8402' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-9744239e-ffe9-4cd5-8c45-2d56522d9e35' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9744239e-ffe9-4cd5-8c45-2d56522d9e35' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-60d925b4-b7f1-486f-a3e7-11b976b53e49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60d925b4-b7f1-486f-a3e7-11b976b53e49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbf42161-141e-49ff-a477-6a318c82d4ba' class='xr-var-data-in' type='checkbox'><label for='data-fbf42161-141e-49ff-a477-6a318c82d4ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-9322a416-fd68-488f-9746-ff559e1dff3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9322a416-fd68-488f-9746-ff559e1dff3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bff4a43-79a5-46af-9257-dbd400b5d75b' class='xr-var-data-in' type='checkbox'><label for='data-7bff4a43-79a5-46af-9257-dbd400b5d75b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2173,7 +2168,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-3d2c380a-5fdb-472b-b5ae-b9163a693e89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d2c380a-5fdb-472b-b5ae-b9163a693e89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feb2b605-4ebd-4343-831a-4a346b1b26d7' class='xr-var-data-in' type='checkbox'><label for='data-feb2b605-4ebd-4343-831a-4a346b1b26d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-c3b646e2-b008-4347-b93c-d1b7a13b7cd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3b646e2-b008-4347-b93c-d1b7a13b7cd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67cecf48-6c7e-4b6c-ad60-fdf91f4eea1a' class='xr-var-data-in' type='checkbox'><label for='data-67cecf48-6c7e-4b6c-ad60-fdf91f4eea1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2208,7 +2203,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-62c7b46e-1eca-4605-8685-7e59c1d0b2db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62c7b46e-1eca-4605-8685-7e59c1d0b2db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-421b340f-be7e-413d-b79b-bc94a2c86c4f' class='xr-var-data-in' type='checkbox'><label for='data-421b340f-be7e-413d-b79b-bc94a2c86c4f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-1adb7aee-5a39-4aa4-8f05-86885c3c4293' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1adb7aee-5a39-4aa4-8f05-86885c3c4293' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f746082-d1f5-4bab-9f98-e0365a108bc7' class='xr-var-data-in' type='checkbox'><label for='data-2f746082-d1f5-4bab-9f98-e0365a108bc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2243,7 +2238,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-ef091886-4f42-4d4f-8209-3ed37e628bef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef091886-4f42-4d4f-8209-3ed37e628bef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35a233b8-3696-4c4a-a9b6-e670e35f7556' class='xr-var-data-in' type='checkbox'><label for='data-35a233b8-3696-4c4a-a9b6-e670e35f7556' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-6a387ed9-26d7-4f6d-bc57-77a6b25020a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a387ed9-26d7-4f6d-bc57-77a6b25020a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-519717f2-f1ea-4fa4-8e06-99971e049710' class='xr-var-data-in' type='checkbox'><label for='data-519717f2-f1ea-4fa4-8e06-99971e049710' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2278,17 +2273,21 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e0d1d5d-9b95-42fa-8165-7d4094ae37ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2e0d1d5d-9b95-42fa-8165-7d4094ae37ea' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f731d07c-ce19-40e9-bc72-7e9282b1ebba' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f731d07c-ce19-40e9-bc72-7e9282b1ebba' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'TAREA' (nlat: 2400, nlon: 3600)>\n",
-       "dask.array<xarray-<this-array>, shape=(2400, 3600), dtype=float64, chunksize=(2400, 3600), chunktype=numpy.ndarray>\n",
+       "<xarray.DataArray 'SST' (time: 1, nlat: 2400, nlon: 3600)>\n",
+       "dask.array<where, shape=(1, 2400, 3600), dtype=float32, chunksize=(1, 2400, 3600), chunktype=numpy.ndarray>\n",
        "Coordinates:\n",
+       "  * time     (time) object 0033-11-27 00:00:00\n",
        "    ULONG    (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
        "    ULAT     (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
        "    TLONG    (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
        "    TLAT     (nlat, nlon) float64 dask.array<chunksize=(2400, 3600), meta=np.ndarray>\n",
-       "Dimensions without coordinates: nlat, nlon"
+       "Dimensions without coordinates: nlat, nlon\n",
+       "Attributes:\n",
+       "    units:      degC\n",
+       "    long_name:  Surface Potential Temperature"
       ]
      },
      "execution_count": 9,
@@ -2297,8 +2296,9 @@
     }
    ],
    "source": [
-    "area = area.chunk({'nlat': len(ds.nlat), 'nlon': len(ds.nlon)})  # 1 chunk\n",
-    "area"
+    "sst = ds.SST.where(wet_mask)\n",
+    "sst = sst.chunk({'nlat': len(ds.nlat), 'nlon': len(ds.nlon)})  # 1 chunk\n",
+    "sst"
    ]
   },
   {
@@ -2318,7 +2318,7 @@
     "    'filter_scale': 10,\n",
     "    'dx_min': 1,\n",
     "    'filter_shape': gcm_filters.FilterShape.GAUSSIAN,\n",
-    "    'grid_type': gcm_filters.GridType.TRIPOLAR_REGULAR_WITH_LAND\n",
+    "    'grid_type': gcm_filters.GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND\n",
     "}"
    ]
   },
@@ -2326,7 +2326,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We now create our CPU-compatible filter with our **NumPy**-based `wet_mask`."
+    "We now create our CPU-compatible filter with our **NumPy**-based `area` and `wet_mask`."
    ]
   },
   {
@@ -2337,7 +2337,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.TRIPOLAR_REGULAR_WITH_LAND: 4>)"
+       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND: 6>)"
       ]
      },
      "execution_count": 11,
@@ -2346,7 +2346,7 @@
     }
    ],
    "source": [
-    "filter_cpu = gcm_filters.Filter(grid_vars={'wet_mask': wet_mask}, **specs)\n",
+    "filter_cpu = gcm_filters.Filter(grid_vars={'area': area, 'wet_mask': wet_mask}, **specs)\n",
     "filter_cpu"
    ]
   },
@@ -2354,7 +2354,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Next, we filter the **NumPy**-based `SST * area` lazily on the CPU's with the simple fixed factor filter."
+    "Next, we filter the **NumPy**-based `SST` lazily on the CPU's with the simple fixed factor filter."
    ]
   },
   {
@@ -2724,7 +2724,7 @@
        "    ULAT     (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
        "    TLONG    (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
        "    TLAT     (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
-       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7ac95959-0da6-4d95-8518-b4a71c24e9d6' class='xr-array-in' type='checkbox' checked><label for='section-7ac95959-0da6-4d95-8518-b4a71c24e9d6' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ff0ec5c7-5945-4e55-956d-949c4109c7a5' class='xr-array-in' type='checkbox' checked><label for='section-ff0ec5c7-5945-4e55-956d-949c4109c7a5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2782,31 +2782,31 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-a462d96d-c51b-47ef-8d64-9c808f9a601e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a462d96d-c51b-47ef-8d64-9c808f9a601e' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-6bcf64d5-a24e-4e19-bf94-d040287af582' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bcf64d5-a24e-4e19-bf94-d040287af582' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fd7d527-13f9-4ecb-b735-002b7c2959fe' class='xr-var-data-in' type='checkbox'><label for='data-9fd7d527-13f9-4ecb-b735-002b7c2959fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-9a30b344-d95b-4e4e-a27d-cc58903cead7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a30b344-d95b-4e4e-a27d-cc58903cead7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16fe5ee3-7138-4d9e-a17f-cec32e5167d6' class='xr-var-data-in' type='checkbox'><label for='data-16fe5ee3-7138-4d9e-a17f-cec32e5167d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-79c10476-07bb-4c24-b0db-73b9a86c20aa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-79c10476-07bb-4c24-b0db-73b9a86c20aa' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-bc142632-8efe-437d-b4c6-5cc3af18653f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc142632-8efe-437d-b4c6-5cc3af18653f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-495a4a34-b93f-40da-9d17-43c47400e409' class='xr-var-data-in' type='checkbox'><label for='data-495a4a34-b93f-40da-9d17-43c47400e409' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-11b8e71a-101b-4ae5-8963-24d2ec8d1baf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b8e71a-101b-4ae5-8963-24d2ec8d1baf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db831cea-0e71-4111-a249-2d6d16c0b7c8' class='xr-var-data-in' type='checkbox'><label for='data-db831cea-0e71-4111-a249-2d6d16c0b7c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-2c3523d5-06cc-4443-a14b-f4cffd3e9626' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c3523d5-06cc-4443-a14b-f4cffd3e9626' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e53deb30-db2e-4564-a61e-da54eba20b91' class='xr-var-data-in' type='checkbox'><label for='data-e53deb30-db2e-4564-a61e-da54eba20b91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-2ae556ad-75a7-4baa-b507-e738cf66bd19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ae556ad-75a7-4baa-b507-e738cf66bd19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3db4b26-893e-4603-8d38-6c83111a24d7' class='xr-var-data-in' type='checkbox'><label for='data-f3db4b26-893e-4603-8d38-6c83111a24d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-c6dfc8d0-9908-46d8-9c4e-e3ecd8d5e774' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6dfc8d0-9908-46d8-9c4e-e3ecd8d5e774' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c3db0e9-e03d-4873-9353-b250699f35f0' class='xr-var-data-in' type='checkbox'><label for='data-2c3db0e9-e03d-4873-9353-b250699f35f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-6fb75095-806d-4953-9578-e0fb5ae9499b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fb75095-806d-4953-9578-e0fb5ae9499b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87c73d08-9b18-4e8e-b5f7-cf64cb6f9ce3' class='xr-var-data-in' type='checkbox'><label for='data-87c73d08-9b18-4e8e-b5f7-cf64cb6f9ce3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-a384ba7a-90de-4c1a-8073-a386f275012e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a384ba7a-90de-4c1a-8073-a386f275012e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68c1b955-1091-4dc9-a3b4-9a9ea1747bb1' class='xr-var-data-in' type='checkbox'><label for='data-68c1b955-1091-4dc9-a3b4-9a9ea1747bb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-baa2b5b6-19a7-4276-b071-611bc1c3cec2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-baa2b5b6-19a7-4276-b071-611bc1c3cec2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4254f00e-686b-46dd-bf6a-3e889e9c8fac' class='xr-var-data-in' type='checkbox'><label for='data-4254f00e-686b-46dd-bf6a-3e889e9c8fac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-361bbe3c-b013-4311-b3ae-ab94f08b66ff' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-361bbe3c-b013-4311-b3ae-ab94f08b66ff' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cc69524f-71b0-498f-9abf-9cc74a2961fe' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cc69524f-71b0-498f-9abf-9cc74a2961fe' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (time: 1, nlat: 2400, nlon: 3600)>\n",
@@ -2826,8 +2826,7 @@
     }
    ],
    "source": [
-    "filtered_cpu = filter_cpu.apply(sst * area, dims=['nlat', 'nlon'])\n",
-    "filtered_cpu = filtered_cpu / area\n",
+    "filtered_cpu = filter_cpu.apply(sst, dims=['nlat', 'nlon'])\n",
     "filtered_cpu"
    ]
   },
@@ -2847,8 +2846,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 2.85 s, sys: 1.84 s, total: 4.69 s\n",
-      "Wall time: 9.6 s\n"
+      "CPU times: user 2.7 s, sys: 1.88 s, total: 4.58 s\n",
+      "Wall time: 4.57 s\n"
      ]
     }
    ],
@@ -3288,7 +3287,7 @@
        "    ULAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLONG    (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
-       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KMT'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ff397f7d-9f71-404f-b0d6-815d126d2f98' class='xr-array-in' type='checkbox' checked><label for='section-ff397f7d-9f71-404f-b0d6-815d126d2f98' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KMT'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7c72f9f9-7985-4876-9470-9589f1344310' class='xr-array-in' type='checkbox' checked><label for='section-7c72f9f9-7985-4876-9470-9589f1344310' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3323,7 +3322,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-e2b74706-2257-421e-bf38-d31e4c877906' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e2b74706-2257-421e-bf38-d31e4c877906' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-23c12658-e648-4678-a8c4-c626d96a7b26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23c12658-e648-4678-a8c4-c626d96a7b26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c12c2a1-184f-4984-a00d-244b442827e3' class='xr-var-data-in' type='checkbox'><label for='data-3c12c2a1-184f-4984-a00d-244b442827e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-6e7e37ad-cc59-43ca-9a67-d2c3f18ce1ec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e7e37ad-cc59-43ca-9a67-d2c3f18ce1ec' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-32318ffb-5d7f-49cc-9c5f-2ebc1b84183f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32318ffb-5d7f-49cc-9c5f-2ebc1b84183f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88708731-a3ea-45c3-9dae-6da75a7cc9b9' class='xr-var-data-in' type='checkbox'><label for='data-88708731-a3ea-45c3-9dae-6da75a7cc9b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3358,7 +3357,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-500929c8-3020-4fb2-ac16-a29f1f24a3a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-500929c8-3020-4fb2-ac16-a29f1f24a3a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8d53436-5cc1-4c68-b73c-9809766fd659' class='xr-var-data-in' type='checkbox'><label for='data-d8d53436-5cc1-4c68-b73c-9809766fd659' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-f98247ab-4f95-4403-a58a-ded9fefe6dd2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f98247ab-4f95-4403-a58a-ded9fefe6dd2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8aff21ee-3f41-4717-9b4d-31941b3144cc' class='xr-var-data-in' type='checkbox'><label for='data-8aff21ee-3f41-4717-9b4d-31941b3144cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3393,7 +3392,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-7c8c1bba-7e06-422c-93ee-90d2fa0eb349' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c8c1bba-7e06-422c-93ee-90d2fa0eb349' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43192476-d2db-4b84-bf1b-e5d7970beea3' class='xr-var-data-in' type='checkbox'><label for='data-43192476-d2db-4b84-bf1b-e5d7970beea3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-bb4cc073-6d8b-4d09-9b21-ed6cfd2cc55a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb4cc073-6d8b-4d09-9b21-ed6cfd2cc55a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a080fb9-2261-4e4c-94b3-e0edc785d67a' class='xr-var-data-in' type='checkbox'><label for='data-1a080fb9-2261-4e4c-94b3-e0edc785d67a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3428,7 +3427,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-1dd775d2-0ea4-49e1-9922-0463ba71a017' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1dd775d2-0ea4-49e1-9922-0463ba71a017' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9afc77a-a895-4fd8-998c-55aaa8ac0459' class='xr-var-data-in' type='checkbox'><label for='data-b9afc77a-a895-4fd8-998c-55aaa8ac0459' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-afaa577f-2797-4f01-b4c0-eee0c46e20ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afaa577f-2797-4f01-b4c0-eee0c46e20ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a2dff7c-ab4c-49e7-ba0e-5dbeff1c91a8' class='xr-var-data-in' type='checkbox'><label for='data-8a2dff7c-ab4c-49e7-ba0e-5dbeff1c91a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3463,7 +3462,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-438ecd53-2c39-4e93-87cf-f8916b94774f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-438ecd53-2c39-4e93-87cf-f8916b94774f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5f12d833-1c9d-4ea2-b9a4-70cfa9e735fa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f12d833-1c9d-4ea2-b9a4-70cfa9e735fa' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'KMT' (nlat: 2400, nlon: 3600)>\n",
@@ -3857,7 +3856,7 @@
        "Dimensions without coordinates: nlat, nlon\n",
        "Attributes:\n",
        "    units:      degC\n",
-       "    long_name:  Surface Potential Temperature</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'SST'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8e556a0c-de9d-4868-a3f8-a61aaf79cf24' class='xr-array-in' type='checkbox' checked><label for='section-8e556a0c-de9d-4868-a3f8-a61aaf79cf24' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    long_name:  Surface Potential Temperature</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'SST'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ee4012f8-377b-4635-9060-83c06a45ed30' class='xr-array-in' type='checkbox' checked><label for='section-ee4012f8-377b-4635-9060-83c06a45ed30' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3915,7 +3914,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-c86ca95b-6f2b-4af3-840f-7fca88366b88' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c86ca95b-6f2b-4af3-840f-7fca88366b88' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-1c849d97-7e59-4e70-a6a7-c866d5602d92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c849d97-7e59-4e70-a6a7-c866d5602d92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30e56d82-e13c-4d11-a6df-56d18f3517d2' class='xr-var-data-in' type='checkbox'><label for='data-30e56d82-e13c-4d11-a6df-56d18f3517d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-37fc7662-751b-4629-ba9e-37b4c1c201d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37fc7662-751b-4629-ba9e-37b4c1c201d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89d66653-cdcb-4683-bc77-1d96d21e4d0b' class='xr-var-data-in' type='checkbox'><label for='data-89d66653-cdcb-4683-bc77-1d96d21e4d0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-05b32c11-5dca-400b-a642-099702bef5a0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-05b32c11-5dca-400b-a642-099702bef5a0' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-529115c4-49aa-4bce-b177-dca59cdda055' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-529115c4-49aa-4bce-b177-dca59cdda055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-297bb2a1-9c67-4f06-a804-4f0e4f11c836' class='xr-var-data-in' type='checkbox'><label for='data-297bb2a1-9c67-4f06-a804-4f0e4f11c836' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-b9693a4b-2303-4b69-a01d-1af53d40d491' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9693a4b-2303-4b69-a01d-1af53d40d491' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddaa11ff-d815-48cc-bc4a-eef32d5264a4' class='xr-var-data-in' type='checkbox'><label for='data-ddaa11ff-d815-48cc-bc4a-eef32d5264a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3950,7 +3949,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-fa3a17fa-de16-4b51-87e0-89786d23531e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa3a17fa-de16-4b51-87e0-89786d23531e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da5335d7-547d-432a-88bc-d90a498172f2' class='xr-var-data-in' type='checkbox'><label for='data-da5335d7-547d-432a-88bc-d90a498172f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-4dafd452-6956-4c67-89db-dca57c9ba628' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dafd452-6956-4c67-89db-dca57c9ba628' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc9347ed-9a68-4f25-958a-80adeed057ed' class='xr-var-data-in' type='checkbox'><label for='data-cc9347ed-9a68-4f25-958a-80adeed057ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3985,7 +3984,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-17dd57c7-6be3-4c96-8ddf-3eb4d394d492' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17dd57c7-6be3-4c96-8ddf-3eb4d394d492' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e399ea05-b96a-478d-a735-2e7ad43e98fd' class='xr-var-data-in' type='checkbox'><label for='data-e399ea05-b96a-478d-a735-2e7ad43e98fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-5155da86-8efa-49f9-9408-bcd3d0c174b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5155da86-8efa-49f9-9408-bcd3d0c174b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebbc73fa-700e-45ea-b616-1ca1066dd633' class='xr-var-data-in' type='checkbox'><label for='data-ebbc73fa-700e-45ea-b616-1ca1066dd633' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4020,7 +4019,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-c0af2eea-00ec-4f91-9eb1-47dd4ab763c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0af2eea-00ec-4f91-9eb1-47dd4ab763c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e389ed-591b-4dfa-9d20-85dee7c7b23b' class='xr-var-data-in' type='checkbox'><label for='data-65e389ed-591b-4dfa-9d20-85dee7c7b23b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-fc2d456c-5b75-4a07-8e55-d7fbb9a919dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc2d456c-5b75-4a07-8e55-d7fbb9a919dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9896bf57-bfd9-4e6c-a5e6-45c02419c14e' class='xr-var-data-in' type='checkbox'><label for='data-9896bf57-bfd9-4e6c-a5e6-45c02419c14e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4055,7 +4054,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-51d2c426-50ed-4942-be0f-d3301060c5c7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-51d2c426-50ed-4942-be0f-d3301060c5c7' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7bee2c1a-aeb6-4f51-aba8-2e49599a3da3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7bee2c1a-aeb6-4f51-aba8-2e49599a3da3' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'SST' (time: 1, nlat: 2400, nlon: 3600)>\n",
@@ -4449,7 +4448,7 @@
        "    ULAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLONG    (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
        "    TLAT     (nlat, nlon) float64 dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;\n",
-       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'TAREA'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5fbc0609-c090-4fe1-bc24-abe8c23fdfa0' class='xr-array-in' type='checkbox' checked><label for='section-5fbc0609-c090-4fe1-bc24-abe8c23fdfa0' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'TAREA'</div><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3e3b5ad9-07bb-4e00-976d-d37f2b0c32a5' class='xr-array-in' type='checkbox' checked><label for='section-3e3b5ad9-07bb-4e00-976d-d37f2b0c32a5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4484,7 +4483,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-2d0e3096-7666-42af-9e22-c91f1f17439f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2d0e3096-7666-42af-9e22-c91f1f17439f' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-80d706bf-678c-489a-9c60-35f3476f0382' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80d706bf-678c-489a-9c60-35f3476f0382' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2529d5a-1560-49f5-bcf0-6d7dc00d6ad0' class='xr-var-data-in' type='checkbox'><label for='data-b2529d5a-1560-49f5-bcf0-6d7dc00d6ad0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-e57e4235-7a9a-4f28-99af-7378dc750480' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e57e4235-7a9a-4f28-99af-7378dc750480' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-070c8546-a792-4109-8cdc-8ad780d6aa3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-070c8546-a792-4109-8cdc-8ad780d6aa3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd201d27-7fa3-48a0-8ecc-6e0550255dca' class='xr-var-data-in' type='checkbox'><label for='data-bd201d27-7fa3-48a0-8ecc-6e0550255dca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4494,7 +4493,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 3 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -4519,7 +4518,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-a6728063-3121-4fa7-8d20-72a4bba695b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6728063-3121-4fa7-8d20-72a4bba695b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bc76ea3-5537-41a0-b918-1d348e192116' class='xr-var-data-in' type='checkbox'><label for='data-2bc76ea3-5537-41a0-b918-1d348e192116' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-03434dfb-9121-4d9a-b8b9-fc5411da7380' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03434dfb-9121-4d9a-b8b9-fc5411da7380' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e3998b0-6faa-4236-b083-ab6136f1a66a' class='xr-var-data-in' type='checkbox'><label for='data-7e3998b0-6faa-4236-b083-ab6136f1a66a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4529,7 +4528,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 3 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -4554,7 +4553,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-a99f732d-8e12-4600-847b-941ef9610eeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a99f732d-8e12-4600-847b-941ef9610eeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cda75161-e69f-4e20-89e4-bca7bc79f5a5' class='xr-var-data-in' type='checkbox'><label for='data-cda75161-e69f-4e20-89e4-bca7bc79f5a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-476aa154-8de5-4527-b1b3-cf01e24b7db7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-476aa154-8de5-4527-b1b3-cf01e24b7db7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a1ff5c0-4320-4a7d-a6ea-005e936fbf1b' class='xr-var-data-in' type='checkbox'><label for='data-8a1ff5c0-4320-4a7d-a6ea-005e936fbf1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4564,7 +4563,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 3 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -4589,7 +4588,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-c95e35d0-a38f-4764-90db-d4e145ab9160' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c95e35d0-a38f-4764-90db-d4e145ab9160' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b2d5e4a-998f-4ff3-a98c-4f0c9f6dd475' class='xr-var-data-in' type='checkbox'><label for='data-3b2d5e4a-998f-4ff3-a98c-4f0c9f6dd475' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2400, 3600), meta=np.ndarray&gt;</div><input id='attrs-bfb2367c-6967-4cc4-9624-b739a57c7431' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfb2367c-6967-4cc4-9624-b739a57c7431' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e7e6dae-3c34-43d8-8d3c-7a75479b41ce' class='xr-var-data-in' type='checkbox'><label for='data-3e7e6dae-3c34-43d8-8d3c-7a75479b41ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4599,7 +4598,7 @@
        "  <tbody>\n",
        "    <tr><th> Bytes </th><td> 69.12 MB </td> <td> 69.12 MB </td></tr>\n",
        "    <tr><th> Shape </th><td> (2400, 3600) </td> <td> (2400, 3600) </td></tr>\n",
-       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Count </th><td> 3 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -4624,7 +4623,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-dbe6d656-5a66-4d74-97db-865253aa9a87' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dbe6d656-5a66-4d74-97db-865253aa9a87' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-8c1181d8-c223-49c3-b544-ce12d4596380' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8c1181d8-c223-49c3-b544-ce12d4596380' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'TAREA' (nlat: 2400, nlon: 3600)>\n",
@@ -4652,7 +4651,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We create the filter with the same filter specs as above, but now with a **CuPy**-based `wet_mask`."
+    "We create the filter with the same filter specs as above, but now with **CuPy**-based `area` and `wet_mask`."
    ]
   },
   {
@@ -4663,7 +4662,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.TRIPOLAR_REGULAR_WITH_LAND: 4>)"
+       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND: 6>)"
       ]
      },
      "execution_count": 19,
@@ -4672,7 +4671,7 @@
     }
    ],
    "source": [
-    "filter_gpu = gcm_filters.Filter(grid_vars={'wet_mask': wet_mask_gpu}, **specs)\n",
+    "filter_gpu = gcm_filters.Filter(grid_vars={'area': area_gpu, 'wet_mask': wet_mask_gpu}, **specs)\n",
     "filter_gpu"
    ]
   },
@@ -4680,7 +4679,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Filtering of the data works the same way as before, except that we apply our filter to our **CuPy**-based `SST * area`."
+    "Filtering of the data works the same way as before, except that we apply our filter to our **CuPy**-based `SST`."
    ]
   },
   {
@@ -5050,7 +5049,7 @@
        "    ULAT     (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
        "    TLONG    (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
        "    TLAT     (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
-       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-651eafd3-1003-467a-8a30-acbc8ff4ac04' class='xr-array-in' type='checkbox' checked><label for='section-651eafd3-1003-467a-8a30-acbc8ff4ac04' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c6fd3b53-7c3c-4597-8837-014aacf53545' class='xr-array-in' type='checkbox' checked><label for='section-c6fd3b53-7c3c-4597-8837-014aacf53545' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5108,31 +5107,31 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-1e25b4d8-35b3-465c-9faa-4060525598e6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1e25b4d8-35b3-465c-9faa-4060525598e6' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-c407d700-245a-4e0c-a21f-dabf660b0b33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c407d700-245a-4e0c-a21f-dabf660b0b33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d51c629-64d0-46a0-9141-03dc89362877' class='xr-var-data-in' type='checkbox'><label for='data-8d51c629-64d0-46a0-9141-03dc89362877' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-4b525e11-65ad-478b-9e76-c7ee33f4c093' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b525e11-65ad-478b-9e76-c7ee33f4c093' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33fac7d5-492a-4539-9dc2-ce5c6ad583f5' class='xr-var-data-in' type='checkbox'><label for='data-33fac7d5-492a-4539-9dc2-ce5c6ad583f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-2bbc73cb-b7e8-4324-b859-3f0f54afc38d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2bbc73cb-b7e8-4324-b859-3f0f54afc38d' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-c13f97e6-68c0-4909-a974-cb989df56842' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c13f97e6-68c0-4909-a974-cb989df56842' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63fda1ca-1e60-4e6a-aaae-67cd32a6c930' class='xr-var-data-in' type='checkbox'><label for='data-63fda1ca-1e60-4e6a-aaae-67cd32a6c930' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-5c5007a6-96c8-42d9-91e5-b44e397eb0f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c5007a6-96c8-42d9-91e5-b44e397eb0f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47f6a2df-c489-4f8f-905b-e51651150200' class='xr-var-data-in' type='checkbox'><label for='data-47f6a2df-c489-4f8f-905b-e51651150200' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-ff0b7fc6-09b8-4606-9880-4755cc47aee6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff0b7fc6-09b8-4606-9880-4755cc47aee6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c287d38c-f2fd-4077-8c68-3b1348862535' class='xr-var-data-in' type='checkbox'><label for='data-c287d38c-f2fd-4077-8c68-3b1348862535' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-143e5384-4861-4b4c-81fb-6edffb2c4e16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-143e5384-4861-4b4c-81fb-6edffb2c4e16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7e7ff3b-c3fd-4873-ad8e-862ed43f37b1' class='xr-var-data-in' type='checkbox'><label for='data-f7e7ff3b-c3fd-4873-ad8e-862ed43f37b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-56b7ef23-fd1c-42ba-8166-d5ec59811e84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56b7ef23-fd1c-42ba-8166-d5ec59811e84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c23bbdc-cc5c-4e1d-80a1-13622968dd03' class='xr-var-data-in' type='checkbox'><label for='data-0c23bbdc-cc5c-4e1d-80a1-13622968dd03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-0ae9cdb4-7a28-47e0-a827-45bd9e6c4463' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ae9cdb4-7a28-47e0-a827-45bd9e6c4463' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c041d9e4-76b6-413a-976a-8a2be65fd2e2' class='xr-var-data-in' type='checkbox'><label for='data-c041d9e4-76b6-413a-976a-8a2be65fd2e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-c23c0195-71ba-482b-b59b-ad01bb1ba288' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c23c0195-71ba-482b-b59b-ad01bb1ba288' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f994b64-0b0d-49ff-be34-3a741d44c507' class='xr-var-data-in' type='checkbox'><label for='data-0f994b64-0b0d-49ff-be34-3a741d44c507' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-9fb9c2a1-0f6b-4987-a0a7-3998d30b57de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fb9c2a1-0f6b-4987-a0a7-3998d30b57de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-971118e6-a94d-47a1-a89a-dcf64bd39fc4' class='xr-var-data-in' type='checkbox'><label for='data-971118e6-a94d-47a1-a89a-dcf64bd39fc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-04b73552-e02c-47d2-8eb3-ad52aa903cdd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-04b73552-e02c-47d2-8eb3-ad52aa903cdd' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cbc1d10f-bf80-4b5f-8edb-1e3bfdd12656' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cbc1d10f-bf80-4b5f-8edb-1e3bfdd12656' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (time: 1, nlat: 2400, nlon: 3600)>\n",
@@ -5152,8 +5151,7 @@
     }
    ],
    "source": [
-    "filtered_gpu = filter_gpu.apply(sst_gpu * area_gpu, dims=['nlat', 'nlon'])\n",
-    "filtered_gpu = filtered_gpu / area_gpu\n",
+    "filtered_gpu = filter_gpu.apply(sst_gpu, dims=['nlat', 'nlon'])\n",
     "filtered_gpu"
    ]
   },
@@ -5531,7 +5529,7 @@
        "    ULAT     (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
        "    TLONG    (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
        "    TLAT     (nlat, nlon) float64 -1.0 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0 -1.0\n",
-       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2695f425-682c-43e8-b6e9-1456cedaf856' class='xr-array-in' type='checkbox' checked><label for='section-2695f425-682c-43e8-b6e9-1456cedaf856' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "Dimensions without coordinates: nlat, nlon</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d8759a99-2f4c-476c-ab1e-7798933bc926' class='xr-array-in' type='checkbox' checked><label for='section-d8759a99-2f4c-476c-ab1e-7798933bc926' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 2400, 3600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5589,31 +5587,31 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-bcfdb4e7-c760-4510-96c5-b73aa0e0ca65' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bcfdb4e7-c760-4510-96c5-b73aa0e0ca65' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-118c13b9-9868-4d73-b0b9-e892199f70b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-118c13b9-9868-4d73-b0b9-e892199f70b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02c2b3b0-3c04-4748-890a-ea421cf47229' class='xr-var-data-in' type='checkbox'><label for='data-02c2b3b0-3c04-4748-890a-ea421cf47229' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-af093f0a-0a27-47bc-baa5-42d5156ba3d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af093f0a-0a27-47bc-baa5-42d5156ba3d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-463725f4-14af-44d4-8204-ddae42aff57c' class='xr-var-data-in' type='checkbox'><label for='data-463725f4-14af-44d4-8204-ddae42aff57c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-c4562fd1-ee4e-49ae-a45f-050b6e2a7e8b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c4562fd1-ee4e-49ae-a45f-050b6e2a7e8b' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-8cd8effa-6790-4056-adf3-8faf35b0b52b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cd8effa-6790-4056-adf3-8faf35b0b52b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64ea210f-f7c9-4230-be9c-2aa5216197f1' class='xr-var-data-in' type='checkbox'><label for='data-64ea210f-f7c9-4230-be9c-2aa5216197f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-8662105f-4edf-44c2-b2d3-ae651676f758' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8662105f-4edf-44c2-b2d3-ae651676f758' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0f6052f-2f0e-4543-b86a-96a8111838fc' class='xr-var-data-in' type='checkbox'><label for='data-b0f6052f-2f0e-4543-b86a-96a8111838fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-1afbc69e-9b03-4295-9cd7-469d395e83d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1afbc69e-9b03-4295-9cd7-469d395e83d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-867299dc-ef03-48d6-a941-afac39a28bc6' class='xr-var-data-in' type='checkbox'><label for='data-867299dc-ef03-48d6-a941-afac39a28bc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-2d4815a6-c2b8-42be-8379-8911cbae7f8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d4815a6-c2b8-42be-8379-8911cbae7f8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08c03fc2-7bf7-445f-bd68-9213b1c2a057' class='xr-var-data-in' type='checkbox'><label for='data-08c03fc2-7bf7-445f-bd68-9213b1c2a057' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-acf217bc-4758-4fc8-8d1a-ed7f661005df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acf217bc-4758-4fc8-8d1a-ed7f661005df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e2283fb-fa21-4b21-904d-745e3533f34c' class='xr-var-data-in' type='checkbox'><label for='data-9e2283fb-fa21-4b21-904d-745e3533f34c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-d9ceb78a-009e-48dc-8c9b-dc01989a29b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9ceb78a-009e-48dc-8c9b-dc01989a29b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c082eb00-9b17-47a5-acaf-f785bd183c33' class='xr-var-data-in' type='checkbox'><label for='data-c082eb00-9b17-47a5-acaf-f785bd183c33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-d1ce5820-bfee-4b0c-a03f-b8d3b0f2d02f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1ce5820-bfee-4b0c-a03f-b8d3b0f2d02f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6056893-c8e0-4b4e-b8d0-1cdd73cfcbe0' class='xr-var-data-in' type='checkbox'><label for='data-c6056893-c8e0-4b4e-b8d0-1cdd73cfcbe0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-6067ccf7-c11c-484a-a637-76ae6aec9d49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6067ccf7-c11c-484a-a637-76ae6aec9d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b8e017c-6ec6-4df4-81e6-977ef69206d1' class='xr-var-data-in' type='checkbox'><label for='data-4b8e017c-6ec6-4df4-81e6-977ef69206d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       ...,\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
        "       [-1., -1., -1., ..., -1., -1., -1.],\n",
-       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7da0875c-7ca1-4036-a7b4-dba8e12fcfb0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7da0875c-7ca1-4036-a7b4-dba8e12fcfb0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "       [-1., -1., -1., ..., -1., -1., -1.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dc883558-4c22-4d45-910c-0838a1fc347d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dc883558-4c22-4d45-910c-0838a1fc347d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (time: 1, nlat: 2400, nlon: 3600)>\n",
@@ -5653,8 +5651,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 212 ms, sys: 161 ms, total: 372 ms\n",
-      "Wall time: 1.52 s\n"
+      "CPU times: user 224 ms, sys: 231 ms, total: 454 ms\n",
+      "Wall time: 997 ms\n"
      ]
     }
    ],
diff --git a/docs/tutorial_filter_types.ipynb b/docs/tutorial_filter_types.ipynb
index 02bf8d1..f3b3dd4 100644
--- a/docs/tutorial_filter_types.ipynb
+++ b/docs/tutorial_filter_types.ipynb
@@ -463,7 +463,7 @@
        "    filename:          averages_00030002.nc\n",
        "    grid_tile:         N/A\n",
        "    grid_type:         regular\n",
-       "    title:             NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d4f25a21-e9b2-42ba-bc4c-269c35a5fc45' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d4f25a21-e9b2-42ba-bc4c-269c35a5fc45' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 241</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 561</li><li><span class='xr-has-index'>zi</span>: 16</li><li><span class='xr-has-index'>zl</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9cb49532-a4cf-40c5-b30f-e4aa86053e62' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9cb49532-a4cf-40c5-b30f-e4aa86053e62' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-54772c3a-7cb2-4fe4-b36f-2b6fd79b3faa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54772c3a-7cb2-4fe4-b36f-2b6fd79b3faa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99b1bf82-8de4-4d3a-8c26-ba88a7d836f6' class='xr-var-data-in' type='checkbox'><label for='data-99b1bf82-8de4-4d3a-8c26-ba88a7d836f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-aee26cc9-5c6a-4d0f-b9c3-a8100c32ea74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aee26cc9-5c6a-4d0f-b9c3-a8100c32ea74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b484699-0d0f-45e5-93ae-0cca9181396b' class='xr-var-data-in' type='checkbox'><label for='data-1b484699-0d0f-45e5-93ae-0cca9181396b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
+       "    title:             NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-810628ff-5daf-4dd2-94e8-d79b56788163' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-810628ff-5daf-4dd2-94e8-d79b56788163' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 241</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 561</li><li><span class='xr-has-index'>zi</span>: 16</li><li><span class='xr-has-index'>zl</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-44a1ecc3-ff82-40c1-8372-eb9d4a37c553' class='xr-section-summary-in' type='checkbox'  checked><label for='section-44a1ecc3-ff82-40c1-8372-eb9d4a37c553' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-46a0d807-dbcc-4038-ba03-722989577170' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46a0d807-dbcc-4038-ba03-722989577170' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29090196-eb46-41d3-81df-c66a5e474ba4' class='xr-var-data-in' type='checkbox'><label for='data-29090196-eb46-41d3-81df-c66a5e474ba4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-56850af5-11c2-4232-9ec8-ae80eb9a2828' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56850af5-11c2-4232-9ec8-ae80eb9a2828' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-285c4ca8-2f96-4df5-9026-f86402a92094' class='xr-var-data-in' type='checkbox'><label for='data-285c4ca8-2f96-4df5-9026-f86402a92094' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 13, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 18, 12, 0, 0, 0),\n",
@@ -562,10 +562,10 @@
        "       cftime.Datetime360Day(85, 9, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 13, 12, 0, 0, 0),\n",
-       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-42e7d517-4278-4c50-904d-40d286fd9bb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42e7d517-4278-4c50-904d-40d286fd9bb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1780776-3df7-4031-9020-93d1a5cac530' class='xr-var-data-in' type='checkbox'><label for='data-a1780776-3df7-4031-9020-93d1a5cac530' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 59.5 59.75 60.0</div><input id='attrs-e8003937-2d13-4302-91ef-51ce1c4f704b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8003937-2d13-4302-91ef-51ce1c4f704b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26ce9cbb-6502-456b-b8ff-984b7a93e0ef' class='xr-var-data-in' type='checkbox'><label for='data-26ce9cbb-6502-456b-b8ff-984b7a93e0ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.25,  0.5 , ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-3d3612a5-f86f-4619-8f1a-3ce9cf8d475e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d3612a5-f86f-4619-8f1a-3ce9cf8d475e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2ed86fc-7d6c-438b-b877-752c1d0f94ee' class='xr-var-data-in' type='checkbox'><label for='data-e2ed86fc-7d6c-438b-b877-752c1d0f94ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-70.0 -69.75 -69.5 ... 69.75 70.0</div><input id='attrs-e0ae3b2a-c462-4c36-93b4-80bfb59b483a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0ae3b2a-c462-4c36-93b4-80bfb59b483a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ea2bf14-5898-4d49-8987-1b6189919368' class='xr-var-data-in' type='checkbox'><label for='data-8ea2bf14-5898-4d49-8987-1b6189919368' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-70.  , -69.75, -69.5 , ...,  69.5 ,  69.75,  70.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zi</span></div><div class='xr-var-dims'>(zi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.022e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-8630556f-fd05-463d-87a6-94c4fa97e41f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8630556f-fd05-463d-87a6-94c4fa97e41f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46f7c8a7-a17a-45e2-a663-df16d04ea714' class='xr-var-data-in' type='checkbox'><label for='data-46f7c8a7-a17a-45e2-a663-df16d04ea714' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Interface Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.495, 1022.705, 1023.005, 1023.47 , 1024.03 , 1024.61 , 1025.185,\n",
+       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-91341290-726f-4efe-b72c-7ceb582f64b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91341290-726f-4efe-b72c-7ceb582f64b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0711ddac-cf44-42ef-94c8-2d845c6ca383' class='xr-var-data-in' type='checkbox'><label for='data-0711ddac-cf44-42ef-94c8-2d845c6ca383' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 59.5 59.75 60.0</div><input id='attrs-ae75f2b2-b92c-4c4f-8fe6-c003604640ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae75f2b2-b92c-4c4f-8fe6-c003604640ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e0701ed-7880-4641-99fa-794cd2140242' class='xr-var-data-in' type='checkbox'><label for='data-5e0701ed-7880-4641-99fa-794cd2140242' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.25,  0.5 , ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-77be1086-20b6-426c-be39-ba72576c321c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77be1086-20b6-426c-be39-ba72576c321c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfd540c9-ef22-490f-9396-fca659ce6b85' class='xr-var-data-in' type='checkbox'><label for='data-bfd540c9-ef22-490f-9396-fca659ce6b85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-70.0 -69.75 -69.5 ... 69.75 70.0</div><input id='attrs-f33a92f3-1ec0-4b68-8c58-1dad6a6710fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f33a92f3-1ec0-4b68-8c58-1dad6a6710fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4ea192a-ef20-4916-8e7b-d715593f9e6f' class='xr-var-data-in' type='checkbox'><label for='data-b4ea192a-ef20-4916-8e7b-d715593f9e6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-70.  , -69.75, -69.5 , ...,  69.5 ,  69.75,  70.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zi</span></div><div class='xr-var-dims'>(zi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.022e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-4a379805-a2f4-4911-ad44-0682369695a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a379805-a2f4-4911-ad44-0682369695a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b093c071-7d20-42fc-b65e-738f144ab8c8' class='xr-var-data-in' type='checkbox'><label for='data-b093c071-7d20-42fc-b65e-738f144ab8c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Interface Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.495, 1022.705, 1023.005, 1023.47 , 1024.03 , 1024.61 , 1025.185,\n",
        "       1025.735, 1026.24 , 1026.69 , 1027.085, 1027.425, 1027.7  , 1027.905,\n",
-       "       1028.045, 1028.155])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-180c25d0-fa04-4211-973c-b984f6b29310' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-180c25d0-fa04-4211-973c-b984f6b29310' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9b63d02-485f-40cc-8198-709600466c8f' class='xr-var-data-in' type='checkbox'><label for='data-f9b63d02-485f-40cc-8198-709600466c8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
-       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cb73dec1-8119-4f3f-9ab5-eee633395aaa' class='xr-section-summary-in' type='checkbox'  ><label for='section-cb73dec1-8119-4f3f-9ab5-eee633395aaa' class='xr-section-summary' >Data variables: <span>(33)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-bdb5eaf9-660f-4448-9874-934822227d77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bdb5eaf9-660f-4448-9874-934822227d77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fae4d46-c525-40c6-b4fe-95e58acb3215' class='xr-var-data-in' type='checkbox'><label for='data-5fae4d46-c525-40c6-b4fe-95e58acb3215' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "       1028.045, 1028.155])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-b031745b-33b3-45dc-9193-59e586ecb9d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b031745b-33b3-45dc-9193-59e586ecb9d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5cb1f62-c5fa-4ba0-800d-29819acc4466' class='xr-var-data-in' type='checkbox'><label for='data-f5cb1f62-c5fa-4ba0-800d-29819acc4466' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
+       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e6affe96-4cee-4868-ba7b-af47b5b4fe14' class='xr-section-summary-in' type='checkbox'  ><label for='section-e6affe96-4cee-4868-ba7b-af47b5b4fe14' class='xr-section-summary' >Data variables: <span>(33)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-97a7ab44-e870-4e5e-8453-49967be4d99b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97a7ab44-e870-4e5e-8453-49967be4d99b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a02a95e-bba1-4448-9c0d-5a3ea19aac6a' class='xr-var-data-in' type='checkbox'><label for='data-6a02a95e-bba1-4448-9c0d-5a3ea19aac6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -648,7 +648,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-f7f281f7-0401-4870-8a58-4ef452bcc706' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7f281f7-0401-4870-8a58-4ef452bcc706' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03b4fab5-d39f-4cd2-90e7-4c61b787e500' class='xr-var-data-in' type='checkbox'><label for='data-03b4fab5-d39f-4cd2-90e7-4c61b787e500' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-7a8f9dfb-2db7-4354-8a50-4aaa713cecb4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a8f9dfb-2db7-4354-8a50-4aaa713cecb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0314f2ce-ba6d-4666-973f-cf829da37dc1' class='xr-var-data-in' type='checkbox'><label for='data-0314f2ce-ba6d-4666-973f-cf829da37dc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -731,7 +731,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-a55702ca-d512-4f4b-b294-093aa014f4d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a55702ca-d512-4f4b-b294-093aa014f4d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c427750-c0e0-436f-b5d8-eef4b818494d' class='xr-var-data-in' type='checkbox'><label for='data-4c427750-c0e0-436f-b5d8-eef4b818494d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-66003f4d-ea85-460a-a4db-2b9084faf805' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66003f4d-ea85-460a-a4db-2b9084faf805' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-442d6100-4c2c-4435-b1f5-1abd42e43e23' class='xr-var-data-in' type='checkbox'><label for='data-442d6100-4c2c-4435-b1f5-1abd42e43e23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -814,7 +814,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_BT</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e83feb28-6420-48d2-aa30-160d47d21cdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e83feb28-6420-48d2-aa30-160d47d21cdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e112245b-2bdd-4f50-9234-b1cff0e320b1' class='xr-var-data-in' type='checkbox'><label for='data-e112245b-2bdd-4f50-9234-b1cff0e320b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Barotropic contribution to Kinetic Energy</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_BT</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-15a7fe37-3cff-4320-ba12-8e77856cc4e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15a7fe37-3cff-4320-ba12-8e77856cc4e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcc99211-589b-454a-b698-47e541e9b2cb' class='xr-var-data-in' type='checkbox'><label for='data-bcc99211-589b-454a-b698-47e541e9b2cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Barotropic contribution to Kinetic Energy</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -897,7 +897,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_CorAdv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-d8229bf1-a998-4c17-8fa2-7b9673c29cfa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8229bf1-a998-4c17-8fa2-7b9673c29cfa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65544a44-f4a2-4e14-87f1-31b25285c6eb' class='xr-var-data-in' type='checkbox'><label for='data-65544a44-f4a2-4e14-87f1-31b25285c6eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Coriolis and Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_CorAdv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-b79c30f0-1db2-4850-8fb9-911e1ce95aa5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b79c30f0-1db2-4850-8fb9-911e1ce95aa5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e745e0d-a8c8-4702-9391-61472f01cd64' class='xr-var-data-in' type='checkbox'><label for='data-5e745e0d-a8c8-4702-9391-61472f01cd64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Coriolis and Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -980,7 +980,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_adv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-fd1aa6d3-456f-4b82-922d-428dfb34c3dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd1aa6d3-456f-4b82-922d-428dfb34c3dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9930968-466a-4fc1-bb36-3f241c44f2ac' class='xr-var-data-in' type='checkbox'><label for='data-c9930968-466a-4fc1-bb36-3f241c44f2ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_adv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-3a55acb3-054d-45e3-8a44-9ee42ef237f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a55acb3-054d-45e3-8a44-9ee42ef237f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e11b1143-dbe9-480b-bac7-4b1d9dc2b869' class='xr-var-data-in' type='checkbox'><label for='data-e11b1143-dbe9-480b-bac7-4b1d9dc2b869' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1063,7 +1063,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_horvisc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e2745312-e6dd-440d-a408-ec8bcd5fda5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2745312-e6dd-440d-a408-ec8bcd5fda5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01396c5c-e21a-4425-a3d9-1ef33b89960d' class='xr-var-data-in' type='checkbox'><label for='data-01396c5c-e21a-4425-a3d9-1ef33b89960d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_horvisc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-ed1e93d1-210f-4619-a447-cf2efdb0f3b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed1e93d1-210f-4619-a447-cf2efdb0f3b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4feaf5c-8540-4fcc-a197-a691e6a0dfb3' class='xr-var-data-in' type='checkbox'><label for='data-b4feaf5c-8540-4fcc-a197-a691e6a0dfb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1146,7 +1146,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-46c989ca-ae30-46e8-b002-6f80ddae333f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46c989ca-ae30-46e8-b002-6f80ddae333f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb3dd4fb-d650-4f24-a483-567128231515' class='xr-var-data-in' type='checkbox'><label for='data-bb3dd4fb-d650-4f24-a483-567128231515' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Vertical Viscosity and Stresses</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-671b6d2d-2ac3-43d0-b396-32757e948611' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-671b6d2d-2ac3-43d0-b396-32757e948611' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3550b309-537c-4ec0-b31e-55c26f305954' class='xr-var-data-in' type='checkbox'><label for='data-3550b309-537c-4ec0-b31e-55c26f305954' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Vertical Viscosity and Stresses</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1229,7 +1229,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PE_to_KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-084954b3-17fa-417b-a846-8ed39bc3ccf2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-084954b3-17fa-417b-a846-8ed39bc3ccf2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91b875f6-c65f-4770-9b22-2f6d90ff9a42' class='xr-var-data-in' type='checkbox'><label for='data-91b875f6-c65f-4770-9b22-2f6d90ff9a42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Potential to Kinetic Energy Conversion of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PE_to_KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-2d408f53-4f90-4ab5-a906-75dac57f8117' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d408f53-4f90-4ab5-a906-75dac57f8117' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e16f1088-a087-4302-b3b3-35f218ba15c8' class='xr-var-data-in' type='checkbox'><label for='data-e16f1088-a087-4302-b3b3-35f218ba15c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Potential to Kinetic Energy Conversion of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1312,7 +1312,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-7dc55a0f-0146-4574-853f-51ab0b78ee1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7dc55a0f-0146-4574-853f-51ab0b78ee1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e51368f-91bf-4564-a459-9c8fa16fa466' class='xr-var-data-in' type='checkbox'><label for='data-9e51368f-91bf-4564-a459-9c8fa16fa466' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-4c48a2ba-7b36-42be-a08d-23e8c74b496a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c48a2ba-7b36-42be-a08d-23e8c74b496a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62e32d6f-f87e-4fe0-ba1b-12ae01fb0a75' class='xr-var-data-in' type='checkbox'><label for='data-62e32d6f-f87e-4fe0-ba1b-12ae01fb0a75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1395,7 +1395,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-3a83f4f7-db82-44a7-88b2-64ff6d3ee4da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a83f4f7-db82-44a7-88b2-64ff6d3ee4da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab3e20d5-4546-4ce7-bd46-729846a35b7c' class='xr-var-data-in' type='checkbox'><label for='data-ab3e20d5-4546-4ce7-bd46-729846a35b7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-6ccd1715-63ce-4788-9fb9-50345d76d0aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ccd1715-63ce-4788-9fb9-50345d76d0aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14734212-d527-4c8b-9462-6082a365622b' class='xr-var-data-in' type='checkbox'><label for='data-14734212-d527-4c8b-9462-6082a365622b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1478,7 +1478,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(time, zl, yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 241), meta=np.ndarray&gt;</div><input id='attrs-153a9516-3e38-4200-bf7d-c5041bc59b62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-153a9516-3e38-4200-bf7d-c5041bc59b62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-624b6a1d-a6f8-4eb7-bfe6-c78370d2d08b' class='xr-var-data-in' type='checkbox'><label for='data-624b6a1d-a6f8-4eb7-bfe6-c78370d2d08b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Potential Vorticity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m-1 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(time, zl, yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 241), meta=np.ndarray&gt;</div><input id='attrs-efbfc0c6-46f6-4c88-9e98-e47fefdb1cf5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efbfc0c6-46f6-4c88-9e98-e47fefdb1cf5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b1237c2-32a9-413e-8485-4a92a65b6de4' class='xr-var-data-in' type='checkbox'><label for='data-1b1237c2-32a9-413e-8485-4a92a65b6de4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Potential Vorticity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m-1 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1561,7 +1561,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd1</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e75b485a-3121-4678-8060-9d3c44d0dd62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e75b485a-3121-4678-8060-9d3c44d0dd62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96e5cb9f-724b-4496-8c6d-cee89097c092' class='xr-var-data-in' type='checkbox'><label for='data-96e5cb9f-724b-4496-8c6d-cee89097c092' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>First baroclinic deformation radius</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd1</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-dfb14e9d-dfc6-4aaa-8e56-cf30dbf33179' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfb14e9d-dfc6-4aaa-8e56-cf30dbf33179' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-177147c3-3c13-4ab9-945e-11211eeb876b' class='xr-var-data-in' type='checkbox'><label for='data-177147c3-3c13-4ab9-945e-11211eeb876b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>First baroclinic deformation radius</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1619,7 +1619,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd_dx</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-0263aa48-1244-44c8-9043-a7a19f9a78d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0263aa48-1244-44c8-9043-a7a19f9a78d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5000b11a-6b7b-4bf7-b10f-dbb65e414f3c' class='xr-var-data-in' type='checkbox'><label for='data-5000b11a-6b7b-4bf7-b10f-dbb65e414f3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Ratio between deformation radius and grid spacing</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m m-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd_dx</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-f6d7c492-7723-4380-bee0-13e867aabf0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6d7c492-7723-4380-bee0-13e867aabf0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e239da34-73a9-45f8-8b23-1b6dec65ab48' class='xr-var-data-in' type='checkbox'><label for='data-e239da34-73a9-45f8-8b23-1b6dec65ab48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Ratio between deformation radius and grid spacing</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m m-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1677,7 +1677,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-25e22825-04a9-4759-8f02-f14e7e8be05d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25e22825-04a9-4759-8f02-f14e7e8be05d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee3194d3-d16c-4154-af06-4fd84e1c51ff' class='xr-var-data-in' type='checkbox'><label for='data-ee3194d3-d16c-4154-af06-4fd84e1c51ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>Length of average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-35c42782-ceeb-44ee-8ae6-ca1d328829ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35c42782-ceeb-44ee-8ae6-ca1d328829ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8929636-fa3b-486d-b7a4-9298c9ed4eda' class='xr-var-data-in' type='checkbox'><label for='data-f8929636-fa3b-486d-b7a4-9298c9ed4eda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>Length of average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1712,7 +1712,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-2a6d8724-f31b-44f6-842e-c9f8450015e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a6d8724-f31b-44f6-842e-c9f8450015e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afcecf4e-8db0-40b8-8939-3a8433d357d6' class='xr-var-data-in' type='checkbox'><label for='data-afcecf4e-8db0-40b8-8939-3a8433d357d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-f21a31e9-946b-410c-bd6b-9ab1ccf6157f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f21a31e9-946b-410c-bd6b-9ab1ccf6157f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c721b5c3-4090-41ea-877a-93f7850c45e9' class='xr-var-data-in' type='checkbox'><label for='data-c721b5c3-4090-41ea-877a-93f7850c45e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1747,7 +1747,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-ebfad619-c9d6-4a91-b4aa-6b0e6295a980' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ebfad619-c9d6-4a91-b4aa-6b0e6295a980' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95105267-b510-4df6-877d-0a04a4d4eb01' class='xr-var-data-in' type='checkbox'><label for='data-95105267-b510-4df6-877d-0a04a4d4eb01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>End time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-df0d2d29-93cd-4665-9a80-863f7f5f0715' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df0d2d29-93cd-4665-9a80-863f7f5f0715' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c52ee6e-37ea-4b91-aa65-1b27b82cf2ec' class='xr-var-data-in' type='checkbox'><label for='data-7c52ee6e-37ea-4b91-aa65-1b27b82cf2ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>End time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1782,7 +1782,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dKE_dt</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-aa80ce56-50cd-4487-b47b-0b4ad5f7f55d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa80ce56-50cd-4487-b47b-0b4ad5f7f55d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8dd4dee-2ae4-4013-b1cf-d53ad2df5a7d' class='xr-var-data-in' type='checkbox'><label for='data-d8dd4dee-2ae4-4013-b1cf-d53ad2df5a7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Tendency of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dKE_dt</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-18dc990f-1af3-45c4-89ac-4b11b7bfcf06' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18dc990f-1af3-45c4-89ac-4b11b7bfcf06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e2f4b43-06a9-4ffd-a681-fbaa2be41a37' class='xr-var-data-in' type='checkbox'><label for='data-3e2f4b43-06a9-4ffd-a681-fbaa2be41a37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Tendency of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1865,7 +1865,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-e5da974c-a011-4e15-8ae2-3e8d29dd8c0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5da974c-a011-4e15-8ae2-3e8d29dd8c0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d170280a-5da9-4792-9300-b2bb27b9ee32' class='xr-var-data-in' type='checkbox'><label for='data-d170280a-5da9-4792-9300-b2bb27b9ee32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-fa95b3fc-7deb-47ce-809a-def2894c7620' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa95b3fc-7deb-47ce-809a-def2894c7620' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef8d2b57-9f97-44ec-a00a-098baaee1ecb' class='xr-var-data-in' type='checkbox'><label for='data-ef8d2b57-9f97-44ec-a00a-098baaee1ecb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -1948,7 +1948,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-3b731c08-ed77-4d39-845c-b2770748ed14' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b731c08-ed77-4d39-845c-b2770748ed14' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bf1f483-1985-445b-96ff-3a56fff64c9b' class='xr-var-data-in' type='checkbox'><label for='data-3bf1f483-1985-445b-96ff-3a56fff64c9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-c839fcd5-7423-40d0-b9a7-9a264cb0feea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c839fcd5-7423-40d0-b9a7-9a264cb0feea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24dc32ed-d56a-46eb-a5b7-76070f6b2d21' class='xr-var-data-in' type='checkbox'><label for='data-24dc32ed-d56a-46eb-a5b7-76070f6b2d21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2031,7 +2031,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>du_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-9874de1f-fcbc-4124-a63d-bbb15a47ff19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9874de1f-fcbc-4124-a63d-bbb15a47ff19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3defc0ff-8de5-49f7-b093-bbf1e47a3ac1' class='xr-var-data-in' type='checkbox'><label for='data-3defc0ff-8de5-49f7-b093-bbf1e47a3ac1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>du_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-bcc53e2a-88e1-4411-925d-876b9cdc53be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcc53e2a-88e1-4411-925d-876b9cdc53be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-564d346a-5656-4dd2-865a-b9505c0b2715' class='xr-var-data-in' type='checkbox'><label for='data-564d346a-5656-4dd2-865a-b9505c0b2715' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2114,7 +2114,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dudt</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-c3c38326-ab3d-4671-9dc3-8880a8aa52b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3c38326-ab3d-4671-9dc3-8880a8aa52b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c0daf1b-dadf-48fb-b9a6-625da00ab344' class='xr-var-data-in' type='checkbox'><label for='data-6c0daf1b-dadf-48fb-b9a6-625da00ab344' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dudt</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-313b051f-9ea0-4165-a6b0-6142d698dbd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-313b051f-9ea0-4165-a6b0-6142d698dbd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f913890-0fed-40d2-b44e-12188d073b5e' class='xr-var-data-in' type='checkbox'><label for='data-4f913890-0fed-40d2-b44e-12188d073b5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2197,7 +2197,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dv_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-79c6375a-db52-45aa-a341-dc0d9941b99c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79c6375a-db52-45aa-a341-dc0d9941b99c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f749a6b3-2949-4ddc-bf07-72760ec3e5f2' class='xr-var-data-in' type='checkbox'><label for='data-f749a6b3-2949-4ddc-bf07-72760ec3e5f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dv_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-2aa9bbe5-c891-494e-bf2f-ead38b2140c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2aa9bbe5-c891-494e-bf2f-ead38b2140c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1345346-9a7e-44c5-9289-3f48cb798b30' class='xr-var-data-in' type='checkbox'><label for='data-e1345346-9a7e-44c5-9289-3f48cb798b30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2280,7 +2280,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dvdt</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-409319e6-f5a3-43e8-b7db-dbacb4a0d36c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-409319e6-f5a3-43e8-b7db-dbacb4a0d36c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d4981d6-6466-40b6-a472-a75ddc4d90f2' class='xr-var-data-in' type='checkbox'><label for='data-2d4981d6-6466-40b6-a472-a75ddc4d90f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dvdt</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-2434ddc0-dcd3-4925-85d0-e30ecb9a1666' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2434ddc0-dcd3-4925-85d0-e30ecb9a1666' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ade51306-3771-471e-8268-259853ca91c3' class='xr-var-data-in' type='checkbox'><label for='data-ade51306-3771-471e-8268-259853ca91c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2363,7 +2363,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e2</span></div><div class='xr-var-dims'>(time, zi, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 16, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-594eb11d-dce5-4b54-97d1-fb0a88c8befb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-594eb11d-dce5-4b54-97d1-fb0a88c8befb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6125c7-c5dc-4499-9473-3f369bbdb8d9' class='xr-var-data-in' type='checkbox'><label for='data-4c6125c7-c5dc-4499-9473-3f369bbdb8d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zi:point yh:mean xh:mean time: mean_pow(2)</dd><dt><span>long_name :</span></dt><dd>Interface Height Relative to Mean Sea Level</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e2</span></div><div class='xr-var-dims'>(time, zi, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 16, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-93a003de-0132-4c63-b0ad-07786f2812da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93a003de-0132-4c63-b0ad-07786f2812da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38d20d3e-8c63-489c-b2f2-c490836d31d6' class='xr-var-data-in' type='checkbox'><label for='data-38d20d3e-8c63-489c-b2f2-c490836d31d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zi:point yh:mean xh:mean time: mean_pow(2)</dd><dt><span>long_name :</span></dt><dd>Interface Height Relative to Mean Sea Level</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2446,7 +2446,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-079de3b6-55be-481e-8805-7f3b81447608' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-079de3b6-55be-481e-8805-7f3b81447608' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c005d54-9347-46ca-a16c-f5fd0f7b0fae' class='xr-var-data-in' type='checkbox'><label for='data-0c005d54-9347-46ca-a16c-f5fd0f7b0fae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:sum yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer Thickness</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-c240e34f-2603-407a-9925-59194e1e5428' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c240e34f-2603-407a-9925-59194e1e5428' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e03f64ac-6541-4ec0-8966-8096e695b8e4' class='xr-var-data-in' type='checkbox'><label for='data-e03f64ac-6541-4ec0-8966-8096e695b8e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:sum yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer Thickness</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2529,7 +2529,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;</div><input id='attrs-a1855933-0f69-48c7-9922-b397716dd28d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1855933-0f69-48c7-9922-b397716dd28d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-004021d1-e04c-434d-b609-46a721d7e13e' class='xr-var-data-in' type='checkbox'><label for='data-004021d1-e04c-434d-b609-46a721d7e13e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>time axis boundaries</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;</div><input id='attrs-f357f88a-a3d2-4474-bd39-f34a512b0910' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f357f88a-a3d2-4474-bd39-f34a512b0910' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d7abdd4-88aa-4818-8a1d-b40946ff988f' class='xr-var-data-in' type='checkbox'><label for='data-4d7abdd4-88aa-4818-8a1d-b40946ff988f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>time axis boundaries</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2564,7 +2564,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-c42f876c-dd32-448c-a27e-a63193462e7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c42f876c-dd32-448c-a27e-a63193462e7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6aae4805-c8f2-4a53-90ae-1e1922faf6f1' class='xr-var-data-in' type='checkbox'><label for='data-6aae4805-c8f2-4a53-90ae-1e1922faf6f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-dcc9d818-1eed-4d8d-9302-fd218d683574' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcc9d818-1eed-4d8d-9302-fd218d683574' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7729ae5-ec70-43be-835c-777da641f36a' class='xr-var-data-in' type='checkbox'><label for='data-e7729ae5-ec70-43be-835c-777da641f36a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2647,7 +2647,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-e97d4601-260e-4020-90e9-19a4b6a82a2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e97d4601-260e-4020-90e9-19a4b6a82a2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0405c278-4ad5-4d33-9660-693b8599dd33' class='xr-var-data-in' type='checkbox'><label for='data-0405c278-4ad5-4d33-9660-693b8599dd33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-49937342-b6bb-456f-ad21-db009c5a1b8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49937342-b6bb-456f-ad21-db009c5a1b8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c0640dd-e91d-4f32-8b9c-beeac1dbd5f9' class='xr-var-data-in' type='checkbox'><label for='data-7c0640dd-e91d-4f32-8b9c-beeac1dbd5f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2730,7 +2730,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uh</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-bfd3e5bb-9369-46af-8766-3e6dd15fb0f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfd3e5bb-9369-46af-8766-3e6dd15fb0f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5aa54074-e6fe-44dc-b8e7-46d17ab4fa85' class='xr-var-data-in' type='checkbox'><label for='data-5aa54074-e6fe-44dc-b8e7-46d17ab4fa85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yh:sum xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uh</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-045e4bab-5eb4-4d11-a6a9-6e1d322d71e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-045e4bab-5eb4-4d11-a6a9-6e1d322d71e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9529e61-76b0-4b9d-8e85-e821994bbe57' class='xr-var-data-in' type='checkbox'><label for='data-b9529e61-76b0-4b9d-8e85-e821994bbe57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yh:sum xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2813,7 +2813,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-c947ed8d-1844-46f6-82e6-9f30774b6958' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c947ed8d-1844-46f6-82e6-9f30774b6958' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2465689c-e086-4929-9b85-46248310868f' class='xr-var-data-in' type='checkbox'><label for='data-2465689c-e086-4929-9b85-46248310868f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-7580e0b7-1770-429f-b6e6-aa01964adec5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7580e0b7-1770-429f-b6e6-aa01964adec5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f27207d-47e3-435a-842f-7658847ccf5e' class='xr-var-data-in' type='checkbox'><label for='data-8f27207d-47e3-435a-842f-7658847ccf5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2896,7 +2896,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-acdc1d61-0179-4030-b7d1-f35cbc8d9846' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acdc1d61-0179-4030-b7d1-f35cbc8d9846' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8341919d-87e5-44f2-8d17-d962c65859d9' class='xr-var-data-in' type='checkbox'><label for='data-8341919d-87e5-44f2-8d17-d962c65859d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-ac1ef9bb-91b0-4de4-baa8-b25b15009ff9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac1ef9bb-91b0-4de4-baa8-b25b15009ff9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac7dd495-702b-4b84-98c2-b8da566806a6' class='xr-var-data-in' type='checkbox'><label for='data-ac7dd495-702b-4b84-98c2-b8da566806a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2979,7 +2979,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-d67fffa2-f91d-4db1-bd87-96af61251829' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d67fffa2-f91d-4db1-bd87-96af61251829' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5e79efd-a056-4a03-a3ec-5984bfbc4aec' class='xr-var-data-in' type='checkbox'><label for='data-d5e79efd-a056-4a03-a3ec-5984bfbc4aec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yq:point xh:sum time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-a3e9a9d5-e0b0-4f56-8bbb-6598cf60c552' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3e9a9d5-e0b0-4f56-8bbb-6598cf60c552' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-821a9fc1-680b-4d0e-bf00-32464eae6f40' class='xr-var-data-in' type='checkbox'><label for='data-821a9fc1-680b-4d0e-bf00-32464eae6f40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yq:point xh:sum time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3062,7 +3062,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5e0abc73-ca6b-4437-adad-fef34a9f1b87' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5e0abc73-ca6b-4437-adad-fef34a9f1b87' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>associated_files :</span></dt><dd>area_t: static.nc</dd><dt><span>filename :</span></dt><dd>averages_00030002.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5d12f0c1-5602-4ea2-9b22-1b0e15ad893c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5d12f0c1-5602-4ea2-9b22-1b0e15ad893c' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>associated_files :</span></dt><dd>area_t: static.nc</dd><dt><span>filename :</span></dt><dd>averages_00030002.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -3500,7 +3500,7 @@
        "    filename:   static.nc\n",
        "    grid_tile:  N/A\n",
        "    grid_type:  regular\n",
-       "    title:      NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e6aa9837-4f64-4fb3-b191-3bff3035665b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e6aa9837-4f64-4fb3-b191-3bff3035665b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 241</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 561</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2fd7e77b-d63d-4cfc-acc2-777b02e48441' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2fd7e77b-d63d-4cfc-acc2-777b02e48441' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0001-01-01 00:00:00</div><input id='attrs-440a5d82-d123-4556-b600-c87266f183c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-440a5d82-d123-4556-b600-c87266f183c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c24ba99-98d9-472a-93da-916b96ced813' class='xr-var-data-in' type='checkbox'><label for='data-9c24ba99-98d9-472a-93da-916b96ced813' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(1, 1, 1, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-ce2f28d9-7dd6-4c4d-a946-05cf9dc4c4cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce2f28d9-7dd6-4c4d-a946-05cf9dc4c4cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e60a7e9c-cd97-4956-993f-8447cc644ac3' class='xr-var-data-in' type='checkbox'><label for='data-e60a7e9c-cd97-4956-993f-8447cc644ac3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 59.5 59.75 60.0</div><input id='attrs-27b6c07e-8141-468f-9d14-31267af8c0b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27b6c07e-8141-468f-9d14-31267af8c0b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f140b6c2-2c61-49bc-862d-ee667100b9bc' class='xr-var-data-in' type='checkbox'><label for='data-f140b6c2-2c61-49bc-862d-ee667100b9bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.25,  0.5 , ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-b3abd3a3-2432-4dcc-a8cc-aa067e0f8d51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3abd3a3-2432-4dcc-a8cc-aa067e0f8d51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1820fd39-0785-4bb6-a231-2fd47bb9ef2f' class='xr-var-data-in' type='checkbox'><label for='data-1820fd39-0785-4bb6-a231-2fd47bb9ef2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-70.0 -69.75 -69.5 ... 69.75 70.0</div><input id='attrs-be5f86dd-bb68-4aad-82e3-a0e2e239ab94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be5f86dd-bb68-4aad-82e3-a0e2e239ab94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-673079f4-3bcd-4786-b537-646a2f72ea54' class='xr-var-data-in' type='checkbox'><label for='data-673079f4-3bcd-4786-b537-646a2f72ea54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-70.  , -69.75, -69.5 , ...,  69.5 ,  69.75,  70.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b74df663-528f-46c9-a260-09fbcfcc8c5a' class='xr-section-summary-in' type='checkbox'  ><label for='section-b74df663-528f-46c9-a260-09fbcfcc8c5a' class='xr-section-summary' >Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Coriolis</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-503d9c4e-d3c1-47dd-86da-151e73248791' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-503d9c4e-d3c1-47dd-86da-151e73248791' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4d1a944-6e0f-46ed-983a-599cdfbf066f' class='xr-var-data-in' type='checkbox'><label for='data-f4d1a944-6e0f-46ed-983a-599cdfbf066f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Coriolis parameter at corner (Bu) points</dd><dt><span>units :</span></dt><dd>s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    title:      NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-313f4e0f-c440-4b7f-b955-34beca8b7cee' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-313f4e0f-c440-4b7f-b955-34beca8b7cee' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 241</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 561</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b057961c-c820-4de6-bb88-4441ed2d1c85' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b057961c-c820-4de6-bb88-4441ed2d1c85' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0001-01-01 00:00:00</div><input id='attrs-a63c30ae-9167-42b3-bcaa-82ebec90e24a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a63c30ae-9167-42b3-bcaa-82ebec90e24a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14b819ac-2ff2-4a9b-8e8f-4321c9807833' class='xr-var-data-in' type='checkbox'><label for='data-14b819ac-2ff2-4a9b-8e8f-4321c9807833' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(1, 1, 1, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-4032f72b-99f3-4a21-acdd-e5660a2979bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4032f72b-99f3-4a21-acdd-e5660a2979bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f5becd8-8034-4587-b292-8dd6e0c04bb9' class='xr-var-data-in' type='checkbox'><label for='data-7f5becd8-8034-4587-b292-8dd6e0c04bb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 59.5 59.75 60.0</div><input id='attrs-8252d4ed-bf73-4167-bc23-af78066be9f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8252d4ed-bf73-4167-bc23-af78066be9f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19de2b88-9fff-424b-88ab-e69b3e2216b7' class='xr-var-data-in' type='checkbox'><label for='data-19de2b88-9fff-424b-88ab-e69b3e2216b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.25,  0.5 , ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-3e46b7e5-8179-4b05-a685-9cdbc86bb919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e46b7e5-8179-4b05-a685-9cdbc86bb919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4f1772a-aebf-4135-8910-291e0ad0f7e2' class='xr-var-data-in' type='checkbox'><label for='data-b4f1772a-aebf-4135-8910-291e0ad0f7e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-70.0 -69.75 -69.5 ... 69.75 70.0</div><input id='attrs-aab774df-1b44-4cb3-bdf6-55aa54aed52a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aab774df-1b44-4cb3-bdf6-55aa54aed52a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f88f1ad6-e287-48e7-9b18-b30087879c64' class='xr-var-data-in' type='checkbox'><label for='data-f88f1ad6-e287-48e7-9b18-b30087879c64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-70.  , -69.75, -69.5 , ...,  69.5 ,  69.75,  70.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a629994b-7c30-499f-bc0b-f6a35ea90ffb' class='xr-section-summary-in' type='checkbox'  ><label for='section-a629994b-7c30-499f-bc0b-f6a35ea90ffb' class='xr-section-summary' >Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Coriolis</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-b9a7b259-b30c-454b-8947-53b45a7e69d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9a7b259-b30c-454b-8947-53b45a7e69d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58e01f16-850e-491e-a23e-f1330a2dc901' class='xr-var-data-in' type='checkbox'><label for='data-58e01f16-850e-491e-a23e-f1330a2dc901' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Coriolis parameter at corner (Bu) points</dd><dt><span>units :</span></dt><dd>s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3535,7 +3535,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_t</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-b4b91090-6efb-4001-bd49-43cd3ed10bbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4b91090-6efb-4001-bd49-43cd3ed10bbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf3d9c99-9c1f-47ed-96ed-1ef4e7c155aa' class='xr-var-data-in' type='checkbox'><label for='data-bf3d9c99-9c1f-47ed-96ed-1ef4e7c155aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd><dt><span>long_name :</span></dt><dd>Surface area of tracer (T) cells</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_t</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-2ed44f1b-b035-4123-a971-26d6b2c8ad01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ed44f1b-b035-4123-a971-26d6b2c8ad01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdd9e78d-f0df-4765-a2af-51943fe25552' class='xr-var-data-in' type='checkbox'><label for='data-cdd9e78d-f0df-4765-a2af-51943fe25552' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd><dt><span>long_name :</span></dt><dd>Surface area of tracer (T) cells</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3570,7 +3570,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-1a003ddc-b78e-4f54-95a2-60316bb3d1dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a003ddc-b78e-4f54-95a2-60316bb3d1dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c840e967-4dac-4da0-95ea-194a9b33d447' class='xr-var-data-in' type='checkbox'><label for='data-c840e967-4dac-4da0-95ea-194a9b33d447' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd><dt><span>long_name :</span></dt><dd>Surface area of x-direction flow (U) cells</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-9db679be-21c0-4b4c-bdc9-8af6b8327fbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9db679be-21c0-4b4c-bdc9-8af6b8327fbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5dc41e3-7d71-4286-b07f-e8ea580542c5' class='xr-var-data-in' type='checkbox'><label for='data-a5dc41e3-7d71-4286-b07f-e8ea580542c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd><dt><span>long_name :</span></dt><dd>Surface area of x-direction flow (U) cells</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3605,7 +3605,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-9dd8c97f-e4bc-413e-8c0e-f721b1968e76' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9dd8c97f-e4bc-413e-8c0e-f721b1968e76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f328baf-1c4b-4752-a92f-d57739e8f5ee' class='xr-var-data-in' type='checkbox'><label for='data-2f328baf-1c4b-4752-a92f-d57739e8f5ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd><dt><span>long_name :</span></dt><dd>Surface area of y-direction flow (V) cells</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-eba880c1-538a-42be-89f5-eaae5d90f2a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eba880c1-538a-42be-89f5-eaae5d90f2a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a4a655a-3fd0-4537-a7de-f2051f3b20fb' class='xr-var-data-in' type='checkbox'><label for='data-8a4a655a-3fd0-4537-a7de-f2051f3b20fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd><dt><span>long_name :</span></dt><dd>Surface area of y-direction flow (V) cells</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3640,7 +3640,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth_ocean</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-bf3d7b0b-4686-46dc-b80f-82367337d5f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf3d7b0b-4686-46dc-b80f-82367337d5f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-445a3565-7aec-4189-b7ef-d5f9c7baf37d' class='xr-var-data-in' type='checkbox'><label for='data-445a3565-7aec-4189-b7ef-d5f9c7baf37d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>long_name :</span></dt><dd>Depth of the ocean at tracer points</dd><dt><span>standard_name :</span></dt><dd>sea_floor_depth_below_geoid</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth_ocean</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-e226222a-4cf2-4599-bef4-408554dad05f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e226222a-4cf2-4599-bef4-408554dad05f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa61d451-18a3-4a30-b80c-55df38ccb502' class='xr-var-data-in' type='checkbox'><label for='data-aa61d451-18a3-4a30-b80c-55df38ccb502' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>long_name :</span></dt><dd>Depth of the ocean at tracer points</dd><dt><span>standard_name :</span></dt><dd>sea_floor_depth_below_geoid</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3675,7 +3675,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-9216ff6d-92ae-4739-bf21-8ded9701b8fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9216ff6d-92ae-4739-bf21-8ded9701b8fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6ce4cec-3648-45d3-aa13-8870ab2f819f' class='xr-var-data-in' type='checkbox'><label for='data-f6ce4cec-3648-45d3-aa13-8870ab2f819f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-6aeea057-4ce2-4050-a454-2f52dadad753' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6aeea057-4ce2-4050-a454-2f52dadad753' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b62ef966-1a78-4196-a944-7098b524b914' class='xr-var-data-in' type='checkbox'><label for='data-b62ef966-1a78-4196-a944-7098b524b914' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3710,7 +3710,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-1180c2e8-923a-4e14-b5e1-6554feb2abb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1180c2e8-923a-4e14-b5e1-6554feb2abb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef6a13be-0961-42a4-819d-ab983e6812bd' class='xr-var-data-in' type='checkbox'><label for='data-ef6a13be-0961-42a4-819d-ab983e6812bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-a836b6df-b0aa-4e8a-8810-1d9173aa5126' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a836b6df-b0aa-4e8a-8810-1d9173aa5126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-171ea99a-65a6-4ce7-852e-d5bce483919f' class='xr-var-data-in' type='checkbox'><label for='data-171ea99a-65a6-4ce7-852e-d5bce483919f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3745,7 +3745,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-413231ea-a064-4192-9e3b-2446dd6500d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-413231ea-a064-4192-9e3b-2446dd6500d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21639573-ca44-4368-a827-28b8f7b2f7bf' class='xr-var-data-in' type='checkbox'><label for='data-21639573-ca44-4368-a827-28b8f7b2f7bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-d3ffb979-99ad-44c9-8a8b-16ba1f13fa85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3ffb979-99ad-44c9-8a8b-16ba1f13fa85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-720d1af4-88a4-4952-a9ae-0636a0e85e10' class='xr-var-data-in' type='checkbox'><label for='data-720d1af4-88a4-4952-a9ae-0636a0e85e10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3780,7 +3780,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-5c1d4b41-302c-4859-bfe2-55a60a5c7ae0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c1d4b41-302c-4859-bfe2-55a60a5c7ae0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78aac409-3843-4e54-8f82-75f252a0f95d' class='xr-var-data-in' type='checkbox'><label for='data-78aac409-3843-4e54-8f82-75f252a0f95d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-ca1281c9-44cc-41f9-839d-3486d573e028' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca1281c9-44cc-41f9-839d-3486d573e028' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d7f212e-1231-41a0-ab78-368c2cd1208f' class='xr-var-data-in' type='checkbox'><label for='data-4d7f212e-1231-41a0-ab78-368c2cd1208f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3815,7 +3815,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-22c91dd9-18e4-4cc7-9c13-7db7370ef113' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22c91dd9-18e4-4cc7-9c13-7db7370ef113' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d018fb87-fb0f-4015-bcc3-b6c09cbb668c' class='xr-var-data-in' type='checkbox'><label for='data-d018fb87-fb0f-4015-bcc3-b6c09cbb668c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>long_name :</span></dt><dd>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-e94eac29-47b8-4f84-b921-806538a64bcb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e94eac29-47b8-4f84-b921-806538a64bcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b2f68c1-49b5-400d-a9d4-5adc9bac22fc' class='xr-var-data-in' type='checkbox'><label for='data-4b2f68c1-49b5-400d-a9d4-5adc9bac22fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>long_name :</span></dt><dd>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3850,7 +3850,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-62f3951c-7f1c-434d-95d0-85d575c0002a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62f3951c-7f1c-434d-95d0-85d575c0002a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fd8fd6c-eca1-4c5e-a3a5-b1c686a6d32d' class='xr-var-data-in' type='checkbox'><label for='data-1fd8fd6c-eca1-4c5e-a3a5-b1c686a6d32d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Latitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-b2ccbbfc-3416-475c-964e-91cd25e8df52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2ccbbfc-3416-475c-964e-91cd25e8df52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccc4c39c-664a-4087-a9b8-d8a9e056fa23' class='xr-var-data-in' type='checkbox'><label for='data-ccc4c39c-664a-4087-a9b8-d8a9e056fa23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Latitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3885,7 +3885,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-728ce9cd-0d3d-4384-b52e-f9d2659d3e34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-728ce9cd-0d3d-4384-b52e-f9d2659d3e34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4beadbf3-b7ab-4eff-9eec-ffae9b7b0b52' class='xr-var-data-in' type='checkbox'><label for='data-4beadbf3-b7ab-4eff-9eec-ffae9b7b0b52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-1d864f91-3a39-4cb4-bf29-de29d507218c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d864f91-3a39-4cb4-bf29-de29d507218c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcb619dc-0112-495e-aac2-68f59cb53d21' class='xr-var-data-in' type='checkbox'><label for='data-fcb619dc-0112-495e-aac2-68f59cb53d21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3920,7 +3920,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-cdc22565-6916-4d48-b088-e37f600df77a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cdc22565-6916-4d48-b088-e37f600df77a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c9803fb-62fd-49ce-b526-581772f905d9' class='xr-var-data-in' type='checkbox'><label for='data-9c9803fb-62fd-49ce-b526-581772f905d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-7f8ded8e-4ab7-431a-8715-1e5fa7431ff3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f8ded8e-4ab7-431a-8715-1e5fa7431ff3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98b83237-45f3-456b-9a26-592a17d9aa76' class='xr-var-data-in' type='checkbox'><label for='data-98b83237-45f3-456b-9a26-592a17d9aa76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3955,7 +3955,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-32ed2559-5f0d-4137-abbc-e4e130c864be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32ed2559-5f0d-4137-abbc-e4e130c864be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b955f19-2bde-4a84-b883-0e91b2d89fdd' class='xr-var-data-in' type='checkbox'><label for='data-9b955f19-2bde-4a84-b883-0e91b2d89fdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>long_name :</span></dt><dd>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-1937411d-e314-47f5-aa40-9f08859a6ffc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1937411d-e314-47f5-aa40-9f08859a6ffc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15af9397-3125-49a7-8d81-98f311e0a56d' class='xr-var-data-in' type='checkbox'><label for='data-15af9397-3125-49a7-8d81-98f311e0a56d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>long_name :</span></dt><dd>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3990,7 +3990,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-6a57ede2-c3ec-4a6e-8ecc-5f8580fc8a69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a57ede2-c3ec-4a6e-8ecc-5f8580fc8a69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2fc7d02-aadd-4128-b2ed-28a699250ef4' class='xr-var-data-in' type='checkbox'><label for='data-c2fc7d02-aadd-4128-b2ed-28a699250ef4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Longitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-29b7540d-e445-48cd-ab00-2e718f34e381' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29b7540d-e445-48cd-ab00-2e718f34e381' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-239adec7-9ce2-4b45-8597-e25a87511518' class='xr-var-data-in' type='checkbox'><label for='data-239adec7-9ce2-4b45-8597-e25a87511518' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Longitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4025,7 +4025,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-0b5d5020-3957-4c01-bf08-3de3a359026c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b5d5020-3957-4c01-bf08-3de3a359026c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83da6b07-f2f2-47c5-b1f9-2c0bb6fe273b' class='xr-var-data-in' type='checkbox'><label for='data-83da6b07-f2f2-47c5-b1f9-2c0bb6fe273b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-5881e28a-2fbd-4641-8193-f448390c89c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5881e28a-2fbd-4641-8193-f448390c89c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9598e93c-ca56-4678-b31b-8a13bfe08da6' class='xr-var-data-in' type='checkbox'><label for='data-9598e93c-ca56-4678-b31b-8a13bfe08da6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4060,7 +4060,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-83c83b51-338e-4b29-bdf8-0831e42b38b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83c83b51-338e-4b29-bdf8-0831e42b38b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8868b0a1-12f1-4624-a1e3-888870696ea4' class='xr-var-data-in' type='checkbox'><label for='data-8868b0a1-12f1-4624-a1e3-888870696ea4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-a52558d3-7a2e-4451-aae0-dfc4524f7d52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a52558d3-7a2e-4451-aae0-dfc4524f7d52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-432eeaf3-753b-4c5c-980e-289bf4d2adac' class='xr-var-data-in' type='checkbox'><label for='data-432eeaf3-753b-4c5c-980e-289bf4d2adac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4095,7 +4095,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-01c59835-566a-445d-9694-c35e00a5ceff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01c59835-566a-445d-9694-c35e00a5ceff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42dc6af7-44d2-4b79-8604-42799fa50a84' class='xr-var-data-in' type='checkbox'><label for='data-42dc6af7-44d2-4b79-8604-42799fa50a84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at tracer points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 240), meta=np.ndarray&gt;</div><input id='attrs-4369f405-5a59-43ce-98c1-21b7fc682d30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4369f405-5a59-43ce-98c1-21b7fc682d30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c02e7edf-d962-4a92-895c-10de80d2dd76' class='xr-var-data-in' type='checkbox'><label for='data-c02e7edf-d962-4a92-895c-10de80d2dd76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at tracer points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4130,7 +4130,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-d8576794-1078-4291-9b5c-c397568d74a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8576794-1078-4291-9b5c-c397568d74a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c7dfa48-b8d2-4b9e-ada0-5359c569369b' class='xr-var-data-in' type='checkbox'><label for='data-9c7dfa48-b8d2-4b9e-ada0-5359c569369b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 241), meta=np.ndarray&gt;</div><input id='attrs-56024d56-2ebd-4e57-b950-ec1cada463e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56024d56-2ebd-4e57-b950-ec1cada463e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0262ee54-45f2-4115-90a4-15daa363aa2c' class='xr-var-data-in' type='checkbox'><label for='data-0262ee54-45f2-4115-90a4-15daa363aa2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4165,7 +4165,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-71c90820-e56a-40a7-8d8b-a4b28781c523' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71c90820-e56a-40a7-8d8b-a4b28781c523' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c33d601d-8d2c-48a5-9ebc-5872f6a9f5a9' class='xr-var-data-in' type='checkbox'><label for='data-c33d601d-8d2c-48a5-9ebc-5872f6a9f5a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(560, 241), meta=np.ndarray&gt;</div><input id='attrs-abc17dd4-ed2c-403d-9905-fb4c61698953' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abc17dd4-ed2c-403d-9905-fb4c61698953' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-297a57ff-aa5d-40a5-92ef-d74254923492' class='xr-var-data-in' type='checkbox'><label for='data-297a57ff-aa5d-40a5-92ef-d74254923492' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4200,7 +4200,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-366a58f1-dfe3-49fa-95c5-a152623a3346' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-366a58f1-dfe3-49fa-95c5-a152623a3346' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59fdfa50-6a15-48ea-95fe-3c6dffd0d5df' class='xr-var-data-in' type='checkbox'><label for='data-59fdfa50-6a15-48ea-95fe-3c6dffd0d5df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(561, 240), meta=np.ndarray&gt;</div><input id='attrs-024a5e8a-cd1e-4962-b4af-7c122b665261' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-024a5e8a-cd1e-4962-b4af-7c122b665261' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c9b82cc-e357-4299-ae6b-287a498116ad' class='xr-var-data-in' type='checkbox'><label for='data-8c9b82cc-e357-4299-ae6b-287a498116ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4235,7 +4235,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f3fe5c16-d2d0-4e44-a5ef-3b4af1678db2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3fe5c16-d2d0-4e44-a5ef-3b4af1678db2' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filename :</span></dt><dd>static.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6007f326-56f8-48e1-a09f-e7b6d1d39487' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6007f326-56f8-48e1-a09f-e7b6d1d39487' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filename :</span></dt><dd>static.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -4330,7 +4330,7 @@
     "\n",
     "MOM6 uses an Arakawa C grid staggering of variables. In this tutorial, we will filter kinetic energy `KE`: a field that is defined at T-points (or tracer points). Note that the `IRREGULAR_WITH_LAND` could also be used to filter U-fields or V-fields on a C-grid (or to filter fields on a B-grid), but we would have to create the filter with different arguments for `wet_mask`, `dxw`, `dyw`, `dxs`, `dys`, `area`.\n",
     "\n",
-    "`wet_mask` and `area` we have directly available from our model output:"
+    "`wet_mask` and `area` are directly available from our model output:"
    ]
   },
   {
@@ -4501,7 +4501,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=200000, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=24, grid_type=<GridType.IRREGULAR_WITH_LAND: 3>)"
+       "Filter(filter_scale=200000, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=24, grid_type=<GridType.IRREGULAR_WITH_LAND: 5>)"
       ]
      },
      "execution_count": 12,
@@ -4514,7 +4514,6 @@
     "    filter_scale=filter_scale,\n",
     "    dx_min=dx_min,\n",
     "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "    n_steps=0,\n",
     "    grid_type=gcm_filters.GridType.IRREGULAR_WITH_LAND,\n",
     "    grid_vars={\n",
     "        'wet_mask': wet_mask, \n",
@@ -4892,7 +4891,7 @@
        "  fill: currentColor;\n",
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;KE&#x27; (time: 100, zl: 15, yh: 560, xh: 240)&gt;\n",
-       "dask.array&lt;open_dataset-cb2e344ae2f2d8ea846dc5fee1367e8aKE, shape=(100, 15, 560, 240), dtype=float32, chunksize=(10, 15, 560, 240), chunktype=numpy.ndarray&gt;\n",
+       "dask.array&lt;open_dataset-0b0924e8e7b9f8d45d6e70b8690f1152KE, shape=(100, 15, 560, 240), dtype=float32, chunksize=(10, 15, 560, 240), chunktype=numpy.ndarray&gt;\n",
        "Coordinates:\n",
        "  * time     (time) object 0084-05-03 12:00:00 ... 0085-09-18 12:00:00\n",
        "  * xh       (xh) float64 0.125 0.375 0.625 0.875 ... 59.12 59.38 59.62 59.88\n",
@@ -4903,7 +4902,7 @@
        "    cell_methods:   area:mean zl:mean yh:mean xh:mean time: mean\n",
        "    long_name:      Layer kinetic energy per unit mass\n",
        "    time_avg_info:  average_T1,average_T2,average_DT\n",
-       "    units:          m2 s-2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KE'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>zl</span>: 15</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>xh</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fd3fb94c-8d9f-46c3-9e0a-247a25031fb8' class='xr-array-in' type='checkbox' checked><label for='section-fd3fb94c-8d9f-46c3-9e0a-247a25031fb8' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    units:          m2 s-2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KE'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>zl</span>: 15</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>xh</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-307a8d48-ff55-4611-8b6d-cc792052b658' class='xr-array-in' type='checkbox' checked><label for='section-307a8d48-ff55-4611-8b6d-cc792052b658' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4986,7 +4985,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-38e593f2-4bd2-459c-b395-69f66ebc768d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-38e593f2-4bd2-459c-b395-69f66ebc768d' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-f8b355a3-b471-49d6-b79a-263d89ad06a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8b355a3-b471-49d6-b79a-263d89ad06a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a18fd1b-23e9-4493-b33a-7df272a4a7fb' class='xr-var-data-in' type='checkbox'><label for='data-2a18fd1b-23e9-4493-b33a-7df272a4a7fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-95eb2e57-5bce-45c8-b00b-0b4961a7fcd6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-95eb2e57-5bce-45c8-b00b-0b4961a7fcd6' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-affc4b6d-8ac8-4607-91d7-3e382af03eb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-affc4b6d-8ac8-4607-91d7-3e382af03eb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cac664c6-b99f-4e30-9eda-df5aae598610' class='xr-var-data-in' type='checkbox'><label for='data-cac664c6-b99f-4e30-9eda-df5aae598610' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 13, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 18, 12, 0, 0, 0),\n",
@@ -5085,12 +5084,12 @@
        "       cftime.Datetime360Day(85, 9, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 13, 12, 0, 0, 0),\n",
-       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-828fa3b9-9c03-4c04-a6a7-4654d49fa1fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-828fa3b9-9c03-4c04-a6a7-4654d49fa1fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de74ad5a-6f3c-4ef8-b923-8820dd499fbd' class='xr-var-data-in' type='checkbox'><label for='data-de74ad5a-6f3c-4ef8-b923-8820dd499fbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-cead632e-f8a2-4247-adf2-7f05ebb0e55c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cead632e-f8a2-4247-adf2-7f05ebb0e55c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f4705c7-fdd8-4047-95fc-a80f55934b14' class='xr-var-data-in' type='checkbox'><label for='data-8f4705c7-fdd8-4047-95fc-a80f55934b14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-0613ee22-5d3c-4c03-9351-9739b0149087' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0613ee22-5d3c-4c03-9351-9739b0149087' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72b4e5f8-03d3-42cf-9a4d-e4a77b578efc' class='xr-var-data-in' type='checkbox'><label for='data-72b4e5f8-03d3-42cf-9a4d-e4a77b578efc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
-       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92c51675-2ce3-43aa-9045-a4da7b0fd1da' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92c51675-2ce3-43aa-9045-a4da7b0fd1da' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div></li></ul></div></div>"
+       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-41d07eac-6bc9-4c45-8ef8-8c054748ca7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41d07eac-6bc9-4c45-8ef8-8c054748ca7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df5cd73b-dd79-4de3-a659-86539e1c75bc' class='xr-var-data-in' type='checkbox'><label for='data-df5cd73b-dd79-4de3-a659-86539e1c75bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-b28b50e3-9384-44bc-a1c6-5bcc0a3dfd9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b28b50e3-9384-44bc-a1c6-5bcc0a3dfd9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31c07865-6a2c-4b8c-975c-fb73ac067c7b' class='xr-var-data-in' type='checkbox'><label for='data-31c07865-6a2c-4b8c-975c-fb73ac067c7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-8f98b0e5-6ccd-4389-88f0-e0b57c1076c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f98b0e5-6ccd-4389-88f0-e0b57c1076c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce32296d-dfb0-40b3-ac16-25f62948128d' class='xr-var-data-in' type='checkbox'><label for='data-ce32296d-dfb0-40b3-ac16-25f62948128d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
+       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d7ed6332-48cc-4b3b-82aa-45a05f5b09de' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d7ed6332-48cc-4b3b-82aa-45a05f5b09de' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'KE' (time: 100, zl: 15, yh: 560, xh: 240)>\n",
-       "dask.array<open_dataset-cb2e344ae2f2d8ea846dc5fee1367e8aKE, shape=(100, 15, 560, 240), dtype=float32, chunksize=(10, 15, 560, 240), chunktype=numpy.ndarray>\n",
+       "dask.array<open_dataset-0b0924e8e7b9f8d45d6e70b8690f1152KE, shape=(100, 15, 560, 240), dtype=float32, chunksize=(10, 15, 560, 240), chunktype=numpy.ndarray>\n",
        "Coordinates:\n",
        "  * time     (time) object 0084-05-03 12:00:00 ... 0085-09-18 12:00:00\n",
        "  * xh       (xh) float64 0.125 0.375 0.625 0.875 ... 59.12 59.38 59.62 59.88\n",
@@ -5491,7 +5490,7 @@
        "    cell_methods:   area:mean zl:mean yh:mean xh:mean time: mean\n",
        "    long_name:      Layer kinetic energy per unit mass\n",
        "    time_avg_info:  average_T1,average_T2,average_DT\n",
-       "    units:          m2 s-2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KE'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>zl</span>: 15</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>xh</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-482052a8-8c6f-44a5-b3ce-04f66f183264' class='xr-array-in' type='checkbox' checked><label for='section-482052a8-8c6f-44a5-b3ce-04f66f183264' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 560, 240), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    units:          m2 s-2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KE'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>zl</span>: 15</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>xh</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0e3eeb12-af37-4d02-9e2b-25ba62853afc' class='xr-array-in' type='checkbox' checked><label for='section-0e3eeb12-af37-4d02-9e2b-25ba62853afc' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 560, 240), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5624,7 +5623,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-c4286f61-48ac-45f2-8134-02e31e7587e2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c4286f61-48ac-45f2-8134-02e31e7587e2' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-9da3ff2e-e1c7-41d0-a564-2e788d18085f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9da3ff2e-e1c7-41d0-a564-2e788d18085f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc706d7b-b93e-4518-b78c-62523870c7e8' class='xr-var-data-in' type='checkbox'><label for='data-fc706d7b-b93e-4518-b78c-62523870c7e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-d367ed97-65ae-416f-bd68-569bc500b634' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d367ed97-65ae-416f-bd68-569bc500b634' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-f91dc995-ff09-4f23-a0b4-697680065b15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f91dc995-ff09-4f23-a0b4-697680065b15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c78e7c7-ddbc-43a3-a695-f15afe5e4167' class='xr-var-data-in' type='checkbox'><label for='data-4c78e7c7-ddbc-43a3-a695-f15afe5e4167' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 13, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 18, 12, 0, 0, 0),\n",
@@ -5723,8 +5722,8 @@
        "       cftime.Datetime360Day(85, 9, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 13, 12, 0, 0, 0),\n",
-       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-e2bc134a-5c1b-4451-9c08-e1fabfa49fa1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2bc134a-5c1b-4451-9c08-e1fabfa49fa1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de8803ac-bc68-4928-a09c-51baaf24209d' class='xr-var-data-in' type='checkbox'><label for='data-de8803ac-bc68-4928-a09c-51baaf24209d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-4b1a0d76-1ffe-4ea0-9356-c60bffd0cf7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b1a0d76-1ffe-4ea0-9356-c60bffd0cf7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-165ffe64-e6c2-4c9a-bbe7-35a0ce82228c' class='xr-var-data-in' type='checkbox'><label for='data-165ffe64-e6c2-4c9a-bbe7-35a0ce82228c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-b2d077ff-6452-4b43-b7fc-a077e21c7b1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2d077ff-6452-4b43-b7fc-a077e21c7b1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-471fb1f6-f87e-41a7-b92a-13e094000dfd' class='xr-var-data-in' type='checkbox'><label for='data-471fb1f6-f87e-41a7-b92a-13e094000dfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
-       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c0a4e47b-5cf7-4d41-a9a4-d7916af6b823' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c0a4e47b-5cf7-4d41-a9a4-d7916af6b823' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div></li></ul></div></div>"
+       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-058b9738-b655-4d34-9359-56af467fcddb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-058b9738-b655-4d34-9359-56af467fcddb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4de4e5b-9558-4d5d-9f42-07a642d772a0' class='xr-var-data-in' type='checkbox'><label for='data-a4de4e5b-9558-4d5d-9f42-07a642d772a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-fa073838-a0b7-40d0-8aa6-70bbb2c7bd95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa073838-a0b7-40d0-8aa6-70bbb2c7bd95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-941a9e52-1d1f-4117-9ab5-938fc4abff3c' class='xr-var-data-in' type='checkbox'><label for='data-941a9e52-1d1f-4117-9ab5-938fc4abff3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-dbdfd918-0a1f-4af9-8096-200ea5bec77f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbdfd918-0a1f-4af9-8096-200ea5bec77f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1894e50-618f-4007-abca-1996cb9e7ede' class='xr-var-data-in' type='checkbox'><label for='data-a1894e50-618f-4007-abca-1996cb9e7ede' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
+       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e473e893-bf0b-4b9e-b417-8dc5245149d7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e473e893-bf0b-4b9e-b417-8dc5245149d7' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'KE' (time: 100, zl: 15, yh: 560, xh: 240)>\n",
@@ -5843,6 +5842,14 @@
    "execution_count": 17,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/glade/work/noraloose/my_npl_clone_20201220/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  x = np.divide(x1, x2, out)\n"
+     ]
+    },
     {
      "data": {
       "image/png": 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\n",
@@ -5857,9 +5864,6 @@
     }
    ],
    "source": [
-    "import warnings\n",
-    "warnings.filterwarnings(\"ignore\", category=RuntimeWarning) \n",
-    "\n",
     "ds['Rd1'].mean(dim='time').plot(figsize=(6,7), vmin=0, cmap='YlGn');"
    ]
   },
@@ -5875,6 +5879,14 @@
    "execution_count": 18,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/glade/work/noraloose/my_npl_clone_20201220/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  x = np.divide(x1, x2, out)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -5895,7 +5907,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We set `filter_scale` equal to the largest desired filter scale in the domain, i.e., equal to the maximum deformation radius."
+    "As described in the [Filter Theory](https://gcm-filters.readthedocs.io/en/latest/theory.html), we set `filter_scale` equal to the largest desired filter scale in the domain, i.e., equal to the maximum deformation radius."
    ]
   },
   {
@@ -5928,6 +5940,14 @@
    "execution_count": 21,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/glade/work/noraloose/my_npl_clone_20201220/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  x = np.divide(x1, x2, out)\n"
+     ]
+    },
     {
      "data": {
       "image/png": 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\n",
@@ -5963,7 +5983,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=array(445500.75, dtype=float32), dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=52, grid_type=<GridType.IRREGULAR_WITH_LAND: 3>)"
+       "Filter(filter_scale=array(445500.75, dtype=float32), dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=52, grid_type=<GridType.IRREGULAR_WITH_LAND: 5>)"
       ]
      },
      "execution_count": 22,
@@ -5976,7 +5996,6 @@
     "    filter_scale=filter_scale,\n",
     "    dx_min=dx_min,\n",
     "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "    n_steps=0,\n",
     "    grid_type=gcm_filters.GridType.IRREGULAR_WITH_LAND,\n",
     "    grid_vars={\n",
     "        'wet_mask': wet_mask, \n",
@@ -6015,6 +6034,16 @@
    "execution_count": 24,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/glade/work/noraloose/my_npl_clone_20201220/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  x = np.divide(x1, x2, out)\n",
+      "/glade/work/noraloose/my_npl_clone_20201220/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  x = np.divide(x1, x2, out)\n"
+     ]
+    },
     {
      "data": {
       "image/png": 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\n",
@@ -6065,7 +6094,7 @@
    "source": [
     "## Anisotropic filtering\n",
     "\n",
-    "Next, we want to use anisotropic filters that have different filter scales in the zonal and meridional directions. Note that zonal and meridional directions are aligned with our NeverWorld2 (spherical) grid directions."
+    "Next, we want to use anisotropic filters that have different filter scales in the zonal and meridional directions. Note that zonal and meridional directions are aligned with our NeverWorld2 (spherical) grid directions. The theory behind anisotropic filtering is described [here](https://gcm-filters.readthedocs.io/en/latest/theory.html)."
    ]
   },
   {
@@ -6083,7 +6112,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=300000, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=35, grid_type=<GridType.IRREGULAR_WITH_LAND: 3>)"
+       "Filter(filter_scale=300000, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=35, grid_type=<GridType.IRREGULAR_WITH_LAND: 5>)"
       ]
      },
      "execution_count": 25,
@@ -6100,7 +6129,6 @@
     "    filter_scale=filter_scale,\n",
     "    dx_min=dx_min,\n",
     "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "    n_steps=0,\n",
     "    grid_type=gcm_filters.GridType.IRREGULAR_WITH_LAND,\n",
     "    grid_vars={\n",
     "        'wet_mask': wet_mask, \n",
@@ -6126,7 +6154,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=300000, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=35, grid_type=<GridType.IRREGULAR_WITH_LAND: 3>)"
+       "Filter(filter_scale=300000, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=35, grid_type=<GridType.IRREGULAR_WITH_LAND: 5>)"
       ]
      },
      "execution_count": 26,
@@ -6143,7 +6171,6 @@
     "    filter_scale=filter_scale,\n",
     "    dx_min=dx_min,\n",
     "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "    n_steps=0,\n",
     "    grid_type=gcm_filters.GridType.IRREGULAR_WITH_LAND,\n",
     "    grid_vars={\n",
     "        'wet_mask': wet_mask, \n",
@@ -6266,7 +6293,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Section 2.6 in [Grooms et al. (2021)](https://www.essoar.org/doi/10.1002/essoar.10506591.1) explains why we need to set `filter_scale`, `kappa_w` and `kappa_s` as follows. "
+    "As explained in the [Filter Theory](https://gcm-filters.readthedocs.io/en/latest/theory.html) and Section 2.6 in [Grooms et al. (2021)](https://www.essoar.org/doi/10.1002/essoar.10506591.1), we set `filter_scale`, `kappa_w` and `kappa_s` as follows. "
    ]
   },
   {
@@ -6288,7 +6315,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=278292.7492304958, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=33, grid_type=<GridType.IRREGULAR_WITH_LAND: 3>)"
+       "Filter(filter_scale=278292.7492304958, dx_min=array(9518.17259783), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=33, grid_type=<GridType.IRREGULAR_WITH_LAND: 5>)"
       ]
      },
      "execution_count": 31,
@@ -6301,7 +6328,6 @@
     "    filter_scale=filter_scale,\n",
     "    dx_min=dx_min,\n",
     "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "    n_steps=0,\n",
     "    grid_type=gcm_filters.GridType.IRREGULAR_WITH_LAND,\n",
     "    grid_vars={\n",
     "        'wet_mask': wet_mask, \n",
@@ -6383,11 +6409,7 @@
    "source": [
     "### Simple fixed factor filter\n",
     "\n",
-    "In our final example, we use an **alternative method** to filter with a **fixed factor of 10**. It is more *ad hoc* than what we did in the previous example, but simpler and faster (especially if you filter large data sets). In [Grooms et al. (2021)](https://doi.org/10.1002/essoar.10506591.1), Section 2.6, this filter is referred to as the **simple fixed factor filter**. The simple fixed factor filter works as follows:\n",
-    "\n",
-    "1. **Before** filtering, **multiply the field by the local cell area**.\n",
-    "2. Apply filter with `dx_min=1` and `filter_scale=10`, pretending the grid was uniform.\n",
-    "3. **After** filtering, **divide** filtered field **by local cell area**."
+    "In our final example, we use an **alternative method** to filter with a **fixed factor of 10**. It is more *ad hoc* than what we did in the previous example, but simpler and faster (especially if you filter large data sets). In [Grooms et al. (2021)](https://doi.org/10.1002/essoar.10506591.1), Section 2.6, this filter is referred to as the **simple fixed factor filter**. Simple fixed factor filtering operates on a uniform Cartesian grid with dx = dy = 1 that is being transformed from the original locally orthogonal grid."
    ]
   },
   {
@@ -6404,7 +6426,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The actual filtering operation in the second step employs a Laplacian on a regular grid, for which we can use `REGULAR_WITH_LAND`. This Laplacian is more simple (and faster) and requires the following arguments."
+    "The `TRANSFORMED_TO_REGULAR_WITH_LAND` grid type matches our data and is appropriate for simple fixed factor filtering. This simple Laplacian requires the following arguments."
    ]
   },
   {
@@ -6415,7 +6437,7 @@
     {
      "data": {
       "text/plain": [
-       "['wet_mask']"
+       "['area', 'wet_mask']"
       ]
      },
      "execution_count": 35,
@@ -6424,7 +6446,7 @@
     }
    ],
    "source": [
-    "gcm_filters.required_grid_vars(gcm_filters.GridType.REGULAR_WITH_LAND)"
+    "gcm_filters.required_grid_vars(gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND)"
    ]
   },
   {
@@ -6442,7 +6464,7 @@
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.REGULAR_WITH_LAND: 2>)"
+       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.TRANSFORMED_TO_REGULAR_WITH_LAND: 4>)"
       ]
      },
      "execution_count": 36,
@@ -6455,8 +6477,8 @@
     "    filter_scale=filter_scale,\n",
     "    dx_min=dx_min,\n",
     "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "    grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,\n",
-    "    grid_vars={'wet_mask': wet_mask}\n",
+    "    grid_type=gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
     ")\n",
     "filter_simple_fixed_factor"
    ]
@@ -6465,9 +6487,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The number of required steps, `n_steps`, is now only 11. (It was 33 in the previous example.) \n",
-    "\n",
-    "If we want to use the simple fixed factor filter, we need to filter the area-weighted field `KE` * `area`. "
+    "The number of required steps, `n_steps`, is now only 11. (It was 33 in the previous example.) "
    ]
   },
   {
@@ -6476,23 +6496,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "KE_filtered_simple_fixed_factor = filter_simple_fixed_factor.apply(ds.KE * area, dims=['yh', 'xh'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "After filtering, we divide by the `area`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "KE_filtered_simple_fixed_factor = KE_filtered_simple_fixed_factor / area"
+    "KE_filtered_simple_fixed_factor = filter_simple_fixed_factor.apply(ds.KE, dims=['yh', 'xh'])"
    ]
   },
   {
@@ -6504,7 +6508,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
diff --git a/docs/tutorial_numerical_instability.ipynb b/docs/tutorial_numerical_instability.ipynb
index c1256fc..944e4ae 100644
--- a/docs/tutorial_numerical_instability.ipynb
+++ b/docs/tutorial_numerical_instability.ipynb
@@ -2,20 +2,18 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "transparent-parking",
    "metadata": {},
    "source": [
     " # GCM Filters and Numerical Instability\n",
     " \n",
-    "The filtering scheme used in GCM Filters may become unstable and lead to wrong answers in case of filtering data over a wide range of scales. In this case, a combination of GCM filters and data coarsening would be more appropriate to maintain accuracy. \n",
+    "The filtering scheme used in GCM Filters may become unstable and lead to wrong answers when attempting to filter data over a wide range of scales. In this case, a combination of GCM filters and data coarsening would be more appropriate to maintain accuracy. \n",
     "\n",
-    "For the purpose of demonstration, we employ output from a global MOM6 simulation having a spatial resolution of $1/4^{\\circ}$ to perform a combination of spatial filtering and corsening to obtain desired output."
+    "For the purpose of demonstration, we employ output from a global MOM6 simulation with a spatial resolution of $1/4^{\\circ}$ to perform a combination of spatial filtering and coarsening to obtain desired output."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "skilled-jewel",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,20 +22,14 @@
     "import numpy as np\n",
     "import gcm_filters\n",
     "import matplotlib.pyplot as plt\n",
-    "import matplotlib.ticker as mticker\n",
-    "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n",
     "import cartopy.crs as ccrs\n",
-    "import cartopy.feature as cfeature\n",
-    "import warnings\n",
     "\n",
-    "warnings.filterwarnings(\"ignore\")\n",
     "%matplotlib inline"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "super-analysis",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -61,7 +53,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "verbal-encoding",
    "metadata": {},
    "source": [
     "### Filtering\n",
@@ -72,62 +63,476 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "cathedral-simple",
    "metadata": {},
    "outputs": [
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+       "    wet_u         (yh, xq) float32 ...\n",
+       "    wet_v         (yq, xh) float32 ...\n",
+       "    zeta          (yq, xq) float32 ...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-02d44239-0b38-4b6a-9a9d-050d1172599c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-02d44239-0b38-4b6a-9a9d-050d1172599c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>xh</span>: 1440</li><li><span class='xr-has-index'>xq</span>: 1440</li><li><span class='xr-has-index'>yh</span>: 1080</li><li><span class='xr-has-index'>yq</span>: 1080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5223e7df-a363-442e-b16b-7b5c43733eb2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5223e7df-a363-442e-b16b-7b5c43733eb2' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3eb654dd-92a7-42a4-ba71-08c596aafe10' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3eb654dd-92a7-42a4-ba71-08c596aafe10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6637bf08-2a45-42b8-8a5c-e5bd8f06898e' class='xr-var-data-in' type='checkbox'><label for='data-6637bf08-2a45-42b8-8a5c-e5bd8f06898e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>NOLEAP</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array(cftime.DatetimeNoLeap(101, 1, 1, 12, 0, 0, 0), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.7 -299.5 ... 59.78 60.03</div><input id='attrs-6067f2b7-1e3e-4dc6-af21-e30f23d635d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6067f2b7-1e3e-4dc6-af21-e30f23d635d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2cd31e0-eed4-4412-b881-afb20b02a831' class='xr-var-data-in' type='checkbox'><label for='data-a2cd31e0-eed4-4412-b881-afb20b02a831' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.724244, -299.476198, -299.22815 , ...,   59.531631,   59.77967 ,\n",
+       "         60.027712])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.39 -80.31 ... 89.84 89.95</div><input id='attrs-d1f6b7e9-d6f3-49ca-a5c2-30336cd29519' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1f6b7e9-d6f3-49ca-a5c2-30336cd29519' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df5a3abc-64b9-4eb9-8ffc-e7066b98b3cd' class='xr-var-data-in' type='checkbox'><label for='data-df5a3abc-64b9-4eb9-8ffc-e7066b98b3cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.389238, -80.308075, -80.226911, ...,  89.729781,  89.837868,\n",
+       "        89.945956])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.6 -299.3 ... 59.91 60.16</div><input id='attrs-9502ce18-d5fb-4cf0-b22b-b70335a195ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9502ce18-d5fb-4cf0-b22b-b70335a195ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab9e55c9-744b-422f-a828-86207470a88a' class='xr-var-data-in' type='checkbox'><label for='data-ab9e55c9-744b-422f-a828-86207470a88a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.594355, -299.346385, -299.098412, ...,   59.661746,   59.90971 ,\n",
+       "         60.157676])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.35 -80.27 -80.19 ... 89.89 90.0</div><input id='attrs-8213ee8f-da82-44d7-bce9-1cf75283bc27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8213ee8f-da82-44d7-bce9-1cf75283bc27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a94b062-1b37-43f2-87aa-88fa7c3842fd' class='xr-var-data-in' type='checkbox'><label for='data-3a94b062-1b37-43f2-87aa-88fa7c3842fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.348657, -80.267493, -80.186329, ...,  89.783825,  89.891912,\n",
+       "        90.      ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ff65526-1134-4e20-aede-ebf127b58a23' class='xr-section-summary-in' type='checkbox'  ><label for='section-2ff65526-1134-4e20-aede-ebf127b58a23' class='xr-section-summary' >Data variables: <span>(30)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ssu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-379c99a5-a316-4698-8af8-8365b1862102' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-379c99a5-a316-4698-8af8-8365b1862102' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26cfcbad-0b6d-4999-8aff-d0fbd2ef3ac0' class='xr-var-data-in' type='checkbox'><label for='data-26cfcbad-0b6d-4999-8aff-d0fbd2ef3ac0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Zonal Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yh:mean xq:point time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-79d98f33-19e7-41d3-aa36-8319e4b878cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79d98f33-19e7-41d3-aa36-8319e4b878cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7850358f-2fc5-4792-bbde-83378a9cc2ae' class='xr-var-data-in' type='checkbox'><label for='data-7850358f-2fc5-4792-bbde-83378a9cc2ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Meridional Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yq:point xh:mean time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zos</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9cd736e7-8876-4bd0-8e92-2c4113a8486d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cd736e7-8876-4bd0-8e92-2c4113a8486d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f69d3fd-95d3-41ed-86ee-83f2eab0c611' class='xr-var-data-in' type='checkbox'><label for='data-8f69d3fd-95d3-41ed-86ee-83f2eab0c611' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea surface height above geoid</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>standard_name :</span></dt><dd>sea_surface_height_above_geoid</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Coriolis</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-db9c75a8-ee30-4870-8243-19cec812a9cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db9c75a8-ee30-4870-8243-19cec812a9cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e9e3a1e-7eb3-4ca1-9925-18e7dcdca83b' class='xr-var-data-in' type='checkbox'><label for='data-4e9e3a1e-7eb3-4ca1-9925-18e7dcdca83b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Coriolis parameter at corner (Bu) points</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-21b9c667-228f-4cf1-88ed-250098e83d9c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21b9c667-228f-4cf1-88ed-250098e83d9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c380828-4cfb-48a8-b477-57d12796362d' class='xr-var-data-in' type='checkbox'><label for='data-8c380828-4cfb-48a8-b477-57d12796362d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_bu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a8858b39-88d0-4d4b-9268-18b1cb9b8cfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8858b39-88d0-4d4b-9268-18b1cb9b8cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c9077ab-316a-43ad-b80c-2f0813dbabe4' class='xr-var-data-in' type='checkbox'><label for='data-0c9077ab-316a-43ad-b80c-2f0813dbabe4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c5e3a94-9112-460d-858e-baa0f4b88efe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c5e3a94-9112-460d-858e-baa0f4b88efe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cddeb8a6-b6bf-49c9-bf96-20f12fa30500' class='xr-var-data-in' type='checkbox'><label for='data-cddeb8a6-b6bf-49c9-bf96-20f12fa30500' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ccfb0eef-5d17-4529-bb42-87b45ed033cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccfb0eef-5d17-4529-bb42-87b45ed033cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fcf118c-7aeb-4dbd-bec1-a5bc5b29f6e7' class='xr-var-data-in' type='checkbox'><label for='data-4fcf118c-7aeb-4dbd-bec1-a5bc5b29f6e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>deptho</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5450ae7b-9f2f-4310-83ac-3bbfdb840d35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5450ae7b-9f2f-4310-83ac-3bbfdb840d35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8aabbb0a-aff6-40e9-b282-721c17b7d1e6' class='xr-var-data-in' type='checkbox'><label for='data-8aabbb0a-aff6-40e9-b282-721c17b7d1e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Floor Depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>standard_name :</span></dt><dd>sea_floor_depth_below_geoid</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-16b5bb57-19ac-4351-9c75-712dafd07086' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16b5bb57-19ac-4351-9c75-712dafd07086' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-068481bc-a93e-490d-882d-4b3bf2ab6787' class='xr-var-data-in' type='checkbox'><label for='data-068481bc-a93e-490d-882d-4b3bf2ab6787' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6fcc0a6b-d285-4987-91f1-6de15ef7deba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fcc0a6b-d285-4987-91f1-6de15ef7deba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7faf8d18-75f8-437a-bc01-8e5845c42d93' class='xr-var-data-in' type='checkbox'><label for='data-7faf8d18-75f8-437a-bc01-8e5845c42d93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-594b1c47-4b15-411f-a8ae-e41126002af0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-594b1c47-4b15-411f-a8ae-e41126002af0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03d4d128-99db-47f7-a7ac-240d3982f4b0' class='xr-var-data-in' type='checkbox'><label for='data-03d4d128-99db-47f7-a7ac-240d3982f4b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-60087045-c1af-4399-abc5-775588c84864' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60087045-c1af-4399-abc5-775588c84864' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68c3e7f2-38be-4d13-bbb5-883b37de360b' class='xr-var-data-in' type='checkbox'><label for='data-68c3e7f2-38be-4d13-bbb5-883b37de360b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e2f24ff3-625d-41c6-adf5-72595c2d8631' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2f24ff3-625d-41c6-adf5-72595c2d8631' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebd03a61-8217-4baa-94bb-61e2836ca041' class='xr-var-data-in' type='checkbox'><label for='data-ebd03a61-8217-4baa-94bb-61e2836ca041' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fb9161cb-74fb-48cc-bad9-52efcd311104' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb9161cb-74fb-48cc-bad9-52efcd311104' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a2b7ddb-7b6d-42f1-afdc-75abe8a1473f' class='xr-var-data-in' type='checkbox'><label for='data-7a2b7ddb-7b6d-42f1-afdc-75abe8a1473f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a6351266-e258-4140-a83b-2904934ecd18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6351266-e258-4140-a83b-2904934ecd18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3172b35f-d4b6-4633-bfc7-f8509f5989b4' class='xr-var-data-in' type='checkbox'><label for='data-3172b35f-d4b6-4633-bfc7-f8509f5989b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d902abc6-c66e-403a-894b-918a6af3f568' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d902abc6-c66e-403a-894b-918a6af3f568' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97695499-8cc5-42b8-b0d3-9413ef7a3d47' class='xr-var-data-in' type='checkbox'><label for='data-97695499-8cc5-42b8-b0d3-9413ef7a3d47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17a74cfb-a5f4-45bb-b94a-744670b8b189' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17a74cfb-a5f4-45bb-b94a-744670b8b189' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3abb73e8-f5a7-4590-9e7f-9db650370478' class='xr-var-data-in' type='checkbox'><label for='data-3abb73e8-f5a7-4590-9e7f-9db650370478' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-533394a8-41cc-4c13-92e5-9257ae6a70a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-533394a8-41cc-4c13-92e5-9257ae6a70a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10315f3a-72ad-47bd-abc1-1ad2cef35e70' class='xr-var-data-in' type='checkbox'><label for='data-10315f3a-72ad-47bd-abc1-1ad2cef35e70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8c6c0d9e-d796-40b7-9b76-1177b0c88687' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c6c0d9e-d796-40b7-9b76-1177b0c88687' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18d3f533-659f-449b-8f61-0213809abd30' class='xr-var-data-in' type='checkbox'><label for='data-18d3f533-659f-449b-8f61-0213809abd30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b9a3171c-1157-442a-a2e9-1f10c4825274' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9a3171c-1157-442a-a2e9-1f10c4825274' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06060992-29eb-4b71-91e7-42aceff03461' class='xr-var-data-in' type='checkbox'><label for='data-06060992-29eb-4b71-91e7-42aceff03461' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a1343d4e-9abf-42b9-a08e-da34c4b0f9bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1343d4e-9abf-42b9-a08e-da34c4b0f9bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6ebd30c-296e-437f-bae5-8e780b1f76f0' class='xr-var-data-in' type='checkbox'><label for='data-d6ebd30c-296e-437f-bae5-8e780b1f76f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3233a9a6-73eb-4a1c-bac2-f3a3dddbcf00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3233a9a6-73eb-4a1c-bac2-f3a3dddbcf00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3a22077-228c-4e17-968e-a3a97926eff8' class='xr-var-data-in' type='checkbox'><label for='data-f3a22077-228c-4e17-968e-a3a97926eff8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hfgeou</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9cc090a0-0321-459c-a99c-7b7f7d4d44cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cc090a0-0321-459c-a99c-7b7f7d4d44cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8489586d-e9ad-47d0-ba7f-3e513eca2b8f' class='xr-var-data-in' type='checkbox'><label for='data-8489586d-e9ad-47d0-ba7f-3e513eca2b8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Upward geothermal heat flux at sea floor</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>upward_geothermal_heat_flux_at_sea_floor</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftof</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-68b15587-cf97-4d2d-ae1b-8258b48884b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68b15587-cf97-4d2d-ae1b-8258b48884b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e983378-9d45-4967-a62e-4ec122720e7e' class='xr-var-data-in' type='checkbox'><label for='data-8e983378-9d45-4967-a62e-4ec122720e7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Area Fraction</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>SeaAreaFraction</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c59b6864-c62a-46f7-9bd8-1f5ce7ba4663' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c59b6864-c62a-46f7-9bd8-1f5ce7ba4663' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2e17e6b-e9f8-4ff4-9f37-c629065c924a' class='xr-var-data-in' type='checkbox'><label for='data-f2e17e6b-e9f8-4ff4-9f37-c629065c924a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at tracer points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5ae06df3-00d7-468c-b8d7-1854124924d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ae06df3-00d7-468c-b8d7-1854124924d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-898d3d21-f0d4-4e07-ac68-adfd54f4f721' class='xr-var-data-in' type='checkbox'><label for='data-898d3d21-f0d4-4e07-ac68-adfd54f4f721' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9349e02f-1d9d-4d70-8086-5678c8d0f1d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9349e02f-1d9d-4d70-8086-5678c8d0f1d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb7105da-b5bf-4fef-8177-5b922995ecb1' class='xr-var-data-in' type='checkbox'><label for='data-fb7105da-b5bf-4fef-8177-5b922995ecb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f66f92c2-fba9-4c1e-9821-ace1850e5b71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f66f92c2-fba9-4c1e-9821-ace1850e5b71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfcd56c5-3c8e-444f-904f-e335524e6688' class='xr-var-data-in' type='checkbox'><label for='data-bfcd56c5-3c8e-444f-904f-e335524e6688' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zeta</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9a102cab-27db-4c21-8f93-4c9cbdd04115' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a102cab-27db-4c21-8f93-4c9cbdd04115' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ca3d8ad-2c73-4291-9bd2-7b5444f9b0be' class='xr-var-data-in' type='checkbox'><label for='data-7ca3d8ad-2c73-4291-9bd2-7b5444f9b0be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4adbaa71-a085-4146-b302-657978e8e0d0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4adbaa71-a085-4146-b302-657978e8e0d0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:       (xh: 1440, xq: 1440, yh: 1080, yq: 1080)\n",
+       "Coordinates:\n",
+       "    time          object ...\n",
+       "  * xh            (xh) float64 -299.7 -299.5 -299.2 -299.0 ... 59.53 59.78 60.03\n",
+       "  * yh            (yh) float64 -80.39 -80.31 -80.23 -80.15 ... 89.73 89.84 89.95\n",
+       "  * xq            (xq) float64 -299.6 -299.3 -299.1 -298.9 ... 59.66 59.91 60.16\n",
+       "  * yq            (yq) float64 -80.35 -80.27 -80.19 -80.11 ... 89.78 89.89 90.0\n",
+       "Data variables:\n",
+       "    ssu           (yh, xq) float32 ...\n",
+       "    ssv           (yq, xh) float32 ...\n",
+       "    zos           (yh, xh) float32 ...\n",
+       "    Coriolis      (yq, xq) float32 ...\n",
+       "    areacello     (yh, xh) float32 ...\n",
+       "    areacello_bu  (yq, xq) float32 ...\n",
+       "    areacello_cu  (yh, xq) float32 ...\n",
+       "    areacello_cv  (yq, xh) float32 ...\n",
+       "    deptho        (yh, xh) float32 ...\n",
+       "    dxCu          (yh, xq) float32 ...\n",
+       "    dxCv          (yq, xh) float32 ...\n",
+       "    dxt           (yh, xh) float32 ...\n",
+       "    dyCu          (yh, xq) float32 ...\n",
+       "    dyCv          (yq, xh) float32 ...\n",
+       "    dyt           (yh, xh) float32 ...\n",
+       "    geolat        (yh, xh) float32 ...\n",
+       "    geolat_c      (yq, xq) float32 ...\n",
+       "    geolat_u      (yh, xq) float32 ...\n",
+       "    geolat_v      (yq, xh) float32 ...\n",
+       "    geolon        (yh, xh) float32 ...\n",
+       "    geolon_c      (yq, xq) float32 ...\n",
+       "    geolon_u      (yh, xq) float32 ...\n",
+       "    geolon_v      (yq, xh) float32 ...\n",
+       "    hfgeou        (yh, xh) float32 ...\n",
+       "    sftof         (yh, xh) float32 ...\n",
+       "    wet           (yh, xh) float32 ...\n",
+       "    wet_c         (yq, xq) float32 ...\n",
+       "    wet_u         (yh, xq) float32 ...\n",
+       "    wet_v         (yq, xh) float32 ...\n",
+       "    zeta          (yq, xq) float32 ..."
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "url = 'https://ndownloader.figshare.com/files/27968028'\n",
     "file1 = requests.get(url)\n",
-    "open('data.nc', 'wb').write(file1.content)\n",
+    "with open('data.nc', 'wb') as fp:\n",
+    "    fp.write(file1.content)\n",
     "\n",
     "ds = xr.open_dataset(\"data.nc\")\n",
-    "\n",
-    "print(ds)"
+    "ds"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "architectural-submission",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 24 ms, sys: 0 ns, total: 24 ms\n",
-      "Wall time: 23.5 ms\n",
-      "CPU times: user 23 ms, sys: 0 ns, total: 23 ms\n",
-      "Wall time: 22.8 ms\n"
+      "CPU times: user 97 µs, sys: 28 µs, total: 125 µs\n",
+      "Wall time: 128 µs\n",
+      "CPU times: user 115 µs, sys: 33 µs, total: 148 µs\n",
+      "Wall time: 153 µs\n"
      ]
     }
    ],
@@ -137,28 +542,47 @@
     "area = ds['areacello_bu']\n",
     "wet_mask = ds['wet_c']\n",
     "\n",
-    "filter_2Deg = gcm_filters.Filter(filter_scale=8, dx_min=1, filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "                              grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,grid_vars={'wet_mask': wet_mask})\n",
-    "\n",
-    "filter_10Deg = gcm_filters.Filter(filter_scale=40, dx_min=1, filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "                              grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,grid_vars={'wet_mask': wet_mask})\n",
-    "\n",
-    "zeta_2Deg = filter_2Deg.apply(ds['zeta'] * area, dims=['yq', 'xq'])\n",
-    "%time zeta_2Deg = (zeta_2Deg/area).load()\n",
-    "\n",
-    "zeta_10Deg = filter_10Deg.apply(ds['zeta'] * area, dims=['yq', 'xq'])\n",
-    "%time zeta_10Deg = (zeta_10Deg/area).load()"
+    "filter_2Deg = gcm_filters.Filter(\n",
+    "    filter_scale=8, dx_min=1, \n",
+    "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
+    "    grid_type=gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
+    ")\n",
+    "\n",
+    "filter_10Deg = gcm_filters.Filter(\n",
+    "    filter_scale=40, dx_min=1, \n",
+    "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
+    "    grid_type=gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
+    ")\n",
+    "\n",
+    "zeta_2Deg = filter_2Deg.apply(ds['zeta'], dims=['yq', 'xq'])\n",
+    "%time zeta_2Deg = zeta_2Deg.load()\n",
+    "\n",
+    "zeta_10Deg = filter_10Deg.apply(ds['zeta'], dims=['yq', 'xq'])\n",
+    "%time zeta_10Deg = zeta_10Deg.load()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "purple-chuck",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/glade/u/apps/dav/opt/python/3.7.9/gnu/9.1.0/pkg-library/20201220/lib/python3.7/site-packages/cartopy/mpl/geoaxes.py:1598: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
+      "  shading=shading)\n",
+      "/glade/u/apps/dav/opt/python/3.7.9/gnu/9.1.0/pkg-library/20201220/lib/python3.7/site-packages/cartopy/mpl/geoaxes.py:1598: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
+      "  shading=shading)\n",
+      "/glade/u/apps/dav/opt/python/3.7.9/gnu/9.1.0/pkg-library/20201220/lib/python3.7/site-packages/cartopy/mpl/geoaxes.py:1598: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
+      "  shading=shading)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1296x360 with 6 Axes>"
       ]
@@ -193,28 +617,26 @@
   },
   {
    "cell_type": "markdown",
-   "id": "arranged-radius",
    "metadata": {},
    "source": [
     "### Data Coarsening and Filtering \n",
     "\n",
     "From the figure above, numerical instability leads to large errors when an attempt is made to filter the data to $10^{\\circ}$ resolution. In order to overcome this issue, we can first interpolate the data from $1/4^{\\circ}$ to a coarser grid and then filter the coarsened data to $10^{\\circ}$ resolution.\n",
     "\n",
-    "As shown below, we first coarsen the data by taking mean over consecutive four gridpoints and then filter data to $10^{\\circ}$ resolution (note that scale factor is 10 in this case). This is only for demostration and, in practice, more advanced coarsening methods can be empoyed. Note that scale factor is 10 in this case. We then interpolate the filtered data back to the original finer grid. With this approach, the numerical instability issue does not seem to appear anymore."
+    "As shown below, we first coarsen the data by taking the mean over consecutive four gridpoints and then filter data to $10^{\\circ}$ resolution. (Note that the scale factor is 10 in this case). This is only for demostration and, in practice, more advanced coarsening methods can be employed. We then interpolate the filtered data back to the original finer grid. With this approach, the numerical instability issue does not seem to appear anymore."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "numerical-toronto",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 3 ms, sys: 0 ns, total: 3 ms\n",
-      "Wall time: 3.07 ms\n"
+      "CPU times: user 100 µs, sys: 4 µs, total: 104 µs\n",
+      "Wall time: 107 µs\n"
      ]
     }
    ],
@@ -225,12 +647,16 @@
     "area = ds['areacello_bu'].coarsen(xq=cor_fac, yq=cor_fac, boundary=\"trim\", keep_attrs=True).sum()\n",
     "wet_mask = ds['wet_c'].coarsen(xq=cor_fac, yq=cor_fac, boundary=\"trim\", keep_attrs=True).max()\n",
     "\n",
-    "filter_cor = gcm_filters.Filter(filter_scale=10, dx_min=1, filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "                              grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,grid_vars={'wet_mask': wet_mask})\n",
+    "filter_cor = gcm_filters.Filter(\n",
+    "    filter_scale=10, dx_min=1, \n",
+    "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
+    "    grid_type=gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
+    ")\n",
     "\n",
-    "zeta_10Deg_cor = filter_cor.apply(zeta_coarse * area, dims=['yq', 'xq'])\n",
+    "zeta_10Deg_cor = filter_cor.apply(zeta_coarse, dims=['yq', 'xq'])\n",
     "\n",
-    "%time zeta_10Deg_cor = (zeta_10Deg_cor/area).load()\n",
+    "%time zeta_10Deg_cor = zeta_10Deg_cor.load()\n",
     "\n",
     "zeta_10Deg_cor = zeta_10Deg_cor.interp(xq=ds['xq'], yq=ds['yq'])"
    ]
@@ -238,12 +664,21 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "elect-collins",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/glade/u/apps/dav/opt/python/3.7.9/gnu/9.1.0/pkg-library/20201220/lib/python3.7/site-packages/cartopy/mpl/geoaxes.py:1598: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
+      "  shading=shading)\n",
+      "/glade/u/apps/dav/opt/python/3.7.9/gnu/9.1.0/pkg-library/20201220/lib/python3.7/site-packages/cartopy/mpl/geoaxes.py:1598: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
+      "  shading=shading)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1152x360 with 4 Axes>"
       ]
@@ -273,26 +708,24 @@
   },
   {
    "cell_type": "markdown",
-   "id": "commercial-watson",
    "metadata": {},
    "source": [
     "### Filtering with Double Precision Data\n",
     "\n",
-    "Filtering accuracy can also be improved by enforcing computations in double precision. Below, we create dataset `ds2` from `ds` and the new dataset `ds2` has double precision, i.e. `np.float64`. By ensuring computations in double precision, we are able to filter vorticity to $10^{\\circ}$ resolution without data coarsening."
+    "The filter accuracy can also be improved by enforcing computations in double precision. Below, we create dataset `ds2` from `ds`, and the new dataset `ds2` has double precision, i.e. `np.float64`. By ensuring computations in double precision, we are able to filter vorticity to $10^{\\circ}$ resolution without data coarsening."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "id": "disabled-blake",
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 8 ms, sys: 0 ns, total: 8 ms\n",
-      "Wall time: 7.37 ms\n"
+      "CPU times: user 101 µs, sys: 3 µs, total: 104 µs\n",
+      "Wall time: 107 µs\n"
      ]
     }
    ],
@@ -302,22 +735,33 @@
     "area = ds2['areacello_bu']\n",
     "wet_mask = ds2['wet_c']\n",
     "\n",
-    "filter_10Deg = gcm_filters.Filter(filter_scale=40, dx_min=1, filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
-    "                              grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,grid_vars={'wet_mask': wet_mask})\n",
+    "filter_10Deg = gcm_filters.Filter(\n",
+    "    filter_scale=40, dx_min=1, \n",
+    "    filter_shape=gcm_filters.FilterShape.GAUSSIAN,\n",
+    "    grid_type=gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
+    ")\n",
     "\n",
-    "zeta_10Deg = filter_10Deg.apply(ds2['zeta'] * area, dims=['yq', 'xq'])\n",
-    "%time zeta_10Deg = (zeta_10Deg/area).load()"
+    "zeta_10Deg = filter_10Deg.apply(ds2['zeta'], dims=['yq', 'xq'])\n",
+    "%time zeta_10Deg = zeta_10Deg.load()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "damaged-lewis",
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/glade/u/apps/dav/opt/python/3.7.9/gnu/9.1.0/pkg-library/20201220/lib/python3.7/site-packages/cartopy/mpl/geoaxes.py:1598: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
+      "  shading=shading)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 576x360 with 2 Axes>"
       ]
@@ -339,6 +783,13 @@
     "_ = plot_map(ax, tmp, vmin=-max_z, vmax=max_z, \n",
     "                   lon='geolon_c', lat='geolat_c', cmap='RdBu_r', title=r'$\\zeta$ filtered to $10^{\\circ}$')"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -357,7 +808,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.2"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,
diff --git a/docs/tutorial_tripole_grid.ipynb b/docs/tutorial_tripole_grid.ipynb
index d7bec49..b959845 100644
--- a/docs/tutorial_tripole_grid.ipynb
+++ b/docs/tutorial_tripole_grid.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Filtering on a tripole grid\n",
     "\n",
-    "In this tutorial, we will use **Laplacians of varying complexity** to filter **tracer fields** on a global tripole grid ([Murray, 1996](https://www.sciencedirect.com/science/article/pii/S0021999196901369)). Examples of ocean models that use tripole grids include **POP** or **MOM6**."
+    "In this tutorial, we will use **Laplacians of varying complexity** to filter **tracer fields** on a global tripole grid ([Murray, 1996](https://www.sciencedirect.com/science/article/pii/S0021999196901369)). For example, **POP** and **MOM6** have configurations that use a global tripole grid."
    ]
   },
   {
@@ -36,10 +36,13 @@
      "data": {
       "text/plain": [
        "[<GridType.REGULAR: 1>,\n",
-       " <GridType.REGULAR_WITH_LAND: 2>,\n",
-       " <GridType.IRREGULAR_WITH_LAND: 3>,\n",
-       " <GridType.TRIPOLAR_REGULAR_WITH_LAND: 4>,\n",
-       " <GridType.TRIPOLAR_POP_WITH_LAND: 5>]"
+       " <GridType.TRANSFORMED_TO_REGULAR: 2>,\n",
+       " <GridType.REGULAR_WITH_LAND: 3>,\n",
+       " <GridType.TRANSFORMED_TO_REGULAR_WITH_LAND: 4>,\n",
+       " <GridType.IRREGULAR_WITH_LAND: 5>,\n",
+       " <GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND: 6>,\n",
+       " <GridType.TRIPOLAR_POP_WITH_LAND: 7>,\n",
+       " <GridType.VECTOR_C_GRID: 8>]"
       ]
      },
      "execution_count": 2,
@@ -59,8 +62,8 @@
     "\n",
     "| Laplacian | simple fixed factor  | fixed filter length scale|\n",
     "| ----------- | ----------- | --------------|\n",
-    "| Ignores tripolar exchanges  | `REGULAR_WITH_LAND`       | `IRREGULAR_WITH_LAND` |\n",
-    "| Handles tripolar exchanges  | `TRIPOLAR_REGULAR_WITH_LAND`        | `TRIPOLAR_POP_WITH_LAND` |\n",
+    "| Ignores tripolar exchanges  | `TRANSFORMED_TO_REGULAR_WITH_LAND`       | `IRREGULAR_WITH_LAND` |\n",
+    "| Handles tripolar exchanges  | `TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND`        | `TRIPOLAR_POP_WITH_LAND` |\n",
     "\n",
     "As shown in the table, the categories in which the 4 Laplacians differ are:\n",
     "* **complexity** (rows)\n",
@@ -477,7 +480,7 @@
        "    cell_methods:    cell_methods = time: mean ==&gt; the variable values are av...\n",
        "    nsteps_total:    9618241\n",
        "    tavg_sum:        431999.9999999717\n",
-       "    tavg_sum_qflux:  432000.00000000006</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-26dc65fd-ec2b-47cc-900e-9767ac145781' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-26dc65fd-ec2b-47cc-900e-9767ac145781' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>z_t</span>: 62</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1b50e302-9f0e-4189-941b-4d3b22e48d4a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b50e302-9f0e-4189-941b-4d3b22e48d4a' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-788e4ca0-6a6c-4425-9db3-1e23912c1f2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-788e4ca0-6a6c-4425-9db3-1e23912c1f2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3af9f757-f855-4891-a7f8-db1df2fb30ba' class='xr-var-data-in' type='checkbox'><label for='data-3af9f757-f855-4891-a7f8-db1df2fb30ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_t</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 1.5e+03 ... 5.875e+05</div><input id='attrs-787ad807-f134-4b62-b04d-d71efc11a7da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-787ad807-f134-4b62-b04d-d71efc11a7da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14a225c6-e4d2-4e3b-b660-0053a3490764' class='xr-var-data-in' type='checkbox'><label for='data-14a225c6-e4d2-4e3b-b660-0053a3490764' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>depth from surface to midpoint of layer</dd><dt><span>units :</span></dt><dd>centimeters</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>500.0</dd><dt><span>valid_max :</span></dt><dd>587499.06</dd></dl></div><div class='xr-var-data'><pre>array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,\n",
+       "    tavg_sum_qflux:  432000.00000000006</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4f377887-1adc-48d3-8dad-7d45922891ae' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4f377887-1adc-48d3-8dad-7d45922891ae' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nlat</span>: 2400</li><li><span>nlon</span>: 3600</li><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>z_t</span>: 62</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-829696ec-d8a8-46d0-b4d6-bebba383d5f9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-829696ec-d8a8-46d0-b4d6-bebba383d5f9' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0033-11-27 00:00:00</div><input id='attrs-01de3569-80e1-43a5-bbb8-740f129d4169' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01de3569-80e1-43a5-bbb8-740f129d4169' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3fa3afe-60e5-4e56-8b78-d06805d7df5b' class='xr-var-data-in' type='checkbox'><label for='data-e3fa3afe-60e5-4e56-8b78-d06805d7df5b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bound</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(33, 11, 27, 0, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_t</span></div><div class='xr-var-dims'>(z_t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>500.0 1.5e+03 ... 5.875e+05</div><input id='attrs-9be4af16-5017-4357-974f-20d5c9591157' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9be4af16-5017-4357-974f-20d5c9591157' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f536166-1520-451e-a954-3844e1976a1a' class='xr-var-data-in' type='checkbox'><label for='data-4f536166-1520-451e-a954-3844e1976a1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>depth from surface to midpoint of layer</dd><dt><span>units :</span></dt><dd>centimeters</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>500.0</dd><dt><span>valid_max :</span></dt><dd>587499.06</dd></dl></div><div class='xr-var-data'><pre>array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,\n",
        "       5.500000e+03, 6.500000e+03, 7.500000e+03, 8.500000e+03, 9.500000e+03,\n",
        "       1.050000e+04, 1.150000e+04, 1.250000e+04, 1.350000e+04, 1.450000e+04,\n",
        "       1.550000e+04, 1.650984e+04, 1.754790e+04, 1.862913e+04, 1.976603e+04,\n",
@@ -489,7 +492,7 @@
        "       1.968944e+05, 2.186457e+05, 2.413972e+05, 2.649001e+05, 2.889385e+05,\n",
        "       3.133405e+05, 3.379793e+05, 3.627670e+05, 3.876452e+05, 4.125768e+05,\n",
        "       4.375392e+05, 4.625190e+05, 4.875083e+05, 5.125028e+05, 5.375000e+05,\n",
-       "       5.624991e+05, 5.874991e+05], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0441ff2c-f88e-441b-b545-b833e26ac9c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0441ff2c-f88e-441b-b545-b833e26ac9c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a3430e7-b544-4ab2-940a-c536e8479450' class='xr-var-data-in' type='checkbox'><label for='data-1a3430e7-b544-4ab2-940a-c536e8479450' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ec125ce2-9087-4e70-a626-a4cf8da756fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec125ce2-9087-4e70-a626-a4cf8da756fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7e1e106-fb60-4b98-a7af-505c143fd8b7' class='xr-var-data-in' type='checkbox'><label for='data-d7e1e106-fb60-4b98-a7af-505c143fd8b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d64561e2-39c4-4943-a22a-16e2e8d59296' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d64561e2-39c4-4943-a22a-16e2e8d59296' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d11b34da-2645-473c-8e08-4a285ac2328b' class='xr-var-data-in' type='checkbox'><label for='data-d11b34da-2645-473c-8e08-4a285ac2328b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0e1fabc3-acff-47ea-a915-4761a2be788b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e1fabc3-acff-47ea-a915-4761a2be788b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb2600fb-e686-4f9d-a870-fc290152e5f2' class='xr-var-data-in' type='checkbox'><label for='data-eb2600fb-e686-4f9d-a870-fc290152e5f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a0d9dd9-8054-4e77-8904-6f39157b611b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a0d9dd9-8054-4e77-8904-6f39157b611b' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>KMT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ee17dd07-9fb1-41da-a058-714911c55733' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee17dd07-9fb1-41da-a058-714911c55733' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f3ef2fb-8981-4859-9223-25f1f3ecece4' class='xr-var-data-in' type='checkbox'><label for='data-2f3ef2fb-8981-4859-9223-25f1f3ecece4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>k Index of Deepest Grid Cell on T Grid</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAREA</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-800f159f-93f5-4179-976f-026b21a72d2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-800f159f-93f5-4179-976f-026b21a72d2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0be3f17-e08f-44e3-8774-0c894a854bbc' class='xr-var-data-in' type='checkbox'><label for='data-f0be3f17-e08f-44e3-8774-0c894a854bbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of T cells</dd><dt><span>units :</span></dt><dd>centimeter^2</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTN</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-43653178-d370-4d99-a4b2-9c6e1b192f97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43653178-d370-4d99-a4b2-9c6e1b192f97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7041fba-bc02-4e5d-b400-e22d92ef08f2' class='xr-var-data-in' type='checkbox'><label for='data-c7041fba-bc02-4e5d-b400-e22d92ef08f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on North sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTE</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cc4f8764-9a4f-48cc-b26a-9794c8676f96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc4f8764-9a4f-48cc-b26a-9794c8676f96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6daf7f43-b21f-442b-a008-f2baa61cea44' class='xr-var-data-in' type='checkbox'><label for='data-6daf7f43-b21f-442b-a008-f2baa61cea44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on East sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUS</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2ce6f75e-2a1b-436a-9573-cfa582174b74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ce6f75e-2a1b-436a-9573-cfa582174b74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-085f1684-be62-4145-a53a-c0174b3454ed' class='xr-var-data-in' type='checkbox'><label for='data-085f1684-be62-4145-a53a-c0174b3454ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on South sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUW</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-24a22042-faf1-44f4-bb61-27703dc9c628' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24a22042-faf1-44f4-bb61-27703dc9c628' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dafe5a2d-8adc-4c5c-a2a8-530e887a5a10' class='xr-var-data-in' type='checkbox'><label for='data-dafe5a2d-8adc-4c5c-a2a8-530e887a5a10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on West sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST</span></div><div class='xr-var-dims'>(time, nlat, nlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96a7bf9d-75b1-4030-9d52-0d71b932f5a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96a7bf9d-75b1-4030-9d52-0d71b932f5a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4897f89-f333-4466-8ac5-b7d54e9a8f16' class='xr-var-data-in' type='checkbox'><label for='data-f4897f89-f333-4466-8ac5-b7d54e9a8f16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a973b631-3f9a-4290-beb2-98e75e087f1d' class='xr-section-summary-in' type='checkbox'  ><label for='section-a973b631-3f9a-4290-beb2-98e75e087f1d' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>g.e01.GIAF.T62_t12.003</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>Conventions :</span></dt><dd>CF-1.0; http://www.cgd.ucar.edu/cms/eaton/netcdf/CF-current.htm</dd><dt><span>contents :</span></dt><dd>Diagnostic and Prognostic Variables</dd><dt><span>source :</span></dt><dd>CCSM POP2, the CCSM Ocean Component</dd><dt><span>revision :</span></dt><dd>$Id: tavg.F90 46405 2013-04-26 05:24:34Z mlevy@ucar.edu $</dd><dt><span>calendar :</span></dt><dd>All years have exactly  365 days.</dd><dt><span>start_time :</span></dt><dd>This dataset was created on 2014-07-19 at 17:28:03.3</dd><dt><span>cell_methods :</span></dt><dd>cell_methods = time: mean ==&gt; the variable values are averaged over the time interval between the previous time coordinate and the current one.          cell_methods  absent  ==&gt; the variable values are at the time given by the current time coordinate.</dd><dt><span>nsteps_total :</span></dt><dd>9618241</dd><dt><span>tavg_sum :</span></dt><dd>431999.9999999717</dd><dt><span>tavg_sum_qflux :</span></dt><dd>432000.00000000006</dd></dl></div></li></ul></div></div>"
+       "       5.624991e+05, 5.874991e+05], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f5857a1e-1409-43d1-afb5-b0f6d659b9a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5857a1e-1409-43d1-afb5-b0f6d659b9a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01439e40-eea9-41a6-837c-595ddfdb55fa' class='xr-var-data-in' type='checkbox'><label for='data-01439e40-eea9-41a6-837c-595ddfdb55fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ULAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fcb3e696-4fa3-49f5-845b-9b61354a0a0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcb3e696-4fa3-49f5-845b-9b61354a0a0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c7b50b3-c8fd-4ded-a79e-b3fa047c75b0' class='xr-var-data-in' type='checkbox'><label for='data-9c7b50b3-c8fd-4ded-a79e-b3fa047c75b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of u-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLONG</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9cc9b42a-c7d1-45a4-a9df-87ca61f9f255' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cc9b42a-c7d1-45a4-a9df-87ca61f9f255' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b637205-f88f-48e0-a36d-7607194b46f0' class='xr-var-data-in' type='checkbox'><label for='data-6b637205-f88f-48e0-a36d-7607194b46f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid longitudes</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLAT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a14099bf-9e11-4683-8042-5de5bd4ffce1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a14099bf-9e11-4683-8042-5de5bd4ffce1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53be6940-3e36-47b9-b086-50a8ad8eeba6' class='xr-var-data-in' type='checkbox'><label for='data-53be6940-3e36-47b9-b086-50a8ad8eeba6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>array of t-grid latitudes</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-93162f18-073b-4677-82ed-36491d2cf131' class='xr-section-summary-in' type='checkbox'  checked><label for='section-93162f18-073b-4677-82ed-36491d2cf131' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>KMT</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-88cfce81-996c-4ffc-9e02-4f939b4244c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88cfce81-996c-4ffc-9e02-4f939b4244c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94fce83e-8120-4f50-8306-838359125728' class='xr-var-data-in' type='checkbox'><label for='data-94fce83e-8120-4f50-8306-838359125728' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>k Index of Deepest Grid Cell on T Grid</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAREA</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f104b25d-63d1-4c37-8486-6b84d02928a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f104b25d-63d1-4c37-8486-6b84d02928a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6a65fd-9063-44ac-a450-e74025f6d4f4' class='xr-var-data-in' type='checkbox'><label for='data-4c6a65fd-9063-44ac-a450-e74025f6d4f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of T cells</dd><dt><span>units :</span></dt><dd>centimeter^2</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTN</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-28398c92-c132-4cc4-9148-856eb4dfdbec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28398c92-c132-4cc4-9148-856eb4dfdbec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f778b581-645c-4716-a837-6e714928c125' class='xr-var-data-in' type='checkbox'><label for='data-f778b581-645c-4716-a837-6e714928c125' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on North sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HTE</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8fdf8a97-31c8-4b2b-b1b7-b1f4f0ff4161' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fdf8a97-31c8-4b2b-b1b7-b1f4f0ff4161' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ffebb3f-f165-4aa9-8b2f-0196523934f5' class='xr-var-data-in' type='checkbox'><label for='data-2ffebb3f-f165-4aa9-8b2f-0196523934f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on East sides of T cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUS</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-709e2cba-2597-43ad-9b37-4295777935b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-709e2cba-2597-43ad-9b37-4295777935b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-527d75b4-19ab-462f-a780-e082988947dd' class='xr-var-data-in' type='checkbox'><label for='data-527d75b4-19ab-462f-a780-e082988947dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on South sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HUW</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fdff5eb4-c0f2-4047-ad02-d189812e44d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdff5eb4-c0f2-4047-ad02-d189812e44d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7344cd56-5bb1-4253-bd9f-7c9a08a7efe9' class='xr-var-data-in' type='checkbox'><label for='data-7344cd56-5bb1-4253-bd9f-7c9a08a7efe9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell widths on West sides of U cell</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST</span></div><div class='xr-var-dims'>(time, nlat, nlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f75b4a64-8981-4167-8b9f-3e572ae079f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f75b4a64-8981-4167-8b9f-3e572ae079f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e0b9a26-1502-41bd-93f7-d747b8160d01' class='xr-var-data-in' type='checkbox'><label for='data-7e0b9a26-1502-41bd-93f7-d747b8160d01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degC</dd><dt><span>long_name :</span></dt><dd>Surface Potential Temperature</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ccfc0281-deaf-4c03-9d1a-4b2da439d430' class='xr-section-summary-in' type='checkbox'  ><label for='section-ccfc0281-deaf-4c03-9d1a-4b2da439d430' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>g.e01.GIAF.T62_t12.003</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>Conventions :</span></dt><dd>CF-1.0; http://www.cgd.ucar.edu/cms/eaton/netcdf/CF-current.htm</dd><dt><span>contents :</span></dt><dd>Diagnostic and Prognostic Variables</dd><dt><span>source :</span></dt><dd>CCSM POP2, the CCSM Ocean Component</dd><dt><span>revision :</span></dt><dd>$Id: tavg.F90 46405 2013-04-26 05:24:34Z mlevy@ucar.edu $</dd><dt><span>calendar :</span></dt><dd>All years have exactly  365 days.</dd><dt><span>start_time :</span></dt><dd>This dataset was created on 2014-07-19 at 17:28:03.3</dd><dt><span>cell_methods :</span></dt><dd>cell_methods = time: mean ==&gt; the variable values are averaged over the time interval between the previous time coordinate and the current one.          cell_methods  absent  ==&gt; the variable values are at the time given by the current time coordinate.</dd><dt><span>nsteps_total :</span></dt><dd>9618241</dd><dt><span>tavg_sum :</span></dt><dd>431999.9999999717</dd><dt><span>tavg_sum_qflux :</span></dt><dd>432000.00000000006</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -743,16 +746,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=50, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=56, grid_type=<GridType.REGULAR_WITH_LAND: 2>)"
+       "Filter(filter_scale=50, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=56, grid_type=<GridType.TRANSFORMED_TO_REGULAR_WITH_LAND: 4>)"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -760,24 +763,24 @@
    "source": [
     "filter_regular_with_land = gcm_filters.Filter(\n",
     "    **specs,\n",
-    "    grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,\n",
-    "    grid_vars={'wet_mask': wet_mask}\n",
+    "    grid_type=gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area':area, 'wet_mask': wet_mask}\n",
     ")\n",
     "filter_regular_with_land"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=50, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=56, grid_type=<GridType.TRIPOLAR_REGULAR_WITH_LAND: 4>)"
+       "Filter(filter_scale=50, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=56, grid_type=<GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND: 6>)"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -785,31 +788,31 @@
    "source": [
     "filter_tripolar_regular_with_land = gcm_filters.Filter(\n",
     "    **specs,\n",
-    "    grid_type=gcm_filters.GridType.TRIPOLAR_REGULAR_WITH_LAND,\n",
-    "    grid_vars={'wet_mask': wet_mask}\n",
+    "    grid_type=gcm_filters.GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
     ")\n",
     "filter_tripolar_regular_with_land"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 12.2 s, sys: 8.42 s, total: 20.6 s\n",
-      "Wall time: 20.7 s\n",
-      "CPU times: user 13 s, sys: 9.14 s, total: 22.1 s\n",
-      "Wall time: 22.2 s\n"
+      "CPU times: user 12.6 s, sys: 7.67 s, total: 20.3 s\n",
+      "Wall time: 20.3 s\n",
+      "CPU times: user 13.4 s, sys: 8.37 s, total: 21.7 s\n",
+      "Wall time: 21.8 s\n"
      ]
     }
    ],
    "source": [
-    "%time delta_filtered_regular_with_land = filter_regular_with_land.apply(delta * area, dims=['nlat', 'nlon']) / area\n",
-    "%time delta_filtered_tripolar_regular_with_land = filter_tripolar_regular_with_land.apply(delta * area, dims=['nlat', 'nlon']) / area"
+    "%time delta_filtered_regular_with_land = filter_regular_with_land.apply(delta, dims=['nlat', 'nlon'])\n",
+    "%time delta_filtered_tripolar_regular_with_land = filter_tripolar_regular_with_land.apply(delta, dims=['nlat', 'nlon']) "
    ]
   },
   {
@@ -821,7 +824,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -835,16 +838,16 @@
     {
      "data": {
       "text/plain": [
-       "[Text(0.5, 1.0, 'filtered with TRIPOLAR_REGULAR_WITH_LAND Laplacian')]"
+       "[Text(0.5, 1.0, 'filtered with TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND Laplacian')]"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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n4neAJt54D30Z0CKEaLoitF8E/i9x+UoEF/0t8F5eTrK+4L+vW0p5fItthELchdfCiO+1+Et8yW2r/9YIJOKba+El0jch4ceBH75qJ0KILCHEd+GbK+MD/kT7KuYLMZnwfRaPgV3hm1zvsmEA3y2EqBdCJOEry/+jS85Xcfh6/zYAtxDia/F91gL+K/AuIcRbhG8eCIvwjcO/KBXfhKZ7wjefyI9fczyKolxP5UB3cD4Husev/ycgHfivQogC/2v7T4CfAn5cSnm+werB1we//4xv1Z77Dlt7hcoDb0flgSoPvAWVB6o8MGRUQ4/PLwD/TvhKjn/MX6b5duAn8b0RF/G9gS59vaRvrOLX4BvLa8dXKvYBfG9k8CUoKf77P4pvMqvrfB7fGziQ5HwBSOL6ssKXjuGG7QfD7+Brrf1WfB/8/y59K0isSt8Y7N/BV679yrKLUsp9fOPuz48PPcKXNKzia/39QXwrC8zcIpZvBj4LfBrfh/5/4DtRXDb2OhCDE99ylD99yWPHUsrPXHPSLxK+lT3O37753OP/RfjGxq/hS7D+GHirfHXyxbu683Fe5Yrj//ZLjiswNvoH8ZVq/yq+cs8lfL1x346vBwfg/8H33v7fwB6+nrCfklJ++sLuD/G9ZwK378E3ieB/Pv8ekr5S909zxZcCf4/U33C7k/vn8U0S+oVz9/2t/76HlOs+1Agvvxb/HF/C/BsXXotZfBNCXvUF6f1cXr48IIQ4xFeG/h7gX0kpb/py8skLMf0svvdxIr7P5lN8f5eLPobv/LaKb5WSVxIO/7nyh/Elzzv4SrI/ce7xLvwT8+F7D30e37CQi34OX/n2Hr5JY//khmNSFOVqKge6u98BSoUQV64KdBn/l6s34TtHjuIbEvNe4HuklB+/8PSgXB+kb/6K/879Gqauo/JAlQeqPPDhVB6o8sCQES93HiiKoijK3QghPgf8DynlR7SORVEURVEURQkflQdGJlXRoyiKoiiKoiiKoiiKEiNUQ4+ihJEQ4lOXlMUeCiF+Mgjbvmy7h0KIv3/zb0e3SDx2IcTfvyourWJSFEVR9EsIMXLFdem7tI5NL1QeGBqReOwqD1S0poZuKYqiKIqiKIqiKIqixAhV0aMoiqIoiqIoiqIoihIjVEOPoiiKoiiKoiiKoihKjFANPUrQCSHEuX+btYxFUaKVEOK9QogvCCH+ixAiyX9fgRAiU+vYFEVRlMikcjBFeTiVgymxQDX0KA8SSCiEEGlCiLcLIb5SSimFEKVCiF8Gvuv88xRFubUp4HeBbwSO/fd9D/CXQoheIcQfCCGSA0/2f+YqhBBx4Q9VURRFCTeVgylKyKgcTIl6qqFHuTUhxCMhxI8KIYqFEBlCiP8A/KD/4TLgvwDv8v+cDBQDQwBSzfqtKHcipfwE8CVgwZ+4Cynlf5RSPgK+EpgEvhdACFEGfBD4I+CZEKIysB0hRIcQ4juFEGlhPwhFURQlKFQOpijho3IwJRaohh6duaxXRwiRIoQo8v/b7D8hdQkhPi6EqPXfn4OvZygL+AEp5S4wAXyDfzO7+Fq8XUKIRGAbaAeGQ3xIihLL6vB9lvAnGmZ/b9ExYASq/M/7p8ColLINeD/wSwBCiEL/Y18FfJv/vgwhxKoQ4k/8Jck/IoSoC+tRKYqi6JDKwRQlqqgcTIlqqqFHB4SPVQhR6z9RZQshfksI8VkhRA8wDfyO/+mlwD8D3gv8MfAH/vslYJNS/hRQK4QwAJ8AHvnHgBuAAf+2vh5wAon+/yuKcj+lwOK5n0uA3wPWgAzgR4UQHf77/5v/OXtAjv/f9cC8lPL78H0uA/eZgJ8DxoA84Kz3SVEURQkelYMpStRSOZgS1UxaB6CElr/36I+AfwBs4mudPsCXPKz6b+/DlyAANOM7KX3B//vvFkJ8uZTy80KIFSHE+wA7YJZSbgshngNfhy/J+DugH/hHgANfyWO2f7+KotxdOTADIIQwSSlngG8RQnwV8DYgAajA93lb8/9ODjDr//chYBNC/Cug239fHfBMSjnAG597JUxqRb50hOC71xK7fyGlfGvQN6woyr2pHExRoprKwWKM3nIw1dAT4/y9R78K/CvgT/0nKifw14HnCCHeDnzE/2Mr8CUhRKKU8hgYBeqEEF8Afhlf6eHvAC7/8z+Jrzw4G/hLKeVnhRDfh2/yskF8pY2KotxPKvC3/n97AndKKT/j/5y9DsQBW4DX/7AVWPGXFw/hSyQSeOMzXgR8jRAi8Dn+K+CTUsrD0B6KAuDAyXvFm4O+3ffKP8m5+VmKooSTysEUJaqpHCzG6C0HU0O3dEBK+UV8Y0wlvvJChBBG//8twDLg9j/dhW8SvwT/z1v4TnRJUsppKeUvSCl7pZSBE9pfAJn4epQC2xg/9/NGCA9NUWKSEOIHhRCDwHcA7xNCtAJfL4Ro8j/+ZYAF3+drGV+SHzifdwIzUkqnlPJISvkbUsr/yBu9uo+AX8E3ceAEkMYbn3clxAQCgzAE/aYoSmRSOZiiRBeVg8UuveVgqqJHPxzADmDDV1IYmBDwq4FeYN//8xK+saI5/ucDJEspD+AsOfEGVnCQUo4LIXbxtWBn+5//BeBfAyVSSq8QwiilPGsJVxTlRh/B1+NrxddbWwA8Af6tECIF3xjw/4Cvt9cM/CjwZUKIRXzJxxcB/PM4CN7oaQJfKfJ/llL2AD3hOBhFURSdUzmYokQPlYMpMUE19OiEv3x4BajBd/Iy4evtafY/bvc/9W+ALwO+HN/SgdnACfgSjPPJghDC4O9V+jvgz/BNAgjwFOjAN/YclWAoyt1IKU+BF/7bp/x3fxr4aQAhRJqUMvDFwCWE+Bi+RCMV+JdSyhH/ds6SCyFE4N+5qORCU4ZXF94JCyHEW4Ffwzec4yNSyl+84nnfjG9ekcdSyu7LnqMoyu2pHExRoofKwWKbVjmYFlRDj75M4J8JXkp54r/Pib8nyZ9EzAgh/hfwL4UQP4Kv5+kH/b/zUrIQOIFJKT+N7wTIuW1PhvZQFEW/ziUYgZ8/Dnz8ht+R/n/m4ZsrYhmYBz4jpfxcKOJULqdFma+/EuCD+CoIloDnQohPSClHLzwvFfgR4FnYg1SU2KZyMEWJASoHi26RPNQq2FRDj04IIZLwjft+u79X6bP4Sglr8SX/8EZp4afxnXwSgTE1QZiixJRMfEuGVuIrIS7QNhwlTDqBKf+qIQghfh94O77S8/N+HvgA8OPhDU9RYpfKwRRF8VM5mBI2qqFHB4QQZuBP8bUiT+BbCvAv8fXqfp+UchveaG329xKNaBKsoighJaXcw7cSxJDWseiREAKjNr1JFmDx3M9L+OYcOCOEaMc3r8efCyFUQ4+iBIHKwRRFCVA5mLY0zME0oRp6dEBK6QK+5oqHt8MZi6IoihISOUKI8/Pp/LaU8rdv+8v+SSN/FfjeYAemKHqmcjBFURRFC6qhR1EURVHCKEQTAW5KKR9d8/gy/qWd/Yr99wWkAo3A54QvvgLgE0KIt6kJmRVFURRFiQVqMmZFURRFUYJOoNlEgM+BKiGEDV8Dz3cA3xl40F9OnhP4WQjxOeDHVCOPoiiKoiixQMMcTBP6OVJFURRF0SkppRv4IeAv8C0Z+wdSyhEhxPuFEG/TNjpFURRFURQlmKK2oudrvuZr5NbWltZhXMnpdOJ0OklKSsJgiP72tNPTUwDi4+M1jiT4vF4vbrcbl8uFlBKj0YjJZMJkMiF0VN4XK6SUeL1ePB4Pbrcbr9cb039TKSUOh4PExESMRqPW4TyYy+Xi9PRUk+Pp7e3tuWH4UxAIzXqTpJSfBD554b73XfHcrwhHTEp0iuQcTErJyckJUkoSExOj/pwvpeTo6Ij4+HhMpqhN26/k8XhwuVy43W7fRKn+67XRaIz6v50eSSnxeDxnOZiUEpPJhNlsxmAwxNzf1Ov1cnR0RHJyctQfm5SS09NTvF6vJufOWM/BtBC1V4ytrS2++MUvah3GK6SUTE5O4nA4aGpqipmLstfr5dmzZ7S1tZGQkKB1OA92enrK+vo6a2treDwe8vLyyM/PJykpSevQlCCTUrK7u8va2hpbW1ukpaWRn59PTk5OTDTCLi8vc3h4SE1NjdahBM3BwQFDQ0PU1NSQnZ0dtv0mJiaGbV+KEs0iNQdzuVwMDAyQnZ2N1WqN+i9eAYeHh4yMjNDZ2RkTx3R4eMjq6iobGxvEx8dTUFBAbm4uZrNZ69CUIPN4PGxubrK6uorD4SA7O5uCggLS0tJi4r08MDCAxWIhJyfn5idHCbvdzsLCAi0tLWHNi1QOFnyx0QoRIdxuN0NDQyQnJ9Pa2hoTJ7AAg8FAZWUlk5OTNDU1aR3OvZycnJw17kgpycvLo6GhQZ1YYpwQgszMTDIzM5FSsre3x9raGlNTU6SkpJw1+kRjNYzb7WZubo7Ozk6tQwmq1NRUOjo6GBgYwOFwUFpaqnVIQeMbHx471wZFiRQOh4PBwUEqKirIy8vTOpygSklJIS0tjZWVFYqKirQO586klGeNO5ubmyQkJFBQUIDVao2ZDlHlckajkfz8fPLz8/F4PGxtbbGwsMD+/v5Zo096enpUfmfa2dnB4/HEVCMPQFFREUlJSfT19VFfX09GRobWIQWN3nIwdXYNkpOTEwYGBiguLsZisWgdTkjk5uaysLDA7u5u1Hzoj4+Pzxp3hBDk5eXR1NQUE1VJyt0JIcjIyCAjIwMpJfv7+6ytrTE9PU1ycvJZo0+0JJ7T09OUlZXFZC9ofHw8HR0djIyM4HA4qKmpiYkKLIS+JgJUlHDY2tpifHycxsZG0tLStA4nJCorK+nq6iIvLy8qrlFSSg4ODs4adwLXWJvNFhXxK8FnNBrJy8sjLy8Pr9fL1tYWS0tLjIyMkJWVRUFBARkZGVHR6COlZHx8PGo7v2+SkZFBW1sbAwMDlJWVUVhYqHVIwaGzHEydaYNgb2+PkZER6urqyMzM1DqckKqpqYn48mG3283KygorKysYDAby8/NpaWmJyfmFlPsTQpCenk56ejpVVVUcHBywtrbG7OwsSUlJWCwWsrOzI/Z97nA42N3dpbq6WutQQsZoNNLU1MTs7Cx9fX00NzfHZKOWoij3t7i4iN1up6OjI6av82azmZKSEmZnZ6mqqtI6nCsdHx+zvLzM+vr6WdVsRUVFVFbNKqFjMBjIzc0lNzcXr9fL9vY2drud0dFRsrOzKS4uJiUlReswr7S8vExmZibJyclahxIyiYmJPHr0iMHBQRwOBxUVFRGbEyuXUw09D7S6usrs7Cytra26mN8lJSWF9PR07HZ7xFUu7e/vs7i4yN7eHgUFBapxR7k1IQRpaWmkpaVRWVnJwcEBi4uLTExMUFBQgMViibj30sTEBNXV1TF/0RVCUF5ezurqKt3d3bS0tET1uVYgMOqoN0lRQiXQo356esqjR4900ZBQXFzMs2fPsFgsEXUe9Hq9bG5usri4iMfjobi4mCdPnujib6I8nMFgICcnh5ycnLP30sTEBG63m+LiYvLz8yPqveRyuZifn+fJkydahxJyJpOJtrY2JiYmGBwcpLGxMaL+FneltxxMNfQ8wOLiImtrazx69EhXvcwVFRV0dXWRn5+vefltoHrHbrcTHx9PSUkJ9fX1Mf/lVwmdQKNPQ0PD2furv7//7P2VlZWl+ftrc3MTg8EQ8xWE5xUUFJCYmEh/fz9NTU2kpqZqHZKiKBrxer0MDQ2RlJREc3Oz5ufkcDEYDFRXVzMxMUFra6vW4ZxV76ytrZGdnU1NTU1EV2Eokc9gMJwN7wq8v54+fRpRVT4zMzOUlZVp/h0oXIQQ1NTUsLS0RG9vL21tbbo59min/kr3NDc3x87ODu3t7bExb8QdmM1mSktLmZmZ0WzYyMXqndbW1oiruFCin8lkoqSkhJKSEvb29lhaWmJ8fFzTKh+v18vk5GREJPnhlp6eTktLCwMDAzQ0NJCenq51SPeip/HhihJsHo+HgYEBsrKysFqtWocTdtnZ2SwsLLC1tRXWVQkDAhUXS0tLZxUXr732WlT38iuRKTExkcrKSsrLyyOmysfhcLCzsxPTw+avUlxcjMlkoqenh/b29qgtctBTDqYaeu5ISsn09DQOh4OWlhbdNfIEBMqHj46OwlY+fLF6p7i4WFXvKGETmM8n8D7s6+sjISEh7FU+i4uL5Obm6na1uMCqhv39/bqYF01RlDe43W76+/vJz8+npKRE63A0U1NTw+DgYFivPRerd6qrqyOiukKJfRerfJaWljSr8hkfH6empka33z0KCgowGAz09PTQ1tamOtkjnGrouQMpJRMTE7hcLl2VCl9GCEF1dTXj4+O0tbWFdF/Hx8dnFVSqekfR2lVVPoEV90LZw+R0OlleXtbFuPDrJCUl0d7eTl9fH9XV1Zr0at+X3pb2VJRgcblc9PX1UVxcHJVLjAdTUlIS2dnZLC0thbzBa3d3l9nZWVwul6reUTSXmJhIVVUVFRUVbG5uMj4+jtfrxWq1kpOTE9LvZpubmxiNRt13MOXl5WE0Gs+GcUXTSsZ6y8FUQ88tSSl58eIFQggaGhp03cgTkJWVFdLyYYfDwezsLA6HA6vVSm1trXrdlYgSqPJxuVwsLi7y9OlTioqKKCkpCcn45ampKaxWq0qygYSEhLPGHo/HQ15entYh3ZLQVdmwogSD0+mkr68Pq9VKfn6+1uFEBJvNxrNnzygoKAj6EAopJVtbW8zOzmI2m6moqIjZZeuV6HS+yifwfWF6evrsHBHs7wt6HjZ/mezsbGpra+nt7Y2yBYn0lYOphp5b8Hq9jIyMkJCQQGVlpWpsOKe6upqBgQGePHkStGFs+/v7zMzM4HK5sNlsEb3EtaKAb96q8vJyysrKWFpa4tmzZ+Tl5VFWVkZcXFxQ9nFwcMDh4SF1dXVB2V4siI+Pp6Ojg97eXjweD4WFhVqHpChKkJ2entLb20tlZSW5ublahxMxTCYTVquV6elpamtrg7JNKSXr6+vMzc2RlJREXV2dGp6lRLzk5GQaGxs5OTlhbm7ubLLkwsLCoH030fuw+ctkZmbS2NhIf38/zc3N6lwRgVRDzw28Xi+Dg4OkpaVRXl6udTgRJykpiZycHJaWligtLX3QtnZ2dpiZmUEIgc1m031ppBJ9jEYjZWVllJSUsLKyQnd399mEoQ8pbQ0sI6znceFXMZvNdHR00NfXh9frxWKxaB3S9YS+JgJUlIc4Pj6mv7+fmpoasrKytA4n4hQVFdHV1cXh4eGDvmR5vV5WV1eZn58nIyOD5uZm9YVWiToJCQnU1tbidDqZn5/nS1/6EsXFxRQXFz+oEloNm79aWloazc3NZ0uvR3zln85yMP0c6T14PB76+/vJzMxUjTzXsNlsLC4u4nK57vy7Uko2Njbo6upiYWGBqqoq2tvbVSOPEtUMBgMWi4XXX3+djIwM+vv7GRkZweFw3Gt7GxsbJCQkRO0qU6FmMplob28/+6KiKEr0czgc9PX1UVdXpxp5rhBY9nh8fPxev+/xeFhYWODp06ccHh7S3t5OXV2dauRRolpcXBxVVVU8efIEr9fL06dPz0YK3MfU1BQ2m00Nm79CSkoKLS0tDA8Ps7u7q3U4yjmqoucKbrebvr4+CgsLKS4u1jqciGYymbDZbExNTd16WImUkrW1Nebm5khJSaGhoYHk5OQQR6oo4SWEoKCggPz8fDY3NxkZGSE+Pp7y8nJSU1NvtQ2v18vU1BQdHR0hjja6GY1G2traGBwcxOPxRGzjvN4mAlSU+zg8PIyeHmKNZWRkEBcXx8bGxq2HtrndbhYXF7Hb7RQWFvL48eOoXSpZUa4S+H5SWlrK8vIyXV1d5ObmUlZWdutFXdSw+dtJTk6mra0t4isw9ZaDqYaeSwRWdigpKVFzPtxSYWEhi4uLtyof3tzcZGpqivT0dFpbW6NqtnZFuQ8hBLm5ueTm5rKzs8P4+PhZj9NNPafz8/MUFBSoleZuwWAw0NzczPDwMJOTkxE6p5rAqKOyYUW5q/39fYaHh9WcD3dQVVVFX18f2dnZ185J4vV6WVxcZGlpSa2gpeiG0WiktLSU4uJiVldX6enpIS8vD6vVeu3CGWrY/N0kJibS3t4e4XOq6SsH08+R3pLT6aSnpwer1aoaee7gfPmwlPLS5xweHtLT08Py8jItLS3U1dWpRh5FdzIzM3n06BFFRUX09/czMTFxZTnx6ekpKysrWK3W8AYZxQwGA01NTTidzmvPR4qiRJ6dnR2Gh4dpbW1VjTx3kJCQQF5eHgsLC5c+Hphk+dmzZ7hcLp48eUJZWZlq5FF0xWAwUFRUxGuvvYbZbObZs2csLy9fmSesr6+rYfN3FFgkY2ZmhrW1Na3D0T3V0HNOoJGnsrIyipbqjRzny4fPOz09ZWRkhNHRUSoqKmhpaVHjvxXdy8nJ4bXXXiMpKelsjiqv1/vScwJVKcFaNUIvhBDU19cD8OLFi4hq7PGVDRuCflOUaLezs8PY2Bjt7e1RtFRv5LBardjtdk5PT1+6f29vj+7ubtbX12lra6OysvLaKgZFiXUGg4GysjI6Ozs5PDzk2bNnbG1tvfQcj8fD9PQ0VVVVGkUZveLi4mhvb2d+fp7V1VWtw3mJ3nKwyI0szAJz8lRVVZGTk6N1OFGrqqqKqakpvF7v2Umyp6eHnJwcHj9+TEZGhtYhKkrEEEJQXFzMkydPcDqdPHv2jPX1daSU7O3tcXJyEqGlr5EvUGUohGBqakrrcBRFucb+/j4vXrygra1NVfrek9FopLy8/Ox8d3x8zODgIJOTk9TW1tLY2KheW0U5x2w2U1NTQ0tLC0tLS/T09HB4eAj4hs0XFhaqYfP3ZDabzxp7Njc3tQ5Ht1STPm+srlVWVqYaeR4oISGB/Px8BgcHcTgcZ2PAVUWColzNZDJRWVlJcXExU1NTzM/P43K5aG5uVuPCH0AIQW1tLUNDQ8zNzUXMEDg9TQSoKDc5OjpieHiYlpYW1RDxQPn5+SwsLDA8PMzBwUEEz5OhKJEjMTGRlpYWdnd3GR0dJSEhgf39ff7e3/t7WocW1UwmE21tbfT09GAymSKms19POZjuv317vV4GBwfJz8+noKBA63Ci3tbWFuvr62xvb9PS0kJZWZlq5FGUW0pISKCxsZGsrCxcLhczMzMcHx9rHVZUE0LQ2NjI9vY2y8vLWoeDEEJXZcOKcp2TkxP6+/tpbGxUK28+UGCi5dPTU3Z2dujs7FSNPIpyBxkZGTx+/JiTkxO8Xi+zs7N4PB6tw4pqcXFxtLa2Mjo6elYtpSW95WCRG1kYSCkZHR0lPT2dkpISrcOJakdHR/T29rK0tERLSwsNDQ3Mzc1pHZaiRB23283a2hqvvfYahYWF9Pf3Mzk5qZKNBzAYDLS0tLC8vMz6+rrW4SiKgm+F0/7+furq6tQS6g+0tbXFs2fPcDqdvP7662RlZb0yX6KiKDfb39/HYDDwZV/2ZZhMJp4+fcrKykpEzfUXbRITE2lubmZwcFB1XoaZroduTUxMYDKZsNlsWocStaSUzM/Ps7KyQk1NDVlZWYDvQ72wsMD+/r5K4BTlDubm5rBYLMTHx5Obm0t2djYLCwt0dXVRW1tLZmam1iFGJaPR+FIJceBcpYVI7v1RlHAIzItYXl6uzmkP4HK5GB8fx+l00traerbQRVVVFd3d3eTm5qqVtRTllgLLqdfX12M0GikrK6OwsJCJiQlWVlaor69Xw0vvKSUlhYaGBvr7+2lvb9d07iM95WD6OdILZmZmcDqdZ5N1Knd3cHBAV1cXLpeLzs7Ol744BebGGBsbU63ginJLx8fHbGxsvFRhaDAYsFqttLa2MjMzw+joKG63W8Moo5fZbKatrY2xsTH29va0DkdRdMnr9TIwMEBxcbFa4fSepJSsrq7S1dVFdnY2bW1tL61mGhcXR1FRkaqsVpQ7WFlZITU1lZSUlLP74uLiaGxspKysjN7eXhYWFtT3mntKT0+nurqavr4+XC6X1uHogi4behYXF9nb26OhoUE18tyD1+tlcnKS0dFR6uvrqaqqurTHKHCyXFtb0yBKRYk+ExMTVFdXXzqvVWJiIu3t7WRkZNDV1aWGIN1TfHw8ra2tjIyM4HA4NInBIETQb4oSDaSUDA0NkZOTQ1FRkdbhRKXAvEYbGxs8fvyYwsLCS3PZ0tJS1tfX1VAJRbkFt9vN3NwcFRUVlz6enZ3NkydPOD4+5vnz5xEx30w0ys7Oxmaz0d/fr9mUBHrKwXTX0LO6usrq6irNzc1qkuB72NnZ4dmzZ5jNZjo7O0lNTb32+ZWVlczMzKj5RRTlBtvb23i9XrKzs698jhCCoqIiOjo6WFlZYWBggNPT0zBGGRuSkpJoampiYGBAfQlSlDCRUvLixQuSkpIoKyvTOpyoI6VkcXGR3t5eSkpKaGpqIi4u7srnGwwGKisrmZycDGOUihKdZmdnKS4uvvYzZTQaqampoaamhuHhYaanp/F6vWGMMjbk5+dTWFjIwMCAev1CTFctHVtbW8zPz9PW1qbGLN+R2+1mdHSU6elpWlpasFqtt6qGiouLw2KxqPJhRbmGlPKsmuc24uPjaWlpobCwkJ6eHpaXl1Up8R2lpqZSX19Pf38/TqczbPsV6GvFB0UJmJ6eBnwdQMrdOBwOuru7cTgcdHZ2kpOTc6vfy83Nxe12s7u7G9oAFSWKHR8fs7m5SXFx8a2en56eTmdnJ0IIurq61OfrHoqLi8nMzGR4eDis+avecrDIjSzIdnd3mZiYoLW1FZNJ13NQ39nGxgZdXV2kp6fT0dFBUlLSnX6/pKRElQ8ryjWWl5fJzMy88/LCeXl5dHZ2sre3R09PD0dHRyGKMDZlZGRQWVlJX19fWOc9MgpD0G+KEsnm5+dxOBzU1dWpIfN34PV6mZmZYWhoiKqqKmpra++cw9bU1DA+Pq46AxTlCtcNm7+KwWCgvLycpqYmJicnGRsbU/Mn3pHNZiMhISHs87nqKQeL3MiC6PDwkNHRUVpbWzWd5TvaOJ1OBgYGsNvtdHR0YLFY7pWgqfJhRbmay+Vifn7+ynHhNzGZTNTX11NRUcHAwABzc3Mqob+D3NxcSktL6e/v1zoURYlJdrudzc1NmpqaVCPPHezv79PV1YWUks7OTjIyMu61neTkZNLT07Hb7cENUFFiwG2GzV8nOTmZR48ekZycTFdXF1tbW0GOMLZVVVXh8XiYmZnROpSYFPMNPScnJwwODtLc3PzSigTK9XZ2duju7qagoICWlpYHN5AFyod3dnaCFKGixIaZmRmsVuuDKw0zMzN58uQJp6en9Pb2hnU4UrQrLCwM2+o/QuhrIkBF3zY2NlhaWqKlpUXNi3hLUkoWFhYYHR2lsbGRioqKB792FRUVzM3NqYoDRTknMGy+pqbmQdsRQlBSUkJ7ezuzs7NMTk6quWduSQhBQ0MDBwcHYdqfvnKwmL7qejweBgYGqKure2mpPOVqUkqmp6eZnJykra2N/Pz8oG27pqaGiYkJVW2gKH4Oh4Pd3d2grT5jMBioqamhtLSU7u5u1bN0B6WlpVqHoCgx5fDwkMnJSTVk/g5cLhf9/f04HA4eP34ctNzVbDZTWlqqes0V5ZylpSWysrLuPCXFVRISEujo6MBoNNLd3a2mrLglIQTNzc1ahxGTYrahR0rJyMgIRUVFZGZmah1OVDg9PaWnpwev18ujR4+CXgGVnJxMRkaGKh9WFL/x8XGqq6uDPpwhNzdX9SxFLH1NBKjok8vlYmhoiObm5mtXsVHesLOzw/PnzykqKqKuri7oi4YUFxezvb2t5nJTFHznqIWFBcrLy4O6XSEE5eXlVFVV0dfXx/r6elC3H6vCV/GprxwsciN7oLm5OUwmEyUlJVqHEhU2Njbo6enBZrNRVVUVsg9ceXm5Kh9WFGBzcxOTyRSyhuhAz5LBYKCnp4eTk5OQ7Ee5O2E0BP2mKJFCSsng4CDl5eWqmvoWpJTMzMyEpJL6PCEE1dXVjI+Ph2T7ihJNpqengzJs/iqZmZk8evSI5eVlXrx4oTrcIoiecrDIjewBNjY22NzcpLa2VutQIp7X62V8fJyFhQU6OjruPRnZbZnNZsrKylT5sKJrXq+XyclJqqqqQrofIQQVFRVUVlbS29urepYURQm5iYkJ0tPTQ9ZgEUsCldQejyckldQXZWVlIYRQw3oVXXM4HOzt7QVt2PxV4uLiaG1tJSkpia6uLhwOR0j3pygXxVxDj8PhYHJyUk38dwtHR0d0d3cTFxdHe3t72FYks1gsbG9vqxOeoluLi4vk5uaGbYL4QM/S0tKS6lnSmBD66k1S9MVut3N0dHTvVQT1ZHNzk56eHqxWa0grqS8KzJeorgOKXo2Pj1NTUxOWVQCFEJSVlVFfX8/g4KCavkJjesvBIjeye3C73QwODtLY2KjGhN9gdXWV/v5+qqursdlsYV3yNFA+PDExEbZ9KkqkcDqdLC0tYbPZwrrfuLg42traSEpK4vnz56qhVVGUoNrb22NhYUEto34Dr9fLxMQEc3NzdHR0kJOTE9b9JyYmkpOTw9LSUlj3qyiRYGNjA5PJREZGRlj3m5aWxuPHj9na2mJoaEhNYaGERcw09ATGhNtsNtLS0rQOJ2J5vV5GR0dZXV3l8ePHYT/RBWRlZWEwGNjc3NRk/4qilampKcrLy4M+0eZtBHqWamtrGRwcZHV1Newx6J4QCJMh6DdF0dLp6SkjIyM0NzerFbaucXJyQnd3NyaTiY6OjrBVUl9ks9lYXFzE6XRqsn9F0YLX62Vqairkw+avYjKZaGpqIisri+fPn3N4eKhJHLqmsxwsciO7o6mpKVJTUykoKNA6lIjldDrp6ekhKSmJlpYWzGazpvFUV1erFYEUXTk4OODw8FDz81R6ejqPHz/GbrczNTWFlFLTeHRFoKskQ4l9Xq+XgYEBampqgrZMcSza39+nt7eXyspKysvLNa16MplM2Gw2pqenNYtBUcJtYWGBvLy8sA2bv4rFYqGpqYnBwUHV4R1uOsvBIjeyO1hdXeXg4IDKykqtQ4lYDoeDnp4eysrKsFqtEVFWnZiYSG5uriofVnRBSsnY2Bi1tbUR8fkzmUy0tbWdDXn1eDxah6QoSpSRUvLixQvy8/NDvphDNFtdXWVkZITW1laysrK0DgeAwsLCs84HRYl1TqcTu92O1WrVOhQAUlJSePToEbOzs8zPz6sONyUkor6hZ39/n9nZWZqbmyPiy1Mk2traYmBggMbGRvLy8rQO5yVWq5WlpSVVPqzEvPX1dRITEyNqaKkQgtraWrKzs+nu7ub09FTrkHRA6GoiQCW2LS4uIqWktLRU61AikpSS6elplpeXefToUURVPAkhqKmpYWxsTH3JVGLe5OSkZsPmrxIXF0dHRwf7+/tqoYyw0SYHE0K8VQgxLoSYEkL8m0sef68QYlQIMSiE+CshRFkwjjaqs0On08nw8LAaE36NhYUFpqen6ejoIDU1VetwXqHKhxU98Hg8TE9PazYu/CbFxcVUVlbS09PD/v6+1uEoihIFtre3WV1dpb6+XnW0XcLj8TA0NITT6aStrU3z4fKXSU9PJz4+no2NDa1DUZSQ2d/f5+joiPz8fK1DeYXBYKCxsZHExER6e3txuVxah6QEmRDCCHwQ+FqgHvgnQoj6C0/rAx5JKZuBPwJ+KRj7jtqGHiklAwMDVFdXk5ycrHU4Ecfr9fLixQt2d3c1nfDvNgoKClT5sBLT5ufnKSoqiujPYXZ2Ni0tLYyMjLC+vq51OLFLZ+PDldjk9XoZGxujpaUlbMuCR5PT01N6enrIyMigrq4uol+j6upqpqamVDWBEpOklGFdTv0+hBDYbDZKS0vp7u5Wq6KGkjY5WCcwJaWckVI6gd8H3n7+CVLKz0opj/w/PgWKg3G4kXvlucHJyQk5OTlhX5YyGrhcLvr6+oiPj6epqSmiyhQvo8qHo9Ov//qv097eTkdHB+94xzs4OTk5e+y9733vS5/Nw8NDvuVbvoW3vvWt2O12AD72sY+RlJTE0NDQ2fM6OjqYn58P30GEwcnJCWtra1ExtCE5OZlHjx6xsLDA7Oys+jwqinKpo6Mj6uvrI7rxWisHBwf09PRQXl4eFef9+Ph4CgoKYu7aG+tUDnY7a2trJCUlRdSw+avk5eXR0NDAwMAA29vbWoejBI8FWDz385L/vqu8G/hUMHYctQ09Xq83YibUiiRHR0d0d3djsVg0X9XhLtLT00lISFDlw1FieXmZD33oQ3zxi1+kp6cHj8fDH/7hHwLQ09PD7u7uS8//n//zf/Lud7+bX/7lX+ZDH/rQ2f0Wi4UPfOAD4Qw97CYnJ6moqIjoHt3zzGYz7e3tHB8fMzw8rHp5g0wIEEYR9JuihJPZbCYjI0PrMCLO+vo6Q0NDNDc3R1VHZFlZGSsrK2qetiihcrDb8Xg8zMzMRNViPWlpaXR0dDA5OakWqwmBEOZgOUKI7nO3779ffOK7gUfAfwzG8UbtxDaJiYlR04gRLtvb24yNjdHQ0EB6errW4dxZVVUVPT095OTkRM2XYq24XC6Oj49xOp24XC7cbvel/3e5XEgpb/VZCVRvGI1GzGYzJpPpyv8fHx/jdrs5Pj7GbDZzfHxMYWEhHo+Hn/zJn+SjH/0on/jEJ8627fF4MBgMGAyGl6pEvu7rvo4vfOELTExMUF1dHfwXSmO7u7s4nU5yc3O1DuVODAYDdXV1LCws0N3dTWtrK3FxcVqHFSOEZkOthBBvBX4NMAIfkVL+4oXH/xnwg4AHOAS+X0o5GvZAlYinzgcvk1IyPz/PxsYGjx49irrXx2g0UlFRweTkJI2NjVqHE9GklDidzrMc7Kr8y+1243a775SDCSFuzMHMZjMnJycqB7uFubm5iB82f5n4+HgePXrE8PAwh4eHET3sLPqELAfblFI+uuKxZaDk3M/F/vtejkyIrwJ+CvhyKWVQWt2jtqFHNQS8bG1tjdnZWdrb20lISNA6nHsJlA/Pzc1RXl6udTiacrvdnJyccHR0xPHx8dnt5OQEKSUmk4nExETi4+PPEoCkpKRLE4O7fFaklHi93iuTlsPDQ1wuF6enp3zjN34jFRUVxMfH89prr1FWVsYv/MIv8JVf+ZWv9PR+x3d8B+985zs5OTnhv/7X/3p2vxCC9773vfzSL/0SH/nIR4L18kWEwLjwhoaGqLxACyEoKysjKSmJnp4eWltbSUxM1Dos5Z7OTQb41fjKhp8LIT5xoSHn96SUv+V//tuAXwXeGvZglYgXjee0UAmc691uNx0dHVGbn+bl5bG4uMje3l5UdhYGi5TyrDPt4i1Q8RQfH09iYuJZw4vZbCYhIeGlxhiTyYTJZLrTZ0VKicfjuTIHOz4+PovtfA72+uuvU15ezgc+8AHe/OY3k5WV9dJ29ZiDnZycsL6+zpMnT7QO5V6MRiPNzc1MT08zMDBAc3Nz1J5bFJ4DVUIIG74Gnu8AvvP8E4QQbcCHgbdKKYM2UWbUNvQob7Db7SwtLdHR0RGRqzrchdVq5enTp1gslqhrgb8PKSWnp6fs7++zv7/PwcEBR0dHZw05gVtubi6JiYkkJCSE9EQf6E26aV6nnZ0dhoeHmZiYICUlhe/8zu/kM5/5DJ/61Kf48Ic/zNjYGB6Phy996UukpKSQlpbGRz/6UVJTU19ZIe/bv/3b+cAHPsDc3FzIjksLKysrpKWlkZKSonUoD5Kbm4vZbKavr4/W1taIWh44KvknAtTA2WSAAEKIwGSAZw09UsrzS64lA2qSJkW5hpSS0dFRjEZj1DbqBwTmS3zx4gWPHz+O6mO5LSklDofjLP/a39/H6XQSFxf3Ug6WkZFBUlIScXFxIX1dhBBnDUTXCeRg4+PjJCcn893f/d186lOf4s/+7M/4rd/6LYaGhvB4PDx79oy0tDTS0tL42Mc+RkpKyis5ZKzmYNE2bP4yQggqKyuZn5+nv7+flpaWiJ93NeJpkINJKd1CiB8C/gJfRfXvSClHhBDvB7qllJ/AN1QrBfhD/zlmQUr5tofuWzX0RLmlpSVWV1dpb2+PiSXmDQYDlZWVMVk+LKXk6OjoLJnY39/n9PSUhIQE0tLSSE1NpaioKCqGJf71X/81Vqv1bEjSt3zLt/DzP//znJyc8M3f/M2Ab9WR97znPXzpS19if3+flZUVJiYm8Hg8JCcns76+zsnJCV6vlx/5kR/hV37lV7Q8pKByu93Mzs7S2dmpdShBkZGRQWNjI/39/TQ3N0d945VOXTYZ4CtdnUKIHwTeC8QBbw5PaIoSfbxeL8PDwyQmJlJZWRnx1+3bSE1NJSUlhdXVVQoLC7UOJ6i8Xi+Hh4cvdawF8pHU1FSys7Ox2WxRMewukIPl5eUBL+dg3/qt3wr4crB3vetdfOELX2B/f5/5+XkODw8RQpCSksLW1hZOpxMhRMzlYNE6bP4qZWVlGI3Gsw63WPi+pzdSyk8Cn7xw3/vO/furQrFf9U6JYnNzc2xvb9PW1hZTLby5ubksLCzERPnw8fExW1tbbG9vc3BwcDbzf2ZmJmVlZVFbtVRSUkJXVxdHR0ckJiby2c9+lh/+4R/mB37gB86ek5OTw8jICMBLqx0EetA+//nPc3JyQn9/P1VVVXzgAx84m/sn2s3OzlJSUhL1FXbnpaWl0dzczODgII2NjVGxgkVEEiCMIelNyhFCdJ/7+bellL99141IKT8IfFAI8Z3AvwPeGawAFSVWeL1eBgYGyMjIwGazaR1OUFVWVvL8+XPy8vKiOreUUnJwcHCWg52enpKamkpaWhqFhYVUV1dH7Rfm2+Zgo6O+gs3zQ7k8Hg8HBwcIITg8PKSrq4u6urqzHCzaF2CI9mHzVykuLsZoNNLb20tbW1tM5ZdhFbocLCJF5xlOYXp6moODA1pbW6O6LPEy0Vw+fHp6yvb2Ntvb2+zt7ZGQkEBWVhZWq5XU1NSoOpbrdHZ28k3f9E28/vrrmEwmWlpaePe7332r3w30JmVmZpKRkUFnZycej4f3vOc9/MzP/AxDQ0Nsbm6SlZVFVlYWGRkZUZVsHh0dsbW1FTPVPOelpKTQ2tpKf38/9fX1atWd+xCaTAQIt5wM8JzfB34zGIEpSizxeDz09/eTm5sbFcun31VcXBzFxcXMzs5G1WpFgU6k7e1ttra2ODo6Ii0tjaysLOrr62NqjrmH5GBGo5GMjIyzHOv1118/q/55//vfT19fH9vb22RnZ5OVlRV1uevKygrp6ekxWXlcWFiI0Wikp6eH9vb2qKg+izihy8Eikjg/+3o06ejokF/84he1DiPspJRMTk5yenpKQ0NDzDXynDc6OkpGRgZFRUVah3IlKSW7u7usra2xs7ODyWQiKyuL7Oxs0tLSYvrvE0oul4udnR22trbY3d3FZDKRk5NDfn5+xM8R09/fT0lJCdnZ2VqHEjLHx8f09/dTXV0dU8eZmJjYc0NjyYPVp5XK33v0Y0Hfbttnf+Ta2IUQJmACeAu+Bp7nwHdKKUfOPadKSjnp//c3AD8T6tdDiU56zcHcbjd9fX0UFRVhsVi0DidkvF4vz549i/hJ+D0eD5ubm6yvr7O/v09ycvJZDpaUlBRVDRSR5Pj4+KzB7ODggOTkZPLy8s7m7ItUbrebZ8+e0dnZGdFxPtTm5iaTk5O0tbVF7QI8l4nlHEwrqqInikgpGRsbQ0pJY2NjzF/AzpcPR1J5rZSSnZ0d1tbW2N7eJj09nfz8fKqqqqKq8iSSmc1m8vLyzsafn56esrGxwYsXL3C5XOTl5ZGfn09ycrLGkb5se3sbKWVMNX5cJjExkfb2dvr6+vB6vTEzDj4cBNqUDd9yMsAf8i/v6QJ2UMO2FOWMy+Wit7eXsrIyCgoKtA4npAwGA1VVVUxMTNDS0qJ1OC9xu91sbm6yurrK0dHRWWVVWlpazOfF4ZKYmIjFYsFisZxVSq2vr9PT04PZbKagoIDc3NyIqyiZnZ2ltLQ0pht5wDcs7/wwrkhujI00WuVgWomcb8/KtaSUjIyMYDabqa6u1sXFLFA+PDc3p3n5sNfrPWvc2dnZISMjg4KCAmpqalTVThjEx8dTXFxMcXExLpeL9fV1xsfHzybbKygo0LzRx+v1MjExQXNzs6ZxhEt8fPxZY4/H44n5Lz6x4BaTAf5I2INSlChwenpKX18f5eXlZx0QsS4nJ4eFhQV2dnbIzMzUNBa3283Gxgarq6ucnJyQm5tLRUUFKSkpusiHtRQYbp+SkkJ5eTlHR0esra3R19eH0WikoKCAvLw8zRt9AsPmo3U59bvKzMykoaGBvr4+WlpaNM+BlcikGnqigNfrZWho6Owkq6eLWklJCc+ePcNisYS9xTowLMtut7O7u0tmZib5+fnU1taqxh0Nmc3ms54ml8vFxsYGExMTZ8mfFu8VgOXlZbKysiJ+aFkwxcXF0dHRQW9vL16vN6KHWUYMnY0PV5Rod3JyQl9fX8wNVb2NmpoahoaGePLkSdhzT6/Xy/r6Ona7ndPTU3Jzc6mqqorJuVeiSVJSEjabDZvNxvHx8SuNPgUFBZpU4U9MTFBVVaWr70jp6ek0NTWdrYiampqqdUiRT2c5mGroiXBSSgYHB8nIyMBqtWodTtgZDAaqq6vDWj7scrmw2+3Y7XZSUlKwWCzU19fr6uIRLcxmM0VFRRQVFeF2u1lfX2doaAiTyURxcTE5OTlhaZRzuVwsLCzopifpPJPJRHt7O/39/UgpY3reiqAQ6CrJUJRodnp6Sm9vL3V1dZpXtWghOTmZzMxMlpeXKS4uDss+HQ4HS0tLbG5ukpubS3V1tWrciVCJiYlYrVasVivHx8esrKzQ1dVFRkYGxcXFYVudc2trC0B3DbEAqampZ4tktLS0qM/KTXSWg6mGnggWGK6Vmpqqy0aegOzs7JCXDweqd5aWljg8PKSoqIiOjg7NS1GV2zOZTGeNPoeHhywuLjI5OUl+fn7Iq3ymp6exWq0RNZdUOJlMJtra2s7G7+tlaIOiKLHL5XLR19dHbW2tLht5AioqKnj27FlIKzW8Xi9ra2ssLS0hhKC4uJiqqipVPR1FEhMTKS8vx2azsbW1xczMDKenp1gslpC/dyYnJ3UzbP4yycnJtLS0MDg4qObsUV6iz28lUWJychKj0Uh5ebnWoWiuuro6JOXDF6t3iouLycjIUNU7US4lJYW6ujo8Hg9ra2shrfI5PDxkb2+PmpqaoG0zGhmNxrPGnsDqc8rl9DQRoKJEI4/HczYnj97PZSaTibKyMqanp4N+nbtYvdPQ0KCr4c+xSAhBTk4OOTk5nJ6esry8HNIqHz0Om79MSkoKDQ0N9Pf3097eTnx8vNYhRSw95WCqoSdCzc7Ocnp6qovVtW4j2OXDR0dHzM7Osr+/T2FhoareiVFGo/HSKh+LxUJxcXFQepjGx8epqalRn1N8Q+kCjT2NjY1hK9tWFEUJFq/XS39/PxaLRVUn+lksFp49e4bD4XjwpK9SSra3t5mdnQVQ1TsxLD4+/tIqH6vVSl5e3oPzJj0Pm79Meno61dXV9PX10dHREfOrjyk3Uw09EWhpaYmdnR1aW1vVl8dzAuXD+fn59z55HRwcnF1obDabmntHRwJVPm63m6WlpbP3Umlp6b0b+TY2NjCbzWRkZAQ32CgWHx//0nhxtRLEBTqbCFBRoomUkuHhYbKzs9V8Y+cIIaipqWF8fJz29vZ7bUNKycbGBrOzsyQlJVFbW6vmE9GJ81U+x8fHzM3NMTMzQ1lZGQUFBfdu5JuamtL1sPnLZGdn43a7zyp7jEaj1iFFFp3lYPo50iixtrbGysoKLS0tqnfjApPJhNVqZWZm5s6/u7u7S29vLxMTE5SWltLZ2Ulubq5q5NGhwPvo9ddfJz4+nu7ubsbHxzk9Pb3TdrxeL1NTU1RXV4co0uiVlJREU1MTAwMDnJycaB2OoijKjaSUjI2NnU0wq7wsMzMTo9HI5ubmnX7P6/WysrLC06dP2dzcpKmpiaamJtXIo1OJiYnU1dXR3t7O4eEhT58+ZWFhAY/Hc6ftHB4esr+/r1b7vER+fj6FhYUMDAzg9Xq1DkfRkGoCjSBbW1vMzs7S0dGhWmCvUFRURFdX163KhwPlwTMzM5jNZiorK9VQEuWMwWCgpKQEi8XC2toavb29pKenY7VabzXWe2Fhgby8PBISEsIQbfRJTU2lrq7urIRYDY30ETpb8UFRosX09DRer5fKykqtQ4lY1dXV9Pf3k5WVdWNnpNfrZXl5mcXFRbKzs9W8IcpL4uPjqa6uxmazsbi4yNOnTykqKqKkpOTGCh0ppRo2f4Pi4mJcLhcjIyNqGpBz9JaDqYaeCLG3t8fExATt7e1qTOU1hBBUV1dfWz4spWRzc5OZmRmSkpKoq6tTPUfKlQwGA4WFhRQUFLCxscHw8DAJCQlUVlZe2eBzenqK3W5X48JvkJmZSWVl5Vljjyqvxlc2rKOJABUlGszPz+NwOGhublZfiK6RmJhIbm4ui4uLlJWVXfocr9fL4uIiS0tL5Ofn8+jRI9XQr1zJbDZTXl5OWVnZS8PqrxuSpYbN347NZmN8fFw1ip2nsxxMP0cawQ4PDxkZGaG1tVX1dtzCdeXD+/v79PT0sLq6SnNzsyoPVm5NCEFeXh6PHz/GYrEwODjI+Pg4LpfrledOTU1RXl6uKu9uITc3l9LSUvr7+1UJsaIoEcdut58NKVJfhG5ms9lYWlrC6XS+dL+UktXVVZ4+fYrb7ebJkydUVlaqRh7lVoxGI2VlZbz++uvExcXx7NkzFhcXX8kbvF4v09PTatj8LVVXV+N2u88mP1f0RXWvauz4+JjBwUGam5tJTEzUOpyocbF8+OTkhKmpKY6Pj6mpqVFDtJR7E0KQnZ1NVlYWdrudrq4uLBYLpaWlGAwG9vf3OTo6or6+XutQo0ZhYSEul4vBwUFaWlr0/WVKZ2XDihLJNjY2WFpaor29Xc2LeEtGo5Hy8nKmpqbOroO7u7tMTEyQnJxMR0eH6rRU7s1gMFBaWkpRURGzs7M8e/aMyspKcnJyEEKwsLBAfn6+GjZ/S0II6uvrGRgYYHFxkZKSEq1D0pbOcjDV0KMht9vNwMAA9fX1qurkjgLlw/Pz83g8HjY2NqioqFATLCtBI4TAYrFQUFDA3NwcT58+pby8nIWFBWpra9X77I5KS0s5PT1lYmKCmpoarcNRFEXnDg4OmJqaUsNK76GgoIDFxUU2Njaw2+14PB6VyypBZTKZqKqqori4mKmpKebn57HZbGrY/D0YDAaam5vp7e0lISGB3NxcrUNSwkQ/TVoRJrCEZ2lpqRpjeg9SSuLi4piamsJoNPLkyRPy8vLUl28l6IxGIxUVFXR0dLC0tITD4VBDkO6psrKSo6Mj7Ha71qFoShhF0G+Kotye0+lkaGiI5uZmNbToHtxuNwkJCQwODmKxWGhvb1eNPEpIJCYm0tTURFVVFUNDQ5jN5kuH1CvXMxqNtLS0MDk5icPh0DocTekpB1NdGBqZmZkhMTFRLQt4Dzs7O4yNjZGdnU1dXR37+/uq5FoJOZPJhNPppLW1lZmZGUwmEzU1NapE/Q6EEDQ1NdHd3U1ycjLp6elahxR+QuiqbFhRIo3X62VgYICqqqobV+9UXialZGlpiYWFBaxWK0KIOy+LrSj3IYQgKSmJ0tJS+vr6ziZsVvn/7cXFxdHY2Mjg4CCPHz/WZyWjznIw/RxpBFlfX2d3d5eqqiqtQ4kqbreb0dFRpqenaWlpobq6GovFwuHhIQcHB1qHp8S4ubk5ioqKyMzMpL29nYKCAnp6elheXkZKqXV4UcNkMtHc3MzIyAinp6dah6Mois6Mj4+Tk5Ojhi/ckcPhoLu7G4fDwZMnT7BYLFRXV58tS68ooSKlZGxsjLq6OvLz88+GbnV1dbG3t6dxdNElLS0Nm83G4OCgyl11QDX0hNnh4SFTU1M0NzerVug72NjYoKuri/T0dDo6Os6WvRZCUFtby9jYmDphKSFzcnLC+vo6paWlZ/fl5eXR2dnJ3t4ePT09HB0daRhhdElKSqKmpoaBgQHdfUEQ/okAg31TFOVmgdWirFar1qFEDa/Xy8zMDIODg1RVVVFbW3tWCRAfH09hYSFzc3PaBqnEtLW1NVJSUkhNTQV8c86Ul5fT1NTExMQEY2NjuN1ujaOMHgUFBaSmpjI1NaV1KGGntxwsciOLQU6n82yFLbPZrHU4UcHpdDIwMIDdbqejowOLxfLKPDxpaWkkJiayvr6uUZRKrJuYmKCysvKVxlmTyUR9fT0VFRUMDAwwNzenGhxvKTs7m/z8fEZHR9VrpihKyO3s7LC8vExjY6Oaz++W9vf36erqQkrJkydPLp1TsqysjNXVVVWhqYSEx+NhZmaGysrKVx5LTk7m0aNHJCcn09XVxebmpgYRRqfKykoODg5YXV3VOhQlhFRDT5h4vV4GBweprKxUE9bdgpQSu91Od3c3hYWFtLS0XDsXSlVVFdPT02qsuBJ0u7u7uN3ua8v8MzMz6ezsxOVy0dXVpYYS3lKgQmpxcVHjSMJJIIyGoN8URbnayckJL168oLm5GaPRqHU4Ec/j8TA+Ps7Y2BiNjY1UVFRcWYVuMBiorKxkYmIizFEqejA3N4fFYrly0nQhBCUlJbS3t7O4uMjQ0BBOpzPMUUYfIQTNzc3Mzs6yv7+vdThhpK8cLHIjizGTk5NkZmaSl5endSgR7/j4mN7eXnZ3d3n8+PGtXrNA+fD8/HwYIlT0QkrJ+Pj4rZYDNxqNVFVVUV9fz+joKJOTk7oblnRXQgjq6+tZXV1le3tb63DCQ2dlw4qiNY/Hw8DAAHV1dSQmJmodTsTb3t7m2bNnJCYm8vjx41t1Tubm5nJ6esru7m7oA1R0IzBsvqSk5MbnJiQk0NraSm5uLt3d3apS5RYCcyYODw/rp3FMZzlY5EYWQ+x2O8fHx5SXl2sdSsRbW1ujr68Pm81GfX39nYa4BcqHT05OQhihoid2u5309PQ7rcySmppKZ2cnJpOJ58+fq7l7bmAwGGhpaWFsbIzj42Otw1EUJYZIKRkZGTmbSF+5mtfrZXJykpmZGdra2igtLb31ELfAfIkTExNqKK4SNBMTE1RVVd16TlMhBAUFBTx+/Jj19XWGh4fV3D03SE5Oprq6WpdzJuqBaugJsb29PRYWFtSY8Bt4PB5GR0ex2+08fvyYrKysO28jUD48OTkZgggVvXG73czNzVFRUXHn3xVCYLPZqK2tpb+/n5WVlRBEGDvi4+Opr69nYGAg9pMyga7KhhVFS/Pz85hMpltVBOjZ8fEx3d3dGI1GOjo67lX5FJgsV13vlGDY2dnB7XaTk5Nz5981m800NTWRmZnJ8+fP1XD6G+Tk5JCTk8PY2JjWoYSeznKwyI0sBjidTkZGRmhubj5boUB51eHhIc+fPyclJYXW1tYHTVStyoeVYJmZmaG0tPRB78f09HQ6OzvPepbUHFJXy8jIoKSkhNHRUa1DURQlBmxvb7O+vk5tba3WoUS0QCV1VVUV5eXlD+qUrKioYHZ2NvYb7JWQklIyMTFxq2HzVxFCYLFYaGpqYmRkhMXFRVVtdg2r1Yrb7WZ5eVnrUJQgUg09IRIoF66srDxbClx5mZSS5eVlhoaGqK+vv1OZ8FUC5cPj4+PqhK7c29HREdvb2xQXFz94W4Ex0BkZGWqi5hsEVtWz2+1ahxI6QuhqfLiiaMHlcjE2NkZzc/Oth33ojcfj4cWLF9jtdh49ehSUoW1xcXGUlJQwOzsbhAgVvbLb7WRkZNxp2PxVUlJSePz4MQcHBwwMDOByuYIQYewJzJk4Pz8f21MO6CwHi9zIotzy8jJxcXFq8uUruN1uhoaG2N7e5vHjx6SlpQVt2ykpKaSlpanyYeXexsfHqa6uDtpwSyEExcXFNDU1MTw8rHqWrlFXV8fc3FxsJxqKooSMlJLR0VHKy8tJSEjQOpyI5HA4eP78OUlJSbS2tl65otF9FBcXs7m5qeZcU+4lMGw+mPOaGo1G6uvrKSgo4Pnz56rq/womk4mGhgaGhobUfD0xQjX0hIDD4WBxcfFBJYexbH9/n+fPn5OTk0NTU1NIhrVVVlaq8mHlXra2thBC3GueqJukpKTQ2dnJ/v4+g4OD6v15CZPJRH19PcPDwzGZaAhAGAxBvymK4mO32zEajRQUFGgdSkSy2+0MDg5SX19PWVlZ0OePNBgMVFdXMz4+HtTtKvowMzNDWVnZg4bNX6WgoIC2tjYmJiaYnZ1VHW6XSE9PJzc3l5mZGa1DCQm95WCRG1mU8nq9DA8P09DQoOblucT6+vrZvEVFRUUh24/ZbFblw8qdeb3eB48Lv4nRaKShoeFsCVDV6/mqjIwMsrKyYjPREIBRBP+mKAoOh4P5+Xk1L88lAvOerK2tBb2S+qLs7GyklGxvb4dsH0rsCQybt1gsIdtHYmIijx494uTkhKGhITV34iVsNhs7Ozvs7OxoHUrw6SwHUw09QTY1NUVeXl5IL6DRSErJ7OwsCwsLPHr0KCjjbm8SKB9WQ0CU21paWiInJ+deK47cVVFREbW1tfT29qoy4kuUl5ezvb2tXhtFUW5FdbRdze1209/fjxCC1tbWsLw+NTU1arl15U6CPWz+KgaDgbq6OjIzM+np6eH09DSk+4s2QggaGxt58eKFmtMoyqmGniDa3t5mf38fq9WqdSgRJZB8HR8f097eHpJyzMsEyocnJibCsj8lujmdTpaWlrDZbGHbZ0ZGBu3t7YyNjcX2BMT3YDAYaGxsZHR0NMaGuAldlQ0rSrhMT0+Tm5tLenq61qFElMDS6fn5+VRVVYX8S3RAUlISWVlZLC0thWV/SnTb2trCYDCEZNj8VUpKSqioqKCnp0ctlHFBYmIiNpuNFy9eaB1KkOkrB4vcyKJMYIWHxsbGsF1Eo4HT6aS7u5u0tDTq6urCvvqFKh9Wbmt6ehqr1Rr2nuBAGfHa2hqTk5Oq9/OcpKQkrFZrDCYaiqIE087ODru7u2FtqI8Gu7u79Pb2UlNTE9Lh8lcpLy9nYWFBVQUo1woMm6+urg77vrOzs2lpaWF4eJiNjY2w7z+SFRYWxv5KqDFONfQEQWApdbXCw8sODw/p7u7GZrOFZMK/21Llw8pNDg8POTg4oLCwUJP9m0wmWltb8Xq9DAwMqDHj5xQVFSGljJ1V9AQIoyHoN0XRK5fLxYsXL1RH2wUrKyu8ePGC9vb2oCydfh8mkwmr1cr09LQm+1eiQziHzV8mOTmZjo4O5ubmmJubU98Xzom5lVB1loNFbmRRxG63YzKZ1AoP52xsbDA4OEhzczO5ubmaxqLKh5XrSCnDNi78OkIIampqziZpPjk50SyWSFNXV8fs7GyMTFytr7JhRQml80upa/UlMdJIKZmammJlZYXHjx9r/roUFRWxt7eHw+HQNA4lMjmdThYXFzWvxouLi6Ojo4PDw0NGR0djctXP+4i9lVD1lYNFbmRRQq3w8Cq73c7s7CyPHj0iJSVF63AAVT6sXG1jY4O4uDgyMjK0DgUAi8VCVVUVvb29KjH2M5vN1NXVMTw8rHraFEU5s7KygsFgUB1tfoEKc5fLRVtbW0RMSh3oxFDLrSuXmZ6exmazRcR71WAw0NDQQHJyMn19faq62i+wEqpayTj6qIaeBwhcUOvr6yPiBBUJFhcXsdvttLe3ExcXp3U4Z1T5sHIZr9fL1NSUJuPCr5OVlUVTUxMDAwNqgkC/zMxMMjIymJ+f1zqUh9HZ0p6KEiqnp6fMzc1RV1endSgRwev1Mjg4SEJCArW1tRE1jC0jIwOTyaTmQFFeovWw+csIIbBarRQUFNDb2xtji0HcX3l5OZubm+zv72sdysPoLAdTDT0PsLy8TGpqasRUAmhtbm6Ozc3NiOlFuihQPnx4eKh1KEqEmJ+fp6CggPj4eK1DeUVqaiotLS0MDQ2xt7endTgRoby8HLvdHiNDuBRFeYixsTGqqqoiMt8IN4/Hw8DAAOnp6VRWVkZUI09AdXU1U1NTMTL8Q3koKSVjY2PU1NRE5PvVYrFQUlJCT0+PGg2Ar9qpvr6eFy9eqMrqKKIaeu7J6XQyPz9PVVWV1qFoLjAefG9vj5aWFoxGo9YhXUqVDyvnnZ6esrKyQllZmdahXCk5OZnW1lZGRkbY2dnROhzNGY1GampqGBsb0zqUB9HT+HBFCYXNzU2klJrPARgJ3G43fX195OTkYLVatQ7nSgkJCeTl5bGwsKB1KEoE2NjYID4+nvT0dK1DuVJBQQE2m42enh5OT0+1DkdzgeKGaJ/zVE85WORGFuHGx8eprKzUfU+SlJKJiQlOTk5obm4O+/Lpd5WRkYHZbFblwwqTk5NUVFREbMNkQFJSEu3t7YyNjbG1taV1OJrLzs7GaDSyvr6udSj3IoTQ1YoPihJsHo+HiYkJNTcivkae3t5eioqKKCkp0TqcG1mtVux2O06nU+tQFA1F6rD5y+Tl5Z3Nm6gWyYCKigoWFxejtuFLbzlY5EYWwba3t3G5XOTl5WkdiqaklLx48QKv10tDQ0NEll5eRpUPK3t7e5ycnETNZzghIYH29nYmJyejtoEjmGpqapiamlJj5xVFh2ZmZrBYLCQkJGgdiqacTic9PT2UlpZSVFSkdTi3YjQaKS8vZ2pqSutQFA1F8rD5y2RnZ1NbW0tvb2/sLDN+TyaTicrKyqivrNYL1dBzR16vl/Hxcerq6qKmYSMUvF4vw8PDmEymiJv07yaqfFjfAsupR+q48KvEx8fT0dHB7Owsq6urWoejqfj4eEpKSqJ2cnU9lQ0rSjAdHh6yvb1NaWmp1qFo6vT0lN7eXsrLy6NuxbH8/HwODw+jf1JX5V4Cw+YjeZjhZTIzM2loaKC/v1/3K6Lm5eXh9XrZ3NzUOpR70VMOFrmRRajZ2VkKCgpITEzUOhTNSCkZHR0lMTGR6urqqPqyHBAoH47W0kPl/lZXV0lJSSE1NVXrUO7MbDbT0dHBwsKC7it7iouL2dvbU18WFEUnAlXE0da5FGxOp5Pe3l6qqqqico4iIQS1tbWMj4+rSV11aHJyksrKyoif6uEy6enpZyui6n1RiLq6OiYmJtQS9BEu+j5lGnI4HKyvr0f05K3hMDExgclkoqKiQutQ7k2VD+uTx+NhdnaWyspKrUO5N5PJRFtbGzMzM2xvb2sdjmaEENTV1UXfChA6W9pTUYLFbreTkpIS0ZO3hprb7aa/v5+Kigqys7O1Dufe0tLSSEpKYm1tTetQlDAKDJuPxgbKgNTU1LPKHj13FickJFBUVMTMzIzWodyNznIw1dBzS+d7kqKxFTpYZmZmcDqdUTfs5TL5+fkcHR2pioBL/Pqv/zrt7e10dHTwjne8g5OTE6SU/MzP/AxNTU20trbywQ9+EPAN43v3u9/NV3zFVzA6OgrA3/zN35CYmMif//mfn23zH//jf8zf/M3faHI8AbOzs1gsFuLi4jSN46HMZjNtbW2MjY3peun1WFkBQlGU6zmdTubm5nS90qnX62VgYIDi4uKomV/uOpWVlczMzKiKgEvEYg4WrcPmL5Oenk51dTV9fX26Xnq9tLSUra0tDg8PtQ5FuYJ+WyzuaHV1lcTERDIzM7UORTOLi4vs7e1F1cTL1zm/3HpUVQSE2PLyMh/60If44he/SE9PDx6Phz/8wz/kYx/7GEtLSwwMDNDf38+3fuu3AvCZz3yGx48f8/GPf5xf+7VfO9uOxWLhAx/4gFaH8Yrj42M2NjaiYmWS24iPjz9bel3P48WjbwUIoavx4YoSDBMTE1RUVOh2pVMpJUNDQ+Tk5ETNxMs3iY+Pp6ioiLm5Oa1DiSixmoNF87D5y2RnZ2Oz2ejv79dtY6XBYIjCymp95WCRG1kEcblczMzM6LonaXV1ldXV1ahYQv0uVPnw5dxuN8fHx2f/Lyws5Ld/+7f5yZ/8ybO/f6BH0ePxYDAYMBgML53om5ubSU9P56/+6q80OYaLJiYmqKqqiqn3b1JSku7HiwdWgBgfH9c6lNsR6GppT0V5qO3tbZxOJ/n5+VqHoolARXlSUlLMTR1QWlrK2tqaWrb6gljLwdxuNzMzM1E9bP4y+fn5FBYWMjAwoNuVfNPT00lJScFut2sdyu3oLAfTZ9fIHU1NTWGz2aJ+uMd9bW1tMT8/T0dHB0ajUetwgq6qqoru7m5yc3Oj+vg8Hg/Hx8c4nU7cbjculwuXy3X2b4/Hc2WLuxACs9mMyWTCbDbzrne9i6qqKhISEnjzm9/MW97yFt75znfyR3/0R3ziE58gJyeHX/mVX6GyspKv/uqv5l3vehe/+7u/e1ZKHPATP/ET/NzP/RxvectbwvESXGlnZwePx0NOTo6mcYRCamoq9fX19Pf309HRocvzVF5eHsvLy2xtbUX1vBWhJoR4K/BrgBH4iJTyFy88/l7gPYAb2AC+T0o5H/ZAFcUvsNJpS0tLTFQS30dgLsFY+5IMvoqAqqoqJiYmaG5u1jqcB3G5XBwfH7+Se53Pwa5iNBrP8i+TycS73/3usxzsLW95S9TnYHNzcxQXF8dkflJcXIzL5WJ4eJimpiZdnqcqKyvp6uoiLy8Ps9msdTjKOaqh5waBOVxqa2u1DkUTu7u7TExM0N7eHrMl03FxcWflw5E+wbTH4+Hg4IDDw0OOj485Ojri5OQEj8eD0WgkISGB+Pj4s4TBbDaTlJSEyWTCZDJdeQHyer1nycjW1hZ/+Zd/ySc/+UkSEhL48R//cX7+53+eo6Mj1tfX+fCHP8wXvvAF3vWud/HpT3+apKQkPvaxj1263Te96U0AfPGLXwzZa3ITKSUTExM0NjZqFkOoZWRkUFlZSV9fHx0dHTH7Wb1OdXU1w8PDZGVlRXyiJQzhj08IYQQ+CHw1sAQ8F0J8Qko5eu5pfcAjKeWREOKfA78EfHvYg1UUP7vdTnZ2NklJSVqHoon5+XmOjo5obm6O+PPafeXk5LCwsMDu7i4ZGRlah3Mtp9PJ/v4+DoeD4+Njjo+Pz+bPMZvNJCQkEBcXd9ZgEx8fT0pKCmaz+dqORI/H81IO9ulPf5o///M/P8vB3v/+93N0dMTm5iYf+chH+Nu//Vu+7/u+j//zf/4P8fHxEZ2DBYbNP3nyRLMYQs1mszExMcHY2JguVwU0m82UlpZGzTxqWuRgWtHft4E7CiwDqLcPLfgauUZHR2lrayM+Pl7rcEKqtLSUZ8+eYbFYSEhI0DocwFfqure3x8HBwVliIYQgNTWVlJQUMjIyKCwsJDExMaiVSF/84hepra09uyi/853vpKuri9LSUv7pP/2n5Ofn8/a3v52f/umfZnJykqOjI4xGI2lpaaSmppKWlvZSCetP/MRP8IEPfECzxofl5WUyMjJITk7WZP/hkpubi9vtZmBggLa2tpgaonYbycnJpKamsra2RkFBgdbhRKJOYEpKOQMghPh94O3AWUOPlPKz557/FPjusEaoKOd4PB7m5+fp7OzUOhRNrK6usrm5SVtbW0znoIH5EkdGRujs7IyYYz05OWF/f//sdnJygtlsJi0tjZSUFPLy8khMTCQ+Pj6o19u/+7u/o66ujtdeew2A7/3e7z3Lwd7znveQl5fH13/91/NTP/VTjIyMcHJyQkJCwln+lZaW9lL1ttY5WCwOm79MVVUVIyMjzM3NYbPZtA4n7CwWC8+ePaO0tDTmvzNGE9XQc439/X1cLpcuhwIEvjA2NDSQmJiodTghZzAYqKys1LR82OPxsLu7y9bWFjs7OwBnF22bzUZycnJYLpQlJSV0dXVxdHREYmIin/3sZ2lvbyc1NZUvfelLvPOd72RgYIDq6mpaW1sB3/tlf3+fg4MD5ufnGR0dZW9vj7m5OZ48ecLOzg6rq6shj/0it9utqy8KhYWFHB0dMTk5SU1NjdbhhF1FRQU9PT3k5eVFblIpBGgzntsCLJ77eQm4rov13cCnQhqRolxjYWGBoqIiXQ4F2N/fZ3Z2lsePH0fuuSyIUlJSSEtLY2VlRbPJpp1OJ9vb22xtbbG3t0dcXBzp6emkpaWddQKGoxHquhzs6dOnvPOd72RoaIjq6mo6OjqQUnJ6enrWKWi32xkeHmZ/f5/l5WXe9KY38XM/93Oa5GCxPGz+IiEE9fX19PT0kJKSEtVLyN+HwWDAZrMxPT1NfX291uFcTbscTBOqoecaExMTVFdXax1G2AVWdygrKyM9PV3rcMImNzc3rOXDUkocDgdra2tsb2/jdrvJyMg4m8lfq+S2s7OTb/qmb+L111/HZDLR0tLCu9/9bo6Pj3nXu97Fb/zGb5CcnMxv/uZvnv2OyWQiKyuLrKwswHdx/4u/+AtMJhMzMzO87W1v433vex8bGxs4nc6wjdOenp6mrKxMV18UysvLGRgYwG63x8zqLLcVHx9Pbm4uy8vLEbu6moBQrdCQI4ToPvfzb0spf/s+GxJCfDfwCPjyoESmKHfkcrmw2+1nVQ164nQ6GR4epqWlRVfDcM/P8xGO4/Z6vezs7LCxscHOzg5Go5GsrCyKioqoq6vTrIHtrjmYEIKEhAQSEhLOGhcODg749Kc/ffZeClRhBxpewjEfZWA59aamppDvK1IYDAZaWlro7u4mKSkp5ivJL8rPz2d+fh6HwxGxxx7CHCwiiehZDu1lHR0dMpRjTre2tlhaWqKlpSVk+4hUU1NTeDweXVYEHB4ehrR8WErJwcEBa2trbG5ukpiYSF5eHtnZ2TFd6hho1NrY2GB9fR2j0Uh+fj55eXkhO26Hw8HQ0BBPnjyJmFLwcHG73XR3d1NXV6erxlrwHfuzZ8947bXX7pzMJiYm9kgpH4UoNABarXXy//z0R4O+3fz3vHZt7EKI14GflVL+Q//P/xZASvkLF573VcBvAF8upVwPeqBKTAh1DjYxMUFSUhLFxcUh20ck8nq99PT0YLPZdFEFcdHi4iLHx8ch62T1er1sb2+ztrbG7u4umZmZ5OXlkZmZGdWLcdzE6/Wyt7fH+vo6W1tbpKSkkJ+fT05OTsiOe2lpCYfDocvvEvv7+4yMjPDo0SNddTSCb5XExcXFe31/juUcTCv66Sq4AyklU1NTMT1561XW1tbY29ujvb1d61A0kZKSQnp6Ona7HYvFErTtHh4eYrfb2dzcJDk5mfz8fGw2m25664QQpKSkkJKSgs1m4/j4mLW1NQYGBgAoKCigoKAgqJU+4+Pj1NTU6K6RB3wVVs3NzWcrccVyI+JFJpMJi8XC/Pw85eXlWofzKv/Snhp4DlQJIWzAMvAdwHe+FJoQbcCHgbeqRh5FKycnJ2xtbcXkKlM3GRsbIycnR5eNPOBbwejZs2ccHR0FbQJuKSXb29usrKywt7dHVlYWhYWF1NfX6yY/MBgMZGZmkpmZiZSS/f191tbWmJ6eJjk5mYKCAnJzc4NWxeRyuZifn4/pCZivE5hyYWhoKObn2LooKyuL2dlZ9vb2IrOjUbscTBP6+JZ5R2tra6SmpkZs2VmoHBwcMDMzw6NHj3R1UrqooqKCrq4u8vPzH9QQ4/F4WFtbY2lpCZPJRFFRERUVFTHda3RbiYmJWK1WrFYrJycnrK6uno1rLi4uJiMj40Hvwc3NTYxGI5mZmUGMOrokJSVRU1PDwMAAjx490sU8DwElJSU8ffo0ZpdzvQ8ppVsI8UPAX+BbXv13pJQjQoj3A91Syk8A/xFIAf7Q//lbkFK+TbOgFV2anp6moqJCV+cs8FVAuN1urFar1qFoRghBVVUV4+PjtLW1PWhbp6enLC8vs7q6Snp6OhaLhYaGBl3nt+B7jdPT00lPT6eqqoqDgwNWVlaYmpoiNzeX4uLiBzeyzczMUFZWppvOzMsUFBRwcHDA1NRUVKxEFUxVVVVMTEzw6FHEFbjojn4/gVfwer3Mzs7qrqLF6XQyNDREc3Oz7soMLwosEzgzM3Ov8uHDw0OWlpbY2toiPz+fpqYmXUxofV8JCQlYrVbKysrY3d1laWmJsbExioqK7jURp9frZXJy8myiaD3Lzs7m8PCQ0dFRXSW4RqMRq9XK7OxsBJaNC82W9pRSfhL45IX73nfu318V9qAU5RyHw4HD4YjsyTxDYGdnh+XlZd13tIHvurW4uMjW1tadF0ORUp5NvXB6eorFYqGzs1PXDQ7XEUKcLfpRVVXF2toaIyMjCCEoKSm5V5WPw+Fgd3dXl3OcXlRZWUlfXx8rKysUFhZqHU7YpKWlERcXx+bmZgRWJ2qXg2lBnfkuWF5eJicnR1dDHbxeL4ODg1RWVpKSkqJ1OBHhruXDgdLg2dlZDAYDxcXFVFdX665H8iGEEGelxU6nk5WVFbq7u0lPT8dms926sWxxcZHc3FzVuOZXWlrKyMgICwsLlJWVaR1O2BQVFfH06VOOj48j670gAHVeUJRLTU5OUlVVpavGjpOTE168eEFbW5uq+PWrrq5mcHCQzMzMW+VRXq8Xu93O4uIiaWlplJeXk5aWFoZIY4fBYKCwsJDCwkIcDgdLS0tMTU1hsVgoLi6+dWPZ+Pg41dXVuvoMX0UIQXNzM8+fPyc5OVlX78nKykqGhobIzs6OrPeCznIw/RzpLXg8HhYWFrDZbFqHElYzMzNkZGSQl5endSgRQwhBdXU14+Pj1z5PSsn6+jpdXV3Y7XZqa2tpb2+P7OWdo0BcXBxlZWW89tpr5OTkMDg4yNDQEIeHh9f+ntPpZHl5WXef4esElvxcXV1lb29P63DCRghBRUUF09PTWoeiKMot7O7u4vV6dTXkNtDRVldXF1kN0hpLSkoiOzub5eXla5/ndruZm5vjS1/6EicnJ3R0dNDQ0KCrL9ShkJycTE1NzdliFs+ePWNqagqn03nt76lh868KzJk4PDyM2+3WOpywSUpKIi0tjdXVVa1D0TX1TfSc+fl5LBaLrko8d3Z22NnZoaKiQutQIk5WVhZCCLa2tl55LNB79PTpUzY3N2lubqapqUlVRAWZEIK8vDw6OzspKipibGyMvr6+KxsspqamsNlsqlf0AoPBQGNjI6Ojo7pKNHJzczk6OrqxgTDchNEQ9JuiRDMp5Vk1j57Mzs6SlZWlvhhfwmazsbCwgMvleuUxl8vF9PQ0z549A+DJkydUVlaqOdmCzGQyUVZWxuuvv05CQgLd3d2Mj49zcnLyynMDw+bVkK1XJScnY7VaefHihdahhFV5eTmzs7N4vV6tQ3mJnnKwyI0szNxuNysrK5SUlGgdSti4XC5evHhBY2NjZJXVRZCamhomJyfPTlKBCp5nz55xcHBAe3s79fX1qicuxIQQZGdn8+jRI2w2G9PT0/T19eFwOM6ec3BwwOHhIQUFBRpGGrmSk5MpLS1lbGxM61DCJjCxp6rqUZTItrOzQ3x8PKmpqVqHEja7u7tsbW1F5uqAEcBkMmGz2Ziamjq7z+v1Mjc3x/Pnz4mLi+O1117DarXqqoNWC4EpCV5//XXS09Pp6+tjYmLipY4jNWz+eoWFhXi9Xl1VuMTHx5Obm8vKyorWoeiWOjP6LS8vY7FYdFUJ8OLFizvNfaJHiYmJZGdns7S0REZGBhMTE8THx9PW1kZCQoLW4elSRkYG7e3tbG9vMzw8fDYePzKWU5ca7PP2x1tUVMTGxgZra2vk5+eHMKbIkZmZyeTkZOTM1SMEQg3rVJSXzM3N6aqax+12Mzo6SmtrqxrmfY3CwkIWFxc5ODjA4XAwMzNDQUEBT5480VW+HimEEBQUFJCXl8fy8jLPnj2jpKTk7Gftl1OP3BwsMIz++fPnpKenR0Y+EgZlZWX09PRQVFQUGUUFOsvB9HOk1/B6vSwvL1NcXKx1KGFjt9sRQuhqFvj7KiwsZHJykrGxMaqrq2lqalKNPBEgKyuLzs5O0tPTefr0KS6XS+PeYC0SjLvtN5BoTE9PX1p6HavKysqYm5vTOgzAlxIKowj6TVGi1eHhIVJKXVXzvHjxAqvV+uBlrGOdEIKioiK6urrY3t6mo6OD8vJy1cijMYPBQElJCU+ePOH09JS/+7u/Izs7W+NGy8jPwcxmM3V1dQwPDyOlVvGGV1xcHOnp6WxubmodCqC/HEw19ABra2tkZ2frpvTz6OiIubk56urqtA4lonm9XmZmZhgaGsJisZCSkqIm+Iswgd4lk8lEdnY2T58+vXROpdCLngt2XFwcNTU1uko08vLy2NnZuXEiSUVRwm92dhar1ap1GGGzsrKC1+tVHW03cDqdDA4OsrGxQWZmJrm5ubpaETcamEwmCgoKSEpKwul00tPTw9HRkQaRRE8uk5mZSUZGBrOzs1qHEjaR1NmmN7pv6JFSMj8/r5tlh71eL8PDw9TX1+umYes+9vb26OrqQkrJkydPqKmpOZsDRoksc3NzFBUVUV1dTXt7OwsLCwwNDYXxS30kJBh3iyE7O5u0tDTdXHiFEJSUlLC4uKh1KG8s7Rnsm6JEoZOTExwOB1lZWVqHEhbHx8fMzs5SX18fGcMYIpCUErvdzvPnzykoKDibC3FqairiJnXVOykl4+Pj1NfX09TUREVFBQMDA8zNzYXxbxV9OVhFRQUbGxu6WQk1OTkZk8kUGcersxwsciMLk+3tbZKTk3UzFGdmZoasrCwyMjK0DiUieTwexsfHGR8fp7GxkYqKCgwGA0IIampqGB8f100VRDQ4PT1ldXX1rKE2ISGB1tZWcnNzef78Oaurqzr6e93tOCsrK1lfX2d/fz9E8USWoqIiVldX8Xg8WoeiKIrf/Pw8paWlumj0kFIyPDxMXV0dZrNZ63Ai0vHxMb29vezs7NDZ2UleXh7gu7bn5+ezsLCgcYTKeevr6yQkJJxVu2dmZvLkyRNcLhfPnz/n4OBA4wjD6fY5mB5XQrXZbLqqYooUum/omZub003J8P7+vlrh4RpbW1s8e/aMxMREHj9+/MpS6RkZGcTFxbGxsaFRhMpFk5OTVFZWvjQuPDCc6/Hjx2xubtLX1xfC+WgirRHp7onGyMiILnpJjUYjBQUF2O12jSMRulraU1Gu4na72dzc1M1KifPz86Snp6ul1C8RqK7v7+/HZrPR0NDwSmNYWVkZdrud09NTjaJUzvN4PExPT78yibrBYKCqqor6+npGR0dfWrk2+KI3B0tOTqakpITJyckQxhM5MjIycDqdGg3tO09fOVjkRhYGgZZmPUwAKKXkxYsX1NfXqxUeLvB6vUxMTDA7O0tbW9u1vYvV1dWqfDhC7O3tcXJyQm5u7qWPx8XF0djYSFlZGb29vayvrwc5gkhLMALulmjk5eXpZghXSUkJS0tLOqryUpTItbS0hMVi0UVOcnJygt1up6KiQutQIs7p6Sm9vb2cnJzQ2dl55TA+o9FIeXm5br4YR7r5+XkKCwuvnDcpNTWVzs5OzGYzz58/x+FwBDmCSL2O3z4ui8XC4eFhZAxpCgOr1aqbfDNSxP7V9Rp6quZZXFwkIyNDF41ad3F8fEx3dzcmk4mOjo4blzuMj4+noKCA+fn5MEWoXCYwLry2tvbGkv/s7GwePXrE0tISY2NjQWqki9QE4+5sNhtra2sR0MsSenFxcWRkZGhblSdAGETQb4oSTfS22umLFy+oqalRq0VdsLW1RXd3N2VlZbd6ffLz8zk+PtbNkONIdXJywtra2o3zmwohsFqt1NbWMjAwEKSKWkms5GBCCOrq6njx4oUuOpBzc3PZ29vTdmEMneVgum3oOTk54ejoSBcTAJ6enrK0tKR6ki5YXV2lr6+P6upqysvLbz1HQFlZGSsrK6p8WEMrKyukpqa+MrzuKnFxcbS1tZGQkBCEnqVoSDDuNoSrpqaGsbExXVS6RMLqD3oqG1aUy6yurpKbm6uLRSHW19cxGo1kZ2drHUrEOF9J/ejRI3Jycm71e4H5EvVyvYpUk5OTZ3NY3kZ6ejqdnZ1sbm4yNDT0gHlpouVvfvs4U1JSyM7OjozFIkIssDCG1nNt6SkHi9zIQkxPEwCOjY1RWVmpi4TqNrxeL6Ojo6yurvL48eM7T0xtNBqpqKhQ5cMacbvdzM7O3rnh8mLP0srKSogijBS37/XKysrCbDaztrYW2pAiQFJSEnFxcezu7modiqLokpSShYUFXax26na7mZqaoqamRutQIsbFSuq7LpmelpZGSkqKLq5XkWh3dxen03nlsPmrmEwmmpqayMrK0slEzbdv7CkvL2d5eTmE80lGjsLCQtbW1tTCGGGiy4Yel8vF1tYW+fn5WocScpubm3i93rOVC/TO6XTS3d1NcnIyLS0t9175Ii8vj5OTE1U+rIHZ2VlKSkqIi4u71+8HepZWV1eZnJy8Q69gtJYL3y7mmpoapqendbEChKarPwgBhhDcFCVKbG1tkZKScucv+NFoenqakpISXRzrbezu7tLX10dVVdWdKqkvqqysZGZmRn1ZDDMpJRMTE9TU1NzrbyeEwGKx0NTUxPDw8B3nTozd/MtoNFJdXc3Y2FiI49Ge0WiksLBQu4UxdJaD6bKhx26362ICQI/Hw8TEBHV1dVqHEhEODw/p7u6mvLycsrKyB1VzqfJhbRwfH7O5ufngeR1MJhOtra1IKRkYGLhF40bs/43j4uIoKyvTRaVaeno6LpeL4+NjrUNRFN1ZWFjQxfyIBwcH7O3t6WYeopusrKwwNjZGW1vbg1cei4uLw2KxaD4MV2/uOmz+KikpKTx69IiFhQVmZ2dvkUfHfg6Wk5ODEEIXK/vqcWEMIcRbhRDjQogpIcS/ueTxfyCE6BVCuIUQ3xKs/cZ2S8clpJTY7XYKCwu1DiXkZmZmKCoqIiEhQetQNLexscHQ0BDNzc23Hgt+k8DFbnV1NSjbU242Pj5OdXV1UBpphRBUV1eTm5tLT0/PNSWzsXAhut0xWCyWsy8nsc5isbC8vBz2/Qp8771g3xQlGpycnOB2ux/8RTHSBVY6raur0/3nU0rJ1NQUKysrPHr06MZFL26rpKSE9fV11WAfJm63m7m5OSorK4OyPbPZTHt7O0dHR4yMjFwzGXG052C3j7+2tpbJycmYr6w2m80kJydrkmtqkYMJIYzAB4GvBeqBfyKEqL/wtAXge4HfC+bx6q6hZ39//2yOhljmcDjY2tqitLRU61A0JaVkfn6eubk5Ojo6gp5cVlZWMjs7q8qHw2B7exspZdAntLRYLFRXV9Pb23vJRSfaE4zzbj4WIQT19fW6qFTLz89nbW1Nm+PUUdmwopxnt9spKirSOoyQW15eJj09XfcrnXo8HgYHB/F4PLS1tQV1rkiDwUBlZaUuqlAjwezsLMXFxfee8uAyBoOB+vp6UlNT6enpuWQ1pljJQ253HPHx8RQXFzMzMxPieLRnsVhYWlrSZufhz8E6gSkp5YyU0gn8PvD280+QUs5JKQeBoC6/pruGnuXlZSwWi9ZhhNzk5GTQKh+iVWAs8f7+Ph0dHSFp3AuUD2s234dOnB8XHgqZmZm0trYyOjrK1tZWSPYRGW5ONlJSUkhLS4v5SjWTyURGRgbb29tah6IouiClZHV1lYKCAq1DCSm32838/LzuVzp1u9309vaSnZ197zldbpKbm4vb7WZnZyfo21beEKxh85cRQlBWVobVar2hujra3W6ex5KSEra2tmK+Ui0rK4v9/f2Yr17yswDnl1Vb8t8XcrpqBfB4POzs7MT8Epe7u7t4vV5dLB1/lUDZtNfrpbGxMaQNXiUlJWxsbMT8SVlLS0tLZGVlkZSUFLJ9JCUl0d7ezuTkpH+CwFjpSbro5uOqqKhgdnb2mlLq2KDJ8C0BwiCCflOUSLe7u0tqamrMrwA6Pz9PcXFxzB/ndZxOJz09PZSUlIR8jqKamhomJiZivgpVS8EcNn+V3Nxcamtr6e3t5ejoCL3mYEIIKioqmJ6eDlM82hBCnFVWh3fHIcvBcoQQ3edu3x/eA7ucrhp61tfXycvLi+nx0lJKJicnqaqq0joUzXi9XoaHhzGbzdTW1ob8720wGKiqqmJiYiKk+9Erl8vFwsIC5eXlId9XfHw8HR0dzM3NxnxFy3Xi4uLIy8tjcXHx5idHsfT0dBwOBy6XS+tQFCXm6aGi2ul0sra2RklJidahaOb09JSenh7Ky8vDUr2VnJxMRkaGdqv4xLhQDZu/TGZmJo2NjfT393N46Aj5/iJVbm4uR0dHHB4eah1KSBUVFcXS53ZTSvno3O23zz22DJy/KBT77ws5XTX06CHJ2NzcJCEhQbfjwr1eL4ODgyQnJ1NVVRW2Rr2cnJyzijEluGZmZrBarWHrHTWbTbS3t7O4uKTJZL3hcXNPmdVqZWlpKabLaoUQFBQUhL9RT4jg3xQlgrndbvb39x+82lKkC1yv9Dps/vj4mN7e3rOFDsKlvLycubm5mL5eaSHUw+Yv2SNpaak0NzcxODjI/v5BmPYbbjdX9VRVVcX8/FOJiYkIIXA4wtyoF/4c7DlQJYSwCSHigO8APhHy40RHDT3Hx8dIKUM69ENrUkqmp6eDNiN+tPF6vfT395OZmRmW6o+LVPlw8DkcDnZ3d8M4eafvb2cymWhvb2N1dY2FhVitarn+fWoymSguLo755WvD36MU/JJhNXRLiXSBuXliuaL6+PiY3d1dXazqepmjoyP6+vqoq6sL+xQJZrOZ0tJSXUxiG07hGDb/hjdykpSUFFpaWhgeHo7hVUCvz8ECjeK7u7thiEU7Fosl5nMwKaUb+CHgL4AXwB9IKUeEEO8XQrwNQAjxWAixBHwr8GEhxEgwjlY3DT16WOlhZWWF9PT0oC1dGU2klAwODpKdnU1ZWZkmMajy4eAbHx8P2SSONzEajbS1tbKxsY7dvhL2/YfH9YlGYPnaV1fCiB3x8fGYzWYODmK151BRtKeHHGxqaoqKioqYbsy6yunpKf39/TQ0NJCRkaFJDMXFxWxvb/vnd1EeKpzD5i+TnJxEW1srIyOjMTyE6focLFDVE8sdyHl5eayvr8f0MQJIKT8ppayWUlZIKf+9/773SSk/4f/3cyllsZQyWUqZLaVsCMZ+ddHQI6VkbW2N/Px8rUMJGa/Xy9zcnC5XeZBSMjo6SkpKimaNPAGqfDh4NjY2zlZGCo9XLzIGg4GWlhaWlhbZ2NgIUxzhdvXF1WAwYLPZYn5SwOLi4vAN0xP4rrzBvilKhHI4HBiNRhISErQOJWQODg44OTkhJydH61DCzuVy0dfXR01NDenp6ZrFIYSgurqa8fFxzWKIJdPT02EcNn95HpKYmOgfxjUUwwueXJ2DpaSkkJCQwObmZhjjCS+j0UhmZmb4VrzVWQ4WwaEFz/b2Nunp6TG9AsLi4iL5+fkhWUI80k1NTWEwGCKikctsNlNWVhbzX4xDzev1MjU1RXV1dRj2dv2SlyaTidbWNqanp3U5B1NBQQF7e3sx3Uuak5MTviRDUXRGD/MjBhbB0Fs1j8fjoa+vD5vNFhEr2mZlZSGEUOfzB3I4HOzt7YWpCu/6So6UlBTq6+vo7x94cHWxvMd/WqusrGRqaiqmK140WQFVJ3TR0BPrSYbH42FpaUnzahYtzM3NcXx8HJbVtW7LYrGws7MT/snFYsjCwgJ5eXlh6AG+3YUzLs5Ma2srL16MBXVywEhIInyujkMPS30aDIaw9sQLIYJ+U5RI5PV62djYIC8vT+tQQmZ3dxchhGZDlrTi9XoZGBjAYrFEVMV8YL5Er9erdShRK3zD5m+XA2VkZFBVVUVfX9+tKuYjtdHmalfHlpiYSGZmZkyvBJuWlhbWzkQ95WAx39DjdrtxOByalpOGmt1up6CgIKYrli5jt9vZ3t6msbExoj5kQghqampU+fA9OZ1O7HY7Vqs1xHu620U/ISHhbHLAYJYQR04icvW+c3JycDgcnJychDGe8IrlzgBF0crW1hZZWVkxvQrV7OysZvOYaEVKycjICJmZmRF37kxMTCQnJ4elpSWtQ4lK4Rs2f7d8JyfHNwdnf39/WBvxwtdgdPV2rVYr8/PzMVvVI4TQ7ST2oRa7V16/zc1NcnNzI6ohIJiklCwuLlJSUqJ1KGG1u7vLwsICzc3NEZlAZmZmYjQaY3pcbahMTk5is9kwGo1ah/KK5OQk6uvrGRgYfFCv0nXJgrYlxJfvQwhBWVkZ8/PzYYhBGykpKeHbmUEE/6YoEWhtbY2CggKtwwgZh8OB2+2O6c7Ey8zPz2M0GrHZbFqHcimbzcbS0lJMLyQQCuEdNn93BQUF5OTkMDb2akfqfXIlifel2+1/L1R52eXbS0hIIDk5me3t7SDvL3KE9Tqhoxws8r4hB9na2lpMlwyvr6+TmZmpq7l5Tk9PGR0dpaWlJaKrmKqrq5mcnFTlw3ewv7+Pw+EIwwn//hfnjIx0SkpKGB4eeaV3JdQNM1qWIufn57O5uakmGn8oga6SDEW/pJTs7e3F9JCm+fn5MFSfRpbNzU02Njaora3VOpQrmUwmrFZrTA85DoVIGzZ/mbKyMtxuN4uLi7foOPNee3vo832/E56czGazMTs7G7Ltay1sk/XrLAeL6YYer9eLw+EgNTVV61BCRm9JRmBMeG1tbcQvI5+YmEhubi6Li4tahxIVpJSMj4+HYb6lh1+ILZYiEhISmJ2dDUov0m0TivC4fHJqg8FAcXGxej8rinIru7u7pKenx2xF9enpKXt7e7paacvhcDAxMUFLS0tEVlOfV1hYyMHBQQwvzR1ckTps/uXflCCgvqEOu93+ygIZt8uj5B1uF38zHHna5a9PSkoKBoOB/f39EO1XiUWRfZZ+oO3tbTIzM2M2ydjZ2SE+Pj7iGzyCJbCMekFBAVlZWVqHcytWq5Xl5WVVPnwL6+vrJCUlkZaWFsK9BK+3paq6ku3tHdbXL192PVyNOOEsIbZYLNjtdlWl9kB6mghQ0a/19fWYrqheXFyktLRUN58/t9vN4OAgjY2NUVFFHpgvcWxsLGbnNgmmyclJysvLQzxs/n5/h4s5jtFopLmlmRcvxjg+Proit7pd402wBScnu/x3rVYrc3NzD9iuAvrKwWK6oSfWk4y5ubmIHR8dCoFKgmiaj8hkMmGz2ZiamtI6lIjm8XiYnp6msrIyhHsJ7gXeYDDQ3NzE9NQ0jsPgr7B2n0ai4Df4vLwtk8lEXl5eTK/+oCjKw0kp2draioglt0PB4/GwtrammwlEpZQMDQ1hs9lC3BkTXOnp6cTHx7OxcXmHjOKzv7/P0dFRCFdPC34jS0JCAnV1NQwODuPxeIK67Tdc31B081Cwh+Rkr/5eZmYmx8fHQV0QRIltMdvQI6VkZ2eHzMxMrUMJCYfDgcfjiaoL7kPs7+9jt9upr6+P6JbTyxQUFHB4eMjBQfCW5Y418/PzFBUVER8fr3Uo17rYU2OOM9PY1MDw8Ahe712rdm5fLvzyb91+zHhwvLyd0tLSmF79ISwMIbgpSgRxOBwkJiZG5KT6wbC8vExhYWHED18KloWFBRITE6NyYu3q6mqmpqZUJeoVAsPmw7Oc+t1dlssE8p+MzAwKCvKZmpzmqjzqNkPlb3sLbPGmhp/bHMNtj/68wMIYCwsL99yeAugqB4vg0B5mf3+ftLS0mL0Iz83NUVZWpnUYYeHxeBgZGaGxsTEq/57nl1tXX45fdXJywtraGqWlpSHcy8Ne9+saTlJSk8kvyGNycvKK/d6nfPj2vxO63qTLxcfHk5qaytbWVlC3qxdCCIQh+DdFiSTr6+shrA7QlpSSpaWlqKoufoiDgwNWVlaoqqrSOpR7iY+Pp6CgIKZXjXyItbW1EA+bD85wLd99F3MdSUmphaOjIzY3t156zvnn3rQC6m3+u7jtl4/v8salm47nPvLy8tja2sLlcj14W3qktxws+r4139L6+jq5ublahxESTqeT/f193UwAOD4+TnFxcXiXPw6y9PR0EhISWF9f1zqUiDM5OUlFRUUIG/EeNvHfTas5AJSWlXB46PA3ftx+Ir+7T8oc3rHmL+/3DWqcuKIo19nY2IjZHGV9fZ2srCzMZrPWoYScx+NheHiYxsbGqK7OslqtrKyscHp6qnUoEcXj8TAzMxPCRry75SlXzW9zdeOK74t7XUMNk+NTnDpPXtmORIL0Pux2yTbDt2jGy/mewWDAYrGwvLwcpv0r0SxmG3o2NzdjNslYWVmhqKgoIkssg219fZ2TkxOKi4u1DuXBqqqqmJ6eVuXD5+zu7uJ0OkPUKPuwxpDryoUvXuCFgIbGWibGp3A6Xdc01ATb7cuGgzk5YEpKClJKNU78voQI/k1RIsTJyQkGgyEqJuy9j+Xl5ZjISW5jYmKCoqKiqO5oA9+X48rKyisqb/Vrbm6OoqKiEH1W797I8+p9VzfwnM+z4uPjqKi2MTo8jveSRppQuS6+yx9/SD72xvOLiopYWVlRowTuS0c5WEw29BwdHREfH4/JZNI6lKCTUrKysqKLCQBPT0+ZnJyksbExJhq14uPjKSwsVJUQfqEdFx7+i198fDwVlTZejLy8wsdljT63LRO++Ps3V/m8/DuXCVZjj+pRUhTlMrG8EMbJyQlutzvqGz5uY2Njg+Pj4xAPqw6f3NxcTk5O2Nvb0zqUiHBycsL6+nqI/r7hz8FycrNJSIxneWnl5Uik51Y517X/Sc+VFT6+f181jw8vPX7RfRt7zGYzycnJ6r2s3CgmG3piOck4ODggMTExZnvKzhsdHaW6ujqmjrWsrIzV1VVVPgzY7XbS0tIiLmG+W9nwy71LuXnZmONMrK2sv7StqxpxLisPvhjHbRp/Xo3rqrivPsbb8/1efn4+6+vrqkfpHvQ0PlzRn1jOwex2O0VFRVqHEXJut5uJiQkaGhpioqMN1HyJF01MTFBZWRkRc19eVc1z/qdXK3leHZ5VWWXFvrTC0fHxuUcuGxbvvuH26u94OddgdK7h57IhXdc1+Nzm2G96tUB1tj2EnnIw7T/dIRDL8/MsLS3pIslYX1/HYDDE3N9RlQ/7uN1u5ubmQrScevAm/vPdf1kFzcuPn5/wr6K6nLnZBZwu543jvi9LVO70/EtieCPG65OLQLz3ZTQaSU9PZ3t7+97b0CUBGETwb4oSAVwuF263m8TERK1DCTopJaurq1G58tRdTU5OYrVaI34lzLtKTU0lJSWF1dVVrUPR1O7uLi6XK4TD5u/y7Nt0rL3awOO78+X8yGA0UFFdxsTYNF7pQeIGvIAXiefc7ab/3nhu4Pd5pfHn8rzt6gafN44vGLKystjb28Ptdgdle7qhsxws5hp6XC4XUsqYuziBb9K0nZ2dmJ17KMD9/7P357GRbPt5IPidE1vuyX0pklXFIlnbXd+rt+jJ05aXsefZbvhZM5b1PMDIAjQYDDAau6GZP9oDo9FowIZkWIJbsGSobbesNjAy7JaNMWaMkbvbsuV5fr73vrvfd28trIXFYnFn7pmxnjN/nIjIiMhIMkkmmQvzK0RlZmRkxIkgmfnL73zf97NtrK+v4+7du70eyoWg1/LhX//1X8fXv/51PHjwAD/3cz8HXdfxB3/wB/jOd76Db3/72/gTf+JP4OnTpwCAarWKv/gX/yK++93v4vXr1wCAf/JP/glSqRQ+//xzf58PHjw4VUeL58+fY2lp6QLCLM9O8rSu68wb7r3e24ciU9xYXsTTx89Cz7XO+Tg4dsYo5t9leM47w2hGaYQRRmjF4eEhJicnez2MC0GxWEQ2mx3KWIAgSqUSqtXq0E4qrq6u4vnz53AcpyfH73UNFrTNdx9nJ3lOqrlC2wdIFQYnUE/ZGJ/IQlEk7O8dxDzvnGJp1mXN2swjfrqLs6h6CCGYmZkZNXkZ4VgMHdFTKBQwPj7e62FcCDw59LDIaNvh6dOnWFpaGkqyDuitfHhrawu/+Zu/iR/84Af48MMP4TgO/vk//+f4q3/1r+K3f/u38d577+Fnf/Zn8cu//MsAgN/93d/FL/zCL+Dv/J2/g9/8zd/097OwsIBf+ZVfOdMY6vU6Dg8PL6A1bXdJnvB+wwRP8LUtM0sAZuem0WjoKBXLZxrTyYNu7QIRN744G1dcMOAZB4F8Po9arTZq83lKEEK6vowwQj+gUCgMLdGztbWFhYWFXg/jQsE5x8OHD3Hv3r2hfV9RVRULCwt4/vz5pR+7H2qw169fI5/PX4BtvvNaIk6VHN5PGxVPhODhAbUN3O0AYOX2Dbx4ugXbvigyz7N/tU7QBeuz4DkcN1nobX+6eoyPJtvOiKtUg42IngHC1tbW0M6weKhUKiiVSkPf0SKbzSKbzWJ7e/vkjbsM27bRaDT82/n5eRBCUC4LUqJcLvth347jgFIKSmmIlPqzf/bP4quvvsLjx49PffzHjx9jbW2tr98YzwMODhDg9r0VPHr4FA6L83s35cTR5XifeHubV3vCp7X7WLfIHkKAubm5Ky+DH2GEEQSKxSLy+Xyvh9F12LaNcrk8tPWlh5cvX2JiYqLvsvO6jaWlJT9s+rLRyxrMs82vrKx074T6DBwcskqxcGMGz9dfumviVTrtlqj6J7iPoMKnnaWrXV3mjTA83rPXY8lkAoQQ1Ov1M1+vEYYbQ6c/LRaLQ/kG1mg0wDlHOp3u9VAuDJxzfPXVV7h79+7QkgBBrKys4IMPPsDMzMyFScEty0Kj0YBpmrAsC4wx/NzP/RzW1tagaRr+yB/5I7h79y7+5t/8m/je976HZDKJXC6HP/zDPwQAfP/738df+St/Bbqu4x/9o3/k75cQgl/6pV/C3/7bfxv/8B/+w47Hc3h4CM75Bcz4XqSaJ7w+9Boeno0JbpdMaZiaHsOrl69x/ea1tsc7Hg4Imn8L4Vc3eXoC0pxFItRfx8FA/O04ENpX8DkxtuCxOsW1a/P45JNPL0ChNcQYuimWEUYQnzeSJEGSpF4PpevY3d3F3NzcUNcmuq5ja2sL3/72t3s9lAsHpRRra2t4/Pgx3nnnnQs5Buccpmmi0WjAsiw/vypag927dw9/62/9LfyFv/AXkEgkkM/n8e///b8H0P0a7NmzZ7h+/Xrf2ObFK+PzeJpr4lUyQNw6bw3D7LVxfPajA5TLFWRyicgxTxpv+O/c296rkQioS/wQt45q1mre1BoBBQnUZeGarHv12MLCNWxtbWFtba2j7UfAlarBhorosW0bnPOh9E9fhU4Pu7u7yGQyyOVyvR7KpUBVVSwuLuL58+fnfoNmjKFUKqFcLqNSqaBarYIxBlmWkUwmoWkaZFlGvV7HH/zBH+Df/bt/h1wuh1/8xV/Ev/yX/xK///u/j1//9V/H7du38du//dv4+Z//efz1v/7Xkc1m8ff//t9HLpdrIRl/9md/Fr/yK7/Scbt4xhiePHmCt99++1zn2orukDztQpdPS/AEi4+l5Xl8+N6PMXtNdOPqbNzRAgOBAiBcTABewREoQiKEjzeeZnHRPEa0uDgLNE2DqqqoVqtDPws86CCEfBfAfwtAAvAPOee/HHn+jwL4uwDeBvB9zvn/eOmDHGFgUSgUMDY21uthXAi2trYu4LOrv7C+vo7V1dWhJOriMDU1hZcvX3bFCWBZForFIiqVCsrlsq+w0DQNyWQSiqJAURTUarWWGuz3fu/38G/+zb/B3/27fxerq6v4nd/5Hfz8z/88/sbf+BvI5XL4B//gHyCfz7fEGZy2BqvX6zg6OroAIu98uTzR/fiqGH81QzuCp2mJQuS1DCDA8t15PH+0hfsPbrgkbWdj9SoqD6SldgoSMR5pE67TxCvciTfOQjVZXD12VszMzODZs/ewuro61ET0CGfDUDEipVJpaIuMvb09fPOb3+z1MC4MjDE8e/YMDx486PVQLhVLS0t47733sLi4eKouJZxz1Go17O3t4ejoCKZpIp/PI5fLYWlpCZlMJrZY+73f+z3cuXMHb731FgAxW/Tee+/h2bNn+Jmf+RkAwC/90i/he9/7Ht555x2/aFlfX0etVkM2m0WhUPBJpL/21/4afvVXf7WjMW9tbWFiYgKpVKrj8zwZl0zy8FbSJ0jwREkfQoHFGzN4+fw1Vu4sxRznZHgzR+L+xRbgZ1X1zM3NYmdn54K6qA0beuPnJoRIAH4DwJ8C8ArAB4SQf8U5/zKw2UsAPw/g/37pAxxh4FEoFDAxMdHrYXQdhmEAABKJxAlbDi6q1Srq9frQdTo9CXfu3MHnn3+Ob3/726d6X2aMoVAo4ODgAIVCAYQQjI2NIZfLYXZ2FqlUKnZ/x9Vgf+kv/SUAgoD63ve+h3v37qFcLqNUKmFjYwO2bWNsbAzlctmf1D5NDfbo0SPcvn27i58/5++uFd1XO5InWmd5BE+L8gfh7dNZFbJKUTwsIz8ZdUS0q8ciamkAHA4IoSAX+LX5rBNvogNqbqi/A3cX/Z2p020MFdFzdHQ0lP7per0OVVWHUqnkYWtrCzMzM0MbwNwOlFLcvn27Y/lwrVbD69evcXBwgGQyienpabz55psdF6BLS0t4//33Ua/XkUwm8Qd/8Af4+te/jn/xL/4Fnjx5grW1Nfzbf/tvcefOHaiqisnJSd9mxTlHpVKBbdvY39/HBx98gJ/6qZ/Cr/7qr6JWqx17XMuy8PLlyy7PJF0+ydNC5HTwoTw7P4mPX34FvWFAS55PLi2KIO+43qyRN34Kf/bIU/YQ6pM37Wxc3bBwTU1NYWPjoxHR0wm81p6Xj28BWOecPwMAQsg/BfA9AD7Rwzl/4T7XD63dRhgwDKt13muEMczwPv+v0hcgAEin0xgfH8fW1taJ2ZCccxwdHWFnZwfFYhHj4+OYnp7GyspKx/X5aWqwZDKJZDKJ2dlZACKvp1gsolarYXd3F59++in+9J/+0/i1X/s1VKvVY497eHgIQkgXidgLJnl4VLUTrb84Op04u746jcefv8abE/Hk22nA/Em3oIonmL3j7Z+CuPWa/zhQkwVJpmb9Fa7TTlOLie5buyOipxP0rgbrCYaKOSgUCrhx40avh9F1DHuR4TjOBZAAg4PJyUm8fPkSR0dHsR/CjuNgd3cXr169gizLmJ+fx/Ly8pmIv29961v46Z/+aXznO9+BLMt455138Au/8AtYWFjAX/7LfxmUUoyNjeG3fuu3Wl5LCEEul8P09DRmZ2fx5ptvYnd3F3/uz/05/L2/9/dQKpXAOY/9IF1fX8fNmzeHjqyML0DEPf8xAa6vzOHF0y3cftN7f+r0e7RQ8wQ/7IXCJ0jueOu9AOYA4dPWH94cY7S4EM+cjuxRFAWyLKPRqLvKtKvzITpAWACwGXj8CsDVfNMdoesYZuv83t4e7t271+thXBiKxSI450M5UdoJVlZW8N5772F2djY2u8YwDGxtbWFnZwf5fB7z8/O4f//+mUiD89RgkiRhcnIS8/PzmJubw/LyMra3t/Fn/syfwW/8xm+0DZa+ONt87xEkTUJKnwBRpCUlZHIaDnZLmJzrJOfUI3NooEoifhg2AQFIcwotSPg0SRrHfz5o44rWZGLbaP11erJncnIST58+RTT7Z4QRyGW3d+4WHjx4wH/wgx/4jx3Hwfvvv4/vfOc7PRzVxeD999/HO++8M7Rql2fPnkGSpKEk6TpFvV7HZ599FpIP27aNzc1NvH79GjMzM6e2d10WOOcoFovY3NxEo9HA8vIypqen/fOoVqv48Y9/jG9961tdmi08T+jfybNKwfXREMA4m1Zz+zglkLjPOMMXP3qGW/cWkM4kOpqJIjHy4aBiJzgLFNyeBLziBM1iAoSG9hVWI8WtQ0cFhoeXLzfBOceNG9cxqIVGMpn8kHP+jYs8xoM33+Xv/d7/3PX9KnenNwAcBFb9d5zz/857QAj5iwC+yzn/P7qP/w8Avs05/8Xovggh/xjA/3uU0TNCO0RrsIODAxwcHODu3bs9HFX3Yds2Pvjgg6GsLQHx+f2jH/0Id+/eRTab7fVweoZXr16hVqvhzp07/rp6vY4XL16gXC5jYWEB8/PzfUlkMsawu7uLzc1NaJqG5eXlUNbly5cvYRhGF8N6L1DN0yZ0OWrXirNpeQRP3HOWaePhR9u4/615oAPBKiXCJh+tk5o1lbglhLas97YUr42+JlyTRSfx0PK4eeST8PHHn2BtbW2gsxIHvAa78LGfBf33jnVGlMvloWzpaZomOOdDS/JYloWdnR38xE/8RK+H0lOkUilMTExga2sLc3Nz2NjYwM7ODhYXF/ETP/ETfR2OSAjB+Pg4xsfH0Wg08Pz5czx9+hS3bt3C9PQ0Hj16hDt37gwdyROn3mkeI6LyIcD1tVlsrG/j3rvX/dmmdiCkmcsj9hHu7MDRnOkJziDBLya8cQNeQYKQbFiM8bxBzEHMzEzj88+/cIme0axSD3BwQpGxBSDYGm3RXTfCCOdGNwJt+xEHBwdDnVtzeHiIRCJxpUkeAFhYWMD777+PWq0GSinW19f9iat79+71taWNUor5+XnMz8+jUCjgyZMnIIRgbW0NiUQCm5ubXVTMn4/kidtXHMlzXCaPeOzEqnfitmfcAWQHuSkFO6+OMLlw8vepJtEj+Y8pkSAU1oKQoZCEir1F4SNeCQQV2EErV7Mm45EJuPNgZmYae3t7yGTSGNVfI3gYGqJnWPN59vf3h7rI2NzcxNLSEii9Qr3u2mB5eRk/+MEPsLGxgcXFRXznO98ZuOuSTCZx//59GIaBJ0+eYH19HYlEoku+4e6pD0/bzrOdR9y7304+DMCfYcrkVTgOQ7VSRSpzfKHBuUfyiJ8/JZfzVn0eC1cikQBjDizLcuXvI7KnLXrzpeEDAGuEkGUIguf7AP73vRjICMOHYbbO37x5s9fDuDA8f/4c9+/f7/Uweg5CCG7duoUPP/wQqqpidXUVk5OTfU3wxGF8fBwPHjxAqVTCV199BdM0sbS01CUl0vlqsE7Cl4P1Vvgxd/NxmkQO506I3BHbOz65w7gDDse/P7Yg4cXHVWRmGUggo8WrtwhpTqhSn+ChLslzWWr6+Lqpk1psenoaH3/8CW7dWm67nxFcDNjf9XkwWN8ij8GwziYNcz4PYwzb29tD3za+E1QqFXz00UfIZrMYHx/HjRs3Bo7kCULTNNy/fx+MMTiOgy+//BK2bZ9jj+ctME5u5xnaNqa7Vjdw7cYEtjcKp34ddwsWDgcMTmBGSzxmwdktvxDyCqDA40hb+KgqSdw7ew7v1NQ09vf3gyM/876GFYQAhJKuLyeBc24D+EUAvw/gKwD/jHP+Y0LIf0MI+fNibOSbhJBXAH4GwG8RQn58gZdihCGB4zhwHAeqqvZ6KF0FYwyVSmVo1S6lUgmyLCOd7iS3ZHjBOcfOzg4eP34MRVGwsrKCqampgSN5gsjn87h37x4459ja2sLLly9xvqiO07/2VG3UQ921mjXLeeqRKCSZID0uo3Jw+lrUYg1YrAGbmXC45dZeNhgsn0wK1mlejcb8x0FLWSR0uqWzWGtd2glUVQUhxO8SOKq/4tGrGqxXGApFD2MMpmkOXetLx3HQaDQG2m95HF6/fo3Z2dm+tiVdNBhjePr0KY6OjnDv3j1ks1lfPjzoxdfLly+xsLCA5eVlvH79Gu+//z5WV1cHjrhs5xFvPh8jF+bxNq7chIaX6wZ0w4Cqtfu9D3q0A4HJ3IEv+SXNAMCgTas56xN+3uvUxcH9MMBg9weh4onvxOWNvRNlz+zsDNbX1yPk7WhmqV/AOf/XAP51ZN1/Fbj/AYSla4QROsbAWudP+B5UOBLt4oXNwl05RG9lL168wPLycq+H0VMYhoEvv/wSsizjm9/8JhzHwSeffILJycmBnmzjnOPx48d46623kM1msb6+jg8++ABvvPHGwNWWHnECMFfV49VYwUkvLw/RgcNNX8XDuHgNdx9nrtnY/YohMWG1JVI825Zn1/KUPhRSQOEjQSIqKJHAwF2LV/h9gvuVlbDdiyelVguXf56t9dhpg5lF9619LC15H+ND+MY1wqkwFERPtVodyhmXw8NDv7X1sIFzjs3NTTx48KDXQ+kZ6vU6Pv/8c8zMzOCb3/ymX1Tcvn0bjx49wte//vUej/DsMAwDr1+/9sOlFxYWMDU1hS+//BIHBwe4c+fOKQi+7uXyxO03LpPHe3xSEGB4u3ZBgIFZLcIws5TG9ssjLK6OARCFCSWSfws0Cw3PD96kWtwP/xZfuOfzZm5RwWK94R7ZA8Bv9eldgyjZE3ctTyoy0uk06vUGHMe50gTuiRjc7w8jjNCCYrE4lG19YxXV7T5SBux7VL1eh2EYQ/lz6xT7+/t4/Pgx7ty5g6mpKX/99PQ0Njc3B9qKuL+/D1VV/Z/vnTt3UCqV8Nlnn+H69eu4du3aKRRL3bRsxayLVfN49VUrycO4E3rscMtdB5/ksbnlkzv+AgdQHNAERbngIJFn/uuAZt3l3Q8SPAAgU9VfTyFBpk6A8GEgkPzJOcIllwRy3HUSmt1Ww2SP2L59PXaaibeZmWl89dXDANEzQiyuUA02FKc6rNLa/f39gVM/dIr9/X3k8/mhk3p3iu3tbXzyySe4e/culpeXQzNH4+PjkGU5YoEZLKyvr+PWrVuhL/uapuHdd99FJpPBBx98gFqt1sGeuis9bSeNPQvJw4Ky3IAfPCzXdeBwCxbT3aWB/IyM4kEdulmHxRpwuBm6bV10Xyoc3XdULsxCsuG4DhWRgiukPDo/CCGYmBhHoRC1p40kxCOMMKwYiBqMxywnoFAczkgAANjY2BhoIuM8YIzh0aNHePnyJb7xjW+ESB5A5CVubW3BNM0ejfB8YIxhfX29pctWPp/HN7/5TRQKBXz++ecd2unP9tkdX1eE//C8uiuu3gpaoKIkT7DWEfVRs3YyvVrLacB0GjCcanOxa9CdGhJzdZS2CAynBovp/m3DLsNwajAcsZ1h12A5zVrMcKownQYsR9RrJtNhM9O3dHljFucWrM+C6qOgdYtFHp8fqVQKpmnAcZzIM6Ma7KpiKIiearU6lPamUqk0mHLoDnBViwxPTruzs4NvfetbbX++a2trWF9fB2Pd8ydfFsrlMur1OmZnZ1ueI4Tg+vXruH//Pj799FMcHBzE7MFD93J5xOP4a9kaBHgcydMsMryiJY7gEYWH3kLa2MyExQ3kZxXsv67AdIsMk+nhxRHLZeK8/nAPExMTMURPc78jEBDS/WWEEXqFvrMan4HU8UA4B+Ecer0OTdU6t++c4Vi9gmVZKBQKQzuReBwsy8JHH30ERVHw9a9/PbajrSRJWF5exvr6eg9GeH5sbGxgbm4uNs5ClmW8+eabmJqawo9+9CM0Go1j9nR+kqddDmB0cq213mrmDLKYyTSHm25ejgnT0ZuTaU4DulMNEDO6T954hI+tHcFhNmpVAw27BJM1/FvdqcJkTYLoUhGYeDtPNlE+P4ZSqRR3gDPvc7hwtWqwoSB6BmI26ZQwDAOKogy0R7gdvPaVfVUYXgJs28Ynn3wCAHj33XeP7YKQTCZ9+fAggXPeUTv1XC6HBw8e4NmzZ3j58mXcni5ukF34ID0vxudUlHbtE8MRRQETVfeYYLBalD1CghydDWuv6omGIMYheo06mXUaG4tT9DT3cOVBAFDS/WWEEXoAbzKiL2qVE4gWj8Q5bvFQKBYxMT7e8fax4+jTtzuvCUY/fzm5CNRqNfzoRz/C9evXcevWrWPPf25uDtVqFZVK5RJHeH4YhoHt7e0TJ1KvXbuGu3fv4qOPPkKxWIw8ezG/vBwxquJjcXE1mjpTgXVwskCgSRLVXNJIkEi6U3XVPjpsZvk1WlB97at4WlQ94XBmIEx+heus+Hr1uFosXlUd3t+VxhWrwYYio8c0zaGzAA1rFzEA2NrawsLCQq+HcamwLAsff/wxFhYWOj735eVlvPfee5ifnx+Y3+/d3V2kUinkcrkTt9U0DQ8ePMAXX3wB0zSxsrLSu8KzpetBOzWPe99v6ym2jXrFORzYTMi+bW4BABzWlIEz6kBOcJSLNaRyrfk8fnN1IsHhCHjCFTgcfgigRBRwP7sHYByBsGYJcMdMISGa1+Mewfd6twtmPi1UVYHjsGNyekbhzCOMMCyo1+u9m7Tp4DtLWzLmhH0cFQpYmL8Wfj7mbSu6fx79DIvuvw/e+l6/fj3QGYBnQblcxhdffIE333yzo/qEEIK7d+/i0aNHePDgwcCQYk+ePMHKykpHGXljY2P4+te/jk8++QRra2stFrbLQDiPJ9xGnfmVkKfvadrhPUWPzS04zPTrLS+jx2Q6OBd1GIMDh5mBCTHASddgvVoBZg1w0rSwNeuwQOgyFfU3hQmZqrC5BZko4FTsT6aO2EaUWD4k/1dGArgDEC9pkYL4503bviUEs3lOg/Hxcbx69eqYLUY12FXCwBM9pmlCUZSBeRPuFMMqq2WMYX9/H6urq70eyqXBNE18/PHHuHnzZqydqR0kScKtW7ewvr6O+/fvX+AIuwPHcfDs2TN84xvf6Pg1kiTh7bffxpdffhlQAp1/LCfZtqLZPEG7lrf+JJKn6cVmvqrGDwJkll9cAPCLEEAUIoRISE7bKO/KkNINUCLBYk2yhwRCAWUiigyZqnAcExJRwYgDmapukaGi5duI/zkuQv9EOREme+C/inYcBOhdm5NCmfP5PEqlEiYmJo7d7spiuD6uRrjCqFQqvbPOew0GLwDlcgn379wNr+wgiDlI/LSQPsF99Og9oFwuQ9O0gZk86gaKxSK+/PJLvPvuu0ilUh2/LpfLIZFIYG9v71S1W69QLpfRaDRO9d0hmUziwYMH+Oijj8AYw8zM9LnGcJJty98mJpsHMY8BRCxbYZLHchqwuRmotYLPm02yhzNYjrhlTNRuJF1A41ACz5XgcAdSsNsWFR22JCpBpqa/3uYqZKK6JA+DTIVlX+YOOHWJqTZkD3FJLFFdEb9hRnOyTbyYcAZOgh25TleLaZoG07TAGOsPpWU/4grVYANP9AxrPk+xWMTt27d7PYyu4/DwEBMTE1fmzcfzg6+urp5ptmR2dhYvX74cCHviixcvcO3atVMXkIQQ3L9/H48ePcLDhw9x9+7xtq/zoTUIMH6rOJLHaWnpCcBX8US7PdjuDJLDW8kem1uQshL0FxIMWweI09LhAYBQ8MCERFXYjgnZJXkkqoI5DDJVwJkDySWDJJfcAZwWsidYWPidHoJTUJwBpDudsjzpcHuiZzSjNMIIw4BKpdIb9XEb0uVYBU+HpJBhGpDlC7bO9+gtcGtrC4uLV6cjT7FYxFdffYWvfe1rSCaTp3792toaPvzwQ0xNTfV1J0nOOR4+fIh79+6dun5SVRUPHjzAxx9/BIBfyCRz+8DhYACzd5/7k2fitceTPOK2qZz21jHuwLB1MM5gOyYc7sB2xHaMOaCpF9AOV1HTNkAJBeMM1J3wkiUVlFJIRIIsuYoeQqFIFhxq+oQPQxIyd0JNtZhbV6rur4tH9jAuyCJxHVyyCZJ/XUL12DmRy+VQLpeP6ao3qsGuCgb+2/YgfAE+LSzLEm8wffyhcla8evXqyti2bNvGxx9/jFu3bp1ZEuvJhx8+fHhinksvoes69vb2cP369TO9nhDgzp3bYIzh2bNn5xpLdEbppJDh1vDl5sxSMJw5SvKIosPyOz4In3ZrGKDNTDTsMmxuweYWGnYZDjOhsxLksQYq+zZsZgrvt9slolfoVueH8fHjPOLNo11ZENL9ZYQReoBLn2xrEx8Sm5kTF8gcF9QcWQpHBUyMjR+/3UnHaTemHoIxhqOjI0xOTvZ6KJeCarXqK3nOQvIAQh0xPz+PjY2NLo+uu9jd3UUmkznz9yFFkfG1r30Nz549x9HR0bnH007NI1ZFW6g3A5j9TlTcU1g3O1MdR/JYbjcskzVg2CKEuWZUYNo6akYZDbOGml6BYemo6e5j7MGxCSydoawXYVgN1IyKmHzrEYL1aThO4HQY1WAn4ArVYANP9AyjomdY83lM04RhGB35owcdjDF8+umnWFxcPPfsSC6XQzKZxN7eXpdG1308fvwYq6urZ5wBdWczCMH9+/dQqVTbBDQPH7SpOsyYQEAv2K9hl0VnLrsGxyWDbGa2tPd0uLdY4aDmCDkVVipFQgADiCPHogXIsecVkA4fjytcaIwwwhBA1/XY7j4Xgk4InjgypoXs4ccuR8UCxsfG2m8T3We740XG2JaIuiTs7e1henr6SiiqG40GPvvsM7z99ttnJnk83LhxA7u7u9D13hEAx8GzzZ89EkH8EiqKgq997V08evQI5XK5ewPsY9RTG0jUllrW14wydLOOhllrLpa4NR292XbdDWT2HgfrseZ9EdCMlgnD4KRipL5qUZvHT1S2w/GBzK37HWF4MbJu9SGOtzwMLnZ3dzE3N9frYVwKHj16hPHxcVy7dq0r++tn+XChUIBt25iePp+3GxBkz9tvv4Uf/ehDpNPpC5t5bOcRj5IffncEHuigEJAQA2gJBAyGAQKA5YgMHsMuAQAkqsKwq8LvLVXBeRb1RhWSikDmDvwAQM+y5XA3n4c7UKQkbMeESpPgxPHPixEHCk2CkkAuIIc72+Dl7jAQ1x4mPN5eOHOcN/zsOFk67OHqSYj51TrdEYYUtm1DkqSLz0hsQ/C03aZFcRNeQU74blMqlXD31lrb7doT3SR8NyaPxxt3KL/nknJ7dnZ2sLKycrEH6QM4joNPP/0U9+/f78r3A0opVlZW8OTJE7z11ltdGGF38fz5cywsLHQld0nTNLzzzjv45JNP8eBBfPv5dui0e2cT0XbizVbqHI4fxuw1t4hT81hMh8kafkaPIGFMmLYOy7Fg2joc5sB0VTqGrYMS6qt2VNXC9NEfhal9jJpTgaYk0DBrkCUFBtWhUAWU6lBc+5YtCau+LKnQZCYCnnECkUiFZcvL5/FqMhHMTPzcnWA9FqzRmk0y4q95XL2WTCbRaOjgnHfw/jyqwYYZA03rc87hOM6xbaoHEcVisYMvR4OH/f39rpAB/Y5Xr17BNE0sLy93bZ+apuHatWt9Jx/mnOPx48e4c+fOWffQsoZSinfeeRuPHj1GvV4/5d7iggBx7Lrwc94MS1BC3Jx9afGJR0geb0bHcIQCp2GXwOCgZh35HR/K+gFsZqFiFEVoc/oIVimJmlmBzSzUzDJMR0fDKqNhlUNKHsOpwuYWDLsGzh2YTPjQLabDYrp7vxEIL/SyhTw1TzDkMNh2vfU6xkmvT6Pq6XxG6YqBXNAywgiXjEuxzl/EhPMxlizLdK3zVGq7DWHuwpuL2G+M4id6PBdtFT4XBMdxUK/Xh25iNArOOb744gssLS11tY6enp6GaZoxrch7i0ajgf39fSwttapSOkPrL10qlcKdO7fx6aefdaDKjdtjXO3gqlSOsW01FS7N+wD3J9D8WiuG5NHtGnS7BsPW0bDEbc0ou3asMgxbR7lRhOWYKNYPYTsWbMfCYX0LDgxUyqJ+KtYOYdg6Ko2isHe5Vi5P1WNY4r5hN9Awa8Ky71rGLFdhbXN3cetD5mY2tip5AtEAp1T1dKLsyWazqFQqp/75DT2uWA020ERPo9E4tySz38AYA2MMiqL0eihdhW3bMAyjd21YLwnlchmvXr3Cm2++2fVZzuvXr/edfPj169fI5/Nn/Lm2r2o1TcMbb7yBzz77HI7jtN2u8+O0FhztOj60rotv62kxHQ27HPiQFzk9hlPzSRnOHdTMAhhnqOhFVPQiAKCsF8CYg3KjCDu9D/NIKHSqRhm2Y6FmlGE5JizHRM0suzk/Jdhc3Drc9LN+DKfqhxa2J3vEuXhtS5vn6V2XZhBiu4Dq00J03upU/j2SD48wwqDhwhXVp7FqtdwPW61aSJk2KFXLyGe7aC9vsY0hdF6XRfYcHR1hYmJi6DrURrGxsQFVVbueBUkIwZ07d/D48eO+ykt8/Pgx1tbWzmWbj8Pk5CRmZmbw6NHjsw8Op1PzBLN5RCaP5duebCZIHo/Ysbnl29hNR4dh6T4JY7o5PKKWqrgkTwG2Y6JQPQRjDIflAg7LYiJqx3mIcbaC/eIhGHdQqpVgORYqjaJP+hi23iSPbB01vQKLmagZ5Rayx8sL8rqBeZ3AvJqsaeFqdnr1rpY3ydgN5PP5U1jw+ud3eoTuYqCJnmG0bdXr9VO1fxwUHBwcnDmQeFDgOA5+/OMf46233roQe1VQPtwPsG0bL168OKMU/OQPlXw+h/n5+a6db7uCIzy7FJllaSk6mrM0wZkbUYDoguzhTQVOxSjCYQ6K9UNf0VOo7YMx5q8rOluApQJsoN+OW5BKpdBonEaRdcmBFb3EFQoCHGF4caGKnpPsWrGKmTbkDgtswzhaMndYc6lUqsimMqF1sa/hPKzyCRJJ0TyfPsDe3t6FdFPqJ5TLZezs7JxDYXw8vLDj7e3tC9n/aVEoFOA4zhlr65N/N2/cuO4rhk7eW/v9BSfXmJ8VeLyax+u65alhvNqLu7b4ZiaO5SpsdFT0IkxXfWMxC1Wj7BM2jDEUqoL0OCiWIUsUskSxc1BCSXqGvHOro6vWKRTpfCKE1qYhx6nR4699NptBpXKa5h7983514bhCNdhAf7MYRqJnGLuIAVejyHj06BGWlpYuVLXUT/LhZ8+e4fr16xeqPrt+fQm1Wh0HBwcXdox+gJ06RONIhu1YqOhFWO5MVM2o+OtsZqFhlcG5Iyxh3IHh1Nzbqm8l81Q90RBAofrhaCGz2rY9Pb64OAmEEBBCz6DIukLFxggjDDBqtVr3P+/a8L3kWEuUIFVIC+ESfl4QNmhdAqjWqsimY+rKuNcFCaDAvmPtXEFiCAgd96JDmjnnQxsJ4MGbaHvzzTcvNGx6dXUVL168gG3bF3aMTnB+2/zJIITgjTfu4/HjJzAM48KO02uYpALHkqDRFA6KwupUrFTBGHfVPSbKjYKrChK1GeMOanoFDndCqp6gnT+a2+hwE9zLIWohtoLqJrj3mwQZAmsBtM3sCSKTyaJaPa11a1R/DRsGmui51G4Pl4RhJK8YY6hUKkPdbevw8BC6rl9463hPPvzo0aOeyofr9TqOjo6wuLh4hld3Pm5CCN588w08fvzkxMIqPp+Ht24TsW01n4m08wwEAnqzS6FMHlfJ46l5PFlxsLUnY45v1yrWD1GsHwIAjmqig9pRdQ+MOShK65Br0yjWD2E5JiquzNh2TFT0IhzuoGqU4TAHNbMMFkP2eJ26vMwer8DwCos4uXDTBw9E7VtxxUX42h4/iwcA6XQatVrt2G3iMSo2Rhih32FZVneJ/siffUu3qhMInlgSJkjuxOyXsPBSrVeRTaRa1hPGw6+L674VOWaLVazdeQTGdNz1OCtKpRLy+fxQd9t6+vQprl27duH1s6IoWFxcxPPnzy/0OCfh9evXGBsb67ptPgpN03D79hq++uphh3s+pq16aLsgsdFq22pOVplg3As9dmA6ul9/2cyEYeuwmAhfNqyGWFxrlWnpqDRKYIyjWKmCEoKDQhWqImF7v4jt/SJSCRVbu0co0mdAaRaqLGP/qAxKCYqVOhjjKNdqfqxGuVEUdV2jGCJ7GmazDvPsWp5lK5jV4024ResxEczMQtfmpOt80kScqiowTesM3xVG9dcwYaDf9YeR6BlGRU+pVMLY2NjQesMdx8Hjx49x7969SznHTCaDXC7XU/nwo0ePcPv27Us5X03TcP36EtbXn3Z931FVS7tAwGgYoOcTN5nukzyGU4XliCLDsHTfv82Yg5JL8ABoIXuK9SPo8gGokQVzvAKCoawXUdaLLvFT9JU9jDPUTDFLEyV7PHUP404oBDBOHt28Bhen6hHS4VEYYBAcACfdX0YY4TLhfXno68/1CIniETbu9ywgYunijvgyJxEaY91qfU2Q/Akd0yOhIoRP2NbVHN9Fq3uGvRFGpVJBoVDA9evXL+V4i4uLODg4OHWziG7Bs83futVdu1E7TE9PgxB0ZOEKIr52iE6w8dD9qG3LI3xsd1KNwfEn2Qxbh+2Y0M06LMf0c3QaZh22Y6Jm1GA7Dsq1BgDgsFiBqsjY3i8indKQTmnYeH2AfC6FH+/9CEvJ+9jaLUDTFBwWheXJe225VhOED3f8Gi5I9jDuoGHV3Y6rjVCLdcZFQ4ygqifertY68Xby9TweiYQG0zRP/bphxlWrwQaa6DEM41St/wYBw0heDWu7eA/Pnz/H/Pz8pQaDr66u4vnz5z2RDx8eHoIQcqk/04WFBZTL5VMEyzURR2RE1TwCzZDiaDaPFwbIPb94QMUT7IrVsOqwHQsNqwbdrIsQQFeR4yl6GHNQqolAwKPqvl84GLSARtXxt/W6QlSCM0jMQaVR8JVCUWWPR/iYrOGOVYxdnIN7TiFVD4stLuJVPaeHkA6fxiM+wggjDAI4511p59zcYfhhW3VL0BKFNhYtj0g5Jep6AymtS5/joTE1H4cIH2+74C3aqHvOgUKhgPHx8a7tr5/AOcdXX311aRNtgMhLvH37Nh4/Pl9Q8Vnx9OnTC7fNR3H37l08ebLeYsUO2o7i0Kqi9tbHKYObah5B9jBfzSNIE2GPcpgJ09FFrWXW4DDHz+nxyJ+aUQNjHNW6sJwVyjUoiozdgxIyqQQ2tg6xsXWIqfEsnm0cAOkyVHsCuUwC23tFyBJFoeSSPdWGP9ZqXTRDCZI9AHwFd8Oq+XWiIHlYrKonWI+Fr1dM961zIJMZdd666hhooodzPlRSVNu2IUlSf8+QnQFHR0dDW2Touo79/f1Lm0nyoCgKlpaWLl0+zBi7cF94HAghuHv3bkcdL46VDvM4widYrERnWJqWLYZgKKAgfQyn6itoGlYdjLl+bbcAaZg1n6zxiJuyWxhE0VB2kHKunf7i9DFOHwZ4FXABIYBD9pkxQv+Dc969SakzkDxhuxZvIVS8/YQUPJ69KmjHctyFAZWaCGL226eHloAiKLSIfceqe/oAjDE4jtNdUq6PsLu766ucLxOTk5PgnOPo6OhSj1ur1VAoFM5omz87NE3DtWvz2Nh42cHWxxM/7W1b7tpAzeXVXR7Z49dhzIFh62CcoWGJOsu0dJiWjobZCJE8pUodqiIsWamkis3XhdiRVe0CkmTsNJflctDBpNtxgcyjybYorlYNNrAsybCRPMDw5vOYpjl0KiUPT58+xa1bt3ryu7i4uIjDw8NLlQ9vbm5iamrqUtVLHnK5LFRVw+Hh4ckb9ykMS8wGOdwR3nHuoNIQmTv7zjpS1hxKNa/1ugj/c7jjq4LKnnXLEMomLxTQI5uY25GCcwem0whLhyOt1qMF13H2LbhbIVSgeWvbv0ZV1ZFseIQRhhCMse4oqtuRPBHSJkjotKp4ECZ3PIInQO40iRq3C5e/NEmbSq2KbCLdattiHHCCpE4rAYTA8TzSxx93qHMXfGVPi/roOMLrjPyRl88zjGCM4dmzZ2fs/Hl+9KLdujfR1osJ4aWlJezs7MA0rUs/drcxkU9jIp/G0+dHmJ7M4PlGEWWyCZRmkEqoOChUQSlFpdoA54I0qtYNl0ASdVy5UQSlkl+PNawaGGcwHd0nqbwg5qB9K9gYAwgqzDtV8nT++5bJjCbbrjoGlilhjA0deTCM+TzDHMJcq9VQq9V61k2MUoq1tbVLkw+bpolXr15heXn5Uo4Xh7W1VayvP20prM4ib203qxQXCMg4CwUAOtyEHiBXambFV/MwzkRwMnfQMOtCUmyJlp+mbcK0TdT1BkzLRl03YVoO6rqJkr0HzZ6EbTuoNKoR6xbzrVtV9xjN4qLpC/csW16hEZQOe2RP0L7VzsLWeq3OltNDCIGiyCOyJwpyAcsII1wiLqIGax+6jBirVpgkCZE7HoHDm+ROcL1Q8HgBy007VaVeRS4uiNnbJqICCit60CR8uLcuLr+nOe5wZ67ANnHXJOa5TjDMtq2trS3MzMz0LMIhlUphYmICr169upTjHRwcgFLas5+nJEm4ceN6WyX5yXVC8PnWGq6ZmSjsYU4wl4cJ25Pj1jSmLbqLGlYDzFX3NK1boqYCgEqtAVmiOCiIfJ7d/QqyGQ2vXlXw6lUFk5MJPH9exuRkAp9vfoEbY2vYOxAKoHK1AcY56g0DjuPAcRzopgXGuL//ckOogxqmaDph2G5DDKcBy2m46iRLED9c2NG422K+ObnWPqfnJJx0zTOZDGq1EdHTgitUgw0s0dNV2XCfYBgVPcNcZDx//hy3bt3qqdXuMuXDT58+xfLyMmRZvvBjtUMymUQ2m+243Xrch2Brt634ULxgIGAwDNDmlk+oNKwaGpb4gPeIF++Dv1Q7DCl2qnUdts1g2wzVuuEWI4ZL+BgwbQsNXgQ3U7Adhrpuoq6bYIy7nSMc3wdeNcqw3Cwgzxfe7ADWAIPjFxnR1p7tbGrB6zXK6blAXESB0cdFxgjDiZ7XYL4yJqLeCXbiCpI7AdLGD0oOWrccjrquI6MkQ3YuwhAhdprqnCD545E+PuETUu/Edek6gewJvO2eh+wZVus8YwwvX77EjRs3ejqOW7du4eXLl7Csi1W5MMbw5MkT3L59+0KPcxKuXbuGw8PDE8+3k8mhKLHhTa4BCOfZ+OtELWPYOhzuwLCEdcuwdViOqJUY49ANMbZaXQclonuWqsgoFBvQNAkH+zoyeQmZvITXr+oYn5KxuVGHkdxBls9D1QiKJQOMi32ZlgPbYbAdBsuyYdo2GGPQTWENa5h191bUgpbTHLvt2s0cV1nNEFT1AO3InGAtdtrrGgSlFJzznnbp7TtcsRpsYImeYVT0NBoNpFKpXg+jqxhWoscwDFSrVUxOTvZ6KJciH65Wq6hUKpifn7+wY3SKmzdv4MWLjY6394uJmHye1g/NsJqnGQgYIEzcD2zdbrYNrxllUCqhrBehSCpKtUPIkopCpQhZknBUqkGWJBTKNRTKNTforwZKKEoVUSTU6joOnQ2k7WvQDQu27cC2BRlkOw5qRg2WY6JmVIQf3e3uJWawrGY7T2a6JM/JIYDBYObOW3ue7vcslUqi0WicvOEII4wwMOhKDRZHZsQpW+IyedrhjBMvnHNRr5/29SFiKYbwCdi+Wixd7ciemGtwFrKHcz601vnd3V1MTU1daiBxHGRZxs2bN/H0afe7ggaxubmJ6enpntjmgyCEYHFxEZubmx2/JhjEHFd3eSpq7xfbI0GinbcAwGaCxLFdMsWvfxwLuikWwCV5KEG51oAsSahUDUgyQaVsQ00QHO1Z0BsMqayE3S0T+QkJO1s6TNTgVFOgFLBMBsMQY6nWdVTrOhjjMAzLJ35MS9SDHsljWjoYc/x6LGrZitq3vPPnoRosSu6cb9JN0zQYhnGm144w+BhYoqfns0kXgGHsItZoNHr+wXQR2NjYwPXr1/siOPui5cOcczx8+LBnvvAo0uk0ZFlGqVRqee7YIObQdsHnA7atwAyTFwgYzLmxmO7LcgGRkVMzREeDSqMIiUg4qu5BllTslzpTHQVR5tvIktlTv66fkUgk0GjovR5GX+EqtfYcYThx7hqsHYkRfC6YyeOtj9i1ggqZYA5PSMkTUPE01TphlY6pG1AlBbCZIGYcLu57S9Ty5Sp9zil4vFDU6/WhmzwExO9eP6h5PFy7dg2lUunClKuebf7mzZsXsv/TYmHhGra3d+Aw59jtPIIi/rnwBJOHqIonuM5hguwxbGHXsh0LjDlgzIFpNTvQ1nUTkiT5YcynwYHxCtPJyw26vmgkEgno+qgGC+Iq1WADS/QMo6KHc94XX6S7BcuyIMvyUJ0TIH739vf3MTc31+uh+LhI+fD+/j40TeurQMfr169jc/OCiC0cX7ycBglNwd5RGamEit3DEtJJDemkhu39IpJJFbsHJWiqgkM3+G+3vokMpmGYzdkp03JchY+YPbIcM6DkMWHaOixmNv3prqe9XQhgMJS5dYaoe95w/xokEjCMUZExwgjDBM752W28xylVAiSPr+Lxn4sheVrIHYQJnog9yyNyuM3AreZSb+hISCqYxWIXf1tbLD754x/7OGVPYOwcHah6IjauE65hOwxj7iMAlMtlJBKJvvkOQAjBnTt38OjRowvZ//r6es9t80FIkoTp6Wns7e33eignQlVkn/AxGqJmqVUYZJWgdGSjdGQjnZFwsCNuXx1tYSZ1DabOYRochAKVqgFVkf19UUqhGxYYE+3fvSYbhi1uLdbMJGzWXsy3bQXRWoOdvbV6u+1HRM/Vxojo6RM4jgNJkno9jK5iGDOHAEF8TE1N9VXXt4uSDzPGsL6+3nNfeBQTE+Mol8uwbfvkjVtwXD4PCyxN21YwDNBiwhblSXUBoKaXQQlFsX4IVUngsHyITDKJnYMSxrIpbO4cYjyXxvNX+3j+ah+T4xlsbB1iLJfC1m7B7fJQgU0akHgSpmXDchfDtFyJsO0upj+jZdg6HOb4cmFPMuww17LFrADh0ww5DJM08aRPnDf8LKHMoyIjBleotecIw4uuTuLEWLVCzwVJHj8EOdCBK5rDE1DgePYp7jBwh/vEDbMcf6nrDSQkBcy0/YVbjr9423H/tU3iBzYL5/gECR+P3ImENR9L9gCxZM9pW7cPaw22tbWFhYWFXg8jhLGxMSiKgv397pIflUoF1Wq1L2zzQSwsXMPrra1TveY44iJo7wLQzLMJ1GEAYDmme2vB4Q4c7sByLFBKoBsWdMOCLFPU6jpkifokj2VxODbgOByccZg6h6IQKApBueggmaYoFx0U7W2My/NwHA5KgXqFQdMklMo6SmUdCU1B1bWFmZYD2xZj9kgen+xxrFBWDwBfpRQMZD7puhx3NTuVE4oabGTdCuEK1WD98031lOCcD5XNSdf1oSKuAPEBNSoyLg8XIR/e2NjA3Nxc3/2tEUIwOzuD3d3dth+ScT7nth5o3yMe9oV7MzB+54dAGCAgwvcaZs3P59HkBA7LB0glEni9f4SJvCB3ZifzeLKxi4W5cSzMjePJswNcmxnD8w2xzevdMhKagqNSDQargZuqO2PEYdsODNOCads+2WM7lt99ywuD9hQ9DnNaVD3e47A3PJDVE+w8Fp1R6sAbPmqxPsIIVwtdI3mimTRxNq4oyeNZtfy3sYA9y7NouaSKp9wJkjs8QNow0wEzHTRMHRqUkMrHe47Z4n6QHArtw90eQeVQqOtXQOHjklDifjzZc1w3rtNk9QyjosdxHBQKhb7IR4zi9u3bWF9fB2Nn61IZBeccjx496hvbfBDpdBqOw7oyiRPOThTEDiCIEe7WYQBgu0oZ7/p69i0AguCRKGSJotEwoSoy6roJSggcm8OxhTrH1MWxHEcodkyDQ1EJqmUHqkawebCNyeQsGAMaNQYtKXJ9kkkZyaSMYqWOhKrAcAOfGeewHTHh6I3FuxXPNwkr73H43INxA1F2uzvQtNFk21XGwBI9QJdnk3qMYSR6qtXq0BUZlmXBNM2+JLC6LR82DAPb29t944OPYn5+Hjs7u8du43vEY3zi8SHEPET0BC1PXgizFwYYUvQYFTef5wAJVcNeoYixbAobrw8wOyVInqX5CTx8vI+Hj/exOJ/D4/VDzM6k8epVBbmshoNDtw2osYU0pmE7zLdv2bYDy+/80PSje2NomDV/nKLtKGt2eXALjbB9q5lHFEfSnLfTVhCEkGOzU68krlDHhxGGE2euv6K2rT753dVtEwlJjX0upOox3MUOE0fccQkfxyV8PEtXMGeIB8ge3p7saVX3nO2chjEj8fDwEFNTU31Z/ycSCczMzODly5dd2V8/2uaDmJufxW5LDXYxH/ZNoiQ4ISfum7YJWZL8eklxSR5ZkmBZDI4DUCqIG0Ul0BvhMeoNhkSSol5lkFUGzgm4Q6BqFNUyE2qfsoVy2UIqoaJaNyDLEmzHCZFO0VsWyTDyQ6ZbOm81cZyVqxWd/Q2MVNUxuEI12EATPcOEYSV6+pEQOQ8ODg4wNTXV62G0RTflw0+ePMHKykrfWgpTqRRM0zy1fes4YsOzbEVtW6xNoOBF4MjcxrjSXzJtD+SMHxmyLJ3RZjekuEJFxgjDiTN90Y6SPMF1ATVPs7sW2qt5XBFmyKoVaIcOh7vWKh5S4PgqHcMJ2bMapgGVS00ix1ssB5wNHlNt2zYkSepLQuQ82Nvbw+xs/zYsuHnzJl6/fn1uFWu/2uaDmJ6ext65a81m7RVEHAlyWThq7GFcm2lZPzE+mN/REgltlJMYxRWqwUZET59gGIke27Z73vqy29jb28PMTOsHQD/h9u3bePLkybnkw6VSCbqu9/25Tk1N4eDg8NKO56lkDFt03WpYNTQs0Sa93ChCVVQclSvIJBPY3i9iciyL56/2cW1mDI/XD7C0mMPSYg5PnxUxN5fCxkYVuTEZe3sNKApBvW7jyNhBTppGXW8WinXdBGNMWLhcZY9uNu1jAERAs+X5wwNqHs5CgYDBnJ6gbDiYVyRw3O/P6b74jGaURhhhuHBR+TyhFurHkTxeBg4QsmqB8ZC6hnv2KpuBGa2WK4/Q0W0DmiOJ54M5PYYD7pE+ZiCjx/ByfNx9+3k+IgeI+2HN8MOaO1f1BDJ7YqxabQOsAxjGjlucc5RKpb5VuAAiqPjWrVt48uTJufbTr7b5IBKJBDhjF2rN1p1ay7ogCcSYA1mSYFo2ZEmCLEkwTAuqIvvKZ0oB0+BIJCkaNQZVI7BNiMweG1AUgmpJ5PTUqwxHxg4mErOu0kfYulIp0cWrWjeQ0BTohsgFYow3VUYRVY8YK2vpInYSuqmoBsTvpONc3mTlCP2FgSV6hm2WQtf1vn5DPy0cx+mrsOJugHM+EHa0RCKB2dnZM8uH+9kXHsX09BQOD6JtzI/7kGxPbHCwE/N5ABGyB4hMHIlIkIiEmlGBIiko12pIJVQcFivIZ1PY2j3CzEQWLzYLmJ1N4fnzEp4/L2FyWsWrlzXkxiQc7ltQNVGAODZHxSxAQx6yRFGu6ihXw6GCtuPAth0wxpskj90kUQzXumUzq6X7Vrxk+OILgJFHPAACcEK6vowwwmXiVJ8NETKiRc0DBOxNCFmY/O3jSJ5gHo+n4PEWx83TiZAwzGKCuPFIHJfssZkDagGObvvkj5/T427jvc4neKwmeRQkfJjlgNuCcPLas3tEVLMrV4DI4VGyJ3itAtcDiCd7otcSwzl5WC6Xkc/n+74umZ2dRb1eR7lcPtPrPdt8v7RTPw6TU1M4PDw6xSvaMJMxiFP1RMkUSoWFyrNS2Y4DWaIwLRuUEhAKWCaHqhE06sKGZRockgx/adQYMnkJ5YKDVIbiqFZAThuDJBOYBkcyRVGvO0glVKQSIj9RVSQ/iBkAHO6AUgmMM1Dafyp4QkjXsqMGHlesBhuub+IDDMMwhupDeRiLDI/k6fciA2jKhw3j9En7Ozs7yGQyfU9oAUAul0O5XOlo2+M7RrnfHqJrA90SvHwe5na5AgJhzERCzahBVSQUK3UkExr2j8oYy6awvVfGWF7DznYd2TEJ2TEJ+7smUlkJpSMbikJgNBgch4Mx4LBUQlrJoVS0kNBkJDQZxYrI76k3DDDGYdo2bIeJ+5Ygdkxbh6aIvznb7UwRyumJZA4BHBSSe36tHbZOvmYnP+9h1PVhhBFGiEVUtRJBiOTx8ms8kse773ChonFcFU+odXqTzOGWS9b4Sh4bzLDhGBbAOJy6CaZb/uLUTbGNbgmCx7ADih7HJYqcFsIneFzujg3BDmBAWNkT7cTlPR+9LKeY6B/GGqxQKGB8fLzXwzgRwbxEfoaAuidPnmB1dXUgJkvHx8dRLBRO8YrOfS6UtBImHoni3TLmgBIKxhgoJb7Kxrvv2ILk0RuCsPFyegD4YczZMQmlIwfjUxIqRQcmLSEtjYFSQJIE2aNqxM8AUhUJttM8HgBIRAqMRdSNSTV9iusCEFwcQaRpo6YYVxX9/y7SBoPwZfs0sCxrqGxOw0ZcAcDR0dFAFBlAUz68vr5+qtc5joNnz55hdXX1gkbWXVBKoaoKdF2PdItqT0BEtwuSHC2kCFpJEsvt/GDYOiiVQKmEhlmDLAlpr6rIKFXqfhetZFJGsWRAcyXA1bIjbFoVt12oJYoNQiE6PyQJmAMk0xSFIxOFIxMJTUa5poNSCsN0OzvYYvZKtBcVY7IdC7bbdtRb51m2vHMJX4tmGHM0nDq4Teh6nUEBpCjyKKNnhBGGCINagwXJHLtmwK4ZsBoGKBPPRRe7osOpG+KxS/44ddMnfpgZIXw8RY9r3/LJpwjZE1bzIL7pzmksXBEMI9EzSDVYLpdDKpXC7u7xDSOi8Gzz09PTFzSy7iKfz6FUKp1jD8T9P/x1NI7kiXuuSfzQwDoCSgTho2mSUOWkKfQGg5akYEy0Wk9lKFIZitKRg+l5GUf7DibnZOwcHmI8PQ7LFHWZJBNwBqiKBFWRwDgHJU2ShxIaGYvkrxeLBHLM+bReke6/tyqKMqrBrihGRE+fQLDRA/vjaMEwFhnFYhFjY2O9HkbHOIt8+Pnz51hcXISqxncf6UeMjY2hWDxPodF/sJgJiQwP8StJMhxnVGT4uEJBgCMMJzquwSJcRKxtC9FsHrGdr+ZhzVbqfi5PRM3jESxBuxbzyBfXauXoNojUWmc5YJAGtxyOxbDVYJzzgesitra2hmfPnsFxOstnGSTbvAdJEpNdlmWdvPGAoGwUkVHGej2MrkKSRg0xQrhCNdjAfrINypvgaTBM5zRsRQYgwg3T6dNJMXuJ08qHG40G9vf3sbS0dAmj6x6yuSyqlfb2rbgW4p56JbyN17aT+QF6zcdeXo+rwnEsSETyA5AppajrJighaOima7MyQSlBoyE+XE2D++F/jsNhWRyEEtQrIhywdOQgnZFwtGejwUqwixkk0xTJNEWpaCKhKqjrBighsCwHjHMwxmE7FhhjsBwTDhNjZCxyDmiGAXqBzDxy/nHXrfmAnSsgUHTd6l0XjRFGGKGPEMybicvm8Z9DRPESCV8OkDyeaoY7PGyhMkReDjNscIcJVY5uwa7qYIYFZliwag1Qh8NpGLCrDX9xGoZY6sHFbFX1uIRS8Lge4cS9pZ2qJxAyHSK4gtcp7todd10xfDWYpxIfpDpZVVVcu3YNL1686Gj77e3tgbHNB5HNZlCtVt1HF/PzoZDCSh4iBZQ0TWUNJdSfNFcVGZbl5fKIW+7aupJpgmqZoVpmmL4mY3/bxvx1BfuvbeSmGShXkc5SOA6Hooisn6ZCh0CWw0qiFjVPTE6PN37vXKKqJeL+i555NyAm20Y12FXEwBI9I/Q3hq3I8ELMBk11dRr58OPHj7G2tjZw55jJBIuMJjg40JI9czyh4XWk8h+79i2gaYGyA2HMHkxLkDymO2NiOy7RwgShQylgNBgUhUBRCGoVhkRSSIZTWYqjPRu5MQkHu+5t+Qgz45MoHTkoHTlIpiVUqgZkSYLuWbecJtnj27OCYdKsGcDsodW6dTYr1mkhuj6MigwfhHR/GWGES8RZvnAfZzVqu12LqqcNyeMTLU3ShRniOS9jxy41RPZOtQFmWD6hYxoGiMlhVxpw6oLsceoGrFLNfazDcdeFyR9h5/L2HwyCFq3d3YDmKNkTsGOREJnFA+QWD53/cfatuOtq2zZkWT71z6hfUalUkMlkej2MU+P69evY29s7sRmBbdt4/vz5wNjmg8hks6hWWmuwThEkNwiaBA4hkiBFECR4BJEjubZ5WVJAiQRZov4CCJKHMY5kUoZtiXwex+GQZOJn9kzNypialXG4Y2PhpoKdTQtLKyqO9m1IMketwpHOSLAsjoQm+5OAqiL+rmRJEqSPJLtjUEIEjnc/eA6t5A7170WvSjcxmmyL4ArVYIP1jS6AQWL1ryKGLXOoVqsNlJoniE7kw4VCAY7jYGpq6hJH1h0kk0k0Gufr6BRHdgS7U/lkj6vosf1MHDNw39uGiY4PhELXHahas3Vn4dBG4dBGJi/InfyEhMNdcbu/bWN8SpA9XG7AaWi+oqdacqCoTdWQ1zbUtl2ChzktiziHZmvP4Lm0dt4SVyH+/vkhyyPr1ggjDBM6qsFOUp+cQs0TJUZC4ctOs6U6s0SXK2YKksepm2CWIxQ8lg2rXINjWD6p49QNWIYJYjqC1CnVRX6Pe+uRPU7d9AmgOMLHC3ZmvqrH8cke3kL2NFuvi/MNBDPHZfWc9rq6GKY6eRA6nsaBUorV1VU8fvz42O1evHiBpaWlgbLNe8i2mWyL4rjsGaFlCeTseARJIOeGEgkSFZ1OAUChCiQiQZEUPxiZUgJFEc8nNAWMcaRSMjgHVI1CVkRA8/iU5E+kLSyr2Nm0cPO2hp1NCws3VTQMHfPzaTRqDLmcAtNykEklkEklYDsMmiq+38iyGLMiibEIAoqKMZGwcoeQZnYPgeSf79kyeU73mpF9/upiRPT0Ac6Syt/vcBwHktR/LQbPikajgVQq1ethnAknyYeDvvBBBCEEIGf9O2q+JtSCPKCCaXaqcq1dkfae4rVCvSO6YIn2nnXdRCIhujhk8hKO9hyMT8oYn5Sx/9rG2JSM/W0LY5OC5PFu8xMSSpUGMskEqiUH1ZIDNUGgN5jbNtQlm2xvPBxOyGbGQucTRFy70vDVaLW5dQPCHz6aTfJxhfzhI4xwLOIyfHziJ3Df25ZFumu5Vi2P4PFJHq+LluXALtXALRt2uQ5uOYLEMSw4FR1ORYdlGqAmE+stG1ah2rwNkT0xS5Dw0S1XSWS3Wsi8sdqs2Xrdaw8fUvM0z7tTVY9/3YYYuq4PVD5PENPT07AsC8ViMfZ5zza/uLh4uQM7JzyCIpmKn2wjIACJ/5opSA4aG8IcDC8OkiUkcF+WXKJFUlxlT3OhhELTxPOphArGOFSNQpIASoFMXkKtwjC3pGBuSdi1lu8m8PqliZtrCextWaCajUZJwsxsErWahYl8GrphQTcsZDMJ2I5otw4AmpIQjTlcUkqhqj/e5phpi/0seA3ds0fwa/lpCaDjth+pqiO4QjXYwBI9w4RhI0WA4ZMN67oOTdN6PYwz4zj58NbWFsbHxwdWsQQIMmuYWkeajgFFGtzftyhGRUYABOAXsIwwwmXiNJNtx+bO9MHvLqMAvXgH66Vh2Jp7AIMfB3BcXuKg2uY9iPrL6PUwugqbGVDo8NRgI+tWAFesBjvxXYUQ8t8TQvYIIV8E1v0MIeTHhBBGCPlGZPu/TghZJ4Q8IoT8bwLrv08I+YgQ8l+4j/8aIeTvBp7/LULI/xx4/H8lhPz6MePq9Bz7Ho7jDBUpAgwfeTXoRUY7+bBt29jY2MDKykqPRtYdJBIJ6HqnhQZ3/z9+BjRO/RIMaAYAh4v25sztBOM4rKnm0WRUyjZSGWHTGpuSsL9tYX/bwsSMUPNMTMs43BXPHe0LNU/xwAZRTMDSoCaIr+aRJPhqHsY4OOdgbtHIGPNVPcHxAUFFkuM/jjnbdlfh2GvUKQbdukUIuUMI+SSwlAkh/wUhZIIQ8j8RQp64t+Pu9pQQ8j8QQv4jIeQNd90fI4SUensmIwwaBrYG68C21XwcsW1BqFdabFtuiDG3OTjjIYUM7KZ1y1PzcIfBLtcBAGahCu4wWEeuWieg0rFsC7xsgJk29M0CuM38W3O/Am45sIpuXk+lIWxfftt1A0w3xa1hwakbwkbmqXocFl64q+ZhEMHMMVk9voXruGt5zPW1bXuo6i9g8CfbMpkM8vk8Xr9+HVpfKBTAGBtI27wHQgiOE5SFM3haVTyEeEoWsV1Lxo2rjJGJCkqon4WjKUk/p0eWFMgyhSxTqK51K+kqblJJFbJEIckEybQEU+eYmlNQOLBROLBxYzWBnU0TK3dS2H5l4NZaBpV6HUvXxlEs6ZifyaFa1zE5nsHkeAaGYSGXTsJ2GNJa2lcYyZIKWVID6p5WJRIJ2bmIf/4kpOSJXB9XGXWetutism1Ug13FGqwT+vgfA/huZN0XAP63AP4wuJIQch/A9wG84b7mNwnxdWrfB/BNAD9BCMkA+AGAnwy8/B0A+cD2PwngP7Yb1DARPcP4oQwM18/IsqyB9E4HMT09Ddu2Q/Lhp0+f4saNGwNPNKqKcqr2np3akxhvDTIOkjyMMT+om3EO4ubnqIqMWs1CMk1RKTrITwgiZ2xKxtiUIHfG3VtB7jjI5CQ/nLlc05FUNZg6h6lzSBKBJ4gRNrGmbcsjmTyyxyN8nGNsWk3iJ/qN4mJAKfXHOYjgnD/inL/LOX8XwAMAdQD/EsB/CeB/4ZyvAfhf3McA8KcBvAfgpwH83wK7+g8Azh72N4BBgCOcG/8YfViDnQktNq3wuqhVKUgIEQY/mwe8lUBhVvN+HMlDKIVVEDki1mEVrGHBruiwKzqsugFiMTReFEATMmqP9kETMurrhwAAfbMEZtiwDmtwaoZYXNKHuR28uGXDrjbALKdJ9vjdwAIhzQ5v2s9c61aT5Iqcdyf2rRg49vBNHnLOB1bx4mFlZQUbGxt+m2vPNn/79u0ej+z8EGRP8/eylaxo/dk1u0wRf5toZyrikzxu6DJVIVEJmpwQFi05AUVSoUhqyL6VcDN0UkkNlBCoioxUQoVjc0xMqaiWHCxeT2Hxegp72wZW72TxelPH2u0ctl/XkcoC1TLH4nwexUods1N5NBomGg0Tk2NZmJaNXDoNhztIqik/K8hbZKr6IczBLlutHbeOs7Z1dh07gSzLA63oGdVgZ8eJvzGc8z8EcBRZ9xXn/FHM5t8D8E855wbn/DmAdQDfcp/zrgJ3738C4DYhJEkIyQNouOvecrf7SYhCZOgxbOqXYcSwWNGC8uFarYZisYiFhYVeD+vckGQZzokfYp2pVjh3QqoXFnkMtJIoTUWPA0opTMuGpklo1ERLz3JREDmVooNK0UF2THTcyuQklIuC3KlXGZIpikaNgxEDElchyQSSTOA4rgqJBY/ZfNAue8dhkXGimx/0pyVuBpfoieBPAnjKOd+A+Mz7HXf97wD4C+59CeIXi6EvzCkjDCr6tQbrdCKno+yYiHolGErczK9xCRLGm3k3XhCzJfJumNsBizsMTrUBALCOBLljHpQBAMZuyVX21GEdNWAdNeAQwNqqQEqrqHy6DWUihfKHW5DSKmoP90FkKsge3YZd1sVS0UXeT7UhSKWqDjjMfcx9ssfL6AHjgozyxu4qk4IZPa3n3cEFDmznXethrCmHYeJQURQsLS3h2bNnAIbDNu9BkiQw56Rf2OBXzvDPk/j/qN95K9ixSgQxq5CoCpmKXB5VSQhlj5yALCnQ5AQ0OQFVkSHLElIJFZJEkdAUJDQR2DyeT6LRsHHtWhqHhzoOD3XcWsnj9esa7t4dx+vXNaytjqNYq2JxdgpHpRoWZidQqxuYnshheiKHum5iIp+D7VjIJccBAKqc8BU9MlUEOUVVQfgQComoflaPF8QsFhI6+yDxddJX9Dh11HE/nyGyz49qsFOg2/T4AoDNwONX7joA+BcAfgTgR5zzCufcBvAx3BkmCObtPwH4SULIAgDCOQ/uK4RhDDAeJgzbz2dYCqd0Oo2bN2+CMTGbeO/evaEooOQ++BBjjLvKFQZKCSyLQVEJTEMEARoNBlUTrT2NBoeWFJYsVaMwdQ5ZIbAsDkkGDMuCIqniywDzSB7uHyd03Ji/tSjB0x8Y/N8zF98H8Lvu/VnO+bZ7fwfArHv/9wH8FIB/BeDXAq/9zwC0hvh1YxlhhEGowaLhytFw4WgoMcJqHt/+FLBsccaFVcp9v3TqBjjjsEo1QCKwjqogEoWxUwKRKYztCpy6BadmwqmZsI8aoJqM8odb0OZzKPzhcySWxlB6fxPKRArVL3aar6tZ7mLCPKgKW5dnCysJBZHtkkxO3Wx23XLJnqAKCVxYcEPWtbjrFbyNey6CYalXhhGLi4t+9zBVVQfeNu9BkiVfqXTcB1KTzPDUKS7h4Yc2k6Zyh6gBskQQPrK7TpMTkIgETREkT1JNQ1US7qIioSqQZQmqIkPTFMgSRS4j7FbzMzkUKw2sLE9gZXkCewdV3F6dxOvdMtZWJ7FzUEY+r6Bes3Hj2hQqtQbmp8dQ103UdRMzE2MwLRNjqUkw5iCt5UJqHurazHw1UiCcOWjbil6H6HVqj9N/4HPe16KT02JUg50ClyZR4Jz/Dpqsm4f/CDFrlATwQwBPAPw/AOyj25LhPgaldOiIkWEgD4IYpnDD2VnxPpjJZHo8ku6BUtqn5MbZQEDAhkcBMzQghKgA/jyAvx59jnPOCSHcvW9DFCNR/AcAf+5CBznCCDEY1WDHgHGADk/NErXRDDqG6VwIIZifnwcAzMzM9Hg03YPkTnINCwgIeJcyCvsB3I0WGHSMarDTo9tEzxaApcDjRXddO/wAwP8ZQALAb0AUF/fRQZGh6zp++MMfnmuw/QLHcWAYxtCcDwBUq9WhOp9arYYPPvhgKMiexcVFLC01/0w3Nzfx6tWrHo7ovOAwTRMcwNar1/66uO24/xxvruHefSaai3tZPAA4T4JzDQx5cM4gcYY0c5B0260383kYGOXgGoejiBlnxsSHK2fuEQM1A2ccIO46gqaZAmLWRaEaUkoa1zLX/XWEAIQSEAJQSkAJAaUU1CagdQLakPzfT0rEfUYk1AhFA5II/CMUFDoIMUFQDcwaiQOEHgfmm1pBjr0XB/Ge8J+O3WYA8GcAfMQ533Uf7xJC5jnn24SQeQB7He2lR/UWIeS7AP5bCFnzP+Sc/3LkeQ3A/wDhgT8E8LOc8xeXPc4RzoxLq8FqtVpnn/Gx39F5++e4++fBIyvdt23/S7+bbcODCiDivuemxJsuT4k3XT7tAISB39QASsDNvLtbsS9bFV/AyeoyjhIynJ9Ko5RW4PyxNIopBczIgmqSyNcBQGQK4hJDRHZvJd19bLqPqXhPNdw/dpMADXcSjEA8596KF7j/Bd4buL8+ANJyp+V5x3FgmuZQ1WDDVFMOVw0m/ibq9QZqH38CEqqRo3/gPHAvLFWLr8W4T7ZwLoMjDc6Tbj3GIXEHCc6gcgbOmZ+fyLir+mNiT5A4WEIQHY7sKq7nmB/a/I1FG5oq+7fmnIMszWMm+yYIbNhpBsWUwKgYn1yVwDmHbIqv0FJRBiEElFDYhMIhFHpApURBQYgDgjoI0UFQCliuSICACVZTretat4mifWFh27ab0Vlqu82AYGBrsF7VX90mev4VgP8nIeTXAFwDsAbg/WO2/yFE0OAW53wPAAgh+xCeu5857kCJRALf+c53Wp8IvK+QaCeHoAeaeZJgHrgPEDfoj3jdHCwRqMcMB8x0wC0HrGHD0UXwq1M3YFcbovtCRYddbcA6qsMuG7AO67DLuvCB13Q0bFEAmI6Fhm3AZg4MxwRmUkh+/z42f03UVQ5nUGhTdqtKIlQsKWuQqYykrEKVFPE4l4AykXRvU5DzoiuBMpaClE1ASmmQM0nImSSklAqaUEA1CVSVQTUJRHHfiFQZVKGATMEpwCkRBRGFe9ssTsTFgmgn5xct7mV2n//hf/ph/M9nQPHRRx/h/v37A915y0O1WgXnHLZtgzGGpaWlUNExiNjY2IAsy0ORNwSIThw7Ozu4d+9er4fSNfzwh0PxnvCX0ZQMA+Iz768A+GX39v918i6I/z55mXBDdn8DwJ+CsPR8QAj5V5zzLwOb/QKAAud8lRDyfQC/AuBnL32wI5wVl1aDpdPpzmqw4PqWLBreDBxmXj3m3gJ+LQbHzbexHDDbvTUcUZ8ZNphpAwSBUGQdzLJhl+rgDoO5XxfWre0KAAi7VlkQM1JKxcEskJjOwPjdh5j+5k3svv8Ms9+6heKHm8i/swB9s4Tk8jiYLqwpcj4BOSdqLW0uB84Y1KkUuMOgTuVAJAo5lwKVJf8YRKIgmgSqUFBVBlEoqCKBSCRcdwGh2kvUWoH6K1p7AS31V7VaxbPnz/D2228f9yMcKAzJ5wcA8fMBBFmaTCYvuQbrrjrKI2w++uhj3Lt/F4mE5q5lzee5S9zA9tdxOG5mIAODLbIQ4YDBgs1MWKwBi4m/UdNpwGIGDKcGkzVg2FUYtg7TqsG0dDTMGgxbbNsw6zDsBkzLhGnZMC0bjHPUdB2apqBQrmE8n8b2YREAMD8zhq2DApbmJ7F1dISl+Unslkv4yek/j9fmU0jZfZSrOmZyYwAA3dQxk5+H5QjrFiUS0oksNDmJpJKCJmeg0iQUKr4rKFISCSkNhSYgUxUKTYJCAfHCpiEWCvFeIR4TCHpIQrDbFgl0Jgt36Tq5njg8PMTBwQHu3LnTwU+1r5U/A1mD9bL+6qS9+u9CFAN3CCGvCCG/QAj5aULIKwDfAfD/IYT8PgBwzn8M4J8B+BLA/xfA/4XH9/KFu30BYubox4HVPwQwA+DT48Z1UVJOfszP3mdd4yS+gRAyIjcvK7eZ/5gSMQvPOINMJTDOoFAZcBjgztA7nEGTFBiOhYSsISFrMB0LSVmDzRxokgKbOVCoDMYZiERDxyASFTNJ3lgiChShCAgwwiT82F157DW6ihgWKbRpmvjss8/AGEOlUsGXX3558osGAMMiS/UwTFZBYDik94SQNMSH9L8IrP5lAH+KEPIEwP/afXwc/rMLGl4n+BaAdc75M865CeCfQnyhDyIYbPg/AviTZJj+sAYQ/VqDnTjuKMlzFvh8D2/m2QRCjP2OW4YFZrghzIYFZtlwKrobulwLkTxiIk73D1F7tA8lq6G4eYCJ+9fw/AdfYvrt63j+gy+Re2Meex+9gDqTRu3hvv8au6TD3K8BAPStEogiwTwogyoybDenx6k2/MwgZjlCxenmCYn26m4gczCLiCPSUv5018nDsNQrw4j9/X08ffoUAPD69esBVvKEwRkHDX63iP16GcyiCSuIm/+aOTYSaeb0SF5mD1GhSEkokgpNTkKWVGhK0g9iTqopQbqoSdFpK6mCEoLxfAa2zTA/PYZKVcfy4jSWF6dRKNWwcn0Gh8UKVq7PolSp48a1KVg2w8R4GvWGifnJSZc4MkMkDwCkE1kobmaQTMX4gtlCXlaPdz5eAHM0hDkc9BLTgv6ckbqiRh7smnLAa7Ce1V8nKno453+5zVP/ss32fxPA3+x0AJzzNyKP/2sA/3Wnr+8bSC7LGvlyRhMy7LIBSZbBXEWPKimomHWokoKa1QBhMohEwThHUtZQsxrIaxmUDMH6z6TGUTHrmEmNo2Y1MJnMw3AsZNMZMMOGMpEMkT3B8QDwiZ8gAdTxe8aoxgcguiVYloVkMtnroZwL6+vrWF5ehiRJmJiYwMuXL3F4eIjJycleD+1csCxrKDpXeBg24moYzodzXgMwGVl3CNEBopPX/zsA+QcPHvAeTZjFBfV+u902nHObEFKCOOeDSxnhCC3o1xqsYyKhkzDhaAizi6YC27W7MjTDmD3VteOproXKmumWUPxYNpya4ZI9XgeuulAA6bZP1CgTKRy9PkJ2YQKP/s2PcPvde/jih5/g/tffxOP3f4zVd+5g5/MNzNxeQONFAQCgzWf9cObk8jj0l0WkVqZgHpShzY/DKtWgTubg1A0AAFUkMW6ZAA4Hl8T4iex6dr3zjHtfaLc+BoRzcHfybkT09B8YY1hfX8e7774LAFheXsZ7772H+fl5KIpySaPwvOLdhWVbUBS1o2OI/BtBXnBw8YgI0pOA+6QII4Kj9oOYqQIGBzJ3wKXjMxkNm4JSCQ2zhlwmibpuYmo8g2KljqX5CewfCeL3xrUp7B+Vsbw4jYNCFUtzkyhW6sgmU9izLMxOTKFh1jCTn3f3q/skTzY5BolISKppyFSBQpN+VzCJiGshyB4lFMIM19YVDKMOXpuTcBbSp/MarH/rtAGvwXpWfw02vdcJzvHDDClfIioeQknTo+2ROx7Z4xErslDbUE0Gd4RSx1PkeAqdpKyBOUKZo0oKGrbhkzwzqXHMpMZR0CuYTOZRNKoYT+RQt3SklQRsw4Sc08AMWxzDJXt8dU+AdCJSzIU4KXywf//eLx2qqsI0zV4P41yoVCqoVquYm5vz1925cwePHz8e+BA90zShqurJGw4IhoEYCWLYzqdPMUUI+VFg+T/1ekAjjBCLAKET2349oHLxlC9w1S/+ffcxsxxB9ugmmG6CM+Z23WJw6iaYLogdu6SDGTacmgVzvwaqyaCajP1XO8ikM9jb28etW7fw4fsf4u4bd/Hh+x9i5c01PPz4S0zfmsfe4y3IOQ1yToN11IBd1kE1GY3nBSgTSTReHEJKaTAPypA0BU61AUIpCKXC6u8pkdzza54L3OsQPX+ESK+2RFnMekKHk+gZ9HPa3NzE9PS0P2EoyzKWl5exvr5+ySPp3mexp0jhnMeqkAmIbz8KtgP3bEhx6hZP1eOpYjyFjEKTUGkCiiQIFVVKQHHbqqvuklTT/qLJCWSTY5AlBeOZHBjjmJucgG5YWJiZxMLMJOq6iaW5adQbJhZnp6CbFuYnJ8EYx1g2D8sxMZNfEDmMnGEiPQNKpFaSR0r6pI5E1dDYg2oe6luzgucORFulB69bN35undVgoxrtnOjLGuzSum6NcAwcHlLgDAuGyX6iKMpAEz2cczx69Ah37twJvdknk0lMTU3h1atXuH79eg9HeD6YpnmJM2IXj2FrjzsieoI4jSfjVDjgnH/jmOc7Cer1tnlFCJEB5CFCAUcY4fzw8nla1p/SqtRtMA5Iw1GrAIAkBVtdDwc8VfWgTuiYpomtrS18+9vhSfz5+Xlsbm6iWq0OdifUwebgWkChgBN7aM5LEHGjGkygJzVYz+qv4flk6zb80OGYTBsaVPpE1DMuYUM1GUSmoJrg0qgqw+EMDmdIyCosZiMhq7CZAxWSa91iyKop36Z10CjhoFHCbHoCBb3iqnvKGE9kUbN0aBMZOHULci4B7jBQTWodl0Rb1Einvxanf4n3oTwsSCaT0HX95A37FHt7e0gkEsjn8y3PLS8vY3Nzc6CJLMMwhiIo28OwEVcjoqcJUWJ0/18H+ADAGiFk2W1R+n2IIMMgvGBDAPiLAP4tH/Rp9BEuBBf1axFVtkTzeTz7FjgHtxyAMd+2BYgGGYRS2MUGiERhHTVEdo+r7rFLOohEUSwWUSwWkdcy2D/Yx3g2j4+/+gxvLd/Ff/zwfbxz9028/8GPsLqygsdfPsbkwgyKrw5QfCVU9Ey3YWyXIecTqK8fQp3JwNgtCVVPoQqiyHAaBpyGsG9xx5XuuDk9CCiTEAifRsx19VVPHV5zRVaGjuhJJBJoNBq9HsaZEbTNB0EIwZ07d/Do0aNLVix17/PYNK3YeqW9xSgaMCzULCJDRtyXiOIHFcu0qZKRXNWMSpuqnqCKR1XcrB4ljbSWhSYnkEuOg1IJk7kpMMYwOz4D0zZh2iYWpuZg2ibmJ2dhWiZmx2fgcAcZeRwW6pjOCsvWWGoSY6lJSFRCLjkGhapIazlXVZT0A5gVKSlyetyxUkJ9VQ+BhKhtq/Vncbp8nk6sXkAnNdjVqc96VIP1rP4aWKLn3OceUsORcBZNuz+GwNUKhh77t7Rp2fK3kZuLQiUoVALjHJqkgHGOhKwBDgeRKZJu8PJEIoeSUcVcehKapOCwUcJcesK9nUTJqCE/OQarUIc6nYZTNyGlVXCH+3Jk//h+FwfqdnAQ3bRIoLuD/5iSZhj1Ob+Uqao6VERPKpVCvV7v9TDOBMdx8PTpU6ytrcU+78mHvYDAQYNoZT486jEAAz1zGYdh+/kMIjjnNoBfBPD7AL4C8M845z8mhPw3hJA/7272jwBMEkLWAfwSgP+yN6MdYSDRre+pHK2Trm5Oj1f7cVsQJ45ugUgUTt2EUzdBFRlWsQYprcLYroAmZFhH4rPby+qp1KpIKwmklQReVw8wJmewpxfwxtQt/KfHn+AbS2/g//fZ+/jayhv48MtPsTy3hBfPXyCTyyKTy8I4qsKpW6516wjqdBr19UPIY0lYhSokTYVdbfgWf4+I8vKFPLtWiMSKyyaKu6a++umYDJQhzOgZ5BoszjYfxNjYGFRVxf7+fuzzF4fufLmv12tIpZLuHuPICwTsWyRi32qamKJWrpB1y7NE+TauhCBXpCRUKeGHMYsgZte6pSSR1nLQ5IQgaYiEicw0AGBubAFzYwuwHRGwzLgjbhnDRGYGlGnIZbOghCKXGAMlFJRQZBNjoBHLlkqTzQBm/1YRi3sOXjetVpsajQQ0H/+zOmsoM2PsmDDmq0Py9Aq9rL9G1i03M4ww3vq77n5Ic/e+ty5IghBFAjEIqCKBSRRUkcEkC0QioAkZKANSWoFTMyHJrrrHsUCJIH4s5kC2hQLI4QxpJYmGbWA8kUPFrGEuLXKnCnoF85kpHOllzI1No1aoIH9jCnbZQPKmaPupTqf94odmZEE8SVSQPAiokbxsoQucYR+GTJsgBrnI2NjYwPz8PDRNa7vN/Pw8Xr16NZDy4WHL5wGG75wsK37G76rCaz176cfl/F8D+NeRdf9V4L6OE9pqjzBCx+gG1+AFMQM+ueFl3TDLAZEo7HIdRBFKCXOvAimtofHiCMpEErWH+5BSKhovCpDSKsr7BSRlFQeNEgBgPJHFzt4OxtdW8dHuJ3h3Zg3/aeMzfGv+viB95u7iy1fruDNxHQdHQkU/kRbKWHO/htTqJOrrh8i8OQtjq4TkzUnY1QbUqRwcl+BRNBXMciApkjgfN5+HRN8GvOvlCcr58Z1gT8IwKSnT6TQqlUqvh3FqcM7x8OFD3L1799ifxdraGj766CNMTU1d8qTI+cOZ6/U6Uqn4ZhiCmGAxigcKAgbukh0cXGzpDke8yt3SzesBAzhtDWG20VRJUUJhSwpkx4IiKTBsHYqkwHIsqHICpq0jmUmjYYow9qnsHAxbx0R6GhazMJGZBmMOFJKAokhQ5XEAQFJN+/v3OmwpNOmTTsHHHukDINBpiwqypyWE2SN4muRXNNco/rqe7u9a1GBxX/mH4/3htOhFDdar+ms0xRqF+0Yc+nB1W5KHLFABwgQB+xahQr0jpVVwm0HOJcB0tzOW2wo0pQnmOyFroIRAlcQXoKQsvohn1ZSv7KmYdVTMOqZT4ygZVcxmJ1GpVZFbmIB11IA2n4VTM/3906QCmnS/UElEjCfScj14nn6otHi/6RicAMepfgY90yYKWZZh2/bAzZIZhoGdnR3cuHHj2O08+fDDhw8H7hyr1epQddwCho8YGbbzGWGEEbqEaAgxAm3GQ081w5mBphWKGRaopsCuNmBXG5AzSZj7FRGQ/LwAdSYD/VUJykQS1YMSkrKGgl5BWkkirSSxWzvCuJVARbOwMraAT/ae4I2pW3h/+0u8MbWMz/ef4mZ+Hq8qe0gpCaSUBCzLglmqQ85paDwvQLuWc0OZU7AKNVBN8S1khFIwyw6NPXiufiBzlz92ZVmG4xzfmWiQkE6nUa1Wez2MU2Nvbw/JZBK5XO7Y7RKJBObm5rCxsXFJIwvifF/2q9UaMplmDXacqidKYETJjqiFy7NxSQElj0eqKFISmpR2bzPQpAwUKYmEnHZbraeR1nLiNpGFpohwZkVSfSuW7N73bkWA8zgIIcgmxlzr15ivGEqrOf94ipSMJXlUKeG3hg9a0ATJE1X2RG1aguSJ/ymd/Su7acapxK8myXPVMLBEz6V9GQ1eoYDtiRACZtg+iUIUWeTzSATEbaWpTCTBDBvatRzssgFtLgttLgvdNJBLZmA6FtKKIH0oJ0NlbRg26xYgcnoGTdXz+PFjrK6udvS7lc/noWlaD+TD50OpVIrNHhpkDJuiZ9jO5/zgF7CMMMLl4dw1WFyXqSgiGTYhZQ8l4JYDIkuwqw1IKQ1SSoNVqEKZTEPfLCGxlEfj+RG0+SzqmwWksmkU9AoyagoFvYyCXkZey2Bvdw+JsTSel7bPd059hGGbbEun0wNXf51km4/ixo0b2N7ehmEYFzyy7qJUKp1IZA0UhvDj1LJMKEqwBrvqJM/VqcEG1ro1aKqDE1G3gJQCtQYwzsSsEXOQ1wRLrtsGppJ5VPU6xmYmYO7XkL4zDbusI3lzAsxwoEyk/N0RRWqqeShtWrZo0MIVMw7SvBWqnTbPt3vsQlXVgZTZHod8Po9SqTQw6pFSqQTDMDA9Pd3xa27fvo0PP/ywB/Lhs6NcLmN2drbXw+gqhk0BMyJ6guA9s26NMEK3MEw1GK+aQFq8317PzeLR0QZWxhawXniFxewMtqsHGE9kYTpi8ooSivzkGOqbBeTfWUD9yQGy78zD2K4geWvCt25xT8mjKX4+j7BsXcC14wjVY559PpVKtX3JIIEQ4pNXg/JZsrGxgWvXrh1rmw9CkiSsrKzgyZMnePPNNy94dFGczcLFOYdlWdA0rW0g7Un2LfFlhENI2wgACZSEBXB+Y2K3LCVEAmUSTAAqmvYtSiTYzAQhEhxmQqYKbEmBwxwwmYExB1AAiwkSNKmm4XAnYM2SAFsGVTgUJQGZKqI9umvF8jJ4hMIonBsUVvMo7rkLNQ8lEprZPFIonyg+gDmo9jk/KSP+boanpjwfrlYNNhjf5GJwpiKDkLbkBfeIjcA63yftESSukkfYK4lvewoSKtT1QMq5BJjhQJ3JwDqqI3lzHOZ+DeZ+DfkbU6jqdUzmxmE6FrJqCqhYUMeSUKgEmUpQqAxNav5RZtQUDMdCLp+DVRD7s47q0OZzYIawhgEAVWRQRQaRKKgiifFJxA9m9scPN6PHXUggkDrqCeeBDmTHgQeeTyaTA90hIQ5jY2MoFou9HkZH8Nqpn+QLj0LTtB7Kh08PzjlqtdrQFLOAm98wRNkKwPARVyOMcNXRM6KHcVHLWQ6IIoEZFqSUBqeiw6nokDNJGFslaPNZNF4UkFgaQ+N5Acn5PIrFIsYTWRw2SshrGeS1DI70MvJqBjYYppJ57NaOMJMax07tEOOJLI70MlRJgc0cNGwDDdtAWkmgcHCE9PIkag/3kVqbgr5ZgjqThl1sQNJUMD2gaGbxXyou8hoOYw2Wz+cHpgbTdR27u7u4fv36qV43MzMDXddRLpcvaGTH4fQ1R9A6H8yNiSMpfMtSyL7ldeBqfUyJ5HerIpBCFi4vnFl0uxKBzKqUgEIT0KQMEq6VS5MzSMhpJJU0kkpKdOJSEsglxpFLjCOpppHx7F3ubRLjkBMMCblpC1Np0g9/Vqh3rNZ1LXatgE2Lel23fLta0KLWvDZxP5MgEXTafB4gat0antpyhJMx1ERPkHhoJXdI6zbudsHOUyRIhABNRYxEA7YtQajQhPgiI6U0cJuJjlg1E6nVKZh7VWTemEXmjVnUNwuYXJ5FqVrG1MQkTMeCUucgWQ0ylXw7V0pJQJUUqJICiVCkNGEFSyzmYZcNJJbGwiRPUhFjcRcviJkocmvHLS+QOdiBK3BdzotBDi9uh0Eiera3t5HNZs8UrDxI8mEvPHqYSJFBmrHsFMN4TudBj9qrjzBC19BTRQ/nIBIFtxxQRYJTN3zrll1tQJvLwdiuCJLnRQHJ5XHUXhcxNjaGw0YJ44ksCnoFBb2CMS2DilmDRCgqZh0pJYGapSMha7CZyLjRJAU1S8dEIoeJRA47tSNMXZ/F0foOMm/OovrFLhJLeRjbFcjZBBxDdP/invWsQ4Syic55fYexBpucnMTBwUGvh9ERnjx5gpWVlVMro3uflxg3G94eh4eHmJyc6GCvrdchLqvHI0PEbbBDVZjsESSLS7ZIguxRqEvKBAgflTbzezRZ5OoklZxPDCXktEsE5aDJaWhyGpKVg5IgYcJISkOT0ki4mUDB43rdtYIkT/P8JBAiIY7UChI2wc/w40KYzwrHsSFJ3jUd4SrVYENN9JwLPrETIEYC94VShoYzegBQTZA9cs4lZZbysI7qSN+dgb5Zgr5ZwtiDJVRfHmHm9gLKpTImxifAKyaUfBIJWQPjDOOJLGzmIKUlkdKSkKkEqslQJlLgNoM2n3VJHqFkkNJqMwzaVRY1b5uKHo/wISQQJu2eZ6i1OgncAse/N8Q8N2xBgABAKYWmaX1fPNm2jefPn2NlZeVMrw/Kh/sdosiY7PUwugrRwWJ4FErAiOgZYYRhQz9Yt4hERDcrN/zYqRsijPmgCm0+C32ziOTNcTSeF5C+JiZqJpN5FPQKxhNZjCeyKBpVpJUkHMOCmkyAcaG+UaiMhm1gTMvgoFHCbHoCryp7eFXZw9LiIjafvcT029dR/HAT2Xfm0XhRgDafhV3RIWkqOGOtE2knIKQsP+fkRTo1eJk2J2F8fHwgJtuKxSJM0zyVbT4Ib5JuZ2enyyPrPg4ODjE1NeU/Pk7VE2wlHlauBBU+zWBmCgXUJ0qCZE/YKqXQhCBfpCb54hE+HkHjkT0Jd0nKeSTlvL9epUn/OWKmkEgp/mtVqbn/qIpHpopPMoWVPF4AswS/41bAthUKn44onRC4guHreDY1DyB44/bt1UcYZlyNn3q7v4sgieHbmNBqYQratlw1j2ffAiWuRYpC0hQQiUJKCT+uMiEUPcmb4zD3qsi+M4/sO/Oorx9i4hvXUXt+iKm1eRjVBpKODJrTIBGKfCYHw7GQnxyDY9twbBvqdMbt5qVAzifc/ff3l0FJkmDbdq+H0VVMTU31/YzS8+fPsbS0dK4v1p58uFQqdXFk3cf+/n6oyBgGDCvRM7JuueAc4Kz7ywgjXCJYGzvShcPvdkrAHQ6qKYLscRU9Tt2AOpWBuV9DYmlMkD3L42hslzA+NYHDRgkzbhdT07EwpmXQsA2Qqg2SU8E4R1pJoGLWfAvXzfw8XpS2sbq0jNWlZTzdeI7lr93G9ifPe3MNOsAwKnoopUgkEqjV0lDHJAABAABJREFUar0eSlt4tvk7d+6cS2m8urqK58+f93DC9OSx27YNy7KQSCQuYTyXB0eXICWG5zNVkDwjJY+PK1aDDTTR0w8zSt0CrdrgmdNnYxOJCDWPIol8noQCmlCElUxTwvk8UqBNPG1mD/mt1bv8PjCIXRJOwuzsLHZ3d3s9jLZoNBo4ODjA4uLiufbjyYcfPXrUt39nhmGAMTZ0RUa9Xh+YwO9OMcroGWGE4cK5PxdCE9d98CWkbIJkTz85MvlHV1D5dBvpu9PCujWWBLNskKBlJ3A/qPC5yC9fkiQNnaoa6P8abHt7G7lc7ky2+SBUVcXCwgKeP+8lmXj87+f+/j6mp1sn2uJVJ6R1m5isnrD6xVP2CGWMl9dDXbWMQhMhG5ewciV8ZU+w5bomC9uVp9JRqGfvSrcszJCRSqu+gkfYs1Qk/Jbq4njBtuphJY/7r0XNE1A0RdVNATVPt21blmVBlge299II58TAEj2EkIv/EAuSHyRMjgRzeuDl81DqW7eklAbOGNSpjMjpWZuEuVcFAOS+voDG8wLGHixB3ywhe2sKKBjAZBKJsTSYaSO3MAG7rCO9PIn08qRo0z6fFYqhtAoprYJqkrifVH2Sx7duJVTfUhYcJ5Fd61kge6gliJkgPrQaAWlxBwXKMM4oJRIJcM6h63qvhxKLR48e4fbt213pmNXv8uGdnR3Mzc31ehhdxzAqejjnA9PF7TJwlfzhIwwnuj4BEFdSxGQKijvuY0UCGANNKGCWDWbZkLIJ2BUd6nQa5l4VyeUJGNsVpJbGUTkqYTo/iSO9jPFEDjVLR83SkVVTYGUd8lgSaTejZ9pV89waW8B6YRP3F1fx1cYTfLXxBHe/dh/PP36MpZ+6h8M/fIqxn7yO2sN9JG+Ow6kafl4jJCoW7xQDkQBdRxsLvWVZrU8MMGZmZvqW6PFs86urq13Z39LSEvb393scqt3+d3V7++QaLD6bJ7DuWLJHCpE9XkBzkOyR3Hwcn5ChapPwcS1WCdea5Vm6lGBuT2ARBE4a4BQJxc3nkYPPCzLJC2L27Fq+xcztrkXchYaIHxo6n3gLW7zdrfncWd43yMg6H4OrVIMNbOVNiPjlbX3ixBe2bxtOIkSHu72ngvHzeCgBZNrsuuWukxKudUsThIuU0gCJQJ3JgOm2T/Z4Ni7jdRnZd+ZhlwykVBVsRigTREetBjL3Z2EdNWAdNZBaFWSPOpMBkSjknAaakCGlVUBy1TuUtih6qCKByMJqRiQayucJZg+1I29CHbfirlnsNRY36XQa1Wr1hB/I4GFubq4vyY+joyNwzruaWdN7+XB7DDPRk0wmez2MrsFxnBHJEwAHwMG6vowwwkAiRtnT0gUVYZLEt9IDIh/RYX7tw3QL8lgSTs2ENp8VZM/NcZh7NeTnJ1GpVTGTGkfFrPs5PaZjQTowIc9lYDPHD2u+mb+GF6VtvDm7ii9frePtr72Nt7/2Nh5/8hXWfuptbP3hI8x89y5K779C7usLMLYrUMbTfkcwPzfR7YIqxh8+V19ZfQHcTyaTGboaTFEUJBIJVCqVXg+lBZ5tvlvqVUop1tbW+iAvsfWX0zQtmKbRVrnUPqsnmNfjfb9oR/aEyREayr3xCB8ZzZDmZl6O34krQPo01T0Zf1Fd9Y/qridOAqoqu/toEjtBcieYx+Md3yd5XBKq2WHrGJIncK3CAczdI3mA4Zw8PA+uWg02sNV3W6Ln2Be17ARAtDtXMIjYJUAiViciUVfR4y6UiJklV9FDE8JKJWkqJE3cVyZSPtmTWpsUap27M7BLOpLL45AqDtiYAm0+C6dmIfPmLMz9mt+pyy7pSN6cEN28ZtIgMoWcS4jjpDQ3G6gZyEw1tankCeQK+RauYHERLbRI4DbuunWIfD7f9xkvZ8H8/Dxev37dV5YmzjkeP36MO3fudHW//SEfbkWlUoGiKNA0rddD6Sps2waldKiIkUajMSoyRhjhKqIb5IVXewEtk1EeeeI1wwBcNbXlQJlIwalb0K7lYB3VkVjKw9yvIj85hopZx0xqzG+XntcyYDs1yHNZJGQNpmNhLj2Bndoh7kxcx/rhJt6+/wYeffYQjz57iPs/9TW8+A9f4vqfeQtHf/AME3/8FmqP9pG8OeEHQgMITA66nYVk9zZgoW+5XoFTjJJdp0UulxvKGmxxcRGbm5u9HkYI9Xq9K7b5KKampmDbNgqFQlf3e168fr2Fa9euXcqxggoeP8w4ZOVSQCG7i9eVK9FK+rjET3AJWrZUmoBdlZDOay3EjqcWCgYuUyhhFU+AzAkRU+1IHhImtbyzFf+ftwZsvnmMiJ6rjYH9NkEI6Y4kNUhmtLOVEoTbrHsWKJkKZY/UnLERyhriq3mklCZsVUnF75jFbYbEUh7MsJFcFm0JtekMiKusSa1Owi7pPsFjl3Rf0ZNYygMA1KmMrxqiiuwej/qBhP0ATdOg63pfESLdgKIoyOfzODw87PVQfLx69QoTExMX8mbeH/LhMF6+fInr16/3ehhdR7lcRi6X6/UwuoparTYqMkLgANgFLCOMcLloCWRuR0yctgQgAGE8vL9gUwzaJE2oIvlKailonXcYlIkkmG5Dm8/5jTHsso7xqQnULB1TyTymknk0bAPZAoDZFDRJQVpJomGbWMzO4HX1AHeX1/B8/Tnu/8TbuP8Tb2PjPz7Eynffxf7/9AjT//ldlD/cQvbdazD3K1DGz5fN0k0M62Tb1NQUisViXzX7ePz4cdds81HcuXMHjx8/7nEt3fxj5Jzj9evtUxE9YeIiRtUDoFXV0/024yehXraRzvVXnuDp1Tzh7UdETxRXqwYbaKKnE0VP03rU6Y6jOTVufo0nF5ZpM+C4y0F6co3BznYnMIsooh07kSmIHG4FDxoYf6DbWIttraMDiRsecy0IIUilUn1FEHQL169fx8uXL3s9DAAiaO3ly5e4devWhezfkw8/fvz4QvZ/WliWhVKpNHRt1QGgVCohn8/3ehhdxajIGGGE4cOZJts8lXTL+njbvD+5FphkC9nQPTtUN1C2gFx3ciyYZfsWel9F7amPXKIqmpUYVCuF4gViLPMd5SQSYd3q5w5VZwUhBNeuXcPW1lavhwIAODw87LptPoh0Oo2xsTG8fv36QvbfOcTv3MHBAcbGxk4M+D2eoIiQPW5WTZDsaW277j0OKHwCyp6m0qZ5X9i5WtU57Ra9wpAby/jWraiCx1MNUcghJQ+NHN/LFIoNXwZ8NU/cNek2hrHBxwidY6CJnn4ImWtauCioKofaq3vyXTmTFOqbtAZlIgVlIgUiUWjzWQCiTbqUVqFWGejaGJhhI7U66Yc4p9YmwQwHiaU8uMOgzorXSdmEr+ohigQpqfnWLSmhRAKjA9YzTzIskfbhyiRqaYsQXx1iWKXD2WwWnHOUy+VeDwVPnz7FzZs3LzRVf2pqCo7j9IV8eGNjA0tLS0PZLrJUKg2domdE9LTiKgUBjjCcOJN9/iJAKYjcJHy8phRSRtRhykRS1E1uVmJiMR9S9dQsHbPZSViOBRkUXCJQJQV5LY26pePG7CJ2Xm9j9Z072Pr4KbY+fopbf+pt7P3bx5j/372N0vubGP9fLUN/WURiaQLMsCBnXeuWIjcX30JPmla0SNh0u/oqlJV4ChBCIMtyf/ycuoyFhQVsbW21qsouGZxzPHnypOu2+Shu3bqFFy9e9FzFxLnIIrp580ZH20ezeuKUPf52ge5TzW1bA5qjpIqf2xMhfTxCJmizkogaWRR3UUGhwDY5NE1r2rJ8YidA+BxD8HikVKckz0lh1edV8wCAaZqjrqcRXKUabGCJHkrp2TsfBQOZgzk9vPl86Dn375ZIEfuWQkEUYd+iivgAl9xuC0pefLFRJjL+LQlYq+RsAlSToUwkIec0SGkFSUgwMxTJm+PgDkdyeRxMt0Vx4lm2pgXJI+dToIoMOZsUVrGkZ+FSIeeT7vikpvoougSUPOEiI3CL8DUKX8POLnU+n+8LMuQisLKygmfPnvV0DLVaDaVS6VK80v0gH7YsC3t7e1hYWOjZGC4SwzjzMiJ6WnGVggBHGE5QSmEYRmcbR63x0dqrZfvAugAZ0sy2aTbCoIrkdh1VwSzHb0pBqMgxpAlZTK7JFOpMBtxmvoVrYnYKE7NTqBsNTE1Mgu83kF+YBCUECpUxkc6jWq5g8d5NHD56jRt/7A3c+GNv4PAPn+LaT7+Fwn94gck/uYba432k12bgVHQo4xlwh/lNOeRMItD4IqBGCmYloqlk4pS01KD+NTvpusZgWGswRVEwMzPTc1XPRdrmg1AUBTdu3Oh5zXl4eIhkMnWq842SFVGyh7QhQsJWLinwOKzuCapomiofOZDh0yR7vA5ZzcXL9pFg1hkSKTVE8njEDnX3GSV4WlVH4bF01ka9+YfcbZKHMQZKu+9AGXRcpRpsoImeM7Xubvdh6d36ViTE27fkgH2LEoBzn+ShmphV8mZzlPEMmGULssfhUMYzTcVNNgGaVCBlNEhpFcpECgmLgs2KzluJBUHsaAt5aO59dVK0V1fyaUHyZNww5kyy2V5dkdzCR/JzhFrG7MqGvXNrqnrat1U/8Rq2eW5YPeIAMDY2Btu2e1pEPXr0CHfu3LmUN3FPPtzLwspT8wxTWLEHwzCgKMrQfSBbljVq7TnCCEOGM9dgQUQnlEIEUKAeadcMIzihJUvNrqOKe19TQDUZVJNE8wqX7GG6jdSKaIphl3WM35yBUW0g1SAwp1Rkcll/Bnz85gwaLwqY+84qSu9vQplIYvY/v4/Se5uY+u5tVL/cRe7dRVjFGtTZPLjliBrQI5wUyR1jQF0tBybb/PM/4Rp1gDjSLJ/Po1gsdr6TAcKNGzewubnZs66gF22bj2JhYQFHR0c9s+NxzvHs2bNLO9/TIo70oUQJET9iUWKXWtlCNp8KkTo0ZN2KhkKT1pBo7w3LJ3jirWnR8GVxr7skDzB8XVxHOD0G9tsSIaS9oify+x47YxQDTojYNkbN4qt6AnYob2ZGeMXFBzdNCvuMnE2CWw7UyZyQDU9lwRmDMpER6h4qCBtJUyFnkqCagrSahJEkQrUjEUHsUAo5kxQBfxKBnE8JciebAFFkX8kjihrZDyZsLr390qgoChhjPZebXhRu377dM5XL/v4+ZFnG2NjYpR1zZWUFGxsbPfl56rqO/f39oVXzHB4eYmJiotfD6Cocx4EkdTFHY2jAL2AZYYTLA6X02C+cp85HjCJAfsQ2wwhkDVJNEYpmN5BZ3BedR6WMBqrJkPOaUPhoMrRrOTDDRvrONNJ3pmEdNZBbmwF5WYV8R7wHKxMpaPNZ2GUDua8voL5+iKnv3kbl021UPt3G5J9aQ+3hPvLfuA7zsILEtQnR2t1Vc0teRo/U2zJ7fHwcR0dHPR3DRUFRFMzPz2NjY6Mnx78M23wQhBC/5uwFdnd3kclkXNXxKW2EJ6h6vHVBVU87G1eUXGmqZ86H0lEN+YlBVFS3/1mMFNXtcHVqsIEmegCc7gt2SDocsW/FyIqjqh4ekd8SiTTVM5SAaFKI7FHGUgBjUKc6y9yQbcC+ABulT/gEQ5hpkNBqlQqHPOFBZVNoxwhv2wYTExNDW2jkcjkkEgns7e1d6nEZY1hfX8ft27cv9biyLOPGjRt4+vTppR4XEF0tVldXh1LNAwiiZ2pqqtfD6CpGs0kjjDCcoJTGN1ro4PtfVDnMQ3VGWEnNA1YtuMHG8CfciK+YoQkFoBQI5BbKrtq5U0h7BuyJ7hdhRKIt5FTQfhZUMSF0DTrZ+fHbaZo21JNtN27cwM7OztmjHM6IarV6abb5ICYmJkApxcHBwaUe13EcPHv2DKurq4G1nf6SxuM4ssf7F2fjiub2eJap1jbsYSWOZ8WKW8ApqmUd2VymjXqnNYsnquQJW7Wa4249h/C1a80u6h6GMQ5ghNNhoL8xJRKJs72590DkwhmHOtkkfJSJjK/MoQkFcta1X1EKrgq1D1Ek36ZFFTlg2Ur6LdWlhAIppYbVPEpgacnnIX4Ic5jsChcZAOKv0xmu3eTk5KV/KF0m1tbW8PTp00stpF6+fImZmRkkEolLO6aHhYUFFAqFS5UPHx0dwbZtTE9PX9oxLxNesPewBTHXarVRkdECfqX84SMMJ45VVbd9EcITRpdkU1Um0k1VT16oehJLovEFM2xk3piFUzORG8/BGleQWMpDSisgMkVqdRLWUR1jP3kd9fVDTPzxFUz88RXU1w99NU9yaQqOYfqZjFJSA1Fkv0FHsP5qaYoRIbb8Guw0k25RRJ4e5sk2SilWV1cvXeVymbb5KG7fvo0nT55cahD1s2fPsLCw0MaG3dk18ImP0Lp4sif4mqC6pxl43MztaRIvYfLlOLImujSqFlLphLB4BQghGiJ9wsQS9XOD2hM87TN54s4/cM4d4/htq9XqqAZrwdWqwQaa6Emn0+f3iLdDjH0LBM0ZGbfVukcwk4CqB0DTwpVPgTtMWK8gcnu8rB45k4SkKZAzCVBNgZxJImXLMMdV8TibBE0okLIJ16ol+dtKSc31nzdzeXySJ1BY0GAgs+wpeaJqHsQXFl3C+Pj40HrEATFjdv36dTx58uRSjmeaJl6/fo2bN29eyvGiIITgzp07ePTo0aUcz3EcPHz4EPfu3buU4/UC1WoVmUxm6PJ5hrFd/HkhRL5Xp+PDCMMJ4lqpuvZlM6iujoYQEzTrGOJmDnoZhIFQZq/ZBaFEdD+ViOh6KlHIuaRoVpHToEwkQWSK5PIEpLQqbFx3Z0DKJjCmARJ1rVs5cJsh88YsjO0K8t9agr5Zgr5ZQu7dxRDJ4ym3PTUR1WR/nETuoClGu2sSvI17rgNMTU0N9WTbzMwMGGOXpqze39+HoiiXapsPIplMYmpqCpubm5dyvHK5jKOjIywtLR2zVee/kJ3buNoTJ0HCB4FtotauoNonSP5El+JhFRNTYy1qnfDrg1YxEjh2/DiD59oLkgcAKpUKstnsKfY5/LhqNdhAEz2pVKq9qqCdojCyLtp9S6xrFhst9q1I0eFbtzwJMSWgCTmS1yO6Lij5lB/G7OXySCkNNKH6BUoWCdQz8B9LKc33nYvXqO5rFEgJBVR1Z42CKh5v8QKYA8UQKHHzhlxJNImEHkYJrrgZpMB20RbscaCUIpFIXBwp1wdYWFhArVa7lFmzJ0+e4NatWz3NPhkfH4ckSZdSPD5+/BhLS0tDbQE6ODgYOtsWMJzt4kcYYQSBZDJ5rKqno0kjEr4fqrmAptLFszp5dY1v3XJJk0AjCimlgbqKaC/bkCqyIHvSKuRcAtp8FkQiSC6PI7k8Du4wpFYnoZZtkDtjfp5PcnkcTs1C9q15WEd1ZN6cR+bNedjVBpI3p8Es2yd5hNpaEvk8UnNcRJH8EOaQmidGXR2qx05x7Y671mNjY0M92QYA9+7dw5MnT2BZ1oUep1e2+SiWl5fx6tUrmKZ5ocdhjOHLL7/EG2+8MdC2+bDap3UpHJYxMTkWSwqR0D9PvSOHSJ8oERWknaIkT9SqFbKqdXg2nbxB2LYtvosO8M9thPNjoH/6qVSqY/Kg5UMwTv4aJTAiM0zcVfRwSgCp6RUHIS1kD9GEwkZKyO7skioUOa5ViyaUJpGT1HziJy+nUdMcUai4yh1vO0EMqcKu5YUvazKo4hUTbmEhi4XKHtnjWrZ6KBYYdvsWIQRvvPEGHj58eKGFRrlcRr1ex+zs7IUdo1Nchnz44OAAtVoNi4uLF3aMfsDh4SEmJyd7PYyugnMO27ZHHbdiwS5gGWGEy8Wxk21BRGuPoG3cRdSiFJp885phhPJ5gspl99af+JIhZZLuBFtaTK65jSzkfApSWoOUVKHN5fx9JBaF8jDjyDDnVCgTSZcMokitTsFpmEitzMCpG3DqBhILk6LhRpTk8RQ9fk1G/DzHXuEqTLZpmoaVlRX8+Mc/vtDmGL20zQchyzKWl5exvr5+ocdZX1/H7OwsMplMB1ufTtUTJDZaCZHmG4S3Pi6ouanAkUEgo6myadq66AlBzY7jwLIcJBJax+PvJk6nBun8GlcqldFEW1tcnRpsuImeDv92WlQ9IVWL+zyNPO/OMFFFFBktZI9ERbt1mQqFj1uEEHe2x8vWaTknrqBOL44oiMvm8WfMcMIM3DmIounp6UsPLL5sJJNJrKys4PPPP7+QQoNz3lNfeBTJZBLT09MXJh/WdR2PHj3CW2+91Rfne1EwTRO2bfe8cOw2Rt7wEUYYbrStwY57u44hfUI1FxCjbgmEMsteiHHTwiWIFTHhBYiOV1SRBNkjS0JNLdFmzmE2CSkb/36bLHM0chdTGoe6tkZtW6HJRU9NHSa/zpLP4+Eq1GBzc3NQVRUvX768kP0bhtFT23wU8/PzqFarqFQqF7L/vb09VCqVU57v6Wq1421czf212KOAWAVNOK8nSvxE1TniX+GgjImJfEi14yl3goun4om1aZHw2OKJq9bzO52S53QYWedHAAac6DkxjLntjFHw+fZ/YDxmZqnb8FQ6NKFAyadEu3VJBk/JkDMJoeDxbVyqmLHS5KaCR6F+kePJlmmcmkdqFkrN4L+IZSt6XeIKizNeilQqBcdxYBjGOa5W/2N2dhapVAovXrzo+r53d3eRSqX6iqG/KPkwYwyfffYZ7t27B03rzSzLZWFvb68vFFrdRrlcHhUZsbgId3j/+sNHGF50oqoO1V0n1A9xSuoLrb8SCtTpLNTpLKgqQ5vPI2VKMCYVyGNJ0KQCbVa8hyUWJsAtB4n5CSTmJ8ADHVWVXNq34nsTfbHNMJRITRaZeGux0APx1+wMl2R2dha7u7unf+GA4e7du9jZ2bkQq9r6+nrPbfNBBPMSuz25WK/Xsb6+fsaJtosge+IJnyjZ0s46FSR/osvezhFm52YC68KvabFwEQnRHJ7osaLjjjuv0xM8p9t+RPS0w9WqwQaa6PHCAC9SpunB/yB2w4w5hdtqXfzhBVU9VKZ+OLInKSaaS8ZoUsByJfnkjW/tSmvISUnUFFuQOgml2T7UJ3lo2K4VCvojvnWrheQJzhxRhAgfkNOreTrJ5wniqhQat2/fxuHhYVdnz7zWlmtra13bZzcgSRJu3brVVfkw5xxffvklZmZmMDEx0bX99iu2t7cxNzfX62F0HaMiY4QRhhvHNsToNj9D0GyG4VnUPQW1G8zcrItEu3WqSJCzSRBFhpxrWrc8UsazzFNNgTKRAVVkJPIZYc1PqSLIWZFEl1RKoc4238/U8Uwze9HL5YnWfV5WojdWV5HkN8WITLzF1mMnTLpxQjrKQlJVFbIsX2q3zF6AUoq3334bX375JRqNRtf220+2+SDy+TwSiQT29/e7tk/LsvDpp5/ijTfeOIf1+vxkT2vb8VbCx3ttnNIHhIKQeBWP98+xHTTqOrLZTPwWQVInltyJy+FpJXgum+QBRl1PRxAYaKIHOEeL9QhC9q1oF4SWD2C0kj2ujStcgDTJmGAB4nu2VbcoSMpuno9o55lXM6gQwyeDBDnkSZPd/WhNFU9U3dPSSt0jeSIBzEF5cHjWrbtqHg9zc3PY2dk5304GAJRSvPPOO3j69ClKpVJX9vnixQtcu3atL/NO5ubmuioffvbsGSRJwo0bN7qyv36GYRjgnA9l0PQwtovvFq5Sa88Rhheqqp5NpRtRsrTYtyLqlnbNMJqBzKIe8sgerxaTUqogezIJSAkFSi4tGltkk75KWs4mRYdTTREkUEJBylFgTgg1tVBaKz7Z43dOdXOAfFV2oF5rTsLRGIV1oCkGEJl4i7lOcdfuuOt6DObn569EDZZMJnH//n188sknXclM7DfbfBRra2tYX1/vSl4iYwyffvopbt26NdwTNS5pc7BfwNTMJAiNIXRIfGByJ+odsSae4LkMksc0Tciy3Je/r/2Aq1SDDTzR01EYYOD3/Oz2LTQJk8AsTIjscQkcv9OCRJvqHqVJ1tCkLMgdRWrm9yRlQf4kZOTVNMpoiEJBa6p5gqSRT/AEjyF56h4CotK2JE+vkEgkQAjp6ixLv0JRFLz77rv48Y9/jGq1eq596bqOvb09XL9+vUuj6y66KR9+9eoVSqUS7t69eyU+oHZ2dvpuhrAbcBwHnPO+kbj3H/gFLCOMcLnotMW6X3e1+zWN1miRyTW/5oo0w/DrngDZQwL1FpGoUPaoMqSMaIQhZZJ+A4xgd1OP/FHyaWSRgJ6lggBKqKGsH4848sgjb//+ZFtAyeMRPFST+6IpxszMDPb29i5FBd9rjI2N4datW/jkk09g2/a59tWPtvkgNE3D/Pw8NjY2zrUfzjk+//xzTE9Pd6kuOb2qJ44E6UTZE2fpilP4RAmcnZ09zM3PnPbELhFne8MYKapPwtWpwQae6Emn092RosYGFIuneIuaBy1kj1jcAsS1U1FFErM4ivuB7wUye50iNCE5FmQPcckfiiRV0XAuMMsmWkT565rrOYlsH0CLVPgU70NXRdUDiFmlt99+G5999tm5fkcfP36M1dXVvm6R6MmHz2NX29raws7ODt55550rQfIAgugZRtvWqNvDCCNcDZym+2lrzUEibdTD23IaURoDJ5I9TXWzO1EmE59o8buWetmHmaQgbJLN7qcAkLEUVOSLa1sdn80Tp7A+Xl3dUfv6AGRZRjKZPPfk06BgdnYWCwsL+OSTT+A4zpn20a+2+Shu3LiB7e3tM+dgcs7xxRdfIJPJdFlNffparoWo8de3J3yi27QjfoL/bNOGbdpIp9PHbueN4yQ7WfttzqrkOTtGRM8IHvr3m2OHyOVyKJfLp3pNrKrHfy6wLo7soaSV7OkypJSCpKyhIVlCvaMG7Fua7M8eUTls1/LkypApOG2GL4fUPEFlEjkpl+dsZM5xmJ2dxc7OzpWYUQKATCaDt956C59++umZyJ5isQjLsjA9PX0Bo+su1tbW8PTp0zMVVFtbW9je3sbXvva1K6MCqdVqkGV5KMOmj46OMDY21uth9Ck4OGddX0YYoRc4tgaLU1NH1ovnEJloCk+ueZ1Pg8SPR/Z0G1JSQy6ZRV1xQJOq2xRD8+1dUibht3H37VpBm77WbIoRzEqMbYoRUFyH6rHW76+x163j5wKYn5/H1tbWqa7JIOPatWuYn5/Hxx9/fCZlTz/b5oOglGJ1dRVPnjw59WsZY/jiiy/8zrHdx9n/Tk+n8Aku4W3jlt2dfTeEuf027S1a8cfp9Bw6PfuzolAoYHx8/MyvH25crRps4ImeTCbTWTbIRRKpXq5PgFxpzjDRkLInmM3jK3wC0l7vdjo9jkOrIoqJwCyVR+74djA3iNArInzvdyAo+kSShwTOITp7FKPmCZ/76S6VqqrIZDIX0hGhX5HNZn2y5zTnHfSFDwLOIh/mnOPZs2fY3d3Fu+++e2VIHgDY3NzE0tJSr4dxITg8PMTU1FSvhzHCCCNcMPL5/Nmz6LpQl3mqnmAjjOZC/YkxKeGSMq7dKqjskbMJyFmvy6kKJaUhQVVYGcnP8vG29wkeTRa1nGevV2hYXRRpiNFR51PvmrSrxwLX7LRqHg/T09M4PDw8s8JlELGwsIBr167hww8/PFWH0H63zUcxPT0NXddP9ffoOA4++eQTpNPpCyJ5PLRjLzt55fGWrniSpT35A4jac2trG9euzZ8w3vb7aH/s48fdGc7+5mjbNmzbHspJxBFOj4EneiilkGX57IFrwb+lOBKjE1WPR/AAPtHC3Q/2FsLHJX08hQ7xFDsydQkgQQRNZ8ZwqJdDr/UJI7/rBPELiqaKB74kmAeIHd9a1pbk8dbHXJsuk2RLS0t4+fJld3fa58hms/ja176Gr776qmN70+vXr5HP55HJZC54dN3DjRs3sLOz05F8mHOOhw8fol6v491334Usy5cwwv6Abds4PDwcCKXWaTEqMk7GVWrtOcJw4yyq6hDaEBbhrJ6AzcnrWBVQ9fjZiO5EGCjCzTC8gORo99MgaaOJ7qceETSpZFGgdT+Dx+94qrnkTpDgCQYwBzuiBgieFpLHC2D2G2SQ5vWI+07cBTUPIGrmubk5bG9vd/6iIcC1a9ewsrKCDz/8sGOr4SDY5oM4bV6iaZr48MMPMTs7i1u3bl0ZyzwAFI6KyGYzUFTFXdOe0IG/xXHEUpPYOb9N63w/h0KhcCU61p4HV6kGG4x3rxPQcaER+Ntpq0wJkCTN59qQPT6x4j4X+hAn4JJY4JEzfvetJlnjzwAFWqgTRUImnYHumOBe1k/Ad+7vI0rweDat4IyQmx/UcRv1S0A+n4eu62f2Eg8qkskkHjx4gJcvX+Lp06fHfhDbto0XL15c8AxL9+HJhx8/fnzsdl6Boaoq3njjjYEppLqF7e1tzM/PD2VhNSoyOgG7gGWEES4fsiyDMdY+kDlSd7VY54EQkdMuH9FvfhEke4J5PYHaKqTw8QgZr3Op5tZZnh1ebS6+8keTMJ0awxGvNSflvNf5DTHCBE9QTSQm4Zr1GWJInl5icXERr169ujIWeg9TU1N444038Mknn5zYjnyQbPNBZLNZZLPZE4m8UqmEH/3oR7h16xYWFhYuaXTAeW1cx5EoJxExQSJnc/MVlpYWA+v6Becfy8HBwUhRfSKuTg02FN+uziodbpvVE5lBaq4LvC5afPgLaSV8PIWPP/sUCAuUSLNo8EOcxe14JodC/RwzZSchUlQ11x8zwxZ67RkPSwgWFxexubl5th0MMFRVxde//nXYto2PP/64rRLt2bNnuH79OhRFiX2+nzE9PQ3DMNr+TXoFxo0bN7CysjKUZMdxEJLhLSwuLvZ6KBeCUZExwghXC9lstjMLPQASJRcik2wtZI9H5sSRPUCLZZ4GJtKCnUmJa+PyJs5oVJ2jNSfaqCojnUjB4BbYBWUvRAOYQ9ciZpvg82dthuFB0zQkk8mzW+4GGLlcDt/4xjewsbHRdsLNs83fvXu3ByM8P1ZWVvDixYvYTCLOOV69eoWvvvoK7777bo8+q89f83WinGmXtWPoJkzDQi6f62j74+xZwbH0CwqFwigjcQQfV4/oafe3GCV7XHRM9pDAtl36e5/JjOOgUQopgIhMA1k8rUqe5uwRmtLgODVPy8xZm2yeuMKiC5ibm8Pu7u6JbVmHEZRS3LlzBwsLC/jggw9weHgYer5er+Po6GhgiQBCCO7evdsiH2b/f/bOOz6yuvrfz51MymTSe++97ybbQLp0BGQpIlUQQUBRwIYooqyKiAUEAfkhiNIREUHaUuQLu8lm03vvbdKTyWQmk7m/P7IzJLvpmT73eXHZzMyd+zkzycw995z3OcdgoLW1lYaGBgoKChwuU2YuxsfHUSqVdt/ccbNITQBXZ2EQp+vIhiWcHz8/v9V9sLVUPUseZ9kk1DHBHtkiFfXRJfPu5nFtAzx8mBA1nyt/Fpd8LRqKYSrLd/+8P8/ifolL/CvZ0T8f65Md448teo+2GuQxEhcX53Il9EaMCTeDwUBpaSkajWbJ48ayeaVSaSMLt4aHhwfR0dF0dHQsuV+n05l6Re7YsQNvb2/bGAiYU0Wz0ZKpnu4eYmKj1x3I2ep662frx9JoNHh6erpUv8uN4mo+mFMEehQKxfrHe8LKJVwrBHs2xSrKHpO6RybAkfIrY7M+YyBHkMsI9g9kWD2+pAxMXFwStkKAx9iP5/OpW6wZ5DGVeq3nfTDD++Pm5kZoaKjLjFpfjvDwcLZv305HRwf19fWm7EtjYyNpaWkOrXTx8fFZIh+enp7m0KFDAHbgYNiWzs5Op23CbHQyXK0UT0LClVlXsu2YJNoy/oYZz3mCSSG9aHDF4immRvWOaXLW4ummbqbyrZH5qaXPN6qDPN2WBHiOnXrK5yqlxf7ZOoI8q71v5iIgIICZmRlmZ2cts4CdI5PJSE1NJSUlhfLycrq7uxFF0WHL5o8mNjYWlUplCmINDQ1RWlpKVFQUOTk5Th0IWGk8Oiw0nx4aUhEeHr6p41hOuWOe4w4PDxMcHGyWY0k4B07R/VQQBDw9PZmdncXLy8ucBwZRRDTGRMQj9yEu/HfkxCyIounsLIoL/xPEz49huo/PT+qiaWfTYscsL3dzRyaTMWuYw9N9afb/8zHwi5RFcIyCZ+G+o4JZywV5jjZjrWCYGYiPj6esrMxpe5WsBy8vL7Zv305vby/FxcWEhYUBOEWPk+TkZA4dOsTExASTk5NkZmbi5+e39hOdmKmpKfR6vdPKaqWyrfUgItpxPbeExEbx9fVlenravAcVjP8TMSZLRZmAYBABARERQQaIAqLhiH91JFAiHPl4CYIMRBAMIqIoIhhY2FcUjzwHMCzNxIqiaPJHguUBtPX2I/NYuCgWjiTXBKNqmgX/09RQefG4dI4egHFkgWOaL3NskGc9yuotukyCIJCQkEB7ezuZmZlbO5gDExgYyM6dO2lpaeHQoUMoFAqHLZtfjEwmIy0tjbq6OgRBQC6XU1RUZGdK4iOfbyvS091DZFTkqoEu65dhmW+9kZERUlJSzHY858S1fDCnSbv6+/tvevLDsmVJxkCJ8YQtHHXf0YGQxY8f3ajZKN91+1zlY1ThfD5BYvkt1D8I1eTokv0XN/czKXiOUvUYHYmlzsSxttsST09PAgMDGRwctLUpNsXYs6ioqIienh60Wq3Dj583GAwMDQ0xNzfHzMwMO3fudPkgDyz0XnL0TOFqSNmk9SJaYJOQsA0ymQyZTLZsT5B1cZSqRzzq9pLElak0fZnpp8bnux2ldF7UG9E4zMLUOPmozaj0Edzd8PD0RObmxpwwv6S3j3EYhmkgxkoqa+FzhbXJZ1sc5LEx4eHhjI+Pu6yqx4hcLicjI4PExEQGBweZmJhw+PdEp9MxMjLC+Pg4wcHB5OXl2VmQx4h1PgsCAoZ5A729fcTFxq6o1rFukGfRF5sZMBgMqNVqhy05tC6u44M5VaBnQ43ljvpsrdQM75hgz+L7jlLNiIKwJIOz2Pk4OuizeBNX2UIDgxmaHF3Y18wc05NnLTWPBUhMTKS9vd3lpj8sx9DQEDExMWRnZ9Pe3k5ZWdnWxtbaAFEU6evr4+DBg2g0Gvbs2YNOp3N4p8kcTE9PMzc357T9awwGAxqNRnIyJCRckHVNP13J7zr6sWWDPcISf+uYpNrRwzCM/pWbsDQQc6Q0fvEU09W2ML9AVJrxzb8xa70fy6l5lvHHLOGLCYJg8sEkoKenh23bthEaGkp5eTn19fUONx12bm6OlpYWSktLUSqV7Nq1i/7+fjv3sa0TXOnp6SEyMhK53CmKWY5hYmICf39/l62QkFgep/lr9/f333hjuaNUg6IgLJRhHa0mFEz/W5ALi0vvWywtNh7HVNIFCyduw+a+ZP28fZmaUTNvmMdN5rbInmUCNUf+XXZ0/FH7rdZ4ecnrOPo4ZsbT05OAgAAGBweJiIgw/wIOwtzcHF1dXezatQu5XM62bduYmJigpaWF+fl54uPjCQ0Ntdsv8Lm5OXp7e+nr6yM4OHiJRDgtLY3GxkYKCgpsa6SNaW1tJSkpydZmWIzh4WGCgoLs9m/UnnAl2bCEa2BMtq1ZdryS33X044Kw1N9apnRe4HMfa0nZvCh8XhlvLJvf5IVupH8Itf1txAZFrJ74Y5FfdSRQs2op/WpBHljd3zLjV2x4eDjt7e1otVo8PT3Nd2AHY2RkBEEQTIrUsLAwBgYGKC8vR6lUEh8fb9eqZLVaTVdXF2NjY8TExLB7925Tr7zAwEB6enrsvDfg0Rde5mV+fp6enl527dppsTU2hvn9pIGBgXX1HpJwLR/MaQI9np6eaLXaJfXV62IjwZ6tfActzlAdcTg+7+OzmnkLqp7BiREig8NMx1ryvOUyPkdlx4z3rVUDbsQaQR4jiYmJlJeXEx4e7rIXiS0tLSQkJCzJNPj7+7N9+3bTCbylpYWwsDCioqLsopmxKIqMjY3R19fH5OQk0dHR7Ny585hsSXBwMF1dXYyOjjpF76HNMD09jU6nc+rXPzAwQHx8vK3NkJCQsAH+/v40Nzevb+dFOTJYxu86KthjespWfDDZkbDQIpW9ILKmWtpH7sPcvB6tqMfDzX1p4sz4MtYI8KyYfFtnkMdSfRIXlv28V4+jjhPfKgaDgaampiXJKEEQiIyMJCIigrGxMVpbW5mbmzPdZw89fObn5xkcHKS/vx+DwUB8fDwZGRnH+NHJyckUFxfbjd22oKenl8jICDtR85j/OsdgMDA6Okp6errZjy3h2NjDX7zZUCqVqNVqfHx8LLfI0Y6H8SeBzzNGi5wXk7JncaBIEI5kpNa3ZFRoOC3dHUSGLorULnru8pPDjr3PHoM8sNCQOCAggIGBASIjIy27mB0yPT3N5OTkik6WUqkkMzMTvV7P0NAQdXV1GAwGQkNDCQ0NRalUWi1AZjAYGBsbQ6VSMTIyQkBAANHR0WRnZ69qQ3p6OlVVVezatcslg3ktLS1O3Ztnfn6e6elpu8542g8iBnHe1kZISJgVb29v1Gr1xpNtG8GkpF5wpkSOUk9zxD8TFiXSllP3GH0iPr9/5TUFIgJD6Z8YJj40ynjIY32sowM8GO87yt/i831sHeQxEhERQUdHBxqNBoVCYZlF7Jienh5CQkKWfe2CIBAUFERQUBCzs7P09/dTWlqKl5eXyQezphJqbm6O4eFhVCoV09PThIWFkZGRsWrJtFwuJz4+nra2NjsPBFhG1aPX6+np6bETNY9lPsRjY2MEBgZKE0/XhWv5YE4V6AkODmZ4eHjjgZ7VVD2mOxftt3ga1zGyYuPtz4M+R5/ojzm28fgr2Obr48OMVsPcvB75StH4lYI4LBPgOepxeyA5OZnS0lLCwsKceuzj0YiiSGNjI+np6Ws6x3K5nKioKKKiotBqtQwPD9PS0oJarcbPz4+AgAACAgLw8fExm6Ot1+uZnJxkfHzc1LQxMDCQkJAQUlNT1/278vb2JigoyAHkw+ZndHQUURSdWs2jUqnsurTQnhBdzMmQcA0EQdhSsm1ZVc/CkU3+Fqa7F0mClpuAujiRtngKqrhI1XPksSPGr2pbZHAYle0NxIVHLxuQWTXAY9x3ufJ5O0EQBFJTU2lqaiI/P9/W5lgVnU5Hd3c3u3btWnNfLy8vEhMTSUhIQK1Wo1KpqKqqYn5+Hn9/f5MP5uXlZbZzoVarZWJigrGxMdOQjuDgYFMp2XrXiY6OpqSkxAGa9Zo/2NPe3k5sbKydqHksQ39/P1FRUbY2wyFwNR/Mqf7qQ0JCqKurIyEhYeNPXinYc/Tji50PWEbds/TxpQf9/Ngr7r6sbQLhwaEMjg4THW5mxctKyqD12GVGPDw8iI6Opr293aVGA6pUKjw8PDY8btvT05Po6Giio6MxGAxMT08zPj5OW1sbMzMzwEJwxdvbG09PTzw8PPD09MTNzc00IQUWFDrz8/Po9Xq0Wq2pcbJarUar1eLm5mYKIkVGRm7JgUlKSnI5+bAoijQ1NZGXl2drUyxKf38/qamptjZDQkLChoSEhGws2bZWku2YfohH+iQud4BjAj7GXZYqemCR2gdhXdeUCm8FIiKzei1e7mZWb6yg5rG2sjokJMTU48VZBwYsR2trK4mJiRsKAgiCgI+PDz4+PiQmJqLX65mYmGB8fJz+/n5mZ2dxc3NDqVSiUChMPpiHhwcymczkhxkMBpMPNjc3h06nQ6vVotFoUKvV6PV6PDw88Pf3JygoiMTExE1PzhIEwdQvcfv27Zs6hvVY5vppk8zMzDA8POLUah6DwcDExATZ2dkWOb6EY+NUgR6FQoFWq2V+fn5zqpBlnA5YJAteUn7FEhWPKeBzTN+do2VBbOq7KzIsgvrWxqWBnqOlwEfdJ67xuL0EeYzExsZSXFxMdHS0S8iHDQYDLS0tWz7pymQy/Pz88PPzIy4uznRsjUbDzMwMWq0WtVrN2NgY8/PzJsdCEASTw+Hm5oanpyeenp74+vqSkJCAp6enWRUacrmchIQEWltbXaYXQE9PD0FBQXbRU8lSzM3NMTs7a9mSWSdDxHWySRKuQ3BwMLW1tRtLtq2WZFucYFscuFmSYDvqovDogM+S4xzZd37jTlhkcBj9I0MkRMWa7FjyGkxKndWVPAv7LHO/DYM8RtLT06mpqWHnzp0uoc5cq2x+vcjlcoKDg02NnGFBDT0zM4NGozGpcubm5kw+mMFgMCXdZDIZ7u7ueHp6mtTPSqXS7AmxwMBAurq6TApc+2fr6p6mpibS0lLtoKTJcp+n4eFhQkJCXOIzay5cyQdzqkAPLHyRjY2NERISsrkDLPO9cozjAcc6Hxtdw3iMde6v9PZmbk6PTq/Dw/1IRH+1PjxHP7543aN+tocgDywELFxJPtzZ2Ul4eDheXl5mP7ZMJkOpVNqdRDcqKspB5MNbZ/EkNWdmaGhImvTg4AiCEAS8CCQAHcCloiiOLbPf28Bu4P9EUTzPmjZK2D8KhcJ0MbuhZNsmgj2bnaIFIC5uwLye4wgCESHhlDVWkRAT97ldi+xduv8iO1fzzdYT5LEiSqWSgIAA+vr6iI6Otpkd1kAURRoaGtZVNr8Z5HK5KQFnT6SlpVFRUUFwcLAdBD8sy0LZPEsCcLbBsp9paRCGxGo43ac8JCSEkZER6y245IS+MFlr8caSTVi6yRZtx+x7ZJN9vn94aBgDw6rPn7toP9N6i2wx2Sew1KFYy0GxYVA4JCSE+fl5xsaOucZwKrRaLf39/ZsrM3RgBEEgPT2dxsZGW5ticVpbW4+ZpOaM9Pf3ExERYWszHIiF+nBzb1vkh8B+URRTgf1Hbi/HA8BVW11MwnkJCAjY3Pl7E77HUh/L6Ct9fhxRED7fZAvbgl91ZDP6WGttAnh6eeDm5saMVrNwrEXHXmK/0Wc78rzPfUFhWRtX9MeO9t2sRFJSEh0dHej1eusubGVUKhWenp4bLpt3dBQKBaGhoXR3d9valHWyuQ+AsWw+PT3NzPZsFMt+gKVBGJvBLn0wi+F0gZ7AwEBGR0e3dpBlPpdLTuhH77PkpL3oZM5qQZ+jNpnAskGgRftEhkfQPzSwJEO0ZoBnORuxbdZoLdLT02loaMBgMNjaFIvR3NxMUlKSSzWeNhIQEIBcLkelUtnaFIsxMTHB5OSk0zfHM5bKOnNpmotwAfDMkZ+fAS5cbidRFPcDU1ayScIBMVey7ZggivHfowI7x/hXRwValvN9jg7+rGsTBCJDI+hTDS5jCxwdxDnGN+MoW+zUBXN3dychIYGmpiZbm2IxjGXzaWm2DgLYhsTERHp6etDpdLY2ZZ1s/MPS0dFJcHCI0/smQ0ND0iAMiVVxukCPXC5HLpczOzu7tQOt8JlZNuOy4u2lwZuj1T6rqn849nEvxUIj3GmNemuvbbnXYrTfDlAqlURGRtLS0mJrUyzC5OQkGo3Gpctd0tLSaGlpccpgnsFgoL6+fs2R885AX18fkZFmbhDv5Igi9phNChdFsf/IzwOA6345SWyJoKCgrSXbjvrKPEYxc0zQ51j/alkV9UrK6fXaJEB4aBj9w4Pmm5hl8vVWSSTagKioKDQajXXV8Vaks7OTiIgIq45Ftyfc3NxISkpyMB97/R+K6Wk1AwMDJCcnWdCe9WD5D3Jvb6/TJxTNjZ36YBbD6QI9YMbyrRUcgWVPyssFfNYI/Kw10nM54mJi6ertWUYKvD4lj9H+Y7Cz69H4+HjGx8eZmJiwtSlmxThOPSMjw+mDAKvh5eVFWFgYXV1dtjbF7LS2thIREeH0PYhEUZRGem4KEYNoMPsGhAiCULpo+8biVQVBeF8QhJpltguWWCeKIuaebyvhMri5ueHu7r61ZNtaPssqAZ8lQR8ZS32xo5XTG8RdLifQL4Dh0ZEV1dfLqqyX88tWe202RhAEsrOzaWxsdLoSLmPZvKv3NImIiGB6epqpKUcSaK794RBFkbq6WrKysmzcg8jyH2S1Wo0gCE7va5ofi/lgdolTBnqCg4MZHh423wHXG/DZIscofEzrf+6YhIaEMjo2yvxiJcSKma512LuRrJYVMToadXV1TqX6GBwcRKlU4uvra2tTbE5CQgJ9fX0OJB9em8nJScbGxlzCiVSpVAQGBjp9DyIHYlgUxaJF2xOLHxRF8YuiKOYss70ODAqCEAlw5N8hW7wACecgODh468m2jfovm/Fjju6VuGKPns+3uOhYOvu6jwnsrKsXz6LbK74eO8HLy4u4uDinK+Fqbm4mOTnZJcvmFyMIAhkZGTQ0NCBuobG5vdHZ2UlgYCD+/rbsWWOdD3JXVxexsbFWWUvCcXHKQI+vry/T09PW//JaUcmz2mPLqHxWUv0IIHOTEREeQd9g/7rVOysGpOzIqVgOYwlXa2urrU0xC/Pz87S1tZGSkmJrU+wCo3y4ubnZ1qaYBYPBQF1dHVlZWS6h1uru7pacjE0gAgbmzb5tkX8D1xz5+Rrg9a0eUMJ1CQkJMU+ybaNfo0craVimTP5olc8GNx9fH+bn51HPatanrD7KL3Mkfyw6OtqpSrgmJyeZnZ0lLCzM1qbYBX5+figUCoaGHCmuv/IHRa1W098/QHJyshXtORrrfJD1ej1jY2OEhoZaZT1nwk59MIvhlIEeQRDw8/NjcnLSzAdmY8qelYI7yz22nu0IMdHR9PT2ICJuTL2zxuuwR+Lj4xkbG2N8fNzWpmyZ9vZ2oqKi8PDwsLUpdkN4eDgzMzPm/6zagNbWVsLDw/Hx8bG1KRZHrVYjiqJLvFYX4dfA6YIgNANfPHIbQRCKBEF40riTIAifAC8DpwmC0CMIwpk2sVbCrvHx8TFfsm09yauVlDMrJM7W6pe4ei9FgbiYWLp7e45JxG0qwGPHCIJAVlYWjY2NzM3N2dqcLWHpceqOSmpqKq2trczP2++F6rEc+/szGAzU1NSSlZXp9GPjYWHaaWRkpPS3LLEmTvtpMHv51mLWCPisGWBZLQC0jud4enri7a1kfGJ8c/Y7EIIgkJubS11dnUOX+Gg0GlQqFXFxcbY2xa5YPG7dkeXDKpWKyclJEhISbG2KVZDUPFtBRBTnzb5tySJRHBFF8TRRFFOPlHiNHrm/VBTFry/a7wRRFENFUVSIohgjiuI7W3wzJJwQsyfb1ptkW0nlvCQAs0zwZyMbEBYWhmp02DwXx3aeeFMoFCQlJVFTU+PQ5+iBgQF8fHyksvmj8PT0JCoqis7OTlubskGWfmiam5sJCwvF39/fRvaAtT7IoijS09NDdHS0VdZzPuzPB7MkThvoMZt0eDVWOUEvGeG5VsR1E98NcbGxdHV3r7jmRu21ZxQKBSkpKQ7taDQ1NZGamuoSmYaN4ufnh7e3N4ODg7Y2ZVNoNBqam5vJzc11iezK/Pw8IyMjkmR404guNfFBwjUJDQ01f0nIGv7Wkv2WS6atQzG9HmQyGRFh4fQPDay8xkq2rbCfPRMREYGXl5cDBgMWmJ+fp729XSqbX4G4uDgGBga2Pq3Y6ix8iAYHh1CrZ2yYaLPuh3lsbAwfHx+pOmDTuJYP5rRXnR4eHsjlcmZmZiy/mDk+4xt0PgL8/ZnRaJjV6davInJgwsLC8PHxob293dambJixsTHm5+cJCQmxtSl2S0pKCm1tbQ4mH16QC1dXV5OZmekyJ12jZFgKWkpISKxEaGgoKpXK/MmZVXyadSfX1jruWhsQEx2zagm9MwR4FpOens7g4CBjY2O2NmXDtLe3Ex0d7TLn6I0ik8lISUlxyH6JMzMztLa2kpubY6NEm/XX7OrqkqoDJNaNU3vqERER9Pf329oM4FiFz0ackWWfJ5MRE7PgaCyLgzoTq5GSksLIyIhDNQYURZGmpibS09NtbYpd46jy4aamJsLCwggMDLS1KVZBkgxvHVHEpbJJEq6Jm5sbPj4+9tF/zQwqnqOf6+XliZeXgonJCdMuK/p2TpBwk8lk5OXlUV9f71Bl9MayeanUeHVCQ0PR6XQO1Q9zfn6e6upqsrOzcXd3t4EF1v9Az87OotVqbVyi5ti4mg/m1IGesLAw63aT38TJfKUA0HqCQZERkQwMDHyugnACZ2I1ZDIZubm5NDQ0OIzEtK+vj4CAAJRKpa1NsXvi4uIYHBx0mN/twMAAGo3GJUapGxkdHUWpVOLp6WlrUyQkJOwciyfb1qnu2XDfxHUEhURBID4+nvaOTqdT76yEQqEgNTWV6upqhymjl8rm14ej9Us0NteOjIw8EvRwog/aKnR2dkpBS4kN4dTffO7u7nh5eTE1NWX9xbeaPVrH8d3kbkRFRtHd0732/k6Cl5cXmZmZVFZWotfrbW3Oquj1ejo6OkhKSrK1KQ6BI8mHJyYmaG9vJyfHVnJh6yOKIq2trdLf85ZxrfpwCdclJCSEkZER61w4ruFnbTShtp79AwIC0M/rbeNj2ojQ0FACAgJoaGiw+4CAVDa/MXx8fPDz87ObSojV6OzsxGAwHBX02Ejk1hybddHpdIyOjhIZGWn1tZ0L1/LBHDbQMzY2hkKh4Pjjj+fOO+/kP//5z7LjHyMjF1QvdoEFvi9i42Lp7e1l3mC/f2TmJigoiNjYWKqqqjAYDLY2Z0Xa2tqIj4+3kaTUMQkJCbF7+fDMzAy1tbUUFBS41O92dHQULy8vp1WnWfOixcC82TcJCWvS09ODQqHg1ltv5c4776SiouKYfWQyGf7+/tbt67JJ32qzo8+Tk5JpbWtdfn0nJSkpCb1eb9el1lLZ/OZISUmhvb3drhOpg4ODDA8Pk52d7TKJNoCOjg7i4+Od9jVrNBqrreVKPpjDBno6OztRKBQkJyczMzPDD37wA771rW9x6NChJTXhFmsIaA3WERiSy+VERkbS07NCrx4nJSoqCn9/f7vNKqnVakZHR6VeJhvE3uXDc3NzVFZWkp2djUKhsLU5VqWtrY3k5GRbm2ExXCkrLyGxVYaGhsjIyMBgMDA0NMRZZ53FU089xeHDh5c01berZNsabKaZc2BQIHq9nmn1tFMHdxYjCALZ2dkMDw/b7bRMqWx+c7i7uxMbG2u3g0/Gx8dpa2sjPz/fpcrxdDodw8PDRERE2NoUi+Eo5wlHQ25rAzaLwWCgra2NgIAAAJ5//nmuu+463n//fcLDw/noo49wd3c3NQScmJgw7WuXbMFBiIuLo7i4mJiYGNzc3Mxnk52TlJREbW0tnZ2dNhyruDzGTJKzRt4tyWL5cFRUlK3NMWEwGKioqCA5OdnlGuGNjo7i4eHh1E6ztZwMERHRjmW+EhLrwdvbm/LyctPta665hltuuYWIiAiuuOIKfvGLXyAIAkFBQTQ0NGAwGGxzYbbSKXgzeYQVjpWUlERrayv5+fmbOKhjIpPJyM/Pp7S0FE9PT7vyr41l8zt37rS1KQ5JTEwMJSUlxMTE2FVCa2Zmhrq6OrZt2+ZSampYEDfEx8c7dXDLWkFjV/PBHPYvJjAwEC8vL1PpzgUXXMAjjzxCXV0d7e3thISE8O677wKOlVHaDK6q6hEEgaysLIaHh+3q9zsyMoJMJnOZSUyWwN7kw6IoUlNTQ1hYGGFhYbY2x+q0trY6tZpHFEVUKpWtzZCQcBhCQ0OXSO1//OMf89prr/Haa6/x4IMPkpeXR09PjynYY3fTMs3YkiMoKAidTsf09LRlbbYz3N3dKSgooK6ujpmZGVubY6K1tVUqm98CMpmM1NRUGhsbbW2KCZ1O57Jqap1Oh0qlcurePGq1Gg8PD1ub4ZQ4bKBnbGyM0NBQTj75ZH7zm9+gUCi47rrr8PDwoLe3l//+97987WtfY3BwkODgYOs1BLQRcXFx9PT02HXPGktgzCp1dnZad8LaChgMBpqamkhLS7O1KQ6Nu7s7cXFxdiEfFkWRuro6vLy8XGrClpGxsTE8PDzw8fGxtSkWY3x8HD8/Pyut5lqNACWck87OToKCgrjqqqt49dVXSUtL46yzzqKgoICZmRmuueYarrjiCsD5k22woOppa2uztRlWR6FQkJOTQ0VFhVV7bKyEWq1mbGxMKpvfIsHBwYiiyOjoqK1NYW5ujvLyclJSUlxOTQ0L37VxcXFOrebp7++3Ylmaa/lgDvtXExMTQ0tLC+eeey733HMPf/3rX01jmQVB4LjjjmN0dJTMzExT2ZZVGwJaGblcTkREhMupemAhKLB9+3ba2tpsnpXv6ekhNDTU5TIOliAmJoaRkRGbZgpFUaS+vh65XE5qaqrN7LAlzq7mgYWyLWeufZeQMDfx8fE0NDQwODjIN7/5Td58803TY4IgcNVVV1FSUsL3v/99/Pz8mJqaWtK7x9kICgpidnYWtVpta1Osjp+fH9nZ2ZSXl9s82NPY2CiVzZuJ9PR0mpqabJokn5ubo6ysjMTEREJDQ21mh62Ym5tDpVLZVRsDcyOKIkNDQy6plrcGDhvoCQwMJDw83JQxuuWWW5bU94miyLZt29BoNDz//PMEBwc7xMjArRAXF0d3d7fLqXrg82BPa2srw8PDNrFBp9PR3d1td/2CHBVBEEhNTaWpqckm64uiSENDAzKZjLS0NJd0HMfGxpDL5U6t5jEYDIyOjhIcHGy9NV0omyThnAQGBhIfH88555zD1NQUt9xyy5LHjTL8hx9+mPLyckJCQmx2brYGgiCQnJxMa2vr2js7If7+/mRlZVFeXm5Kulqb4eFh3NzcpLJ5M+Ht7U1QUJDNEsiLgzyuGgRwBTXP1NQUSqUSudx6bYNdyQdz2L+curo67rrrLhoaGgB45JFHlpRVPPbYY1RVVfGtb32LO+64gx/+8IfU19fzt7/9zWmnq7i7uxMZGWnXIy8tiYeHB9u3b6elpcUm/QBaW1tJTEy06peVs2O8+Lb271MURVN9uqtmB0VRpLm5mZSUFFubYlFGR0cJDAy0miMliiIG0WD2TULCmtTW1vLcc8+ZVLTvv//+ksf37t3Lueeey65du/jCF77A66+/zrvvvst7773ntMqeoKAgtFrtksmvrkRAQIDNgj0Gg4Hm5mapbN7MJCUl0dXVxdzcnFXX1ev1lJeXk5CQ4LJBntnZWYaGhpxazQPWLttyPR/MYQM9mZmZfPzxx3zpS18C4JRTTlny+O233878/DwPP/wwAC+++CJjY2PU1dWRkZHBwYMHrW6zNYiPj6e/vx+tVmtrU2yCh4cH27Zto6mpyaplXNPT00xNTTl1szRbkZaWRnNzs9WUasYgj8FgICMjwyWDPLBw8vX19XVqNQ9Ad3c3MTExtjZDQsKhSExM5Prrr+d3v/sdvr6+S8o7R0dHOXDgAG+++SbFxcUAPProo3h7e/Pb3/6WXbt22UXvD3MjCALp6ek0NDQ4dU/I1QgICCAjI8PqZVzd3d1S2bwFkMvlJCQkWFWpZlTyxMXFER4ebrV17Q1jos2Z1Tzz8/MMDw+7ZFmetXDYvx4PDw/279/PAw88QGho6DFN8IaHhxkdHWVkZISOjg76+vq48sorueiii3jqqae47LLLeOSRR5zuZOzm5kZycjLNzc22NsVmeHp6UlhYSHt7O729vRZfz1ji46rKD0vj7e1NcHCwVX6XBoOBqqoqZDIZmZmZLvv71Ov1tLe3O31vHo1Gg06ns2Ij5gUMzJt9k5CwJj4+PgwNDfHlL3+Z4ODgJSqWoKAghoeHUalUjI+PU1tbS2NjI7t37+aRRx7h9NNP55xzzjlGBeQM+Pn54ePjY7VRwfZIYGAgmZmZlJeXW0XdpNPp6O3tJTEx0eJruSJRUVFMTExYZaqcRqOhtLSUhIQEl+6bNz4+jlardfoAyMDAAOHh4VYPZrmSD+awgR7jhKlbb72Vrq4uTjvttCWPK5VKFAoF3t7ehIeHExgYiEKhwN3dnT179vCHP/yBO++80ykb54WFhTE7O+uy8mFYCAQWFhYyODhIW1ubRQN6KpUKLy8vl5wGYC0SExMtLh/W6/WUlZUREBDgsj15jLS3txMbG+v04y57enqIjY21tRkSEg7H8PAwPj4+PPfcc9TX1x9z/lMqlfj4+ODp6UlSUhIeHh5EREQwODjIL37xC9LS0ti3b5+NrLcsKSkptLW1OW2J2noICAggPz+fmpoai5det7S0kJiYiJubm0XXcVWMSjVL90ucmpqivLyczMxMly3XgoXkcVNTk0soynt6eiRFtYVx2EDP3NwcJ510EocPH97Q8+Li4ujq6iI7Oxt/f3+nzLpI8uEF3NzcTKNe6+vrLfJeGAwGWlpaXHYik7WQy+UkJibS0tJikeNrtVpKS0uJiYlxyRHqi9FoNAwPDzv9yddgMDA0NGSDrKGIKM6bfZOQsCZDQ0NceeWVDA0Nrfs5bm5uhIaGMjw8zAknnMDMzIxTBkM8PDyIioqio6PD1qbYFKVSSWFhIS0tLRYbhjI1NcX09LRLqz+sQUBAAHK53GItEUZHR6muriY/P5+AgACLrOEouErZ/Pj4OJ6ennh5eVl5ZdfywRw20COTyfDy8uLss8+moqJi3c8LCgpiamqKhIQEUlNTTSVOc3Nz/PWvf6W0tNRCFlsX45fEwMCArU2xKTKZjOzsbDw8PKisrDS7U9nZ2UlkZCSenp5mPa7EsURGRjI5OWl2+fD09DSHDx8mLS1NchZZGE+blpbm1HXhsCAZDgsLs/rrFBFdauKDhHOiVCqpqanhi1/84oaU0bGxsXR1dfHlL3+Z+vp60zl5aGiIhx9+2Gl8lri4OIaGhmw+btzWGEvpe3t76ejoMGvCzdhPTyqbtw5paWm0tLSYvV/iwMAATU1NFBYWolQqzXpsR8NVyuZhoa9WXFyc1dd1NR/MYT35kZERSktLmZqa4pJLLuHxxx9f1/MmJiaorq7mwQcfZGRkhJNPPhm1Ws3evXt5+umnueiiizhw4MCS5wwPD3Paaadx1113OZRCJiUlhfb2dqfMmG0EQRBISUkhJCSEQ4cOMTMzY5bjarVa+vv7XV4BYi2MSrXGxkazfQ4HBwepqqoiNzeXoKAgsxzTkRkdHUUURauOGrcVkmRYQmLzjIyMMDg4SHNzM1/+8pf54IMP1vW85uZmWltbueGGG7jiiivw8PCgqamJE044gXfffZcTTzzxmMDRxx9/zEknncTzzz9viZdiEWQyGSkpKS7dL9GIXC5n+/btTE9PU1NTYzafdGhoSCqbtyJeXl6EhYXR1dVlluMZS5T6+vooKiqSEqa4Ttm8TqdjenqawMBAW5vi9DhsoCc7OxuVSsX27dvx9PTkO9/5zrqySj//+c/54Q9/SEBAAB0dHfzjH//gn//8J3Nzc+zfv5/LLruM//znP0ue09jYyGeffcZHH33Ec889Z6mXZHY8PDyIjo6mvb3d1qbYBTExMWRkZFBRUcHw8PCWj9fc3ExycrLTKx/siYCAADw8PLb8+zM6GL29vezYsQNfX18zWei4GN8TVxhPOzk5ibu7u80mtLhSNknCOcnOzubTTz/F29ub+vp67rnnnnU9b9euXTz00EMkJCTw9NNP09DQwL59+7juuut444038PX1paSkZMlz9u/fz8TEBHfeeadDlUOFhoai1+sZGxuztSk2RyaTkZOTQ0BAgFkSbgaDgdbWVqls3sokJCTQ19e35cm+Op2Ow4cPI5PJ2LZtG3K53EwWOi6uUjYPC4m26Ohomynx7M0HEwQhSBCE9wRBaD7y77IRMEEQ3hYEYVwQhP8s9/hyOOwVqqenJz4+Ptx3332msX9rOe2iKPLnP/8ZjUaDSqXi9ddfZ9++fQwMDFBYWIhcLue2227jb3/7G3V1dYiiyMMPP8zevXs57bTT+OMf/8jdd9/N+Pi4FV6heYiNjUWlUrm8fNhIQEAARUVFdHR00NraumllyMTEBLOzsy7dMM5WpKambkk+fLSD4e7ubmYLHZOenh4CAwNdQjrd1dVlE8mwhISz4OnpSXJyMtdeey3Dw8PraoTb3d0NLHzX7Ny5k3379vG73/2OwcFBdu7cCcDdd9/Nd7/7XWZnZ5mZmeGmm27igQce4Prrr+e2227jzjvvtOjrMjfGJrbmLndxVGJjY82ScOvo6JDK5m2Am5sbSUlJW+qXODExQWlpKfHx8aSkpEhld0doaGhwibJ5URTp7+8nKirK1qbYEz8E9ouimArsP3J7OR4ArtrIgR3+rykpKcn081ofDmMm6JlnnuH2228nKCgItVpNdXW1qVQhJiaGn/3sZxx//PEEBATw4x//mO9973u88cYb/O9//0OpVHLfffdZ7PWYG5lMRkZGBrW1tQ5VdmZJPDw82L59O3q9nvLy8g1PcpLqwm2Ll5cX4eHhm5IPSw7G8mg0Grq7u12iLlyn0zE1NWWzUj0R0aVGe0o4N8bvjPWUe77wwgsAfPLJJ+zZs4cdO3ZQUlKCSqUiJCQEgAsvvJCsrCwSExMJDg7mnXfe4c033+T666+nu7ubjz76iLfffttyL8jMKJVKgoODHUqJZGm2mnDTarUMDAxIZfM2Ijw8nJmZmQ1P9hVFkd7eXurr6ykoKHD60eEbYWBgALlc7hJl8yqViqCgIJupuOzUB7sAeObIz88AFy5ruyjuB6Y2cmCHD/TEx8ev++IkJiaG6upqLr30Unx8fNBqtQQGBjI5Obnkw3X99ddTW1vLN77xDSorK7njjjsQBIG7776b1tZWhyvzCAwMxMfHh56eHlubYjfIZDLS09OJiori0KFDGxr/OTAwgK+vr8P9HTgT8fHxG5IPGwwG2traaGhokByMoxBFkdraWjIyMlxCPt3X10dUVJRNg3z2JhuWkNgs11xzDQCzs7Nr7nvdddfR0dFBQkIC0dHRTE1N4evry+joqCnwKggCzz77LK+++ip33HEHjY2NnHrqqfT09PDkk0+iVqsdrn9FUlISQ0NDZh8k4MgYE27z8/OUlpZuSHXe1NRESkqK0ysf7JXN9EvU6XRUVlYyNjbGjh078Pb2trCVjoNOp6O1tZWMjAxbm2IVurq6iI2NtakNduiDhYuiaBxNOACEb/WARpziW9JYurUW7u7upKSkAAudzR955BHOP/98ZDLZMQ2hoqKieOCBB0hMTAQWIpB+fn5UV1fz05/+1LwvwAqkpqbS3d0tlXAdRUREBNu3b6ejo2PJBJCV0Ov1tLW1uYTywZ4xyofX0+hSrVZTWlqKwWCQHIxl6O3tRalUukQzalEU6evrIzo62tamSEg4BcaSpISEhDX3DQ4OJjx8wX8dHBxk//797N27l7GxsSXfP25ubhx33HHcd999pqBOU1MT27Zto7+/n1NPPdX8L8SCyGQysrKyqK2tlUq4FiGTyUhLSyMlJYXy8nJ6e3vXDBxMTEyg1WqlZI2N8fPzw9vbm8HBwTX3ValUHDp0iMjISHJyctZV5ulK1NfXk5qa6hJtBIy9dJ10dHyIIAili7ZvLH5QEIT3BUGoWWa7YPF+4sKXoNlKcJwi0PPwww/z6aefbug5559/Pq+//jopKSns379/zc7fP/3pT5mcnHTYcg83NzcyMzOlEq5l8PLyYvv27SiVSkpKSpiYmFhx346ODmJiYhwuo+iMhIeHo9FoVpQPi6JIV1cXVVVVpKenSxnAZdBoNHR1dblMQ8vh4WECAgJsq1wSRURx3uybhIQtkMvl3HXXXfzyl79c93NmZmZITU3lrbfeYnJyEq1Wu2aPxUsuuYSYmBgCAgK2aLFt8PPzIzg4mM7OTlubYncEBgayc+dOxsfHqaioWFGpayybz8jIcEg/3NlITU2lra1txQSpXq+ntraWnp4eioqKTEFeic8ZGBhAJpO5TL/P7u5um6t5LOiDDYuiWLRoe2LpsuIXRVHMWWZ7HRgUBCES4Mi/Q+Z6uU5x1fP1r3+d7du3r3v/P/3pT3z44Yfcf//9TE9Pc+aZZ645nvH+++9HoVCsa7KXvWJstCqVcB2LIAjExcWRl5dHY2Mjzc3Nx5y8jE28bf4lJQF8Lh9uaGg4Jnip0WgoKytDrVazc+dOafzqMrhayZYoirS3t0t9HSQkzIhCoeAnP/nJur9jRVFk165dALz66qt4eHisqzH6P//5T1Qq1ZZstTVJSUkMDg5KJVzLIJfLyc7OJiYmhtLSUgYGBo45r/f39+Pr6+usagCHw8PDg6ioqGX7T42OjlJSUkJAQAAFBQVS0+xl0Ol0tLW1kZ6ebmtTrIJOp2N0dFRS4y3Pv4Frjvx8DfC6uQ7sFIGejaBWq/ne977HaaedRl9fH7/4xS849dRT15w04+vrS3BwML29vSvuo9fr+eijj44ZZ67X69Hr9Waxf6tIJVyro1QqKSoqwt3dneLi4iWOZVNTE6mpqZIqxI7w8/PDx8fHJB+en5+ntbWViooKEhISyMzMlGTCK+BKJVuw4Hh6eXnZfKqYiGiP9eESElbh3XffpaWlhccff5wzzzyTl19+mUsuuWTN5yUlJa3qfwFMTk7y1ltvMTW1tFfl7OysXSiZF5dw2YM99khoaCg7duxgeHiYw4cPm5Krer2e9vZ2qWzezoiLi2NoaMjUo2t2dpbKyko6OzvZtm2bTUdo2zv19fWkpKS4TIVAR0cH8fHxNr+GslMf7NfA6YIgNANfPHIbQRCKBEF40riTIAifAC8DpwmC0CMIwplrHdjlrliVSiUNDQ3ccMMN/O53v2N2dpZPPvlkzd4s7777LgqFYsmULyMGgwG9Xs/evXu58847OfHEE2lqagKgpKSEiIgIzj77bIu8no0il8ulKVxrIJPJSEhIYPv27fT19VFWVsbAwADz8/OmySAS9kNKSgptbW0MDg5SXFyMTCZj165dLjG9YLO4WskWQFtb27Lf3xISEtbj1FNPpbm5mRdffJHh4WHq6urw8/NbU+Xy5JNPctZZZx1zvyiKiKJIT08PhYWF7Nu3j1NOOcXk3zzyyCMEBgbywAMPWOT1bBQ/Pz+CgoKkKVyr4OHhQU5ODikpKVRXV9PU1ERra6tUNm+HyGQyUlJSaGxspKOjg7KyMqKioti2bdua5ZiuzMDAAIIguEzJlk6nY3h4mMjISFubYpeIojgiiuJpoiimHinxGj1yf6koil9ftN8JoiiGiqKoEEUxRhTFd9Y6tssFemBhYs/Y2Biw0BzwF7/4BUNDQ8sGe0RR5Fe/+hVf//rX+eMf/4hcLmdiYoKf/exnnHzyyURHR7N7927+/e9/Mzo6ysGDByksLDSNjLzrrru47777OHz4MDMzM9Z+qcsSFBQklXCtAy8vL/Lz84mPj6empgaFQrFmQFDC+szPzyOKIi0tLWzfvp3ExESbZwzsGVEUqaurc5mSLVhQ83h4eNiN5N8Os0kSElbB3d2dmJgYUyP9G264gSuvvHLFoRpjY2NceeWV/Pe//+Wuu+4CoKGhgW9+85vs3LmT4OBgfvSjH3H//ffzla98hU8//ZSGhgb0ej3j4+P85Cc/4U9/+hPvv/++1V7jWiQnJ0slXOsgICCAXbt24ebmRldXFx4eHlKC0g6RyWQMDw+jVqvZtWuXVJqzBsaSLVeZsgXQ2dlpF2oeI67kg9nHO24Drr32Wl599VXa29tJSkoiMjJyWVnwG2+8wR/+8AeSk5M555xzmJqa4s4776SpqYmf//znlJWVodfruf7667nxxhuRy+XI5XL0ej2vvfYa/f39XHPNNWRlZVFWVkZdXR1f+MIXuPbaa/nwww9t8MoXSE1Npaen5xiJs8SxaDQaYmJiUCgUHDx4kO7ubmlyhh2g1Wqpr6+nsrKS9PR0ZDKZ5ASug46ODpcq2YKFyYz2I/kXMYgGs28SEo7E4cOHeeutt3jooYeIiopCp9MtG/j42c9+RmlpKUNDQ3z1q19Fr9dz3nnnkZCQwGOPPcann37KY489xt/+9je+8Y2FISdyuZy5uTnuvvtuLrnkEi666CLKy8vR6/U8//zz7Nmzh9tuu81mjZGNJVzV1dVS8mgNBEFgenqa3NxcRkdHOXToECMjI7Y2S4KFUsmysjK6u7vJz89nenrabi7k7RVRFKmuriY1NdVl1Gk6nQ6VSmVHah7X8sFc+hN5zjnnmMbZxcXFHXMBPzY2xl133cXk5CS+vr5ERESg1+t54403eOihhzjxxBMJDw/npptuYnZ2llNOOYW5uTlqamro7Ozktttu46GHHkKhULBz506Ki4t54okniI2NJTMzk+uuu44///nPNrk4lcvl5ObmUlNTYzf9g+yRubk5Ojs7SUlJISEhgZ07d6LVajl48OC6RoFKmB+dTkdjYyNlZWWmjF9ISAgpKSnrGrfuyoyNjaFSqUhLS7O1KVZjbGzMrtQ8EhISC30PTznlFNPtpKQk2traluxTXl7OE088YToHZ2dn88477xAdHc0PfvADtm/fTmZmJmFhYeh0OmJjY6mrq8Pf35/f/e53FBcX85Of/ITAwECio6Opra1l3759nHXWWcjlck4++WQOHjxo7ZcOLJRwGe2VWJnR0VEMBgMRERFkZ2eTnZ1Nb28vhw4dMinzJazL9PQ0FRUVNDc3k5ycTEFBASEhIfj7+9PX12dr8+yatrY2/Pz8XEr11NnZSVxcnBQEtBEO+6739fWh0+nMdjy5XE5ERAQ9PT3s37+f448/nqKiIlpbWzn//PO54ooryM/P54UXXuD0009f0qvlq1/9KgA1NTW8+OKLREVF8dRTT/HQQw9x2mmnodfrqaiooLKykg8//JCIiAh+8IMf8MEHH3D77bfz7LPPmu11bAQfHx/i4+Olfj2r0NbWRkJCgqnExd3dnZSUFIqKipienubgwYPLToeQMD9zc3O0tLRQWlqKj48Pu3btIjIy0tToLzQ0FL1eLzl/K2BUQOXm5rrUCbe1tdWuevOIuJZsWMI5Mff3bFBQELOzs6jVau6//35OOukkjjvuOAAeeughsrOzSUtL469//SvXXXfdkuf+6le/Aha+437zm99w5pln8thjj/Gvf/2LmJgYOjo6UKlUvPnmm7S2trJnzx4efPBBHnnkEU455ZRjBmhYi+joaIA1m0y7KqIo0tTUtCQxoVQqycvLIyMjg46ODg4fPszExIQNrXQd1Go1VVVV1NfXEx8fT2Fh4ZJpe8nJyXR0dEjJ4xUYGRlhdHTUjtTFlmdubg6VSkVUVJStTTHhaj6Yw3r7Go2GL3zhC1RWVprtmHFxcfT09BAaGmpSC5x88sk8/fTTVFRUEBMTw9/+9je+9rWvLXmej48PKpWKM888kwcffBAvLy/i4+O58MILGRoa4sorr2RiYoIPPviApqYmqqqqAEwy5ezsbLO9ho0SFRWFXC6nu7vbZjbYK2q1mvHx8WW/oDw8PEhPT2f79u2MjY1x8OBBurq6pBOcBZiZmaGhoYGSkhI8PT3ZvXs30dHRywYr0tPTaWpqkgJvR2GUC6elpblUg8SxsTHkcjm+vr62NkVCwqno6+vjqquuYnh42CzHEwSB5ORk2traMBgMlJSU4Ovry49//GOuu+46qqqqcHd359NPP2Xv3r1Lnrt3715UKhUDAwO8++671NbW8sMf/pDo6GiKi4vZu3cveXl53HfffQAmf6exsRFgXePdLYEgCGRmZtLV1SWV0S9DT08PgYGBy05K9PX1Zdu2baSmptLa2kppaSkqlUo695sZURQZGxujoqKC2tpaoqOj2bFjB4GBgcfs6+7uTlxc3DHKPImFaWSNjY3k5eW5VKKts7OT2NhYl3rN9obDvvPe3t5ce+21nHfeeWars3Z3dycsLIzAwECOO+446urquPHGG5mdneXpp5/mggsuYGRkhJNPPvmY5xrLAuLj4/nwww/53e9+hyAIfOc73+H1119ndnaW2dlZVCoVL774Iv39/ezcuRNYqEG35ckpIyOD/v5+KStyFI2NjaSlpa06GtLT05PMzEwKCwvR6/UUFxfT2Ngoja/fIkbnory8nJqaGgICAtizZ8+aJwylUinJh5ehtbUVf39/l5saZ1+9eY4giswb5s2+SUhYk/DwcAIDA7n00kvNpq4OCgpCo9FwzTXXADA1NcVNN93Em2++iaenJ2q1mgsuuGDZMkwfHx+USiVqtZrp6WluuukmAE4++WTq6uqYnp7mS1/6Em1tbVx55ZX8+9//5q677kImk/Hggw+axf7NIJXRL8/c3BxdXV1rfn/7+fmZSvhUKpWUdDMTBoOBvr4+SkpK6O7uJjEx0dT8fDViYmIYHR21m+Ez9oDBYKCqqoqMjAw8PT1tbY7VmJubY3Bw0KRctBtczAdz2EDP7Owsjz76KMPDw9xzzz1mO258fDzd3d0mJ+HBBx/kww8/ZNeuXbz77rtcccUVq15oPvfcc9TV1ZGYmAhAU1MTQUFBpkaxBoOBkJAQAgIC+MlPfsJxxx1HTU2N2ezfDG5ubuTm5lJbW8vc3JxNbbEXhoeHcXNzWzZrsRweHh4kJSWxZ88e/Pz8qKqqorKyktHRUSnDtAH0ej29vb0UFxfT3d1NUlISO3fuJCIiYt0ZAUk+vJTh4WHGx8dJSUmxtSlWZXx8HDc3N7tT8yzIhl2nEaCEczI8PEx3dzcHDhzgzTffNMsxBUEgKSmJkZERU7DnkUce4Z133uHiiy/mH//4B1deeeWKzw8JCaG2tpaPPvoIuVxuCkDt2LEDvV5Pf38/kZGReHp6kpOTw80330x4eLjNJ5D6+PiQkJBATU2N5C8c4eiy+bVQKpVkZWVRVFTE/Py8KemmVqstbKlzMTs7S2trKwcOHECtVpOfn09eXt6SEq3VEASBtLQ0k1pOAlpaWggJCXGpARhgv715XM0Hs693fwMkJiZy9913k5iYyJlnnmm24xpVPfHx8QAUFRXxl7/8hS984Qu89NJLXHHFFas+39vb2xTkAXj77bcpKSlhYGCAuLg4urq6AFAoFPziF7/gs88+42tf+xoDAwNmew2bwdvbm+TkZKqrq13e0TAYDDQ3N2+qYa1MJiMyMpJdu3YRHx9PX18fn332Gc3NzdIo1RUQRZHh4WGqqqooKSlhdnaWbdu2bci5WIwkH/4co1w4Nzd3VWWaM2KXah4JCSchLS2N3Nxc4uPjycrKMttxg4OD0Wg0ppL2wsJCnnrqKdP9xx9//KrPj4mJMSVoPDw8aG1t5Zvf/Cbu7u7HlKg/+uij9Pf3s3v3bpurcCMjI/Hw8DD5iK7MamXza+Hu7k5iYiJ79uzB39+fhoYGiouL6erqMmtfT2fCmGArLS2lurraVCKfmpqKl5fXho8XFBSEIAjSdDRgaGiI6enpJdeFroDdqnlcEIcN9AB85Stfoa6ujssvv9ysx42Pj0ej0fCjH/2Iffv28emnn5oisRtt6hkSEkJERATT09M0NDTQ0dFxzD6/+tWvOPvsswG44YYbUCgU/POf/9zy69go4eHheHt726wxob3Q3d1NaGjolnuZBAQEkJOTw+7du/H19aWpqYni4mI6OzvRarVmstYxEUWRqakpGhsb+eyzzxgaGiIuLo49e/aQnJy8ZXmrJB/+XC6cmZnpUnJhWFDzyGQy/Pz8bG3KMogYDPNm3yQkrIlMJuPnP/85DQ0NpKenm+24giCQmJhIVlYWDz30EIWFhcDC9KXdu3dvOGAdFRVFRkYGhw4dYmBgwHROWHzh9eMf/5i7774blUpFYWEhCoXCJqPXMzIyGBgYYHx83Opr2xONjY2kp6dvKTkhk8mIiIigsLCQgoICDAYDZWVllJWVMTAw4PJj7Q0GwzEJtuzsbHbs2EFMTAxubm5bOr6xX+LiScauxszMDC0tLeTk5Lhcoq2rq8uOe/O4lg9mj78Bm+Pu7k5sbCxXXXUVHh4euLm54e3tzdDQEO+9996Gj+fm5saLL74IsCTQ89prr/HII49QVlbGzMwMTU1NvPPOOwA8//zzNlHWpKWlMTo6yuDgoNXXtgd0Oh29vb1mjb67ubkRERHB9u3bKSgoAKCyspLi4mJaW1uZnJx0CRXV/Pw8KpWKuro6PvvsM1pbW029d7KysggICDDbydDV5cOiKFJbW0t4eLjLyYWNk1pSU1NtbYqEhMQmMI5qvuyyy2hsbGTPnj00NjbywgsvbKpp8bZt27jxxhsBTIoZQRB48MEHefXVV7n77rvRaDS8/PLLJgVDSUmJ+V7QOpHJZOTl5VFXV+eySQqVSoVcLicgIMBsx/T09CQhIYHdu3eTlpbG5OQkxcXFlJWV0d3dzezsrNnWsmd0Oh19fX1UVlZy4MCBYxJs5hzUoFAoCAkJsXlZpK3Q6XRUVlaSnZ2Nh4eHrc2xKrOzswwODhITE2NrUySA9RW/uiDx8fEUFxej0+kICwvj1ltv5dFHH2XHjh2bOt7555/Pq6++umTC1llnnQUs1G+6u7vzz3/+k71793LPPffwpS99iZtvvpnvf//7VpX8yWQy8vPzKS0txdPT06wnW0egpaWFxMTELWczVsLT05P4+Hji4+PR6XQMDw/T3t7O9PQ0AQEBhIaGEhAQ4BQnBlEU0Wg0jIyMoFKpmJ2dJSgoiPDwcDIyMiwe6Q8KCqKrq4uRkZE1Gwg6G62trbi7u5tKUF2J/v5+fH19l23Yag+IInY9ilNCwtYIgkB6ejr19fU0NjYyNTXFO++8w8svv7zsBKb18Otf/5pdu3aRkJBguu/mm28G4LHHHjP5YHfddRdRUVF8+ctfZmBggGuvvdaqfb4UCgXZ2dlUVlZSVFSEu7u71da2NQaDgZaWFrZt22axNXx8fEhLSyMtLQ21Ws3w8DA1NTXMzc0RHBxMaGgofn5+FvMBrYnBYGBqaorh4WGGh4cRBIGQkBCSkpLw8fGxuMokMTGRkpISIiIinMKnXS8Gg4HKykqSk5M31X7A0WlubiYlJcVO1Tyu54M5bKDH0tkONzc3kpOTKS8vJy0tjfHxcb785S9vKfBxzjnnLHv/Sy+9RFZWFv/617944IEHCAgI4M033+Tmm2/m9NNPp76+3qone3d3dwoKCigvL6egoABvb2+rrW1LpqammJ6eJjMz0yrreXh4EBUVRVRUFAaDgYmJCYaHh02NhP38/AgICCAgIAClUmn30s/5+XkmJycZHx9nfHycmZkZvL29CQoKIj09fdMO+lZIT0+noqKCXbt22e1Jx9z09vYyNTVlUo+5Enq9nvb29k0H5K2DyLwLORkSzomlS1+MwdqJiQnS0tLo7OzkvPPO2/TxvLy8li3zn5+f55VXXuHEE0+kpqaG0047DS8vL958802uueYaampqePzxx7fyUjaMv78/ycnJVFRUUFhY6DLnrq6uLkJDQzfVF2YzKJVKlEol8fHx6PV6RkZG6O/vp6GhAZlMhr+/v8kHs5ZNW0Gn05n8r/HxcfR6Pb6+vgQHB7Nt2zarB1vkcjkJCQm0trZaza+2NaIoUlNTQ3h4OGFhYbY2x+qMj4+j1WoJDQ21tSmr4Fo+mMMGehoaGkx1vJYiLCzM1EzKy8sLjUZjdoXLn//8Z5544gm++c1vUl9fz3HHHQcsjIz8+9//zhlnnMHLL7/MV7/6VbOuuxYKhYKcnBwqKyspLCx0+mi8KIo0NjaSkZFhk4CKTCYjMDDQ1ETSmIkZHx+ntbWV6elpPDw8TCNklUolPj4+eHh4WN1eg8GARqMxjbFVq9Wo1WpEUTQ5Runp6SgUCpsHp4zy4e7ubpdQt4yMjNDT00NRUZHN33tb0N7eTmxsrNN/X0lI2JqmpiZTMN9SJCYmmoIelijD1Wg03HTTTcjlcpqbm7nkkktMF/TZ2dm8++675OTkcPfddxMbG2v29VcjLCwMjUZDTU2NSzTTN5YV7dq1yybry+VywsPDCQ8PBxaSBhMTE4yNjdHT04NOp8PLy+sYH2y9U8HMyfz8vMnvMvpgMzMzppK3gIAAEhIS7OI8GBkZSU9PD9PT03arsjUnLS0teHh4EBcXZ2tTrI7xOio7O9vpv68cCYcN9AAUFBRQU1NjsckqgiDQ1tbGrl27+Oijj8xexzs7O8v3v/99nn76aW677TY++OCDY+Sip59+OjfccAMXXHCB1RURfn5+JCcnm4I9zpxVGhoawsvLy26atxqzSf7+/qYAhU6nM53YVSoV7e3t6HQ63Nzc8PT0NG0eHh6mn93d3XFzc0Mmk5m2oxFFEVEUmZ+fx2AwMD8/j06nQ6vVmrbFt2EhgGJ0dEJCQlAqlXYrdU5MTKS4uNg01cRZmZ6eprGxkcLCQrv9XVgSjUbD8PCwzS4U1osILt2gUsI50Gg0nH/++fznP/+xmNrBy8uLyspKcnNzLTIV68CBA/zf//0f3/3ud3n++ed5//33lzweFBREfHw83/3ud3n55ZetfvESHx9PQ0MDra2tpKSkWHVta9PS0kJSUpLdnLvkcjnBwcGmsm9RFJmdnTUFVnp7e1Gr1ej1etzd3Vf0weRyOTKZzOSHLfc3JIoiBoPBtOn1+hX9L51Oh0wmMwWb/P39iYqKQqFQ2KWPbuyX2NDQQGFhoVMHAHp7e5mennZJNTUslM37+fnZfUDP1Xwwhw30xMbG0t3dTUFBAVVVVRbrYxMREUFdXR0pKSlmHc0oiiLf+c53OPPMM3n44YeRyWTLNg/du3cvP/3pT3n00Uf53ve+Z7b110tYWBizs7NOnVWan5+ntbXVNN3DXvHw8MDDw8Ok+jEyPz+/xCnQarUm+aROp1viQBi/3I7+PQqCsMQZWeyw+Pv7L7ltj87EasjlchITE51aPqzVaqmqqiIvL8/lJmwZaWxsJC0tzeH+PiUkHBF/f38+/fRT9u7dy6uvvmqRYI8gCPT397Nt2zazNoqFhVLtO++8k6uvvprvfe97fPvb3152je9973tcccUVVFRUWLR3zEoYy497e3uddlTx5OSkVcvmN4MgCCgUChQKxTFlKXNzc8cEZqamptBqtej1elMCbbWLS2Mizs3NzZS8MwaMfHx8liTvHM0PDwgIwNPTE5VK5bTlTK6upjaWze/cudPWpkgchcMGekJDQ7nhhhv46U9/SlZWFnV1dWYP9mi1Wn7/+98zPj7OE088YVbl0CeffMLHH39McnIyvb29qFSqZbM2SUlJvPTSSzz++OM2CfQAxMXFmcYEOuMkm87OTiIjIx32Atk4Fc5VeiltBmeWD+v1eioqKsjIyHC617ZeRkdHEUXRQZpui3bXCFAQhCDgRSAB6AAuFUVx7Kh9CoA/A37APLBPFMUXrWqohN2QmJhIUFAQH3zwAaeddhr79+83e7Cnrq6Ot99+m8HBQX71q1+Z9di//e1vSUhI4O9//zsADz30EPfff/8x+1100UXceOONfPTRRzYJ9AiCQF5eHqWlpXh5eTnId9z6sXXZvDlwd3fH3d3dZc+/6yE1NZWysjJCQkKcLhkzNTXl0mpq+Lxs3jGax9ufD2ZJHPrT9r3vfY9f//rXAGRlZTEyMmLW4z/wwAN0d3dz2mmnkZ+fv2Q0+lZ57rnnSEpKYv/+/Rw+fJjp6ekVpbknnHACxcXFprIZW5Ceno5araazs9NmNliC2dlZBgYGXKJ/iytjnOLS0NDgVKPs5+fnqaysJDY21uXGqBsxjlNPS0uztSmOzA+B/aIopgL7j9w+mhngalEUs4GzgD8IghBgPRMl7AmZTMbLL7/MpZdeSllZGeeff75Zj28wGLj++usBuPbaawkODmZsbGyNZ62fv//973R0dODj48PMzAxqtXrFfU866SQ+/vhjs629Udzc3CgoKKCxsZHx8XGb2WEJBgcHUSgUdlM2L2EZvLy8iIiIcLpriJmZGaqrq11aTW0sm5fGqdsnDqvoMXLbbbdx6qmn8p///Mes0t4DBw6wb98+ZDIZTz75JAqFguLiYqKjo82yzszMDLGxseTn5695gjt06BCBgYE2jYIbs0oVFRUIguA0jcbsfQyghPkwlqA5i3zYOMIzLCyMqKgoW5tjM3p6eggKCrLJVLdNIYoYDHaXTboAOPnIz88AHwE/WLyDKIpNi37uEwRhCAgFxq1ioYTd4e3tzTPPPMNFF11k9gDEgw8+SEVFBRdffDHf+MY3UKvV1NTUsHPnzi0rP0RRRKvVsmvXLgIDAxEEYdVjFhcXExISsqU1t4qnpyfbtm2jvLyc7OxspxjbPD8/T1tbm92XzUuYh/j4eIqLi4mKinKKoIhGo6GiooKcnByXVnM5XNm8ffpgFsPhAz0Aubm55ObmmvWYv/nNb4AF5Y3xAiI1NZWmpiby8/M3fDxRFHn77bd54YUXqKuro6amhrvvvpvKyspVnzczM8NFF13EfffdR19fH21tbQQHB1NbW8vJJ59MZGTkxl/cJpHJZBQUFJiCPdaeQmFuxsfH0el0dj4GUMKcpKWlcfjwYYeXDxuDPCEhIQ7/OdwKc3NzdHV12X0D5sWIgEG0u0aA4aIo9h/5eQAIX21nQRB2Ah5Aq6UNk7B/LrjgArMez2AwcM899wCYyqmUSiUBAQH09fVtqlfNzMwM//jHP3j33Xf55JNPmJiYIDIyck2l9GeffcYf//hH/vOf/9DW1kZ7eztKpZKRkRFOOOEEqypRFAqFyQfLyclxeBVMR0eH01z0S6yNm5sbycnJNDc3k5OTY2tztoRGozEFXR39c7gVHKtsfgE79cEshlMEeizBV77yFby9vZfIkUNCQujq6mJsbOyYhrhr8fjjj/Pd737XdDs0NJT77ruPs846a8XnGAwGLr/8cvR6Pb/85S/53e9+R3JyMgcOHDDt8+yzz3LxxRdvyJatIJPJyM/PNwV7HFWqJ40BdE08PT1N8mFLNXC3NMYgT1BQkNMo6zZLW1sbCQkJNhlxa4eECIJQuuj2E6IoPmG8IQjC+0DEMs/78eIboiiKgiCsWN8oCEIk8CxwjSi6kLckYTVkMhnXXnst27ZtW6JWTEpKoqSkhPDw8A1/5i+99FL2799vuh0dHc2vfvUrfvvb3674nL6+Pq655hpgoXzM09OTmJgYiouLTftYoj/kanh7eztFsGd2dpbBwUF2795ta1MkrEhYWBjd3d1MTk469N9ueXk5WVlZTqGs2yzGsvm8vDxbmyKxCpJ3vAKXXXYZl1122TH3p6enU1VVxa5duzakCLj44otJT08nJSWF6OhoZDIZ/f39qwaM6uvrqa+vZ8eOHdx4441cccUVwMKXjCiKfO1rX+P222/H39+f008/feMvcpMY68XLy8sRBMEhJ0E4yhhACfOTkJDAwYMHHTKTaDAYqKqqIjAw0OX7Sk1OTjI+Pu5wvXlEROYtIxseFkWxaMV1RfGLKz0mCMKgIAiRoij2HwnkDK2wnx/wJvBjURQPbtliCYkVePTRR4+5z93dnfj4eJqbmzc8oem3v/0tY2NjpKamEhISgiiKdHV1rRosf/nll8nLy2NsbMxUcgIwPT1Nd3c3d9xxB6eccgolJSVWLQf29vYmPz/fNHre19fXamubi+bmZlJTUx1aWSuxcYz9Eo3XNo6WaDUGeTIzMwkICLC1OTalq6uL4OBghxsEY0EfzC6RvmE3iFKpJCIigtbWjSnWQ0JCOOWUU4iNjTWd2CIjI1edUlFVVUV3dzeiKHLJJZeY7vfy8kKhUPDCCy9w//33c/HFF5t19Pt6cHNzY9u2bfT19dHX12fVtbeKcQzgSs2vJZwbmUxmkg87EgaDgerqavz9/UlISLC1OTbFYDBQV1cnKfLMx7+Ba478fA3w+tE7CILgAbwG/E0UxVesaJuEhIno6GjUajWjo6Mbel5GRgZ79uwx9doRBIH4+PhVvz+qq6t56623+OY3v7lEWeTj40NmZiZvvvkmRUVFNpmIqlQqyc/Pp7q6munpaauvvxWMZfO27nskYRt8fX3x8fFhYGDA1qZsCK1WS3l5ORkZGRuu6nA21Go1fX19JCUl2doUiTWQAj2bICEhgdHRUSYnJy26zqeffgoslGd5eHgseUyn03HNNdfw3e9+l/POO4/6+nqrTxMyBnt6e3vp7+9f+wl2gmONAZSwBGFhYczOzjIxMWFrU9aFKIrU1NTg6+vrsCVn5qStrY2wsDDHVOSJYBDnzb5tkV8DpwuC0Ax88chtBEEoEgThySP7XAqcCFwrCELFka1gqwtLSGwEQRDIzs6moaEBvV5v0bX+8Y9/AHDvvfce81hHRwd79uzh8OHDZGVl2SRxoFQqycvLo6qqatWpYfaEsWw+PT1dCtK7MCkpKbS3tzM/7xjKCq1WS1lZGenp6S4f5BFFkdraWjIzMx1znLx9+mAWQwr0bAKjo1FXV4fBYLkWBc8++yzAstn7l156iZdeegm9Xs/rr7/O7t27iYmJQaPRWMye5ZDL5Wzbto3u7m56e3utuvZmmJmZkcYASpjkw42NjXY/bt1YrqVUKqXsCQslWyMjIw6salqY+GDubUsWieKIKIqniaKYKoriF0VRHD1yf6koil8/8vPfRVF0F0WxYNFWsfX3Q0JiYygUCmJjYy0aXDFegH7/+99ftrzo3nvvpbKykunpaX72s5+Rl5fHD37wg2P2szQ+Pj7k5eVRWVlp8eSjOZDK5iUAPDw8iI6Opr293damrIlGo6GsrIy0tDSCgoJsbY7N6erqIiAgwIFL1+zPB7MkUqBnk/j4+BAeHk5bW5vF1tDpdKSnpy/72E9+8hP8/Py4++67aWlp4Sc/+QnBwcFcffXVFs9yHY1cLqewsJDBwUHa2trs+sK5qanJscYASlgMo3zYntVoc3NzlJWVERAQQHJysq3NsTmLS7akz7CEhOsSExODWq1mbGzMIsc3XoCGhx87gK6lpYWXX34ZQRDYv38/hw8f5sorr+TFF1/kz3/+s0XsWQ0fHx/y8/OpqalhZGTE6uuvF6lsXmIxsbGxqFQqqyeoN8LU1JSpJ48jTZayFMaSLckfdRwkT3kLJCQkMDIyYpEsyszMDMCKjUZFUWRycpJzzz2XiIgI7rrrLkpLS5mZmeG2226zSRlXQUEBGo3GJmVk68ERxwBKWBajfNjawdH1oNVqOXz4MDExMS7feNlIe3u745ZsHcE42tPcm4SEK2FUVtfX11uk/MM4WWu57xqdTsf8/DxxcXHk5uaSlZXFX/7yFz7++GN++9vf8vLLL5vdnrVQKpUUFhbS0tJit8mL9vZ24uLipLJ5CWChX2JqaipNTU22NmVZRkdHqa6uJj8/34HVK+bD4Uu2juBqPphTB3q0Wi3XXXedxfpwWLKES6FQ8Pjjj/O73/1u2ccHBwcBSE1NNd3n7u7OqaeeylNPPUVjY6NZ7VkPMpmMrKwsPDw8qKystKvaW+MYwJUUUhKuiYeHBzExMXR0dNjalCWo1WoOHz5MWloaERHLTcR2PaamphgeHnbgki0JCdeirq6O73//+xY7viVLuE4//XT+3//7f+zdu/eYx0JDQwG46KKLlvSZMU5DvPrqq81uz3rw9PSksLCQvr4+uzunzczMMDIyIpXNSywhJCSE+fl5iynzNsvAwABNTU0UFhaiVCptbY5d0NXVhb+/vxT0cjCcOtBz77338vzzz1t0hLKPjw9hYWFmL+ESBIGrr756xZPiGWecwf3337/kvtLSUu6++24ef/xxMjIyzGrPehEEgZSUFIKDgykrK2Nubs4mdhxNT08PQUFBDjcGUMLy2Jt8eHx8nMrKSvLy8qR68CMYDAZqa2vJyspygpItkXlx3uybhIS9UVhYyMMPP2zRNWJiYpienjb7hWJYWBhf/epXl73IM34vX3fddUvu//GPf8yBAwcoLS01qy0bwdg3cWpqyq560DU2NpKamio1YJY4Bnvrl9jZ2UlPTw9FRUUWvX50JGZmZujr63OSskvX8sEc3WNeEbVaze9//3tSUlJWHWFuDixZwrUSr7/+Ot/+9rdNt9VqNSeeeCKwoF6xdSlKbGws8fHxlJaW2vwCem5ujq6uLqmRrcSy2JN8eGhoiPr6erZt2+bQ5Unmxliy5evra2tTtowo4lKNACVck88++wyABx54wKLrWLqEaznc3NzQaDRLLnr279/Pk08uDKibmpqyih0rIZPJyMnJQRAEqqurLTo0ZD0Y+wZJZfMSy6FUKgkMDLT5QBej8n9iYoLt27cjl8ttao+94CwlW0ZczQdzqkCPKIrs27ePnJwcQkJCADjnnHO44447OP/88/ne977HHXfcwS233MK///1vs538ZDKZVaZwrYZSqeT555/Hy8uLm266yVTaZUvCwsLIzMykvLzcpo5Pa2srCQkJ0pe2xIrYg3y4u7ubzs5OioqKUCgUNrPD3pBKtiQkHAOVSsU3vvENIiIiOO2004CF8qprr72Wiy++mLvuuovvfOc73H777VRVVZltXWtM4VqLPXv28Ktf/QqASy+91GZ2GBEEgbS0NPz9/W2qrjYYDDQ3N0tl8xKrkpSURGdnp82S1AaDgZqaGkRRJDc31wmUw+ajq6sLPz8/qWTLQXHYv+Ta2loeeOABWltbee+997j11lv55S9/yX333ccf/vAH/v73v3PDDTfw0EMP8e9//xuVSkVQUBC+vr7I5XJ+8pOfEBAQwIUXXshbb7215UyQpUq4NsKFF17Ijh07CA0NtZvJCwEBAeTl5VFTU8PAwIDV15+enmZiYoKoqCirry3hWNhKPmycJDU6Osr27dulRpWLcK6SLSOiSzUClHBOGhoa+Ne//kVLSwvPPPMM3/nOd7jssst49tln+fjjj3nyySdJT0/n1ltv5aOPPsJgMBAYGIiXlxfj4+N86UtfIjw8nFtvvZXKysot22OpEq714u3tzY033gjAWWedZTc+WHx8PDExMZSWljI9PW319Xt7ewkODpbK5iVWxd3dnfj4eFpbW62+9uzsLKWlpfj5+ZGeni6VFy7CuUq2jLiWDybYS03kRsnIyBCzsrIoKysjLCyMnJwcxsbGKC0tNTVf9vPzY2ZmhrGxMVJSUujo6ECpVBIeHk5fXx/BwcHExsby6aefEhMTw9e+9jW+9a1vbbpkwmAwcOjQIdLT020W+aytreXrX/864+Pj1NbW2s3F0dzcHDU1NXh7e5Oammo1uw4fPkxycrIUiZZYF42NjSiVSqs1jJydnaWqqoqwsDDi4+MlB+MompubcXNzs1rZpUKhOCyKYpEl14jLDBLvfPoMsx/3tt0vWtx2CQkjKSkpYlBQECMjI2RkZODr64ter+e9995Dq9Xi7e2Nt7c3k5OTTE1NkZSURHd3NyEhIXh5eTE4OEhKSgqiKFJdXc2OHTu46aabuPzyyzf9PTgzM0NFRQU7duywWcD8//2//8dvf/tbzjjjDP74xz/axIblmJ6eprq6msTERKs1+J+bm6OkpIRdu3ZJimqJNRFFkeLiYnJzc63WAHl0dJSGhgYyMjKknohHYTAYKC0tJS0tzWrXUJIPZn4c9ptXqVTy3HPPmW6//vrrPPvss3h7e/Puu+8SFBTE+Pg4U1NTJCQk4OPjg1arxd3dHZlMxtTUFB999BEvvvgigiDQ3d3Nz3/+c+Li4rjiiis2ZZNMJiMvL4/y8nKKiorw8PAw18tdN1lZWfj5+dHW1mY3jc1gIVpfUFBAe3s7hw8fJi8vz+JNzlQqFe7u7lKQR2LdJCcnU1xcTEREhMUdU8nBWB2VSsXk5CTbt2+3tSlmRQS7rueWkFgP/v7+/O9//wMWxo3/+c9/5h//+Aenn346jz76KHNzc4yPj6PT6UhNTcXNzQ2tVmvqmTg0NMQLL7zAe++9R3V1NYcOHeLQoUOceuqpmw5EeHt7k5SURE1NDQUFBTYJnJ977rnceuutdjV1FBZU50VFRdTU1DAxMWGVhFtLS4tUNi+xbgRBID09naamJrZt22bRtURRpLOzk6GhIbZv327xXq6OSFNTE6GhoU53DeVqPph9yD02weI6zu7ubr7yla9w0kkn8dlnn5GYmIi/vz/x8fHk5OSYFDqenp6mE5uvry9f+tKX+Pvf/87g4CAdHR385z//4ZJLLtmSXQqFgtTUVKqrq20SaNFqtTQ3N6PX6/nTn/5k9fVXQxAEkpKSSExM5PDhw4yPj1tsLYPBQEtLC2lpaRZbQ8L5kMvlFpcPi6JIR0cHLS0tbN++XQryLINGo6G5uZnc3FxJ5SQhYYcs9m+ef/55fvOb33DPPffw7LPP4ufnR3BwMMnJyWRmZiKXyxEEYcnFVFhYGN/+9rd544036O3tpb6+nv37929ZbRIREYGXlxednZ1bOs5m6erqQi6X8+abb/J///d/NrFhJYwJN3d3d8rKytBqtRZba3p6msnJSals3omwRjAkMDAQmUzG8PCwxdbQ6/VUVVUxMzNDUVGRFORZhsHBQTQajdQb0Qlw2EBPc3Mzzz33HLOzs0RHR/P1r3+dl19+GZ1Ot+Fj+fj4EB4ezmmnnWYWFU5oaCi+vr426dfj5eVFW1sb7733Hr///e9tUu+6FiEhIRQUFNDQ0EB3d7dF1ujq6iIsLEz6ApfYMNHR0YyPj6NWq81+bMnBWBuDwUBVVRWZmZk2UUVaHNG1RntKOCft7e18+OGHAJx33nnEx8fzwQcfbCrBFRQUREJCAscdd5xZbEtPT2dwcNAm/Xp27tzJ1NQUN998Mw8++CCjo6NWt2E1jAm3hIQEiyXcRFGksbFR6nfiZMzOzlplnbS0NJqbmy0y3EatVlNaWkpISIiT9f4zHzMzM7S2tpom9zkdLuaDOexfeFhYGE8//TSnn346TzzxBA899BC7d+/mjDPO4P3337e1eaSkpDA6OmqzhnxpaWkMDg6Sk5ODSqWyiQ2r4e3tzY4dOxgfH6empsasMmetVktfX58UiXZCrBEYMU4raWxsNOtxJQdjfTQ2NhIeHk5gYKCtTbEIIiIGg8Hsm4SENfH29uaWW27h8ssvp7q6mrfeeouysjKuuOIKWlpabGqbsYy+vr5+U8k/c5Cbm8vbb7/Njh077KqM3sjRCTdz2jg8PIyHh4fTlXxIWAeFQkFoaKjZE8FDQ0NUVlaSlZVFdHS0WY/tLMzPz1NVVUV2drbTDgZxNR/MYa80goODeeutt7j55pv505/+xN69e7n11lu5/fbbufbaa2lvb7epfUZHo7Gx0ezyWFEUefjhh/nBD37Ak08+yeTk5DH7+Pj48Otf/xqAxx9/3Kzrmws3NzdycnLw9/enpKRk2dexGVpaWkhKSsLNzc0sx5OwH6yVUQoMDMTNzc0s8mFRFOnp6ZEcjHUwMDDA7Ows8fHxtjZFQkJiFSIiIvjoo4/Ys2cPV155JT/72c947bXXiI+P54orrrDZmGQjliyjHxsb46c//Sk/+MEPeOutt5Z9rWeddRZnnXUWfX19VFRUmHV9c2FMuE1MTFBZWWmWoJixbD41NdUMFkq4KomJifT29prlb3J+fp76+np6enooKirCz8/PDBY6Jw0NDURFReHv729rUyTMhMMGemChn8bll1/OJ598Qnp6OhdddBFnn302t912G7fffrvNsyienp6kp6dTVVVl1mifTqfj+9//Pi+99BLvv/8+KSkpZGdnc+utt/LGG29QX1/PwYMHyczMJD8/n3379pltbXMjCAKxsbHk5uZSX19PW1vblt6ryclJZmZmCA8PN6OVEq6IOeTDWq2W8vJyJicn2blzp+RgrIJaraatrc155cKLMIjzZt8kJKyNsc/Ohx9+SFNTEz/60Y/45S9/SWBgII899pitzSM0NNQ0nMKc1NXV8cADD1BXV8evf/1rIiMjOe644/j1r3/NG2+8QUdHBx999BHf+MY3ALjvvvvMur45MSbcoqKiKC0t3bICXCqblzAHbm5uJCYmblkdOD4+TklJCT4+Pmzbts05y8HNRF9fH3q9ntjYWFubYnFcyQdz2EDPYpVMYGAgv/zlLznzzDPZuXMn55xzDtXV1dTX19vQwgWCg4MJCgoyq5TZ09OTmpoa08n08OHDPPjgg/j6+vLYY49x9tlnc8MNN/CnP/2J1NRUDh48aLa1LYWPjw87duwwjfPbTH8UqS5cwpxsVT48MDDA4cOHiYuLIysrS5o8sgrz8/NUV1eTk5PjtHJhCQlnYnEiLTU1lZdeeonm5mbOO+889u3bx+9//3ubJ9tgYZKiucvojz/+eP75z39SVVXFJZdcwuHDh/nWt75FU1MTf/7znyksLOTuu+/m8ccf5/rrr+evf/2r2da2FGFhYRQWFtLT00Ntbe2mFFlS2byEOYmIiGB6epqpqakNP9dgMNDc3ExTUxP5+fnExsZK1wWrMD09TWdnJ9nZ2dL75GQI9nAi3gxhYWFiV1fXMff/4Q9/4J133iE5ORmDwcAf//hHm184iKJIWVkZcXFxhIaGmu24Go2G7373u3zwwQf4+fkRERHB3r17GRkZISQkhPDwcKKiosjLy3OoD+7ExAR1dXVER0dv6Mt5YGCAkZERsrOzLWyhhKswPz9PcXExRUVF684Ezc3N0dDQgMFgcN6GwmampqYGf39/m2eSFArFYVEUiyy5Rky6v3jLE8eb/bh3nfxfi9suIWEkNTVVrK6uXnLf/Pw8e/fu5fjjj+evf/0r99xzD5dddpmNLPwcrVZLaWkphYWFZlWadHR0cMUVV6DT6RBFkZycHE477TSGhoaIiooiPDyc5ORkhypFFUWRvr4+Ojs7yczM3FCvtNraWoKDg7c8OU1CwsjExATNzc0UFhau+1pgenqa2tpawsLCSEhIcKjrH1ug1+s5dOgQOTk5+Pr62tQWyQczPw6bYl6p782tt97K66+/jk6no7u7mx/96Ef89re/tbJ1SxEEgdzcXEpLS/Hx8UGhUJjluAqFgscee4zi4mLm5+c5dOgQN998M2eccQbh4eEMDg5SX1/Pl770JTIyMpicnOQb3/iGzT/Ia+Hv78/OnTtpbm6mrKyM7OzsNZ2z+fl52traKCwstJKVEq7AYvlwVlbWmvuPjIzQ2NhIYmIikZGRVrDQ8ent7cVgMBATE2NrU6yCCHY9oUFCYj0s1zvDzc2NP/zhD5x88snccMMN/PjHP8bPz4+zzz7bBhZ+jqenJ5mZmVRXV1NYWGi2RvgJCQl88MEHJtX0U089xTe+8Q1uvfVWqqqqGBwcpLq6mt/85jd0dnYSHx/P5ZdfbteN+AVBIDo6mqCgIGpqavDz8yM1NXVNm41l8+s5T0pIrBd/f3+8vLxQqVSEhYWtuq8oinR2djIwMEB2drbdX+vYA6IoUldXR1xcnMu8X67mgzlsoCclJWXZ++VyOa+88gqnnnoq/v7+LKf6sQUeHh5kZWVRVVVFUVGRWRsF79q1C4A9e/ZwzjnnLGmCd+mll/Loo4+abv/kJz9hcnLS7stI3NzcyMjIYGRkhLKyMuLj44mKiloxMt/R0UFUVBSenp5WtlTC2YmIiKC7u5upqakVT4R6vZ7m5mZmZmbYvn271J9gnUxNTdHV1cWOHTukrJuEhAMREhKy7P0JCQk8//zzXHrppYSFhZl9cs5mCQoKYnx8nObmZtLT0812XE9PT0466SQAioqK+OUvf2lquD82NkZUVBRf//rXTft/9tlnPPLII2Zb31IoFAqKioro6uqipKSEzMzMFRu0SmXzEpYkNTWVw4cPExISsmLAUa1WU1dXZ0oU23Mw1Z7o7u5GJpNJQ0KcGKf8JBgncl122WU89NBDtjbHREBAAFFRUdTU1Fikdl0QhCVBHo1GwxtvvIGbmxvXXHMNAFdddZVDTaMKDg5mx44dTE5OcujQoWVrdWdnZxkcHCQuLs4GFko4O4IgkJGRQWNj4zGfW6PMvaSkBD8/PynIswFmZ2eprq4mLy/P7gPP5sW1RntKuB579uzh5Zdf5tvf/jZf+9rXbG2OicTERDQaDT09PRY5vlKpXHLBVFxcDMAFF1xgKtvfs2ePRda2BIIgEB8fT05ODs3NzdTW1i6r5BocHMTb21saNiBhETw9PYmMjKSjo+OYx4xJturqalJTU0lLS5OCPOtkeHiYgYEBMjMzbW2KlXEtH8xpPw3R0dHccsstdlcrHBsbi5eXl1mbM6+EQqFg3759vPDCC0xMTHDPPffwhz/8weEyLu7u7mRmZpKRkUF9fT319fXMzc2ZHm9qalqXtFhCYrP4+fnh5eXF0NCQ6b6pqSlKS0sZHx9nx44dREdHO9xny1bo9XoqKyvJyMhAqVTa2hwJCQkzs3v3bq655hqb90hcjLGMvq+vj+HhYYuvd/rpp/OVr3yFBx54AK1Wy0cffcTFF19s8XXNjY+PD4WFhQQHB1NaWkp3d7cp6WEsm5fGqUtYkvj4eAYGBkxtO0RRZHBwkJKSEjw9Pdm1axcBAQG2NdKBmJqaorm5mYKCAodK/ktsHOnK2AakpaWhVqstllVazO23387ZZ5/Nv/71L+69915CQkL417/+ZfF1LYGfnx87duzAz8+PkpISent7GRsbY25uzqxNriUkliM1NZXW1la0Wi0NDQ3U19eTnp5OVlaWXV3M2DsGg4GqqipiY2MJCgqytTlWR8S1RntKSNgTbm5uFBQU0NTUtKlpPhtd669//SvDw8NMTk7ypS99ifT0dDo7Oy26riUQBIGIiAh27tyJRqOhpKSE8fFxU9m8NHTA9bCmelkmk5GSkkJTUxNqtZqysjJUKhVFRUXExcVJSbYNsFhN7YqfW1fzwVxJL283GLNKhw8fxsvLa8Vad3Ny2223cfrpp+Pr68vevXtJT093SLmesVFgWFgYLS0t1NfXk5uba2uzJFwADw8PlEoln332GWlpaVI/gk0giiINDQ34+/sTFRVla3NsgyhiMDjmtEsJCWfAw8OD/Px8KisrrVJuGxAQwG233ca1117Lu+++y6WXXsrHH3/skGW+crmctLQ0pqenqaurY3p6muOOO87WZknYgNnZWauuFxgYSH19PZOTk2RnZ0sKnk2g1+upqKggMzPTddXULuaDSYoeG2HtrNKPf/xjQkNDyc3NJSQkhNLSUouuaWnc3d3x8/MjLCyMzs5O6uvrl60dl3BurOUoG3tEubu74+npSXBwsBTk2QSdnZ0YDAaSkpJsbYqEhIQLo1QqycjIoKKiAr1eb9G1EhMT+eY3v4lSqeSss86irq4OlUpl0TUtjY+PD56ensTExHD48GG6urrsuk+FhOMiiiL9/f0cOnSIqKgo5HL5io3BJVbGqKaOj48nMDDQ1uZIWAkp0GNDjFml6upqi0fG6+vr2bVrFzExMRQWFnL55ZdbdD1Lo9fr6ejoIDMzkx07duDv709paSnNzc1L+vdIODeW/txMTU1RXl5Oc3MzGRkZZGVlkZKSQnNzs0XXdUYGBgYYHh4mKyvLpYNkC7Jhg9k3CQmJjREUFERcXBxVVVUWD1L89re/JS0tjS984Qs89NBDxMbGWnQ9SzM2Nsb8/DxpaWns2rULnU7HwYMH6e3ttciwEQnXQxRFhoaGKC4uZnx8nKKiIlJTU/Hz86O/v9/W5jkURjV1QEAAkZGRtjbHpriaDyaVbtkYpVJJZmYmFRUVFBUVWWz6jPFLsaqqyinG6LW1tREXF2fqjRIVFUVERIRpAlJkZCRxcXEuNs1Hwlyo1WpTP56UlJQl2Y/Q0FC6uroYHx+XpMPrxNjLobCwUGqaLiEhYTdERUUxOztLQ0MDmZmZFgtCDw8Pk52dzTvvvENwcLBF1rAWoijS1NRETk4OsFDOlZKSQlxcHB0dHRw8eJDExETCw8NdOqgvsTlEUWRkZITW1lZ8fHzIz89HoVCYHk9OTubQoUOEhYVJPv46MaqpExMTbW2KhJWRPG47IDAwkPj4eItllURR5H//+x9ZWVlOEeSZmZlhdHSUmJiYJffLZDJiYmLYs2cPbm5uFBcX09HRwfy8/TbJkrAvNBoNNTU11NbWEh0dzY4dO46RuBrHrTc1NUmZy3UwMzNDXV0d+fn5UtPqIxgMotk3CQmJzZGYmIjBYLBYk+Tp6WlaW1s588wzHT7IA9DX14e/v/8xPT48PDxIS0tj+/btjI2NUVxczNDQkHSelFg3Y2NjlJaW0t/fT05ODtnZ2UuCPLDwdxYbG0t7e7uNrHQsBgYGGBkZcXk19WJcyQeTAj1WwthAbCUiIyMJCAigoaHB7CfF4eFhHn30UYcv1zLS2NhIWlrail9YMpmM+Ph4du/ejSiKHDx4UKofl1iV2dlZ6urqqKysJDw8nB07dqzqkPv4+ODr6yvJh9dAp9NRWVlJTk7OMc6ahISEhLUoKSlZ8TFBEMjKymJ4eJiBgQGzr/3vf/+b6upqzj33XLMf29oYy+aTk5NX3MfT05PMzEzy8/NRqVSUlJQwPDwsBXwkVmR8fJzS0lI6OzvJzMwkNzd31WbBMTExDA8Po9ForGil42FUU+fn50tqahdF+q1bie3bt/Pvf/971X2MWaWOjg6zrm2c7BUREWHW49qCkZERBEFY11hmNzc3EhMT2bVrF3Nzcxw4cICOjg6ph4+ECePkkPLycoKDg9m1axehoaHrynokJyfT3t5u8Uaejsr8/DyVlZUkJyfj5+dna3PsB9G1skkSEramvr6ek046adWBDTKZjPz8fNrb2xkbGzPr+gUFBQDEx8eb9bi24Oiy+dVQKBRkZ2eTm5traqY7MDAgJd0kgIVqg+HhYQ4fPkxbWxtpaWkUFBTg4+Oz5nNlMhlpaWk0NTVZwVLHRK1Wm9TUUonbIlzMB5MCPVbAqORZLQMCn2eVxsfHzSIhnpmZoaenh/z8fHJzcznxxBO3fExbYjAYaG5uJj09fUPPk8vlJCcns2vXLgRB4NChQ9TX16NWqy1kqYQ9s9i5aGhoIDQ0lN27d2+4n4AkH16Z+fl5KioqiIyMJCwszNbm2BUiIgbR/JuEhMTyGKeMenh4rLqfu7s727Zto76+nvHx8S2vOzMzw4cffsjOnTv5+te/7vDJtpXK5tfC29ub3NxccnNzmZiY4MCBA7S3t0tJNxdlfn6e7u5uDh48yODgoKncb6MJoeDgYAwGA6Ojoxay1HGZmZmhsrKS3NxcSU19FK7mg0khPitgLO9Yzzg7Y1apoqICQRCIi4vb1JqdnZ1kZGQssWF0dHTTx7MHenp6CA4O3vSXllwuJz4+nri4OFQqFfX19aYyr6CgIKl21cmZn5+nr6+Pnp4e/Pz8SE9PX1fmaDViYmIoLi4mJiZGOpkewWAwUFlZSVhY2IYvCCQkJCTMTU1Nzbr39fLyYtu2bZSXl5Odnb3pMc7PPfcc119/vel2XV0dExMT61Ij2ytrlc2vhUKhID09neTkZHp7ezl06BABAQHEx8evWqYj4RzMzs7S3d3N0NAQkZGRFBYWrhl8XYu0tDSqq6tNiVyJhV6TFRUV5OTk4Ovra2tzJGyMFOixMLOzs6aa7/VO6JHJZBQUFJiCPZsZwxkXF8fzzz/PE088QUBAAK+99hp79uyhpKSE3NzcDR/P1szNzdHT08POnTu3fCxBEAgLCyMsLIypqSk6OztpamoiNjaWyMhI3NzczGCxhL0wOztLV1cXKpXKbM6FEaN8uLGx0STPd2WMQZ6QkBCHHx9sSaTSBQkJyyOKIlqtlsbGxg09T6FQmHywnJycTZWeXnDBBXR0dFBdXc3c3Bxvvvkm0dHRqNVqh+yVMTIygkwmM0ugSkq6uRYTExN0dnai0WiIjY1lz549ZvsMKJVKgoKC6O3tlRJLLAR5jEFqqWR+ZVzJB5MCPRZEo9EQFBTENddcA7ChD93Ryp6NfoEJgsCFF17IhRdeCMBJJ51ESUkJExMTGzqOvdDS0kJCQoLZ60x9fX3JyclBq9XS09PDwYMHCQoKIioqCj8/P8nhcFAMBgMqlYq+vj50Oh1xcXGkpKRYxMEODg6mq6uL0dFRh87WbhVjkCcoKMihlYMSEhLOwXvvvccFF1ywqay2t7f3loI9SqWSu+66C4ChoSFTfx6dToeXl9eG7bElBoOBpqYmsyczVkq6hYeHExUV5XDvk6vj5eXF7OwssPB3PjAwQH9/P56ensTHxxMQEGARnzopKYni4mLCw8NderLn7Ows5eXlZGVlbVqJKOF8SIEeC2I8ST3zzDPAwofQ29t73c93c3OjoKCA8vJyBEHY0mj0jz/+mKeeeoprrrmGxsZGh2rMNT09zeTk5JJSNHPj6elJcnIyiYmJjIyM0NHRwczMDOHh4URGRkplOQ6AKIqMj4/T39/P2NgYISEhpKSkWEW6mp6eTlVVlcvKhw0GA1VVVQQGBjpFw1FLIh5pBCghIWFZjMGZqakpYGFi1EZ8H29vb/Lz8029LjZ7LgkLC0OtVvOVr3yF7373u/z5z3/e1HFsRU9PDyEhIRb1g4xJt7m5OQYHB6mqqkImkxEZGUl4eLhD+ayuyszMDENDQ/T396PVaomIiKCgoABPT0+LriuXy0lISKCtrW3DPTydhcVBnvVWj7gqruaDOZ5+1A649NJLueqqq0yjIldq6isIAq+88orpdkxMDL/61a9WnfxwNG5ubmzbto2+vj76+vq2ZPd1113H1NSUWZoMWgtRFGlsbCQ9Pd0qF9AymYzQ0FDy8/MpKirCw8ODmpoaDh06RG9vrzRhyQ6ZmZmhpaWFAwcO0N/fT3h4OMcddxzp6elWq0/29vYmKCiInp4eq6xnTxgMBqqrq/H39ychIcHW5jgErtQIUELCnGg0GsLCwnjuueeABR9hJR9s586d/PCHPzTdzsvL47XXXtvQekqlkvz8fKqqqpient603TKZjDvuuIPKyspNH8MW6HQ6uru7SUxMtMp67u7uxMTEsHPnTrKzs5mdnaWkpISqqipUKpVLlVw4AqIoMjY2Rm1tLQcOHGBycpLU1FR2795NQkKCxYM8RqKiohgfH3fJIStarZby8nIyMjKkIM86cSUfTAr0bJCZmRn6+/t55ZVX8PPz46qrriIkJIR33nln2f3PPfdcBgYGuPHGGxFFkZ///OeccsoptLa2rntNY7Cnt7fX1Nh5MwwMDCCTyRyqblOlUuHh4WGTLy+jw7Fjxw5TedehQ4eorKxkcHBQCvrYEI1GQ1dXFyUlJdTV1eHt7c3OnTvJysoiODjYJqqapKQkurq6XGqSiCiK1NTU4Ovra7ULAQkJCddlbGyMqakprr/+evbs2cO2bdsICQlhZGTkmH1lMhn33HMPlZWVnHjiibS3t/PVr36Vm266aUMXhMZgT2Vl5ZaCPW1tbURGRm76+bagtbWVxMREmyhqFAoFycnJ7Nmzh7i4OIaHhzlw4AANDQ2MjY1JQR8bIYoiExMTNDc3c+DAAXp6eoiIiOC4444jLS1ty0MuNoMgCKZ+ia6EVqulrKyM9PT0dQ38kXA9pEDPBrniiitMozr1ej2vvPIK3t7efO973+OZZ55Bo9Ec8xx/f3/+8Ic/8L///Y+8vDyam5s5+eSTefHFF9e9rlwuZ9u2bXR3d5uaO2+Ul156ifPOO89sjWgtjcFgoKWlhdTUVFubgkKhICkpyZSlmJyc5NChQ5SWltLR0eGSWQRrYjAYGBsbo6mpiQMHDlBbW4soiiblVVRUlM2l3Ub58EaCuI6MMcjj7e1NUlKSrc1xIEQMBvNvEhLOjsFgIDk52XS7oqKCxsZGvLy8+PrXv85///tfk9J6MWlpabz99ts8+eSTeHt78+GHH3LcccdRXV297rV9fHzIy8ujqqpq0+f7F154gYsvvnhTz7UF09PTTE1N2Tw4JQgCAQEBZGZmsmfPHoKCgujr6+PAgQNUVlaaevFJWA69Xs/g4CA1NTV89tlndHZ24uPjw65du8jNzbVZgm0xgYGByOVyVCqVTe2wFjqdjrKyMtLS0ly6P+TGcS0fTCp63SAvvfQSb7/9Np9++im5ubn897//5f3336e5uZmbbrqJm266id27dxMWFkZERARnnHEGJ598Mkqlkh07dvDMM89wzjnn8Morr3DVVVehUqm49dZb2bt3LwUFBdx+++3Mzc0tq2CRy+Vs376dw4cPIwgC4eHh67a7r6+P3//+97z88stmfDcsS2dnJxEREXbVkE8QBPz9/fH39yc1NRWNRsPw8DCNjY3Mzs4SFBREaGgogYGBDjlZw57Q6XQMDw+jUqmYnp4mICCA0NBQkpKSbB7UWYmoqChKSkqYnp62SVbLWoiiSG1tLV5eXqSkpNjaHAkJCRdAJpPR19fHiy++iEqlIioqimeffZaqqirefvtt3n77bQB2795NbGwsSUlJnHXWWezYsQM3NzeuuOIKxsfHKS8v59RTT+Wcc87htddeIyoqivPOO497772Xc889l8nJyWV9MF9fX3Jzc6msrKSgoGBDPRfffvtt6urquOCCC8z1dlgUURRpaGjY0jh1SyCTyUwNnEVRZGpqCpVKZeplGRISQkhICL6+vnZltyOiVqtRqVQMDw+j1+sJDg4mOjqa7Oxsu31v09LSKC8vJzg42Kl9cGOQJzU1leDgYFubI2HHCMtlPxyBwsJC8dNPP7W1GQAMDg7y7LPP8te//pWxsTFOOukkioqKkMlkvP3225SVlbFz507y8vK46KKLuOmmm/jjH/9IdHQ0F1xwAc3NzaZjeXt7MzMzwzPPPMOll1667Hpzc3OUlZURGxtLVFTUmvaNjo5y3nnnceGFF/L973/fbK/bkmi1Wg4fPsyuXbscZtz5/Pw8o6OjDA8PMzY2hkKhIDAwkICAAPz8/Jz6pGMOdDodExMTjI+PMzY2hiiKhISEEBoa6lBO2/j4OG1tbWzfvt3WplgEg8FATU0NCoWClJQUh/m9rAeFQnFYFMUiS64RlqwUL/1NltmP+8jFpRa3XULCiD35YNXV1Tz11FO89NJLeHl5cc4555CTk0NPTw///e9/GRwc5Pjjj6eoqIgTTjiB888/n66uLt577z1uuummJWVf4eHhDA4O0trauqJ/NTk5SU1NzbobNJeWlnLRRRfxwgsvcNxxx5ntdVuSoaEhBgcHyc3NtbUp6+bo5JC/vz8BAQEEBASgVCqd6lxlbkRRZHZ2lrGxMcbHxxkfH8fLy4vQ0FBCQ0PtKuG6Fi0tLbi7uzvtYAhj4+WUlBRCQ0NtbY5ZkXww8yMFesyIwWDg//7v/3jmmWd47bXXSEpK4vTTT+e4445DJpNx+PBhXnnlFZqbm/n000/Zvn07Wq2Wyy+/nP/+97+m49x3333cfffdlJaWkp2dzb333su111675EtLr9ebptwkJCSYTmA9PT2cd955FBYWUlBQgFar5ZFHHuHyyy9n3759DnOiq6mpITQ0dEOqJXtCFEVmZmZMJ8zJyUlkMpnJ6QgICLBakzp7xNhA0/j+TE1N4ebmtuT9cZQSw+WoqqoiMjLS6U7Cer2eiooKQkJCnLLxsrWcjIt/nWn24/750sN26WRIOCf26INpNBr+9a9/8eyzz/J///d/HHfccXzxi19k27ZtDA8P87///Y/XX38dDw8P6uvr8fT0ZHR0dMlE09NOO43IyEjeeecdOjs7GR8fZ9++fTzwwANL/Ce1Wk1lZSUZGRlLyib+9a9/sW/fPo4//njTePaXXnqJJ554gvPOO8+q78dmMRgMHDx4kMLCQof1UwwGA5OTkyYfQ61Wo1AoTP6Fn5+f3SqDrcFa74+/v7/DJFmPZn5+nuLiYtNAFWdienqaqqoqMjMznbInj+SDmR/X/ZazADKZjBNPPJETTzyRRx99lIqKCt5//33uvfde5HI5N9xwAx988AF+fn6mLx9PT09effVVVCoVzc3N+Pv7k5OTw7///W/Kysrw9fXl17/+NTk5OQQEBKDX69FqtXh5eZGbm0tNTQ2vvvoqfX19+Pr68uSTTzIwMMAXvvAFKioq0Gg0vPbaaxQUFNj2zdkAk5OTzM7OEhYWZmtTNo0gCCiVSpRKpcmJnJubM51Uu7u70el0+Pj44O/vj1KpxMfHB09PT4cJxq0Xg8HAzMwMarWaqakpJiYm0Gq1KJVKAgICiI2NxdfX16kUT84oH9ZqtVRUVBAfH09ERIStzZGQkJBYgkKh4PLLL+fyyy9nYmKCTz/9lPfff58//elP7Ny5k6uvvpoHHngADw8P00V+UFAQ09PT9PT00NTURF5eHl5eXrz88ssm1c8jjzzCXXfdhUwmY25uDq1WS1BQEHl5eVRUVHDw4EHi4uJobW3lL3/5C6mpqSQmJvK///2PmJgYysrKHOo701g276hBHmBJYg0+V6yMj48zODhIU1MTsNBD09fXFx8fH5RKJe7u7ja02jLo9XrUarXJBxsfH8dgMODn50dAQACpqal4e3s7je/p5uZGUlISLS0tZGWZX7lhK8bGxqivrycvL8+pWwNImBdJ0WMFRFHk7bff5h//+AfvvfceRUVFXHbZZaZpAstdCJaVlXHqqacSFBTEwMCASXYql8vx9PQ0NWRWKBRcdtllpKSkUFlZyQUXXMCpp57qsJFeURQ5dOgQmZmZVhuNbSuM9eWTk5Oo1Wqmp6fRarXIZDJTkMjofCgUCrsPGCx2JoyvR6PRIAgC3t7eptfj7++PQqGwtbkWp7W1FTc3N6dQvhiz1+np6U5dD26NbFJoslLc+8sMsx/38a+U2WU2ScI5cSQfbGZmhn/84x+89NJL1NTUcM4553D++eeTlpZGZubymd2HH36Yu+++G6VSiVqtxt3dHTc3N9zd3Zmfn2d8fNykQr399tvp6uoC4MILL+QLX/iCw6pFjGXzu3fvtnufY6vo9XomJyeZmpoy+Sx6vR53d/djfDBHSMLpdDqmp6dNr0WtVqPT6XBzczO9FqMP5owBrcU427XE4OAg7e3tFBQUOFQZ3UaRfDDz41SBnrGxMT788EMuuuiiNZ+v1+v51a9+xdVXX23VOs6ZmRneeustXnvtNRoaGlAqlfzud7+jsLDwmJOISqWipaWFwsLCY+SHBoMBQRBMz+nq6mJwcJCCggKH/gIfGBhgdHTUqaLwG2V+fn5JsEStVqPRaBBFEblcjoeHB56enqZt8W0PDw+zOyMGgwGtVmvadDrdMbcNBoPJmVjsICkUCrt3jiyFs8iHx8fHqaurW3c/CkdGcjIkJNbHcj5YfX094+Pj7NmzZ83n9/T08MQTT/Czn/3MqgGFgYEBXnrpJT766CPKy8v54he/yL333rtsP56Ojg5GR0eX7bdmMBhMdhv7lnl5eZGamurQ5zxHL5s3Bzqd7hgfTKvVAuDu7r6i/+Xp6YlcLjf779+o5F/O/9JqtczNzSGKIu7u7qbAlNEHs4RP6ChMTk7S2NhIUVGRQ78HznJ9tx4kH8z8OGygZ/v27eJnn3225L59+/Zx3333MTw8jFKpXPX5n3zyCWeccQb79++3WXM8g8HAs88+y759+/D29uYHP/gBl1122aadHkeP+DrLhbElMZ7wlzvZ63S6FUeMCoKAm5sbMpnMtMHCe24wGEzbct8HgiCs6NQYbzt75m+zDAwMMDIyQnZ2tq1N2RTGYHNBQYFLqLCs4mQkeYsXWcDJeOLycrt0MiSck+V8sKCgIBQKBb29vWs+/7bbbuOJJ55genraZr1ApqamuO+++3jmmWcoLCzk3nvvpahocx8hURRpampCp9ORnZ3tkOfEiYkJmpubl008Siz8jufm5lb0v7RaLXq9ftnnGv0uox8mCAKiKJp8L6Mvthxubm6r+l/2Gszx8vJidnbWpjbU1tYSEhLikIFLURRpaWlhZmaG3Nxch/xO2SiSD2Z+HFNbCiaFgyAItLS0kJKSQmNjo+mxtQI9L7zwAgDbtm2zuK0rIZPJuOaaa7j66qv53//+x1lnnYWHhwd79+7d1PHCw8Px8PCgrKzMIWs429vbiY6OloI8qyCXy5HL5Wv+fS9GFEWTQ7E4sAMcE/xxhROJNQkPD6e7u5vJyUn8/Pxsbc6G6Onpoa+vb1lFoYRzIQhCEPAikAB0AJeKojh21D7xwGuADHAHHhZF8THrWiphL8zNzZn+7e3tJSEhAY1Gs66AsMFg4IknngCwacNXX19f7r//fu69916efPJJTjjhBHp7e5c0V14vgiCQnp5OR0cHZWVlFBQUOFT5liiKNDY2kpmZaZdBA3tAEAQ8PDzw8PDYkH+9OKCz2A9b7HctDgA5C7YO8gCkpKRw+PBhQkJCHKq5tMFgoLa2Fnd3d/Ly8pzq70LCujjsVZ0gCHR1dVFeXk5ubi7PP/+8KYukUqlWfa5KpeKpp54iMDDQKlnq2dnZFSP1sPBaZmdniYyM5KyzztrSWoGBgeTl5VFVVcXY2NjaT7ATNBoNKpWK2NhYW5vidAiCgEwmM/V3UigUJmmvl5eXqTGlMwZ5bK1sMzr/jY2Ny6ql7BFRFGltbUWlUklBHgux2Ok317ZFfgjsF0UxFdh/5PbR9AN7RFEsAHYBPxQEYfn50xJOj06nY3Jyku985ztkZmbS3NwMYCpxWY0PPvgAgDvuuMOiNhqZmZlZ9XF3d3d6e3u56KKLNhXkWUxCQgLR0dEcPnx4Xe+FvTAwMICPj4/Tl+faAqOi2lj25e3tjY+PD97e3iYfzM3NTbqYtwCenp5ERUXR2dlpa1PWjV6vp7y8HB8fH9LT06W/Cwtghz6YxXCcdMNReHl5mU5MANdddx0AZ5555orN9QAaGhq48cYbAbjpppu2ZMP/+3//D7Vazbe//e0l94+OjvLYY49RV1fHxx9/zMjICLGxsXzhC1/g2muvpbGxkfb2dtNF6H/+8x/Gxsb461//uiGlxkr4+Piwfft2KioqSExMdAjJYlNTE6mpqU4ZbJCwHfaQUfLz88Pb25vBwUG7n7wiiiL19fWIokh+fr70ebQAImAw2F3Q7wLg5CM/PwN8BPxg8Q6iKC6uC/XEgRNFEltHoVBQU1PD9u3beeqpp8jLywPgN7/5zarPe/vtt7nssssAOPvssze9vl6v54c//CHnnnsup5xyypLH6urqePrpp6msrKS2tpaRkRG2bdvGueeey+7du6mqqmJ4eBgfHx9GR0d55ZVXSEpK4tlnn920PYuJjIzEw8ODw4cPk5+fbxa/zpLMz8/T1tbGjh07bG2KhITZiYuLo7i4mKioKJsn/9bCON00NjZ22b5hElvHTn0wi+GwgR5BEMjLy6O8vJynn36aO++8k8LCQurr600ZprPOOmtJo+XS0lJOOOEEYOGDv1I2qaamhqmpKcbGxpienmZ4eJja2lqT2uSf//wnOTk5vP7663h7e/PJJ58wNTXF1NQUXl5eVFVVcckll3D66afzi1/8gtDQUOrr6/nLX/7C3XffTUZGBsnJyaa63vvvv58TTzxxUxdV1dXV/OUvf6G3txetVotGo0Gn05GcnMyXv/xl5HK5ya65uTlmZ2fRaDRER0cTFBRkF429xsbGmJ+fJyQkxNamSEhYhNTUVEpLSwkNDbVb+bBOp6OqqoqgoCASExOlLJJrES6KYv+RnweAZbMDgiDEAm8CKcD3RFHss5J9EnaGcYSxQqHg2muv5ZNPPiEoKIhnn32WhoYGCgsLOeecc5YoRO677z727dsHLCTajj/++GWP/eGHH+Lv709nZyczMzP09fXR2dlJamoqXV1dfPzxxyQmJlJSUsLLL7/Mnj17GBoaYn5+Hq1WS29vLzfeeCM33ngju3fvRqlU8sknn/D000/z8ccfk5ubS0REBGq1mqCgIP773/+SkbHxng2iKPLmm2/y0ksvMTU1hVarZWZmBjc3N3Jzc7nqqquorKwkPj4eg8GATqcz+WDZ2dm4u7vbRXlXe3s7MTExknpTwimRyWQkJyfT3NxMbm6urc1ZkYmJCWpra0lLS5OuhyTMhu3PMFtAoVCQkpKCp6cnzz33HF/5yldMwZiysjJ+8YtfcPPNN/OjH/0IQRBM0mLj44uzLGNjY/z973+ntbWVxx9/HD8/P7Zt20ZAQADBwcFkZ2fT29uLWq3ma1/7GlNTU9x22234+flx8OBBwsPD8fHxYXp6mqKiomP6cezYscPs2ZI33niDb33rW9x8882cccYZprKc0dFR+vv7ueWWW/jf//7H/v37GRkZ4aWXXsJgMKBQKKioqAAgLy+PE044gauvvtqUkbMmxgaGOTk5637O/Pw8s7OzHDp0iO3bt7Nnzx7a2tp44IEHiIuL40tf+hIqlYqgoCA6Ozu55ZZbSElJYe/evcdk/ow2aLXaYyL9nZ2dxMXFodVqOffcczEYDDz99NN0dHTw4IMPctppp3H22WeTmpoKLPR9+uEPf8gdd9xhUnmJoohGo0GtVhMcHCwpJFwUDw8PoqKi6OjoIDk52dbmHIPRwUhNTSU0NNTW5jg3IhgsU8YXIghC6aLbT4ii+ITxhiAI7wPLScp+vMQ8URQFQVjWQFEU/3975x0Wxdn14XsAQYoIUhSQolJEEUXs0dhrNJZYY4s16mtPjNFooiZ2ExNjS+y9a4w1sfdKR1Ep0gSl97473x+480kARUUBmfu69pKdnfLMuDtznlN+Jwxwfl6y9ZcgCAdFUXxWDGOXKYNUq1aN+Ph4vvnmG6pXr86uXbvQ19enQoUK7Nu3j9mzZ/P777/TrVs3ANzc3ABo164dK1euzLOvhw8fcvDgQe7fv8/hw4epXbs2VlZWGBgYYGJiQp06dXj06BGampp8+eWXpKWlsXr1avz9/YmKisLU1FR6vjZu3DhfEKt79+507969WM//q6++4sqVK0yYMIGqVatKIrlPnjzBz8+PkSNHcuvWLTZt2sT9+/e5ePEiFStWlDInNTQ0aNGiBe3ateOLL74okexrVdl806ZNi7xNWloagiBw4cIFmjVrhoWFBQAHDhygSpUqNG/enKdPn2JmZsa+ffvYs2cPdnZ2TJw4scAut6oW4C8GQRQKBU+ePMHKygofHx+GDh1KvXr12LJlC7/++iuenp5069aNjh07YmJiQkZGBnPnzuXcuXMsXryYzp07S/tJS0sjOzv7rcvyZMouJiYmhIWFkZCQgIGBQUkPJx/h4eGEh4fToEEDdHR0Sno4HzbvzgYrlZTZrlsvtvZ89OiRlLmyf/9+du3ahaurK9OnT2fy5MnMnTuXXr16cfToUXbu3ImamhpGRkYsXboUQRCYN28eO3fu5JNPPsHV1RVHR0fatGlTqiPamZmZNGnShCVLlhSa/jxixAg+/vhjrl69Srt27ahZsyZOTk5UqlQJDw8PDA0Nefr0KefPn2fjxo04OjpSuXJlrK2tGTp06HtpcR4eHk5qaioODg5FWv/u3bsMHDhQ0mOaP38+P/zwQ551Zs6cycqVK8nKyqJSpUokJyfTpk0bEhMT+W+XEFEU0dPTQ6lUkpiYKEW0QkNDcXBwYPv27URHR7NixQqGDh3KnTt3uHDhAq1atcLOzo7Tp09LNcDx8fHcv38fyO0+kpaWRmZmJpqammRmZtKrVy927dolO3vKKUqlklu3buHi4lKq0odVBoazs3O5NzDeR8cH4xo6Yo8FtsW+363DfN547IIgPATaiKIYKQiCGXBRFMWX3pQFQdgMnBRF8eCbHFOmbKOywZRKJXfu3MHOzo5bt25x4MABTp48yahRo2jdujUjRozAzc2NatWqMXnyZMzMzNi6dSs//PADffv25cmTJ0ydOhV3d3eGDh1KrVq1aNGixUtL8EsD9+7do3Pnznh5eWFkZJTvc1EUsbGx4fLly7Rr1469e/dKmT4aGhqcPXsWFxcX7t69y/Hjxzl06BAdOnRAFEXq1avHmDFj3otjwsvLCwsLiyJnEOzevZtRo0ZJ7wuywQ4dOsRnn32GsbExMTExAHTq1AlnZ2d+/PHHPOtGRUVhbW1NgwYNuHHjhrR827ZtjBs3jsDAQCZNmoSmpibx8fFUrVqV/fv3M336dAICArh48SL29vYkJiaSkpJCZGRuYqKOjg45OTlkZ2ejra1NWloa69at44svvniTyyTzAZCSksK9e/do0qRJqZnfKZVK/Pz8UCgU1K1bt9RmfL8vyrENVpSGGA2AdYA+oAAWiqK471X7LvMzzsTERNTV1YmNjaV69eosXLiQR48eYW9vT4cOHVi4cCHff/89e/bs4cCBAxgaGrJx40aCg4OxsbHB0tKSxMREvLy82LRpExMmTKBt27al5iZQGFeuXEFPT++lNe52dnb8/PPPODo6cuLECerVq4evry+RkZG4uLhgY2NDs2bNmD17Ng8ePGDIkCFYWlry+PFjWrVqhaWlJXp6eowdO5YffviBH3/8kQMHDuDj41NoG+/XIScnh5CQEGrWrJlneUhICKampixfvjzP8u3bt0tdMe7du0ffvn1JTk6mUqVK/PvvvwCsWrWKAwcO8MknnwDQq1cvIDeC6OHhQYsWLfKI4h4/flx6/+jRI2m5j48PAF9//TXLly9n2rRpzJkzh9jYWAD69u3LmjVrCAgIYN++fYwZM4br169LxtKkSZN48uQJKSkpJCQksG3bNv766y8qVarETz/9RHR0NElJSaSkpLz1dZQpG6ipqWFra5vne1aSqLo6xMXF0bhx43Lv5Hl/iCiVxf96S/4Ghj//ezhw9L8rCIJQXRAE7ed/GwItgYdve2CZss2TJ0+oXr06Dx48oH379mzevBkvLy9Onz7Nrl27GDRoEDNnzuTPP//k1q1b1KxZk71797J8+XJMTU1p0aIFbdq0wd/fn0WLFjFq1KhS7+QB2LlzJyNGjCjQyQO58gK2trZ8//33NG3aFB8fH8zNzbl79y4pKSl07NgRY2NjunTpwurVq/H29sbV1ZUaNWqwf/9+WrVqhba2Nq1bt+aLL77gp59+4ueff+bUqVMEBQUVi7h/YWXzx44dQ1tbm9u3b0vLlEolkydPZtSoUbRq1Ypbt25ha2tLxYoVqVy5Mnv27AFyHUHjxo2jZcuWpKamUrduXQDat2/PihUr8jmFFi1aBICnp2eec/Lw8ACgd+/enDx5knnz5rFmzRr2798PwPDhw9m3bx9hYWHStTl58qS0/fHjx4mKiiI1NZXY2Fjq16/P+PHj0dbW5tixY6Snp/Ps2bNSLaIqU7zo6emhr68vOQNLmvT0dO7cuYOenh716tUr906e90eptMGK0hAjDRgmimJdoAvwqyAIBq/acZl29KiiRE5OTqxfvx5vb28pDVVDQ4O+ffvSuXNnXFxc2L17N9bW1nz//fdUqlSJkydPEh0dzZMnT9iwYUOZECx+ka1bt9K/f/+XrjN79myaNm1KTEwMFy9eJD4+nsaNG/Ps2TMePHiQ5wGnqanJoEGDWLp0KampqaSlpbF8+XJGjx7Njh07WLZsGTk5ORw8eJD+/fszZcqUtz6HwMBArK2t86VYf/fdd3zyySesWrWKhIQEafnvv/8u/R0cHMycOXPYtm0bGhoaREdHEx4ezpgxYzh69ChHjhwBkOrhZ8yYwbNnz4iIiMiT1ePh4UGdOnXo3r07gwcPlhw527ZtY/369Xz77bc8ffqUu3fvUqFCBebOnQvA1atXgVxjrl69egwYMAAtLS2pPHDfvn3o6OhI2Tt169Zl8uTJ7NixAy8vL5ycnLCwsMDe3p5z58699bWUKRuYmJiQnZ2d53tdEsgGRskhiqWy48MSoKMgCP5Ah+fvEQShkSAIG5+v4wjcEgTBC7gErBBF0edtDyxTdlm9ejX29vY4Oztz69Yt3N3dSU9PR6lUoqurS7t27fjmm2/w9/fnxo0b9O3blz59+uDi4oKHhwdRUVGEhIQwbdq0UpXl+Cqys7PZs2fPK22wU6dOcePGDerXr8/vv/9OtWrV8gTcXsTExISpU6fyww8/cP/+fYKCgjhz5gy+vr7s27ePhQsX8vTpU9auXUvLli05dOjQW52Dqp36f7Op09PTmTJlCp9//jk//fRTnvU3bNgAwK1bt7Czs2PChAkcOHCAxMREunTpQnh4OL1792b8+PFcvXqV9PR05syZQ3p6OpMmTeL8+fOsXbuW7Oxsab93795l0KBBWFtbS01VlEolO3fu5NGjR1hZWQG5cgu1atWidevWwP87gjQ1NWndujUdO3akdu3anDlzRhqjlpaWFLT95ptvWLBgAb/99hsrV67EysoKGxsbOnfuzOPHj9/qWsqUHWxtbXn8+DE5OTklOo7Y2Fg8PDywt7fH2tq61CcXfEiUUhusJ7mNMHj+b6/84xYfiaLo//zvCCAKeKXWQpl29BgaGtKjRw+MjIxwcHDgxx9/ZNu2bTg5ObF//37mz5+PIAhs27aNY8eOsXDhQqpXry5tr6am9tpR7NLg/c/IyODs2bN8/vnnr1x3ypQp7Nu3DxMTE5KSktDQ0KB+/fpSR4iC2n/269ePgwcPMnDgQGbNmiUtnz9/Pvv27WPbtm14e3u/1TmkpqYSHx8v1XarUCgUHDp0iBkzZtClS5c8zh1Vlg5AREQEDg4OtGjRAiMjI5YvXy79X6pu5EOHDuXAgQOoSvwqVaqEra0tK1eulBw133zzDYMHD+bixYtUqFCBR48eoVQqOXbsGJUqVWLcuHHMnTuX0aNHA0jfn7FjxxZ4XhUrVqR+/fo8ePAgz/K6deuydOlS+vTpw4EDBwgPD8fT01NKT544cSJJSUlvc0llyggl3W5dNjBk/osoirGiKLYXRdFOFMUOoijGPV9+VxTF0c//PiOKorMoivWf//vny/cq86Fjb29P/fr1ad68OX5+fmzbto3vv/+emjVrUrVqVfr374+pqSnXr19ny5YtzJgxI09gR1NT87UFgEuDDXbr1i3MzMxeKeyq0hO6cOGC5NzX09OjcePGPH36NF/ADXJFrqdPn46vry8tW7aUxKtV2cUqbca3tcGePHmCoaFhvo5g169fp0KFCvzyyy88fPhQCoypq6vj6uoK5GrqZGZmMnz4cEJDQ6lVqxazZ8+WsptmzZqFl5cXAIMGDSIjIwNBEKhbty4ZGRlMmTKF4OBgAPbv348oihgbG3Ps2DEgt3Q+NTWVypUrs2nTJsaMGUO7du0AJJvx008/LfC8mjdvDuQGEl+kT58+zJgxg7Fjx3L+/HkCAwN59OgR3bp1o1WrVqxfv75UfLdk3i0VKlSQKhdKAlEUefz4MYGBgbi6umJoaFgi45ApdRSpIYYKQRCaAJpA4MvWgzLs6MnJyaF69eoMHDiQ2NhYBg0axMGDB7G1teXs2bP4+vrmKwl6W7y9vdHV1X2tDIyIiAjpgfYioii+8URvxYoVtGzZskiiqdeuXUNfX5+kpCTJgy0IAjVr1qRmzZq4ubnlyy4YNmyY5FQ5eDBXfkEVJQGKxSHx6NEjHBwc8k0y1dXVWbZsGZ06dSI9PZ1Tp05Jn2lra9OjRw969uwppXYHBwfz5MkTHj9+zKRJk6RrWq1aNf744w/mz58v1bn379+fa9euceLECTp16sSwYcN49OgR06ZNQ1dXl5SUFLKysli1ahX6+vr06NEDQRCYPXu21K2tQYMG0tgKY/Pmza80wipUqECtWrXo2LEjd+/eRalUUq1aNby8vKSadpkPEz09PSpXrkxExPttWCQbGKUHpSgW+0tG5n0iiiJNmjShSZMm+Pv78+effzJ16lS6d++Oj48PBw4cQFtbu1iPuWHDBnR1dUlMTCzyNvfu3Stw/bdxtM+ZM4dhw4a9cj1RFLlx4waiKKJQKKRjamho0KBBgwIDboIgsHDhQkm0f8aMGUCuo0fF65x/QajK5gtqDNC8eXOaNWtGq1atqF69ej4bbMGCBTRs2BAdHR1EUSQqKgojIyPWrVvH7t27pXXt7e2Jiorif//7H4IgoFAoqFq1Kjk5OWzZsoWmTZvy22+/oVAomD59OjExMeTk5KBQKBg1ahQDBgxAX18ffX19Vq1aJWXdL1u2DDs7O9LS0go8N3V1dU6fPp1PC+i/6OvrY2lpybRp0zh37hw7d+7E1dWVqKgouaT+A6d69erExMQU+h16V+Tk5ODl5UVGRgaNGjVCS0vrvR5f5v95RzaYsSAId1945ckIEAThrCAIvgW8er64npj7oCj0AfVcR3EHMEIUxVd6p8uso8fX15fKlSvz888/s3HjRqldeIcOHTAwMCAgIKDYI+aq7Jb/ZmsURFhYGJGRkTRr1ozmzZvj5OTEokWLuHDhAuPHj0dHRwdXV1cWLFjAJ598wuDBg4s8wU9PT6d+/fqvXC88PJy5c+diaWnJp59+mm8bIyMjXFxcePjwIaGhoQVer9DQUABatmwpLfPy8pI6NAQEBLBr165CNXtEUWTgwIFs375dWhYTE4OamlqhE81JkyZx5swZtLS0pFIpgP/9739cvXqVOnXqcOjQIeLj4/Hy8mLYsGEIgsCuXbtYu3attL4gCHzzzTc4OjoiiiLHjx/n888/R19fX2oH27RpU7p37061atXQ09Nj9uzZpKSkMHjw4EJbzx89epSOHTsW+BlAnTp1pE5cRaFy5cqsXbsWURRp1qwZlpaWPH36tMjby5Q9atWqRXBw8HtLH87JycHb21s2MGRkZIoFLy8vzMzMiIuLY9OmTUButmKrVq1ISEggKiqqWI+Xk5MjdbN89uzljd6USiVhYWGcOnWKdu3a4eTkROPGjfnzzz85d+4cXbp0QUdHhyFDhjBjxgzatWvHnDlzipzRkZGRUSQb7PDhw/j6+hIeHs7q1avzBLZeFXBTIYoi7dq1o3LlytIyb29vmjVrhiiKXL16ldOnTxc6hoiICNq0aZMn+KQqmy+otbuOjg5bt25l0aJFmJmZ5RFe/uGHH1ixYgU9evRgz549knhykyZNABg1apRUUgW5WdQrVqxAS0tLyvDp27cvOjo69O7dmw0bNmBvb8/atWtJTk7GwsKCWbNmoa6uXmhZnJGREd7e3oVqIwG0bt36tTorOTg4sGbNGh48eIC1tXWB3Vll3p7SUp6ppqaGvb39e9VLTE1N5c6dO5iamuLo6Cg3ZfkwiRFFsdELrzxZz8+zpZ0KeB0Fnj134KgcOQU+QAVB0AdOAN+JonizKIMqs9+0evXqERERwbVr1xg8eHCeH03NmjWliEVxER0dLR2jQYMGiKJYqFGwe/duHBwcqFmzJl26dMHb25tVq1YRERHB1KlTMTAwYOrUqfj5+REZGcmXX34pZZIURkxMDGfPnmXp0qXs2LGDTp06vXS8sbGxtG3blsGDB+Ph4cH06dMLXE9bW5tGjRqRlJSEt7d3PofN3LlzJd0aFe7u7tSvX58///xTapO6YsWKAvfv7u7O0aNH+fHHH1mxYgUKhQJ/f3/s7e1fOn5HR0c2bdqUR2xaT0+P33//nSNHjrBy5UopotatWzdu3LiBpqYmX3/9dYEZV4IgkJ6ezurVq0lJSZFEkgcPHoympiZdunQhKioKPT09PD092bNnDy1atODs2bMvHWdxojJiAZYuXSqnEX/AVKhQASsrK4KCgt75sRITE7lz5w4mJiaygVEKEKE0CgHKyLwWdevWJT4+np07d+YJBKmpqVG/fn0CAwPfOvPkRR4+/H/dbzs7u5c+H8eMGYODgwN9+vRh9erVXLx4kenTp3Pjxg2mTZvGwIEDsbS05NChQ5iamjJr1iz27NkjlXT/F1EUCQ4O5siRI0ydOpW4uLhXOnquXLnC9OnT6dChA9ra2oW2dn8x4FaQyHJISIhU0gS55e2enp44OjryxRdfMGHCBMaPH5+nY9WL7Ny5Ey8vL7p3787ly5cLLZt/EUEQ6N69Ozt37sTGxkZa/tFHHzF27FjWr1/PuHHjpGyjH3/8kcOHDwPQokWLAh1xDRs2JD09nQEDBqCmpkZ6ejopKSn8+uuvnDhxgrFjx6Kjo8PRo0extLRkxIgRfPLJJ1Kw8V1jZ2cnlbH5+vq+V9uvvJCRkVHSQ5AwMjJCFEXi4uLe6XFEUeTJkyd4eXlRt25dzM3N3+nxZF5NKbXBitIQQxM4Amx/nW6nZdbiV1dXLzQjRFULHBMT88rIT1EICAjAysqKmzdv0rRpU7y9vWnXrh2NGzdm+fLl1KhRgy5durBo0SL+97//8fXXX3Px4kXOnDnD+vXrMTExoV27dqxevRovLy969uzJr7/+Su3atVm7di2ffvopy5YtY+vWrdy6dSvf8f/3v/9Rp04dli1bRmxsLEeOHJEyagrjwIEDtGjRAltbWzp37oy1tXWh66qrq+Pk5ES1atW4e/cu0dHR0md6enp5dIxEUeT8+fMYGhqyePFiLl++zIwZM/K1LVexfft2FixYwMWLF9m3bx+///47RkZGhaZ0i6IotRosCAsLC1asWEFMTIyU7nzgwAHMzMykSXP37t0L3V5bW5uaNWty7do1tLS0uHTpEv3792fz5s107dqVy5cvc+vWLQIDA3n69Ck9evQo1PgrbpYuXSpFsdavX0+/fv3e+UOovFFaIkqQmz4cFxf3ztKHlUolAQEBPHz4EGdnZ9nAKC2IpbLjg4zMa1GhQoVC76cVKlSgQYMG3Lt3r1jubytWrKBRo0YYGhrSvXt3KYt70qRJjBgxgpo1azJo0CB+//13OnbsiIeHBw8fPuTmzZv069ePWrVqMWjQILZs2YK3tzdBQUGEhYWxbNkyZsyYQceOHVm8eDHjx4/Pl1mTnp6Oi4sL7dq1Y9euXZiamnL58uV82jb/ZdWqVfz00088efKE6dOnv9TBrq2tTePGjVG1qk9NTZU+MzIyyrOtu7s7ZmZm7N69m6ioKG7dukX79u3zdMh6kW3btnHu3Dm2b9/OkCFDuHDhQoFl8yoyMjLy6duoEAQBFxcXTp48yf3793ny5AmQm7nUtWtXrly5AuTNAP8vLi4uZGVlERkZSVxcHOfPn2fYsGGcPHmSnJwcQkND0dTUxNPTk/Pnz9O0adNizw4rCB0dHUJCQrC0tASgR48eLFy4sFBbUqbs4+DgwKNHj96ZXmJmZiaenp4kJCTQpEkT9PX138lxZF6T0mmDFaUhRn/gY+ALQRA8n78avGrHZdbR8ypUUaWgoKAid7jJyspizpw5DB06FCcnJ0aMGIGzszP16tWjXbt2BAYG8r///Y+7d+/SvXt3Wrduzffff8+UKVOYMmUKSUlJ6Ovr4+PjQ5MmTWjZsmW+h3tmZqaUFnr9+nXpYVujRg2WLVvGN998k2f9p0+fsnnzZvz8/Pj3339ZtmyZJIj3MkxNTUlJSZHSlItC1apVcXV1JTw8nPv37xdYVuLp6YmRkRGrV69myZIl2NjYcOLEiXydG1R4eHjQvHlzLCwsOHnyJMbGxsyfP79Q4+/atWs0bNiQRo0asXXrVkaOHMnFixelG/GIESOYMGECxsbG1KlTh9DQUJKSkvjoo48ICQnB39+fP/7446VdhAYOHEhcXBzTpk0jPDyc5ORkhg8fLjlV7Ozs0NHRISgoCAMDAzp27MiECRPei6bKzz//zKJFi/jtt9+wtbWlWbNmhTrRZF6f0hRREgQBOzu7PJHq4iIlJYU7d+6gpqZG48aNXzkpkZGRkSlOtLW1qVu3Ll5eXnm6LL2MkJAQxo0bR9u2benevTt9+vShbt26zJ07lz///JObN2/Srl07Lly4wO+//46Hhwd79+5l9+7d9OjRg4cPH9K7d29u376NpaVlgVk3Dx48YPny5XTp0oVJkyZJy/v370+LFi3yNIAAOHLkCNra2gQFBXHw4EFmz55NtWrVXnkuVatWJTo6mqtXrxbJBlNTU8PW1hYHBwe8vb0JCwsrcAJ68eJFSd9m48aNVKhQgX///bfALOnExESioqKoX78+bdq04dChQ3h5ebFt27ZCJ7dLlizBycmJXr16SbpLAQEBQG4p/+DBg+nRowd16tRhx44dXLt2jeXLl/P5559jbW3N33//za5duwo9TwsLC2rXrs2DBw/o1q0bp0+fZtSoUWhoaNC+fXsArKysMDMzIzExkYSEBOrUqcOCBQveeamzrq4u+/fvZ/bs2ezatYvLly/TvXv3966nJ/N+0NHRwcjIiPDw8GLf97Nnz3Bzc6N69erUrVu3wDJJmbyU5yqGIjbE2CmKYgVRFBu88PJ81b4/6G+eKqrk7u6Oi4vLSztshYSEMGTIECm1FKBNmzZMnDgRLS0t6tatiyAI9OvXj379+gG5X0pLS0u6dOlC7dq185QZFYZKc+bMmTP5slrMzc3z6MKIosiYMWOYPn36S+uRC8LV1ZWxY8eSmprKDz/8UOTttLS0aNCgAREREdy+fRtHR8c8mVOnTp2iadOmnDx5kq5du6JQKDh16hT379/Pt6/4+HgePnwoGVvR0dF8/PHHnD9/ni5dunDgwIF8be0bNmyIuro6ixYtYs6cOdy/fx83Nze6d+/OwoULyczM5MKFC3h7ezNkyBB0dXX5/fffOXfuHL169WLkyJF5OoUVRKNGjVBXV2fx4sUAHDp0CD8/P3bs2MHx48e5ceMGlSpVkgQUAbZs2cKgQYPeeVaEsbEx06ZNk963bt2azz//nLFjx/LNN9/ID4sPDCMjI8LCwoiNjX3t33hBiKJISEgIT58+pU6dOnIE6TVQRaffB8pX6+fJyJR5KleuTK1atfD09MTV1fWlWS3//vsvX375Ja1ateKjjz4iNjaWDh06YGlpSfXq1aVn7/jx4xk/fjyQa6OtW7eO+vXr06xZs1d2IlUqlVKgbMuWLfk+NzMzy2ODxcbGMmvWLDZu3Jhv3Vfh6urK3LlzSUlJQU9Pr8jbVa5cmSZNmvDo0SPc3d2pW7eulDkliiKnTp2icePGNGzYEAsLC65evYqFhUWB9ufly5dxcXFBXV0dpVJJTk4OgwYNon///gQHB7NixYp8NkWjRo1o0aIFn3zyiVROfvDgQbZt24aZmRm2trZ4enry3XffMXr0aObNm8elS5dYsmQJjRs3ZsWKFXTo0OGl5/jxxx9z+PBhjh49SoUKFfjuu++Ij4+nc+fOrFmzhgULFrBo0SLJGZWamsrixYuZOnXqO3+mNWjQgAYNGgDQs2dPli5dykcffcSaNWvo1q3bOz22zPunRo0a3Lp1i2rVqhWqy/k6ZGdnS930GjVq9NpdBcsroihy796993a88mSDfbAZPSq0tbVxcnJ6aVQpICCA2rVrY29vz82bN5kxYwY7duxg+PDhuLq64uTkVGCaq5qaGtOmTaN27dpFGktcXBy///477du3LzC1NSoqKk8nratXr/L48WPmzZtXtJN9ASsrK/T09Bg9ejTLli17rW0FQcDCwgIXFxcCAgKkluO3b99m7dq12NnZ0bx5c+mBq1AoCkzhXrVqFb169aJSpUokJyeTkpKCpaUlmzZtokWLFkycODHfNqGhodjY2NC1a1du3LhBaGgof//9N1u3biU1NRVXV1f++ecfevToga+vLykpKTRo0ABPT0+OHTvG/fv3adasGTdvFq5R1blzZw4cOCC1Sg8PD2fEiBHs2bMHMzMz1NTUaNOmDRs2bCAhIYH09HTS09Olzlvvk27dunH9+nWuXr1Kx44dS6wlpMy7QyUK+LbRjPT0dKmDi5wm/HrExsa+k6iejEx5x9TUFFNTU+7du1doFsnu3bvp2bMnixcvZvv27fz000+sW7eOzz77jCZNmhQaYDE2Nmbu3LlF7u516tQplEolW7ZsKVCsNzo6Oo8NtmrVKnr06PHS5guF0bhxYwwNDWndunWeZhRFQV1dHUdHR2xsbHB3dycyMlIaT1paGqGhofTo0QPInSAVZH+JosiyZcsYPXo0kNsgxMTEhJo1a3Lu3Dm8vLwKdGAFBwdTr149xowZQ0REBLGxsSxatIjVq1dLnbSCg4NZsmQJ+/fv56+//sLV1RUrKyt27NjBwoULGTBgwEuzYBYvXsyMGTPQ0dFBQ0OD8PBwunXrxu7du9HV1UVXV5fPP/+c06dPk5aWJtlg7/uZpq6uzuzZs9m5cyfTpk1j8uTJecrqZMo+Ghoa2NjYFFqu+DrExsZy584djI2NcXZ2lp08r0FgYGCxONpk8vPBO3ogb1SpoMnUzJkz+fTTT1mzZs07zZi4du0aQKFtH6Ojo3n69KmkNXP48GFGjhz5Rl9+QRD49NNP2bhx4xtPIFVCzZqamly/fp0pU6awfv162rZti6+vL+np6airq+Pg4ICfn1+ebRMSEtiwYQMzZ85EFEUePnwo1YULgoCrq2uBzrOkpCSptaWmpiYmJiZYW1vTokUL9u3bx+jRo9mxYwcAlpaW/Pbbb9y5cwelUknXrl0xMTFh9OjRDBo0iKlTpxYqBtm2bVu8vLxYv349SUlJLF++nOTkZGxtbQE4e/YsI0eOZNCgQa91zSIiIvj222+LVXfF3Nyc48eP07t3bz7++GO2bt1abPuWKXl0dHQwNjZ+44wSldifh4cHtWrVwsHBQRZcfg1SUlJ4+PChFMV915RSIUAZmXeGqsNTQZOpnJwcxo8fz88//8zAgQPf6ThUz05V1vZ/iYqK4uHDh1IZ95EjRxgzZswbHcvR0RFBELh06dIbT2CMjIxo3LgxMTExnD59mu3bt7Nr1y7q1avH3bt3gdwun/fv38/nRDt37hwpKSl89tlnZGVl8eTJE2rUqAHk2sSF6fQkJyeTnJwMgKGhITo6OvTr14+7d+8SFhbGsGHD2LlzJ5Dbiv3YsWPs3r2bs2fPMmzYMAYMGICtrS1NmzZlw4YNBdqfGhoajBs3jsDAQCZMmMCDBw9Ys2YNZmZmWFpakpqayvbt2+nYseNLy8AK4uLFi6xZs6ZYdVc++ugjbt++TUpKCs2aNePOnTvFtm+Zksfc3JzExERp7vG6KBQKHjx4QHBwMA0bNsTMzKxQDSyZ/Dx58oTk5ORCJUCKm/Jmg5Wb2YAqquTr65vvAaCmpoaDg8M7F2qdOnUqAM7OzgV+/vTpU27evEnjxo1p27Yt69evx8XF5Y2Pt3z5coAiaxQVhCAI2NjYEBQUxIQJEzA3N2fevHlYWVnxyy+/ALndN3x9ffNst2HDBrp27UrNmjWJjo6mYsWKedqD3rlzh8aNG+c7nrGxcYEC2uPGjWPdunXUqlUr3+cWFhYsX74cLy8vTE1NWbJkCa6urjx58oSGDRty6NChAh/66urqDB8+nKlTp6JUKtHR0eHff/8lLCyMLVu20K5dO06dOvVaN/9nz57x22+/YWRkVKytG9XU1Jg8eTIbN25k/Pjxhbazlymb1KhRg7CwsCJrWaj4r9hfYQL1MgWTmZmJt7c3zs7O76/lvFi+jAwZGYDatWuTnJycz6Gtrq5OVlZWgfZAcZKens7x48dp2LBhoZOwK1eu8Pvvv1OrVi3atm2Lv78/dnZ2b3Q8dXV1Vq5cCfDa9/UXqVChAvXq1ePixYvMmzePhw8fcu7cOS5fvszNmzcxMjJCR0cnX3eq5cuX880336Curk5AQAA1atTIo1149+7dAq+5IAj5sla0tbUZMmQI69evx9bWNp8N1rhxYw4ePMixY8d49OgR27Zto0uXLpId9WJr9xcxMDDgp59+ksbRokULPDw8uHfvHsuXL0dTU5P169e/1vW6ceMGX3/9NTVr1pQcVsVB5cqV2bx5My1atOD7778vtv3KlDyCIODg4PBGeomJiYncvn0bHR0dGjZsWKoafpQFVNnUzs7O7885Vs5ssHLj6IHcqJKmpmaeqJJSqcTHx+edq/pfvnyZiIgIfv7550KFgkePHs2dO3fw8/OjT58+3Lx5UxJufhPOnz8PFO5YKirp6eksX74cc3NzLl26RM+ePcnOzpbaTzo7O+d7kP/7778MHDgQVeef/xpLFStWJD4+Pt+xfH19C6zvbteuHb6+vjx8+JCYmBiCg4PzrWNiYsIPP/yAn58fzs7OHD9+HGNjY+bNm8enn34qCQr+lyZNmgBIWThVqlRh4MCBnDhxgvT09Neqr3dxcZEyturXry/9H6gQRZGrV69y9epVPD09CQgIICIigvj4eNLS0sjJySnQKSWKImlpacyePZt58+bJKaEfGKr04cK+o/9FFEWePn0qi/0VAV9fXxYtWsSJEyeYOXMm7u7uwP+3KXZwcHit37iMjMzrIwgC9erVIzw8nNjYWGm5yvFT0DO9OPn6668B2LNnT6HrnDp1ipCQEM6cOcPgwYMJCAh4qbbjqzh58iSA1MnpTfHx8WHXrl00adKEe/fu0aZNGywtLTl37hyQa4P5+PhI66empnL79m369Okjlc3/V0BaS0urQBssMjKSZs2a5Vs+dOhQVq1aRY0aNbh8+XKBdoqTkxObN2/mxo0bPHz4EA8PDwwMDPjkk0+YMWNGoY4XlW6S6vOaNWsyceJEEhMTX7vr6bRp02jfvr2kU6cqe1ORmprKuXPnuHHjBr6+vjx+/JinT5+SmJhIRkYGCoWiUBvM19eXEydO8N13373WmGRKPwYGBmhqaubpOvwy/tvV1MrKSs7iKYSjR4+yYsUKjh07xvTp06XkgxezqV/WQEfm7Sh3MwMHBwc8PT158uQJFhYWLFy4kCpVqvDrr7++0+OqjIwRI0YUuo6lpaVkELzYDeJNUdWtF7V+vSBEUWTSpEm4urri4ODAsGHDuHz5MgqFgkePHuHv70/9+vU5cuRInu0ePnyIo6MjwcHBmJmZ5YuWDxkyhE6dOuVzWhw+fLjAenhBEOjZsyfnzp2ja9eunDx5kgkTJhQ4Zj09PSl76N69ezRq1AhnZ2d69eqFh4dHvjRqlZB0p06dXv8CFcDXX39NvXr16NWrF4MHD2b9+vVS9wsfHx9u3ryJKIqEhYUBudlmWVlZZGZmkpmZiVKpRE1NTSq/USqVUvpznz598nVmk/kwMDMzIyws7JXinampqTx48AAtLS1Z7O8VXLlyhcGDB9O/f39+/vlnUlNTuXjxIpcuXcLPz4/q1asXiwj26yAionxH7VxlZEozGhoaNGjQADc3N5ydnalYsSJDhgxh6tSp9O3b950ee/PmzdjY2GBlZVXoOiqHg6mpKY0aNXrrY6omfm9jgyUkJDBkyBAWL17MpUuXOH78OIsXL8bc3JwLFy4giiLOzs54eXnRvXt3IFd3smbNmmhqauLj41NgmdaQIUPYunWr1OkKcjvPHjt2jOPHj+cbR40aNahUqRJKpZLk5GT8/f0L7PQFuRqRKg2ks2fPMmnSJDw8PPj2229Zs2ZNvvVVpf8ff/zxG12jF6lYsSLHjx9nxowZrF69mnHjxjFixAhiYmKIjo7m9OnTZGVl4enpKW1jampKRkYGmZmZZGVlIYoi6urqCIKAKIoolUpp2cqVK1/aPl6m7GJnZ4eHhwdGRkYvLX+Pjo7G398fMzMzGjVqJJfKF4Ioivz8889s2LCB7t27c+DAASmgvmjRovefTa0aVzmzwcqdo0cQBJydnbl79y6ampr4+fmRkpJCUlISnp6eNG3a9J14ZevVq0eLFi3e6oH/OoiiyFdffQUgdU54E1auXMm9e/c4d+4cX375JaNHj6ZWrVrcv3+fjIwM7ty5Q/369fH19UWhUEheWX19fRISEkhISCgwOmRvb4+9vT3Hjh3js88+k5ZfuXKlUPHp//3vf8yePRsTE5N83br+S5s2bYBcY+bOnTu0atWK8+fPs3LlSsaMGZOnxEV1k16wYAHDhg176X4zMzO5ceMGQB4jICcnh+zsbLKysnB3d+f06dNAruGyZcsWjI2NMTAwICEhAWdnZ27cuMHw4cPx9PQkJiaGoUOHMnDgQJycnKRuX0qlUtI0Ujl+FAoFp0+f5ujRo4waNeqdp7vLvD9eTB8uqLwgJyeHoKAg4uLiqF27doFioh8ye/bswdjY+JXCqKpo7OHDh5k2bRrbt2+X7gdKpZIhQ4bw888/069fPywsLN71sGVkZF5AS0tLygK2tbXF3d2dpk2bEh8fT0REBE5OTsV+TKVSiYmJiVRK9T6IjIyUnBpv2sghOzub4cOH0759e3r16kXDhg3ZtGkTrq6uTJ48mbZt23L48GFcXFzyZCoZGBiQlJREVFRUvrJ5FQMHDmT+/PlERUVhamoK5Aqi6ujoUKdOnXzra2trM378eG7cuEFSUpK0TWG0bt2aM2fOsGDBAhYvXsz169f56KOP6N69O506dcoTwVcFsrZs2cKcOXNeut9nz55x//596fn4XxssMzOTo0ePcuXKFaysrMjJyWH37t0YGxujqamJlpaW1O2yX79+/PXXX5ibmzNw4ED69etHtWrVpOCaygZT2V+CIJCcnMyGDRvw9fXlu+++e+V1kCk7VKxYkapVq0pNYf5Leno6Dx48QE1NrdyVaaWnp7Nu3To+/fRTScu0MERRRBRFZsyYwaVLlzh//rxkaz179oyuXbty7Ngx2rVrJ2dTvwfKpRtSXV0dFxcXAgMDWblyJT169MDGxoa2bdsSExPzTo65adOmd5419CIxMTHcv3+fVq1aYWxs/Nrbp6amMnHiRP7880/27dvHmjVr8PDwYObMmUCuI8Xf359bt25x5MgRvvrqqzyp1xYWFjx58gRbW9tCvd2jR4/O1/XBysoqn7CzCkNDQ1JSUsjMzHylcK0q3VpPT49q1aqRlJTEzJkzOXHiBGPHjs2zbs+ePYHc1u6v4s8//6Rr16706dOHLl26MHz4cObNm8fvv//O559/zueff86KFStISEigf//+2NraMnPmTKysrNi7dy9xcXE0b96ca9eusX79em7evMlff/0FQO/evalfvz4bNmzg+PHjJCUlUaFCBTQ0NHjy5AmLFi3C0dGRhQsXYmJiwogRI966U5NM6aKg9GFVmdbt27epWLEiTZs2LXdOnuDgYEaOHMmnn37K0qVLSUpKAmDbtm14enqSk5ND27ZtWbVqFTo6Oujo6DB58mSOHTsmOXkg15k2d+5c1NTUmDJlCvv37y9W0c6iUp7qw2Vk/ouenh516tQhICAAPz8/vL29sbCwoFevXu/keGpqaoSGhtKlS5d3sv+CuHjxIgC///77GwUPAwIC6Ny5MxoaGsydO5cvvviCNm3a0KpVKymbUxAEdu7cSVRUFI6OjpIWkJmZGXFxcQWWzaswNDSkZ8+ebNu2TVpWrVo1YmJiCtV1rFKlCikpKWRkZBRY9vUiKhvM3t6elJQUzMzM+N///sfXX3/Nhg0b8qz76aefArxyAgm5dmO3bt3o3bs3Xbt2Zdy4cSxZsoQVK1bQr18/hgwZwoEDB6hatSqtW7embdu2zJkzh7i4OHbv3k2lSpX47LPPuHfvHitXriQgIID58+fj5eVFgwYN6Nq1K3v37uXKlSuIokiFChVQU1PDzc2NiRMnYm9vz7lz54iNjWXhwoWvHK9M4ZRGR4m1tTURERFkZmZKyxQKBYGBgXh6emJlZUX9+vVL5djfJbt27eK7777jo48+4tSpU+Tk5JCZmcny5cuJjY3l4cOHdO3alXnz5qGjo4OJiQm3b9/m7NmzeQJqVapUYdWqVWzfvp3Zs2fj5uZWIudTnmwwoSSM3OLA1dVVVHWxelNU2RcqZ4SFhQVRUVFUqlSpmEZZsujr65OdnU1aWtprGRrp6en06dMHMzMzWrVqxb59+0hOTmbv3r1SaVl2djbt27enT58+6Ojo8PjxY3r27ImhoSG1atXi22+/5eOPP6ZHjx6FHjsrKwtra2suX74sGSObN2/mn3/+Yd++ffnWj4+Px8HBgWXLlrF//35OnDhR6L7Hjx/P1q1bOXPmDO7u7ri5ubFt2zYyMzOpXbs2J0+exNHREcidRDo6OuLv7y+1XC+MW7duSRPHDh06EBoaSmhoKAYGBujq6tKxY0dcXV2pWLEigYGBhISEsGXLFhwdHTly5AjW1taF7lupVNK9e3cuXLhA586duX37Np9++impqamcOXOGAQMGMGLECBo0aICvry+NGzcmPDz8vZeeyLxbMjIycHd3p1mzZqSnp+Pn50fFihWxt7cvt2VaOTk5rF69Gg8PD/bv3w/kio3OmDEDgDlz5vDTTz8BueUhOTk5zJo1K49opqr7nyiK2NjY8Ndff7FkyRImT57MqFGjANDW1nYTRfHtazZegoGVltjq6+LPJDo+5fE7H7uMjIrisMESEhK4f/8+DRo04NSpU/z6669cuXKlmEZYsiQlJVG1alU6d+4sBXOKSnBwMG3btmXixIkolUq2bdvGxx9/zMqVK6Uyh+DgYD7++GP27t3LkSNHqFOnDvb29tjY2GBubs64ceMYP378S7sJurm50bdvX4KCgiRb6vPPP6dNmzb5AmIABw4c4PDhw2hoaFC/fn1JkuC/ZGZmSsGIqKgohgwZQt++fRk6dCju7u7069cvj1bmr7/+yqxZs0hPT3/ltZk+fTrr1q3DwsKCWrVqERwcTFRUFHp6ejg6OuLq6krz5s1JTEwkICAANzc3zp07x/Dhw1m2bNlLW7SnpaVhZGREtWrVqFq1KllZWbRo0QI/Pz/Cw8MZOXIkw4YNw8zMjHnz5nH58uV8OowyZZ+nT58SGxtL3bp1pTItc3NzrKysym2ZVkREBDt37uSXX34hMTGRtm3b0r59eykDr1+/fhw4cCDPNufPn6d58+bS+5ycHNzd3bG2tkapVLJ//35WrFjBv//+K83HZBus+CnXjh7IdTa4ubkRFRXF4sWLuXHjxgcjqLVz507GjBnDpUuXJMHhorBgwQKOHTtG7dq1uX//Pt988w09e/bM58EODg6mVatWfPXVV8yaNYujR4/i6OhIaGgoUVFRBAUFSeVjBREXF4eFhQXXrl2TsmmSk5Oxt7fH3d0dMzOzfNtYWlpy4cIF2rVrx7///kvt2rXzrRMVFYW1tTUWFhYEBASQkJCAtbU18fHxiKJItWrVePDgQR4HybNnz15ZDga5+jtr1qzBzc1NSm/29PSkefPmHDlyJF/EMDY2lurVq7Nly5YitY6NjIwkLi6OunXrcuHCBR4/fkxKSgpdu3bNE5k7cuQIO3fu5NChQ6/cp0zhVKxYkYyMjJIeRj4CAgKIi4tDFEUcHBzKXQZPYWRlZdGhQ4cC29vOnz+fJk2a0Lp1a0RRzGOQiaLIo0ePUCgUUttjgGPHjrFixQouXboEvCcjw1JLbPlV8RsZJ6aVTiND5sOkuGyw+Ph4Hjx4wMGDB9HS0mLRokXFMLrSQdu2bbl58+ZrBduUSiXt27fH3Nwcf39/atSowYQJE/j444/z7WP//v0sW7YMZ2dn9uzZQ2BgIImJiZKTo2bNmrRo0aLQY129epWOHTvmGd+ZM2eYO3dugbawl5cXX3zxBevWrWP48OHcv3+/QBHVffv28cUXXzBp0iSWLVvGoUOH2LFjB3/99RfXr19nxowZvPjdycrKIi0t7ZXPOVEUpUyhyMhIaf0lS5Ywf/584uLi8skjqMYSEhJSpDIrHx8fTE1NMTAw4O+//yYhIYHs7GyGDh2aJwg8ceJE6tSpU6hWpEzZRRRFbt26hZqamhRkK28ZPIURGBjIRx99RGJiYr7Ptm7dSp06dahXr56kNapC5eSxsrLKIww/depUjIyMmDt3LiDbYO+C8umafAFNTU3JyWBnZ8fZs2d59uyZVA5QllF1tnhZFsl/uX//PosXL8bX1xdjY2OuXLnCgAEDCrzJ2djY0LhxY7Zu3UrLli2ZPHkyhoaGWFpaUqFCBUxMTF7amlzVkv3FNuSVKlWiT58+bN++Pc+6CoWC69evo1Ao0NfXx9DQMJ8AtAqVyLFKTNHAwIBKlSqxceNGVq5ciZ2dXb4smKI4ecLCwlizZg0ODg55athVZTYFCRNWqVKFw4cPF1lo0szMjLp16wK5RuLIkSOZPHlyvvTrFi1acOvWLR4/flyk/coUTGlz8qjKtJ49e0ZaWhr169cvl06e5ORkfvnlF06fPs2cOXP4/vvvyc7ORlNTk4sXL0oZOCoWLFjAN998Q5s2bSRNBRWiKOLv709OTk4eJw/kCoW+z3IOAJHylTYsI/MyDA0NcXBwwMXFhczMTG7fvs2zZ88KLeEuS6iez68TPNy4cSM3b97k3LlzjBs3jr1799K6desC99G3b18CAwNxc3OjZcuWzJo1C0dHRzQ1NdHQ0CAmJualrd3//fdfqlSpkqdjV/v27UlMTMxXUpGens65c+ewsLDA0NCQ0NBQ7t69W+B+Q0JCgP+3iczNzUlMTOT8+fMsW7aMdu3a5VlfU1OzSM+5HTt2ALnZnC+uf+vWLaBg0evOnTvzzz//FFlLp169elStWhUtLS369evHmDFjmDBhQr5M/27duvHHH38UaZ8yZQdVmVZOTg45OTnUq1evXDp57t27x5o1azh27BiTJ09m586dANSqVQt3d/c8mTpVqlRhz549DBgwgHr16gHkc/J4eHhgaWmZr/vfmTNn6Ny583s4o/+nvNlg5d7RA7nigG3btqV3797s3r2b+vXr07VrVzZv3pxnPVEUmTx58nsV9HsbWrduzTfffFMkJwbkpq0OHDgQdXV1ZsyYwcqVK1/ZWtTOzg5/f3/s7Oxo2bIlCxYsICwsDB0dHc6cOcO9e/d48OABWVlZ+bb9+OOPuXDhAtOnT89T7z1q1Cg2b96MQqEAICgoiGbNmjFo0CAGDRrE0aNHMTU1LTC1GJDqy1/sXHbixAmmTJnC3Llz2bt3b5Gux39ROab+m4atqi8vSLxNEAS6du1a7K2vtbW183nMZco2KuM6JiaGxo0b4+joWOR262WB6Ohonj59ypMnT/j++++xtLSUnLL/JTIyku+++47evXsjCALLly/n6NGjQK7+2KZNmwDo2rUr165dk0q4CiIgIICsrCzq1KmTb7Lk5OTEzZs3i+kMZWRk3oQqVarQsGFDmjRpwqxZs3BxcaFVq1b4+/vnWS82NpYuXbq8dsvtkmLx4sVs3bq1yOt7e3tL5ab79+9n5MiRL3USqampUatWLQICAhg2bBh37tzh5MmTKJVKfHx8ePbsGbdv3yY0NLRAPb8ffviB6dOn5+nkqaamxsiRI/PoJ546dQpbW1s2b97MoEGD+OGHH5g6dWqhnclUwS9VFnOzZs3o06cPn3zyCWlpaW/cnlxVJjVx4kRpWWhoKKdPn6Z///4FbmNgYFAs3bz+S8WKFWX76wNCFEUiIyO5desWGhoatGjRAgMDA549e1bSQys2AgMDSU9P5/79+7Rp04bOnTsXqlF4584dvv76a0aNGoWamhpjxoyRdIs8PDykpjSrV6/m6tWrheqrKRQKPDw8sLCwKLBKQ7bB3j3yXeo5+vr6dOvWjTFjxuDn58eBAwdYsWKFJMgWFBRElSpV2LBhQ4Ff1tJIgwYNmD9/fpHX379/P/7+/lSqVInp06cXaRsHBweUSiVeXl4sXbqUjIwMAgIC2LlzJ/fu3aNJkybo6+tz9+5d/P3980WXmjVrRrdu3fIYFQ0bNsTU1JTTp0/zzz//0KpVKyIjI3F2dubChQts2rSJ7OxsqlSpUuCY2rVrh6+vLx999JG0rH79+gAYGxu/UoenMDp37oybm1u+DKmbN28SHx//Xh/6K1asoFOnTq+VrSVTOklOTsbDw4PAwEDs7e1xcnJCU1NTavmqEh4u63Tr1o0aNWpga2vLihUriImJKVRU3d7enn/++QfIzfITBIGhQ4cyf/58SfS9cuXK7N+//6Ui6gEBAWRkZFC3bt0CJ0yVK1fOoxXxvhDF4n/JyJRl6tSpQ4cOHVi4cCFBQUFMmjSJGTNmEBgYiCiKnDt3jurVq3Pp0qUyY4MNGjSIAQMGFHn9WbNmSfoXRXVO2Nvbo1Qqefz4MWvXrpW0AY8cOUJERARNmzYlKyuLmzdv8uTJkzwOH3V1dSZPnkxgYCDu7u7S8uHDh3P06FHi4+P56aefGDNmDAqFgoYNGzJr1iwePXqErq5ugWVbkJth6e/vL3XUEQRB0gqqUaPGG2dIrF69Ol+mV/Xq1bly5cprOdTelpycHObNm/dSaQKZsoEoikRFRXHz5k0SEhJwdXXFxsYGNTU1bG1tCQoKkoLOZZn4+HicnJyoUqUKrq6u3Lp1i8uXLxd6bl988QWzZ88mOTkZFxcXINdpevr0acnJM336dEaNGkWNGjUK3IfKyWNubo65uXmB61SuXJmgoKBiOMPXozzZYLKj5wUqVqxIw4YNOXfuHBMnTiQsLEyaTNetW5eMjAyWLl1aJK2VsojqATpv3rwil4uohAF79uyJjo4O3bp1Y9WqVWhoaLB3714EQcDc3JxmzZqhra3NnTt3pLRIFVOnTmXt2rV5ymiGDx/OgQMH+OqrrzA1NZU66Pz999+S133r1q0FdocQBIFatWrlWaaqJ42JiXllt4jCUFNTKzAr4H0r8KsEnqdOncrGjRuZOXNmoaKIMqWX1NRUvLy8ePjwITVq1KBhw4Z5hCJV7dYfPHhQIp2hiptNmzZJWmG1a9dm/PjxNG7cuND1hw8fDuRGna9fv85vv/3GunXriImJYfbs2SQmJkrpxAURGBhIWloaTk5OhUbFmzVrRmBg4AcVtZORKasYGRlRq1YtduzYwdatW/nnn39wcnLC0tKS7t27A7kaKv99vn8oqDJWVHoVRUFlg3Xr1g17e3v09PRYtGgRQ4YMYerUqWhoaGBra0ujRo1ITU3l5s2bREZGSs+UChUqMHHixDyZ6qamprRu3Zp169axbt06IFcXcPv27axbtw4/Pz8WLlzIzZs3C5woamtr5wuopaamAnlL9V8XPT29fJnTampqUgey98WuXbvQ1tbGzs6OvXv38sknn0gZpzJlA1EUiYmJ4fbt20RHR9OgQQMcHR2l3xPklhSam5vn6ShcVjE0NGTv3r1S6VTr1q2luVpBBAQESHpp48aN48GDB0ycOJEJEyYwZswYnJ2dOXXqVKHZlQqFAk9PT6pVq5an69Z/admyJSdOnHjLs5N5GbKj5z/cvXuXn376ieXLl/Prr7/i7OxMdHS09OOYOXNmqdP1KC6++uorJkyYwJdfflnkbZydnYHces5Hjx7RuHFj3Nzc+PPPP/No1qipqVG9enWaNWtGhQoVJH0ZhUKBk5MT9evXZ9euXdL6mZmZVKxYkYSEBHJyciRHRvXq1Vm2bBkAEyZM4JNPPilSi3FVO88//vijzHepun37NjExMfTu3ZtDhw6xatUqKftBpvSTlpaGj48P9+7do3r16jRq1KhQx2qlSpXQ09P7IBwRKsMAcp3K06dPLzQiDNCkSRNJ26pnz56MHTuWGTNmcPjwYSpUqIClpWWe8swXCQoKIiUl5aVOHgArKysaN26cr0TknSKCUln8LxmZso5SqeTAgQP8888/bN68ma+++ooqVaoQGxsrNV6YN29eyQ7yHXL8+HH++OOPPPoXr0Jlg/n5+REcHMzgwYNxc3Nj9uzZVK5cWVpPU1MTe3t7XF1dSUxM5ObNmzx79gxRFBk5ciQXLlzIk92YnZ1NTk4OampqDBgwQBrTJ598wpgxY4BcHcFffvmlSONcsWIFQD79xbLI9evX8fPzo3///mzatInz589z//79kh6WTBGJi4vjzp07REZGUq9ePerWrVugvhPk2ghRUVEfxLyvZ8+e/PnnnwBcunRJ+h0XRNWqValWrRqDBg0Cch29y5cvx9HRkevXr2NgYEBYWJg0t3oRVZWHqanpKysoevfuTVRU1PsNZpYzG0x29DwnLi6ORYsWMXjwYGbNmkXLli2pV68eZ86cITg4mKCgII4fP06/fv2K5Fgoi5iamvLzzz+/1jZOTk7o6+vj6+tLVlbWK50oampqWFlZ0axZMwRB4ObNm4SEhPDVV1/xyy+/SNGhgIAAnJycSE9Pz1cLPWDAAO7fv0/37t1xd3dnyZIlrxxneHg4QJl38ly7do1hw4YBuQr3p06domfPnigUCqpXr86UKVNKeIQyhZGRkcH9+/fx8fGhWrVqNG7cuEjfxw8pfVhHR4dr165x4cKFVxoAK1askEQ2FQoFoiiSmJhIRkYG8+fPJywsjJycHJKTk/NsFxwcTFJSEvXq1StSOaUgCFLt+ftABESlWOwvGZmyTGhoKJ999hm7du3iu+++o27duvTo0YOAgADCwsLw8PDg+++/l8qwP0Tat28vPd+LikobIzg4mOrVq6OpqfnS9bW0tKhduzYuLi7ExsZy+/ZtMjIyGD16dJ6snoCAAGrUqIGWlla+jOVVq1Zx8uRJAL7//vs8Ys6FodJjMzExeZ3TK3XMmzeP7du3o6WlxZUrVzhz5gyQm41VtWpV9u/fX8IjlCmMhIQE7t69S1hYmNQd6lU6pKoSrrfJRCtNtGjRgsuXLxcqpK6iUqVKrFmzRgoiq8rsExISCAkJ4fLly6SkpPDvv//m2U6pVOLp6YmxsTGWlpavHI9CoUBTU5P09PQ3PKPXp7zZYMWrEFtGEUVRSi3z8fHB1tYWyNW48fT0lKLC7du3p3379iU51FJHZmYmlStXZtSoUURGRhZ5O3V1dWxsbKhevTqhoaEoFApq165NWlqa1N3gn3/+QaFQSE6kFw2YGjVqsGnTJqpWrcqPP/7I8OHDX5oeaGxsDEDTpk3f8ExLlhfbikKuUawymJo2bcrRo0c5duwYPXr0kGrgx40bV1LDlXmBzMxMHj9+THx8PLVq1crX+elVaGpqYmFhwePHj6V7U1nmZZo6L2JpaYm7uzv379+na9euPHz4kG+++SbPb9jKyooKFSpI74ODg4mPj6d+/fpF1swyMTEpsARURkbm/fD48WPq1KmDs7MzFy9elKLroiji7e0t3TNmzZpVksMslSQnJ1OrVi2qVKmSp/T3VVSsWJE6deqQlpZGUFAQrq6ueRpN5OTkcPDgQZRKZYGT3LZt27Jx40ZGjx5Nhw4dXpl1quqYWlY7GHl4eEit6j///HP++OMPqeylSpUqXL16ld9++40ZM2YQHh5O/fr15flCKSEpKYmAgACpHP6/HdRehYmJCWFhYcTHx2NoaPiORvl+0NXVfWnJ/It069aN27dvc+bMGZYsWcKiRYtYs2ZNnozDyZMnS3+rMnmMjIywsrIq0jFUOl6ZmZmvdLrJvBlyRg+wbds2IDf19cWJlI6ODvXr18fHxydf1Fgml4MHD9KlSxcePHjwRpE2DQ0NatasyfTp02nVqhU+Pj6Eh4fj6OjIzZs30dDQ4LPPPiuwxKNSpUrs3LmTzp07vzKKNX36dO7cuSM5fMoagiCwfv16ZsyYQUpKSp6o2OzZs4HcaODYsWOZNWsW06ZNk2vGS5iMjAwePnyIu7s7lStXplmzZpiamr6RloClpSXR0dHvNerxrlC1LS0Kenp6NGnShO+++45+/fqhUCjyREz3798vTRxCQkJe28kjiiK3bt167w7g8pQ2LCPzMnJycvj222/R1NTkxo0beUooqlatirW1NR4eHkW+Z5Q3fvnlF7788ksuX778Wo4eFTo6OpibmzN16lR69+7N3bt3iYmJoW7duty8eZPY2NhC2x/36tWLH3/8sdCOOy9y7tw5PD09X3t8pQVHR0e+/vprtmzZwqZNmyQnT3R0NHFxcfTv359+/fqhp6fHd999R/fu3T8IbZeyTEJCAp6envj7+1OrVi1cXFxe28mjwsHBgUePHn0QeomZmZlFPg8LCwuGDBmCg4MDX375JQ0aNMiT+adyviuVSry9vTE0NHytJjH37t3DwsLivTvQypMNVu4zeq5du8a0aQbqAYoAAC37SURBVNPYvHlzge2xdXV1adCgAV5eXtSpU6fIIsXlherVq5Oens7MmTMZNGjQG3eBUiqVpKen06hRI8LCwtDT0+Prr7+mb9++hQovCoLAZ599xmefffbK/evo6ODk5PRGYystqMRp/0tkZCT6+voIgsAvv/xC3bp1sbGxYdSoUZiamr5Wvb/M26NKbc3IyMDKygo7O7u37sj2YvpwWS9d6NevH2fOnMHf3/+l3XP+/vtv5syZw/z585k+fTr+/v7Mnz+fX375hfj4eIKDg3FwcEAURR4/fkxCQgINGjR4rWutUCjQ0NBg3LhxksNURkbm/bF48WLu3LnD7du3C/ztqvQR3dzccHFxeWVQp7xRt25d4uLi+Pvvv0lNTX2jiWxGRgYRERHY2dlhYWFBYGAgH3/8MT179qR79+55tH5eRFdXt8iNIMp6h9CKFSvy448/5ltubGxMRESENFE9e/YsFy5cIDY2lo4dO3L79u0ynwXyvqhYseJba+EolUqioqIICQlBS0sLGxubYpm36erqUrlyZSIiIl5aPVDaSUtLw8jIiDZt2kiaiYUxZ84cLly4wObNm9m7dy9NmjTh5MmTjBs3jr59+5KWlgbk2lFeXl5UqVKlwHn0yxBFkYiICMaOHcv333//pqcl8xLKdUaPp6cnP/zwA3PnzpUEpwpCV1cXFxcX/Pz8iIqKeo8jLP1Uq1aN7OxsvvrqqyKn6hXE999/z/Xr19HU1KRWrVqcPXuWixcvEhgYiLe3t9Q1SyY/BgYGkoGsrq7O2LFj6dSpE8uWLaNz586cPn26hEf44aNUKqVucCEhIVhbW9O0aVPMzMze2smjwsTEBIVC8cZd40oDOTk5REdHo1AoOHr0KJs3b2bBggX59IcSEhIYMGAA/v7+TJgwAW9vb+bNm8epU6fYtWuXpDMB8ODBA9LS0l7byQO5GYXe3t4MGDCAoUOHFtt5vhQRRGXxv2RkyhKiKHLs2DE2btzIkSNHcHBwKHTdatWqUatWLdzc3KTJhUzuNVRlIy5dujRPx6DXwdzcnJEjR3Lq1Cn09PSwtbVl9erVXLlyBS8vL/z9/T8IMdp3gSAIeRw5ZmZmfP7550yaNImOHTtSp04doqOjS3CEZYe3+Y5lZ2fz+PFjbty4QWJiIs7OzjRo0KBYg/O1atUiODi4TGcXquZS7u7u3L59m9mzZxeoK/X333/z888/4+7uTufOnalYsSJr1qyROnAZGxtjZWVFVlYWbm5uVK1a9bWdPJArkeLm5oaFhcX7C0qXMxtMKKtpaK6uruK1a9feah8GBgZMmzaNb7/9tkgPyKysLDw9PTE3N3+lkGh5IDU1FV9fX5o0afLWrS1TUlKoWbMmjx49wsDAgDZt2nDr1i1OnTpF/fr1CQ4OJjs7GysrK0xNTYtt8vyhs2PHDmbOnImnpyempqYlPZxSz+tGlLKysggPDycyMhITExMsLS0L7d5QHBTnb64kUGlxQG5b3+zsbOrUqUNCQgKLFy/mzJkzrF27lh49enDp0iVmzZrFvXv3SEtLY8CAAaSkpDBt2jS6d+/O3r178fHxQVdXF1tb27e+HteuXaNDhw5uoig2Ko5zLYxKFlpio/HVin2/F+eGvvOxy8ioeFsb7Pbt23Tr1o1169bRr1+/Im2TmJjIvXv3pCYQ5Z2wsDDS09PzdDh9U/755x+WLl3K+fPnUSgUknZGREQE6enphIWFoa2tjbW1daEZPjL5GT16NMHBwZw5c6ZMPrNLOykpKYSGhpKQkED16tUxNzcvtGV4cVCcv7mSYNWqVcycORNDQ0MpaGhtbU21atUYNWoU0dHRTJ8+XbJjr1y5QqtWrZg9ezY1a9YkMDCQxYsXs3HjRvr06YOnpye2trbFIrK+YMECFi9eLNtgxUyZLd0KDQ3l7t27NGr0ZtfUy8sLPT29Ijt5IFcU1dXVFW9vbzIzM6lZs2a5vnE/fPgQe3v7YrkGenp66OrqEh8fj4GBAampqWhra9OmTRsADA0NSUtLIzQ0lMDAQCwsLLCwsMgjxCqTn6FDh+Lv78+IESM4ceJESQ+n1FNUJ4/KuEhMTMTCwoKmTZu+U+NCha6uLgYGBmU2fViVuVO1alV+++03Bg4cyJw5c8jKypJKE5s1ayaVH3z00UcoFAqWLVuGuro6Xl5eAFy4cIHdu3fTpk2bInV2KApFFSiUkZHJ1cTKzMx84yySa9eu0b59+yI7eQAqV64sldLb2dmVWc294iA7O5vQ0NBi0xerXr06T58+Bf7/Pr1gwQIMDQ0xNDTEzMyMhIQEHj9+TFZWlhx0KyLr16+nbdu2rFy5kunTp5f0cD4IRFEkNjaWkJAQRFHE2tr6tZtcvCnVq1fn1q1bpKWllUnxYJWdOnToUCIjIzlw4ADnz59n+fLljB07FoCWLVsCoK+vLwXmFi1aRPv27XFzcwPgp59+wtTUlCZNmhSb43fgwIEsXry4WPYl8/+UWUdPTEwM7dq1Iykp6bW3vX//Pn369GHlypWvbaSoq6vToEED/Pz8uH//PnXq1CmXzp7o6GjU1dWLtfZYXV1dal2flJSUT3hWR0eH2rVrk5OTw5MnT7hz5w6GhoZYWlpK0SeZ/PTp04djx46V9DDKPKIoEhMTQ2ho6Hs3Ll6kZs2a3L59m6pVq74X51JxYmtry5gxYzh37hwDBw4Ecru3GBgY0LlzZwIDAxk1ahRPnjwhKiqKSpUqYWtry40bN9i7dy+QO/kwMzPDw8OjWMut3qf2R2lO85WRKQqxsbHMmzfvjQzzvXv3smrVKs6ePfva2+ro6NCwYUM8PT3JysrC3Nz8tffxIRAYGIiNjU2xPQPU1dUlgVbVvVDVEh3+v0TJ0NCQ9PR0Kehmbm6OhYWFrJ1UCBoaGvTs2ZOIiIiSHkqZJycnh8jISMLDw9HX18fe3v6NxZXfFEEQsLe35+HDh7i4uLzXYxcHQ4cOZdu2bZw+fZpHjx5Ro0YNzM3NWblyJd999x1nzpyhY8eOdOvWjUOHDgGwa9curl69yi+//EJkZCTjx4+nU6dOpKWlFWt23/vMkipPNliZLd0SBEEE6Nu3Lzt27Hjl+unp6cyZM4eQkBBu3LjBihUrXqrL8ypEUSQoKIikpCScnZ0L7Ar1oaJUKrl16xYNGjQo1jKV3r17IwgCffv2Zfny5Tx48OClXYZEUSQ6Oprw8HCys7OpVq0aZmZmssHxAjk5OfTv3x8rKyt+/fXXkh5OmSQ5OZmIiAhiYmIwNDTEysqqxB2LYWFhpKWlvVTXorSiUCjYs2cP9evXp0mTJtja2uLj4yN9np2dTXJyMlWqVMm3bUpKCt7e3gQEBFC3bl1cXV2LdWza2trvJW3Y9cviTxu+9EPpTBuW+TBR2WAHDhyge/fur1w/ICCAhQsXEhERQUhICAcPHnyrBgk5OTl5BEDLU8DtXZTwxsXF4eLiwuDBg6lbty6jR4/G2tqaBw8eFLpNTk4OERERREREoKWlhZmZmZzl8x9CQ0Pp2LEjK1asoEePHiU9nDKHKnsnIiKClJQUqlWrRvXq1Uvczvf09MTS0hIjI6MSHcebEB0dzcmTJ7GysqJbt24sWLCAGTNmSJ8nJiaiqalZ4PwuMjKS4OBgLl++zOjRo4v9/GUbrPgps44eGxsbMSQkBMhtsfvfG+izZ884e/Ys/v7+aGhosGTJElq0aMG4ceNo0aKF1MnhbQkPDyciIoIGDRqU+I3nfRESEkJ2dnaeVvTFQWZmJsbGxuTk5DB+/HgGDRpU5HKKzMxMnj59ytOnT6lQoQLm5uaYmJiUKwdcQSxcuJDLly9z6NChEndOlCUyMzOJjIzk6dOnaGlpSd+n0mLAqtqC16tXD11d3ZIezmuxcuVK9u7dS61atRg6dCh9+vTh7NmzfPTRRy/dLj4+Hj8/P5ydnd/Zd/m9GBnmWqLL2OI3Mq7ML51GhsyHibGxsRgbGwuAr69vvu6YDx484NSpU2RnZxMcHMyWLVv48ssv6dSpE23bti2WIJFSqeTevXtoaGhQu3btcuPscXd3p2bNmsXeBTYsLAx7e3saNmxIhw4dGD9+fJFt5ZSUFCIiIoiOjsbAwABzc3MMDAzKzf9JQSgUCrp06cJHH33EDz/8UK6vxeuSlJREZGSkFGAzNzencuXKpeYapqen4+npSdOmTUuNXVgU0tLSmDZtGnfu3KFjx45YWFiwdOlS7ty588rsyODgYGJjY6lfv/47yyaXbbDip2zl/b+AkZER9+/fR1dXl/79+5OamsrDhw+5desWixYtIiwsjBYtWuDq6kpGRgZnz56lWbNmxT6O6tWro6WlhZubW7FnuJRGsrKyePLkSbHVhb+IlpYWt2/fpmLFitSoUeO1t7W2tsba2loyOAIDA8utwZGRkcGIESNwd3fn/PnzspOnCOTk5BAVFUVERARKpRIzMzMaNmxYKh24giDg4ODAo0ePylz68MmTJ/H29qZ169ZMmjQJgA4dOhAWFlao5sazZ894/PgxDRs2pGLFink+UyqVxMXFvZVex6VLl7hy5cobby8jU96wtrbmzp071KxZky1btvDDDz/g5eXF4cOH2bp1K/Hx8fTt2xdjY2MqVarE48ePiy3ApkJNTQ0nJycCAgLw9vamXr16ZWrS9SZER0ejoaFR7E4eAEtLS06fPk2jRo1eO4Cgp6eHvb09dnZ2xMXFER4ejp+fH6amppiZmZW5gMTb8ujRIz7//HNsbGyYO3duubI/35SMjAwpwKatrY25uTl2dnal8jetra2NsbEx4eHhb9Vx+H2TlZXF9u3bcXBwICMjg/nz55OWlkbz5s1RJU/8F1EUefjwIdnZ2bi4uOT7/0hPTycnJ+etyujWrFkjSXfIFC9l1tEDuQ/56dOn88svv0gPkSpVqjBz5kycnJxo167dexmHiYkJFSpUwN3dnXr16n3Q3SACAgKoWbPmO8uUcXR0fOt9vGhwxMfH8+TJE/z8/DAxMcHc3LxcGBy///47iYmJeHl55ZsYy/w/oigSFxdHREQEycnJmJqa4ujoWCa+I4aGhoSGhhITE1PqRUkvXLjAlClTePbsGXZ2dixcuJCNGzeyevVqYmNjSUlJKfQcQkNDefbsGa6urvnE14ODg9m0aRMrVqzg7t271K1b943G99133xEcHPxG274+IqKybGbSysi8iKqM4ueff+bnn3+mWrVqKJVK1q5di42NDQ0aNHjnYxAEATs7O0JDQ6WA24fapEGpVBIQEPBOnfutW7d+q+0FQcDIyAgjIyMUCgXPnj3jwYMH5OTkYGZmRrVq1Upl8KS4mTx5Mn369GHWrFmyk+clFBRga9SoUZn4DdeoUYPbt2+Xie/08uXLWbt2LWlpaUycOJGQkBCCg4M5ceIEly5dKjSjWqlU4uPjg7a2Nk5OTnm+y9nZ2Tx79oyePXvi7+//Rpq5kJut/fXXX79HvbXyZYOVaUcP5Cp/6+rq8uOPP/Lrr7/y5Zdflsg4DAwMpG4QDg4OZbJu81UkJSWRkpJSLM6Y94EgCFSpUoUqVaqgUCiIioqSDA4TExNMTEzQ09Mr9odwTEwMKSkp2NjYFOt+X4fKlSujr68vO3kKQJUBEh0dTVxcHIaGhlSvXr1MZn3Z29vj6elJlSpVSmXUS0VERASVK1fmxIkT2Nvbs3XrVmxsbJg8eTIVKlQgKCgICwuLPFofoigSEBBAWloarq6u+c5v586djBkzRnr/Nu09tbW12b17N507d37jfRQVUQQ5cCXzISAIAnfu3GHSpEkcPHiQQ4cO0bBhwxIZi5WVVZ7s6g/x2RcaGoqpqWmZOTd1dXXMzc0xNzeXyqHd3d3R1NSUbLB3cS4BAQEYGxu/k6ynoqKvr4+pqWmZsyneB1lZWcTExBAdHU1qaiqmpqbUqVOnzHWx0tDQwMbGhsDAwFI/L7p37x7Dhw/H1taWb775hsDAQH777Tf69u2Luro68+bNIyIiIk+DnZycHDw9PTExMcHa2jrP/kRRpH379ty5cwfglaX3L0NHRwdNTU0CAgLey3egvNlgpXdmUEQEQWD27Nmkp6eXmJNHha6uLq6urvj7+xMZGVmiYyluVKl7ZbUOXl1dHTMzM1xdXXFxcaFixYoEBQVx/fp17t27R1RUlNRS9G1ZsmQJjo6OaGtrs27dOmJiYoplv69CFEXCw8M5duwYa9eu5dNPP30vxy0LZGRkEB4ejoeHBzdv3iQ6OhoTExOaN29OnTp1MDQ0LJPfa21tbUxMTPJ0RymNNGnSBB8fH0aOHAnAuXPnGDx4MN26dePzzz8HcgUAVai0N3JycnB2ds7n5Llw4QKzZ8+W3k+ZMgVTU9M3Glt0dDQPHjwok+3qZWRKGgMDA3bs2EF6enqJOXlUVK1aFQcHB9zd3UlJSSnRsRQ3qrL5kgwgvQ1aWlrY2NjQrFkzHBwcUCgU+Pj4cPPmTfz9/UlISKC4NEPr1auHmZkZtWvX5tixY2RmZhbLfl+FQqHAz8+PLVu2cOPGDdq0afNejlvaEUWR5ORkgoKCuH37Nh4eHqSnp1OjRg2aN2+Ora1tmXPyqDAzMyM5ObnU32+aNWvG9u3b2bhxI/Hx8fz666+sWLGCL774ggEDBgDksbMyMzO5e/cu1atXz+fkAfjxxx8JDQ2V3s+aNeuNx3bhwoUCjyFTPJT5jJ7ShpaWFo0aNcLLy4u0tDRq1qxZJieQ/yUqKgodHZ0PoixNU1NTijIplUoSEhKIjo4mMDAwT6TpTfWWlixZgqurKyNHjmT69OlMnz6dsWPH8ttvvxXreSiVSsLDw9mwYQPu7u54e3sjCAIuLi58+eWX0gS6PCKKIomJiURHRxMbG4u6ujomJibY29ujo6PzQfwmVdjY2HDr1q1S3XHOzs6OXbt2kZGRwciRIzl27BiQ28Hh7t27QK6mAeROaLy9vTEyMiqwm46Pjw/Dhw9n165dtGrVigULFrB7926WLFnyRmPz8fFBT0/vvUZ/y2gPBBmZUo+hoSHOzs54e3tjZ2f3Vpl+pQl/f39q1ar1QTSY0NXVRVdXFxsbG7Kzs4mNjSUsLIx79+6hr6+PiYkJRkZGb1y+ExERwa+//sqyZcvo378/AIcPH6Zr167FeRpkZ2fj7u7Ozp078fb25t69e1StWhUXFxe2b99e7A1LyhIKhYLY2Fiio6NJSEhAT08PY2Pj12pcU7FiRTIyMt7xSN8OlV7igwcPcHV1LbW25YgRI9DW1qZy5cooFAqGDBkC5Ja/e3h4AODt7U2rVq1ITEzk3r171K5du8Dup5s2bWLfvn3cvn0bIyMj2rZty99//0379u3faGyXL1+mfv36xeboLQrlyQYrs123XF1dxWvXrpX0MApFVUudkpJCvXr1ykS9aWEoFApu3bqFq6srWlpaJT2cd0paWpqUUpqVlUWVKlUwMTHBwMDgjUpjfHx8WLBgAcePHwdyU4p1dXVRKBQoFAqys7PJzs4mMzOT9PR00tPTSU1NJSUlheTkZBITE0lMTCQuLo64uDhiY2OJiYnh2bNnxMTEoKurS9u2bRkyZAjOzs6Ym5uX2gfNu0ZlMEZHR5OUlETlypUxNjbG2Nj4nXUIKC1ERESQmJhY6tOHr169yuzZs7lz5w5//PEHgwcPRk1NjTt37lCjRg00NTW5d+9eoRO0kJAQ2rVrx9KlS+nbty8PHz6kS5curFixgs8+++yNxiSKIl9//TVBQUGcPn36nXdN0DPTFJ1HFn/HhxuLwkplxweZD5PSboOpHMaGhoZlPuCWlJTEw4cPadSoUZk+j1chiiJJSUlSgEZNTQ1jY2NMTEzQ1dV97XNXKBT8+++/9OnTB4Du3buzceNGlEolSqWSnJwcsrOzycrKkmywtLQ0UlNTSU5OlmywhIQE4uPjJftLZYMlJiZiZGTEkCFD6Ny5M/Xq1aNy5crv4tKUCdLT04mOji42+7ks4ePjQ9WqVd84s/h9sXbtWubPn4+NjQ0LFy6kQ4cOZGZmcvPmTVq0aMGzZ88IDw/H2dm5wCyr48ePM2nSJM6ePUutWrXYt28fs2bN4t9//31jx2Z8fDy9evWiX79+zJgxQ7bBihnZ0fOOefr0KUFBQdSrV++tFMlLkqCgINTU1MpsyvCbkpOTI2m5JCYmoqmpiYGBAQYGBlSuXPm1nHfff/89y5cvR0tLCy0tLdTV1VFXV0dDQwNNTU20tLTQ1tZGW1tbinbp6+tTqVIlDA0NMTAwkAQOjY2NpQfKh+54KwxRFMnIyCAhIYGEhAQSExMlEUgTExP09fWLxSAuCxElyL0ed+7coU6dOqW6w1rXrl25f/8+np6e6OnpoaGhwblz5+jRowf+/v4vNTBiYmJo3749X375JRMmTCAoKIhOnToxb948KTpVGEFBQVy7do2hQ4cW+HlMTAz169cnLi7uvRgZTl9ULfb93loSXiqNDJkPk7JggymVSvz9/UlNTS2zATdRFLl79y4ODg4fREb165CZmUlMTAxRUVGkpaWhq6sr2WD6+vpFdh5kZ2fj5OREaGioZBu8aIOp7DIdHR20tbXR09NDR0dH0jo0MDCgSpUqGBoaYmJiItlgxsbGH0SG1ZsgiiIpKSmSDZacnIyWlpZ0fcpqKdabkpmZiZubG82aNSvVTi1tbW3GjBnDypUrUSqVVKhQgf79++Pn58fevXtRKBTUrVu3wO/19evXGThwIEeOHMHV1ZW//vqLadOmcfz48Vc2wjhx4gSmpqY0bty4wM/37t3LyZMnOXDggGyDFTMfdpi7FFCtWjX09PTw8fHBxsYGMzOzkh7Sa5GRkcGzZ8/eSTv10o6GhgampqaShz4zM5OEhARiY2MJDAxEqVRKRoCBgUGBJUHZ2dncuHEDX19f2rZty8mTJ0viVMo8SqWSpKQkyahITU1FW1sbAwMDqlatip2d3TvJ2ikLTh4oO+nDenp6REVFSd0VPv/8cw4dOsT48eMJDQ2ladOmBRoYKSkp9OrVi08//ZQJEyYQEhJC165d+fbbb1/p5AGYM2cOkZGRBTp6MjIyWLFiBfr6+sTFxb39Sb4CUQSxHAkBysiUFGpqajg4OPD06VPu3r2Lk5NTmQu4PXv27IMpm39dtLS0sLCwwMLCAlEUSU1NJSEhgfDwcJKTk1FXV88TfCso8JWYmMjZs2epUKECP/30E1999VUJnEnZJzs7W8puSkhIICsrSyp5tra2Rk9Pr1Q7ON41WlpaVKtWjZCQEGrUqFHSw3kpGzZsYMOGDUBuEPrGjRtMnz4dbW1tatSoUaD9eO/ePQYNGsTmzZtxdXXl5MmTTJkyhaNHj77SyZOWlsb//vc/xowZU6CjJzw8nK1bt2JnZ1c8J/gKypsNJjt63gN6eno0btwYHx8fEhMTsbe3LzM3RFVdeFkZ77tES0uLqlWrUrVqridYoVCQlJREYmIijx49Ii0tTXI++Pr6cvDgQc6ePUuNGjXo1q0bgwcPLuEzKDuonGqqbB2FQiFlN9nZ2X1wOjvFQeXKlalYsSLR0dGlNn14ypQp9OzZE0EQGD16NP/++y+//PILJ06c4OjRo7Ro0aLA7c6cOYO2tjYLFiwgLCyMTp06MWXKFEaPHs3jx4+pXLlygbXkOTk59OvXj2vXrqGnp0d6enoe7S1PT09Gjx5NrVq1uHz5MlZWVu/s3GVkZEqGshpwUygUBAUF4erqWtJDKXEEQUBPTw89PT2qV68O5JbnqZwPISEhZGdnU6lSJfT09Pjnn384evQobm5uNG/enEmTJsk2WBERRZG0tDTJBktKSkJNTU1yqllaWpbbbPKXYWNjw82bNzE3Ny+112ft2rXUqFGDdevW8ffff/P48WO+++47/vjjD9q1a1eoXb1u3TrGjx9Phw4dOH36NF9++SWHDx+mXr16+Pr64uDgUGDGZHBwMJ988gmpqak8ePAgz2eiKLJ3715mzpzJ+PHjmTFjBhs3bnwn512ekR097wkNDQ0aNGjA48ePcXNzw9nZudTeCFSovPYfiphhcaOuro6hoaHUjvD06dP4+PhQq1YtsrKy6NevH6NGjaJSpUro6uqioaFBQkICurq6VKhQgbi4OA4fPoyTkxMLFy5EqVTSo0cPunXr9l4mnEqlkg0bNtCoUaMSMSRV5VcqTaLU1FRSU1PJyclBU1NTmrzXrFmzTKbclwR2dna4ublhbGxcKp2zLVu2pGXLlgB06dKFhw8fkpyczMmTJ6U2nQWhassuCAIXLlwgNDSUmzdv8uuvvxIWFkbt2rUlQcEX+eOPP0hPTycgIIBJkyYxYMAA5s2bh4ODA7/99hvr169nyZIlDBo06L06DstTa08ZmdJAWQy4BQcHl+pJY0mjap5RpUoVfHx8+PPPP1FTU0NfX59q1aoxZcoUyfGjq6tLcnIyoihKZUWPHz/m3Llz1K5dm6+++gonJye6d+9Op06d3ksGVUxMDFu3bmX48OElYmcrlUpJk0hlg6WlpaFUKtHR0cHAwAALCwscHR1L/W+lNKCmpkatWrXw9/fHycmppIdTICNGjACgdevWBAcHEx0dzYYNG3jw4AHOzs4FbhMfH8/Vq1f5/vvvAdi1axcxMTGsWrWKgwcPArBgwQJmzJiRZztRFJk+fTqDBg1i7NixtG/fnu+++47Ro0ejra3N1KlTefToEX/99dd779hYnmww2dHzHhEEgZo1a1K5cmXc3NyoU6fOe+308jqo2qnXrVtXzpx4CSdPnmTFihXcuHEDKysrZs2aRU5ODo0aNaJBgwaIokhmZiZJSUmkpaUREBCAj48PCoVCqmu+efMmdevWpVmzZhw7doyffvoJCwsLunTpQufOnWnSpMlrlSWJosjTp0/x9/fnwYMHPHr0iEGDBuVz5uzdu5fFixdToUIFPD090dXVLe7LA+Q1JlQGhcqYqFixIrq6uujp6WFhYSE5wWTeDC0tLczMzEp1+rAoipKB4erqyhdffMG8efMKNYwSExPZu3cvQUFBUpvWVatWcezYMcLCwujTpw/Lly/Pt92TJ09YvHgxZ8+eRV9fnz///JOVK1cyYsQIgoKCaNeuHdevX5eiwzIyMh82ZSnglpGRQVRUVLksmy8qCoWCVatW8ccffxASEkKnTp0YNmwYsbGx9OrVC1NTU5RKJenp6SQmJpKeno6fnx+BgYFAbllceno6V69eZfTo0WhoaLBz504mTJhAo0aNJBtMFWQoKjk5OYSEhPDo0SP8/PyIjIxk1qxZ+bJOv/nmGy5cuICXlxc7duwo1mvz3/Go7C+VDZaeno4gCOjo6Eg2mKmpKbq6urJT5y0wNTUlLCyMxMTEUivMnZOTg6+vL1paWri6uvLpp59y+fLlAr/jCoWCa9euUbFiRXr37k1CQgKOjo78+uuvrFq1Csgt/5o0aVK+bY8ePcrjx4/Zu3cvmpqanD59mgULFtChQweioqKYPHkyW7dupWLFiu/8nMszsqOnBDAyMsLFxQVvb2/MzMywtLQsdc6UyMhI9PX1S7Wwa0nzxx9/sHTpUn7++Wf++ecfNDQ08vw/ZmRksH//fq5fv862bdsAaNiwIba2tixYsABDQ0MUCkWeh++oUaMYNWoUaWlpPH36lH///ZctW7ZQrVo1HBwcaNSokdSd6MVjZWZmsmTJEv755x+pTby9vT0ODg5kZmby448/8tdff+UZf3R0NH379iUiIoINGzYwderU1zp/hUIhdavIzMzM87fqvVKpzGdMmJiYoKOjU25FDN811tbWpTZ9+EUDo1GjRqipqUnOzx49elCnTp0863/77bf89ttvDBs2DFNTU+bPn8+BAwekLLqTJ0/Stm3bPNtkZWUxY8YM/vnnH8aOHUvt2rWBXCfYt99+y7fffktOTk6JdmIrT/XhMjKlibIScPP398fW1laedBdCVlYWo0eP5smTJ+zcubNAbbrw8HD+/vtvTp8+zZkzZ6SW7fPmzaN169aYmprmC0LVqVMHpVJJcnIyT548YcOGDaSkpGBtbY2joyONGzfG1NQ0n7335MkT5s6di7u7OyEhIZiamuLg4ICDgwN3795l165d+SbDMTEx/PLLL0yfPh1vb+9CMyoKQhRFFApFofZXZmYm2dnZiKKIurq61ORDlaWjra1d6uYdHwIqvUQ/Pz8aN25c6q5xamoq3t7eWFtbY25uTkZGBomJiWzfvh07O7s890KFQkGzZs3w9fVl69atZGZm0q9fP7Kzs0lOTsbJyYnjx4/nCyqGhITw9ddfc+3aNfbv34+mpiYAFhYW/PHHHwCyDfYekR09JYS2tjaNGjXCz88PX19f6tSpU2omvjk5OTx+/JgmTZqU9FBKLYmJicydO5erV69ib2+PUqlk165dhISEkJqaSmJiIjt27KBFixa0adMGPz8/HB0dcXd3Z82aNVhbW0v7Uk1aXyQnJ0d6eD99+pT79+8TGhrKnj17qFSpktTFTRAENDU1CQsLIyMjgylTpmBvb4+Ojg5qamqoq6uTnp7OwoULCQkJoUKFCqirq6Ompoa5uTlRUVEMHTqUixcvEhISIrUdVSqVKBSKfH+r2pFCbpqqqluFqnOYvr5+nveykfr+UVNTw9bWtlSkD6elpfHgwQNsbW1RV1eXnNtVqlSRvhu7du3i7NmztGnTBltbW1JSUhgwYACBgYFcuXKFmzdv4uzsTFBQEJs2bcLNzS1Pmrsoivzzzz84OjpiZWXF1KlTiYyMZNeuXbi4uBQ4rhI1MERQltFulzIyHwqlOeAml82/GlVQ69SpU+jr65OQkMDWrVtJSkoiJSWF0NBQjh49ytChQ/nkk09YsmQJrq6umJiYMHToUOn5o6Ojg7GxcZ59i6IotV3PyMjg8ePHPHjwgIcPH+Lh4UHVqlVxcnJCQ0MDNTU1NDU1OXPmDCYmJvz2229UqVJFsn/U1NTw8fHh7t27PHnyRLLLBEHA2dmZrKwsJk6ciLu7O5UrV85jdxVkh2VnZ6NQKACkjmEqe0tLSwtdXV1p2X8DgjLvB1W54NOnT0tcDyw+Pp5Hjx7RuHFjoqOjCQwMxMrKSvrOV6xYkQsXLrBnzx6sra1p2rQpkZGRTJ8+nT/++ANjY2MiIyMxMDDgzz//REdHhyNHjuSx7dPT0zl+/Djdu3cnOzubzz77jF69erF06VJq1qxZ4LhkG+z9UWbbqwuCcBowfuWKMjIyMjIyRSNGFMUu7/IAOlU1xdqDi18s22Plk1LZ2lPmw0S2wWRkZGRkihnZBitmymxGz7v+IsjIyMjIyLwLSlvasCAIVYB9gA0QDPQXRTG+kHX1gfvAX6IoTnxfY5QpXcg2mIyMjIxMWaS02WDvErmuQkZGRkZGpnzzLXBOFEU74Nzz94XxI3D5vYxKRkZGRkZGRkbmjSizGT0yr4cgCBsBAXgIhAEHRVHMLtlRycjIyJQ/SmFrz55Am+d/bwMuAjP/u5IgCK5AVeA0UOpSlGVkSiOy/SUjIyNTeiiFNtg7Q87oKQcIuWpsPQEvQB/oAigEQagiCMIRQRDcBEFYJQiC+gvbGAuCoFlCQ5aRkXlHCIKgJwjCR4IgDBIEYaEgCAsEQZB7jJdvqoqiGPn876fkOnPyIAiCGvAz8PX7HJiMTFlGtr9kZGReRLbBZN4nsqOnfGAJhIuiuEoUxTmiKA4HdIHFwFVgMFAZaA8gCEJVYC1wThAEq+fLfhEEQRJeFARBbgchI1MKEQShwgt/6z43IhYJgqDxfLI+FrgENAOUgBsQVzKjLYeIICrFYn8BxoIg3H3hNfbFwwqCcFYQBN8CXj3zDC+3Q0NBXRomACdFUQx/Z9dGRubDQ7a/ZGTKEbINVsp5dzZYqUQu3SofWAB1BUFYBdwTRfEPwA5wAcaLoqgUBOEkMBz4F/gE2E6u4OY4QRB+BFyB2sBVQRBqAgGCIPQQRfGEIAgVganAZlEUo973ycnIlCeeR4itAS1RFB8+X2YKbCL3d31XEIRJz8V07cmdRFwFFoiiOFsQhMfk/lanlMwZlG9E3lnacMzLOj6IotihsM8EQXgmCIKZKIqRgiCYAQXdx5sDrQRBmADoAZqCIKSIovgyPR8ZmfKObH/JyHxAyDZY2eYd2mClEjmjp3wQAPQHbgHtBUHoATgCSaIoaY+rAdWe/50BGD1/ryGKYjpwk1xDA+AjwB1weP7eGZgGJL7j85CRKdc8NzAOAneAv54v0wB6kav/0ATwITdaDLm/0auiKB4Aaj1fFg04CoIwRBCEOYIgbBMEwe69nYRMaeRvcieaPP/36H9XEEVxsCiKVqIo2pBbvrVddvLIyLwS2f6SkflAkG0wmbKG7OgpB4iiGC2K4l+iKO4CTgEtgE7k3oxUOJIrEgi5N6uxQG9gyfNlOUDV53WkRsAFwOz5Z22As6IoZr5YZy4jI1O8PC+r+YXcCG+6IAgVRFHMAYYAu0VRTAJ+BzoKgmAIXAHaCoJwDNj9fDdx5Gqw9AEU5HZQin6/Z1K+EcXif70lS8j9zvgDHZ6/RxCERs+FZGVkZN4A2f6SkflwkG2wD4NSaIO9M+TSrQ8cQRA0nt+EVGiQG/lpBNx+YbktuR5qRFF0IzdqpPJeQ65xEUuukZINhAIazw2PGsDx5+uVo4Q4GZn3jyiK1wRB0CM3A9Wa3IixObkGA6IopgmCkA3Ueb7uDnJFQK8830UauRHh2aIoBr33E5ApdYiiGMtzjZD/LL8LjC5g+VZg6zsfmIxMGUa2v2RkPjxkG0ymLCE7ej58tARB2ANoAv5AfXK9zWFAYwBBEBoA2uTWkPI8KqR87rlWI/fmlQUkA53JTVsEMAaGPV9+AyRvt4yMzLslFYgnNxU4gFxNFQdyO7sAhJA7ebgmiuKNArZNIreWXDYy3jciKEuxcJ+MjEyxIdtfMjIfJrINVlYpZzaY7Oj5wBFFMVUQhFnk3lBqk5viexpAEITugiDcJ9e7/D3g8XwbxQu7UEWI7pMbZdIH/IBK5HqyR5LrlQ5+92cjIyMDuQa9IAiR5BoW/5D7+6z7wipBgAFI9eOqSJNIrgZEBjBCEIRq5P6uE4F1cnTp3SMCohx3l5H54JHtLxmZDxPZBiu7lDcbTHb0lANEUQwg1+N86j/LBz1v02kkiuKDQrZVuT19yW35OR+IIPemtYb/V5OXkZF5vzwCqjz/+29ggCAIDkA6oE6u+Cf/KR2AXAPDj1xdCAdyJxiewJN3P2QZGRmZ8oNsf8nIfLDINphMqUeQMz1lioIgCMbAHHI9zqp2gs+A66Io9i7RwcnIlDMEQdAhNwrcC1hEbjTJglzxTg1gjyiK3wuCIMjp/KULQRBOk1t2UdzEiKLY5R3sV0ZGpgSR7S8ZmdKFbIOVXcqbDSY7emTeGEEQKgFaoijGlPRYZGTKC4IgVABOAKbk1oHfB9aTK9BpIopiVAkOT0ZGRkbmHSPbXzIyJYNsg8mUJWRHj4yMjIyMjIyMjIyMjIyMjMwHglpJD0BGRkZGRkZGRkZGRkZGRkZGpniQHT0yMjIyMjIyMjIyMjIyMjIyHwiyo0dGRkZGRkZGRkZGRkZGRkbmA0F29MjIyMjIyMjIyMjIyMjIyMh8IMiOHhkZGRkZGRkZGRkZGRkZGZkPBNnRIyMjIyMjIyMjIyMjIyMjI/OBIDt6ZGRkZGRkZGRkZGRkZGRkZD4QZEePjIyMjIyMjIyMjIyMjIyMzAfC/wGbnNeHVvjy8gAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 1440x576 with 4 Axes>"
       ]
@@ -865,16 +868,16 @@
     "    gl.xlocator = mticker.FixedLocator(np.arange(-170,180,60))\n",
     "    gl.ylocator = mticker.FixedLocator(np.arange(80,90,2))\n",
     "    ax.set_extent([-20, 340, 82, 90], ccrs.PlateCarree())\n",
-    "axs[0].set(title='filtered with REGULAR_WITH_LAND Laplacian')\n",
-    "axs[1].set(title='filtered with TRIPOLAR_REGULAR_WITH_LAND Laplacian')"
+    "axs[0].set(title='filtered with TRANSFORMED_TO_REGULAR_WITH_LAND Laplacian')\n",
+    "axs[1].set(title='filtered with TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND Laplacian')"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "* **Left panel**: The `REGULAR_WITH_LAND` Laplacian **does not allow** exchanges across the tripole seam.\n",
-    "* **Right panel**: The `TRIPOLAR_REGULAR_WITH_LAND` Laplacian **allows** exchanges across the tripole seam."
+    "* **Left panel**: The `TRANSFORMED_TO_REGULAR_WITH_LAND` Laplacian **does not allow** exchanges across the tripole seam.\n",
+    "* **Right panel**: The `TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND` Laplacian **allows** exchanges across the tripole seam."
    ]
   },
   {
@@ -888,7 +891,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -901,24 +904,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/glade/u/home/noraloose/gcm-filters/gcm_filters/filter.py:266: UserWarning: Warning: Filter scale much larger than grid scale -> numerical instability possible\n",
-      "  UserWarning,\n"
+      "/glade/u/home/noraloose/gcm-filters/gcm_filters/filter.py:11: UserWarning: Filter scale much larger than grid scale -> numerical instability possible\n",
+      "  \n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=200000, dx_min=array(2245.78304344), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=98, grid_type=<GridType.IRREGULAR_WITH_LAND: 3>)"
+       "Filter(filter_scale=200000, dx_min=array(2245.78304344), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=98, grid_type=<GridType.IRREGULAR_WITH_LAND: 5>)"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -929,7 +932,8 @@
     "    grid_type=gcm_filters.GridType.IRREGULAR_WITH_LAND,\n",
     "    grid_vars={\n",
     "        'wet_mask': wet_mask, \n",
-    "        'dxw': dxw, 'dyw': dyw, 'dxs': dxs, 'dys': dys, 'area': area\n",
+    "        'dxw': dxw, 'dyw': dyw, 'dxs': dxs, 'dys': dys, 'area': area, \n",
+    "        'kappa_w': xr.ones_like(dxw), 'kappa_s': xr.ones_like(dxs)\n",
     "    }\n",
     ")\n",
     "filter_irregular_with_land"
@@ -937,24 +941,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/glade/u/home/noraloose/gcm-filters/gcm_filters/filter.py:266: UserWarning: Warning: Filter scale much larger than grid scale -> numerical instability possible\n",
-      "  UserWarning,\n"
+      "/glade/u/home/noraloose/gcm-filters/gcm_filters/filter.py:11: UserWarning: Filter scale much larger than grid scale -> numerical instability possible\n",
+      "  \n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=200000, dx_min=array(2245.78304344), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=98, grid_type=<GridType.TRIPOLAR_POP_WITH_LAND: 5>)"
+       "Filter(filter_scale=200000, dx_min=array(2245.78304344), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=98, grid_type=<GridType.TRIPOLAR_POP_WITH_LAND: 7>)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -973,17 +977,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 25 s, sys: 15.4 s, total: 40.4 s\n",
-      "Wall time: 40.4 s\n",
-      "CPU times: user 26.1 s, sys: 15.4 s, total: 41.5 s\n",
-      "Wall time: 41.8 s\n"
+      "CPU times: user 26.2 s, sys: 15 s, total: 41.2 s\n",
+      "Wall time: 41.3 s\n",
+      "CPU times: user 27.5 s, sys: 15.1 s, total: 42.7 s\n",
+      "Wall time: 42.7 s\n"
      ]
     }
    ],
@@ -1001,7 +1005,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1018,7 +1022,7 @@
        "[Text(0.5, 1.0, 'filtered with TRIPOLAR_POP_WITH_LAND Laplacian')]"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1063,12 +1067,12 @@
    "source": [
     "## Global MOM6 data\n",
     "\n",
-    "Next, we filter surface vorticity field from a $1/4^{\\circ}$ global MOM6 simulation using the `REGULAR_WITH_LAND` and `TRIPOLAR_REGULAR_WITH_LAND` Laplacians. We use these Laplacians for **simple fixed factor filtering by a factor of 10**."
+    "Next, we filter surface vorticity field from a $1/4^{\\circ}$ global MOM6 simulation using the `TRANSFORMED_TO_REGULAR_WITH_LAND` and `TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND` Laplacians. We use these Laplacians for **simple fixed factor filtering by a factor of 10**."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -1463,11 +1467,11 @@
        "    wet_c         (yq, xq) float32 ...\n",
        "    wet_u         (yh, xq) float32 ...\n",
        "    wet_v         (yq, xh) float32 ...\n",
-       "    zeta          (yq, xq) float32 ...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-fa2438b7-b5ab-4c87-af3a-49266b718448' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fa2438b7-b5ab-4c87-af3a-49266b718448' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>xh</span>: 1440</li><li><span class='xr-has-index'>xq</span>: 1440</li><li><span class='xr-has-index'>yh</span>: 1080</li><li><span class='xr-has-index'>yq</span>: 1080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7416510e-52a3-4a2e-8484-ba690b0e7ca9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7416510e-52a3-4a2e-8484-ba690b0e7ca9' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ea135773-670a-43f5-9847-dccc66dae319' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea135773-670a-43f5-9847-dccc66dae319' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3fa8136-3087-49a9-a589-afa690f9806c' class='xr-var-data-in' type='checkbox'><label for='data-f3fa8136-3087-49a9-a589-afa690f9806c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>NOLEAP</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array(cftime.DatetimeNoLeap(101, 1, 1, 12, 0, 0, 0), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.7 -299.5 ... 59.78 60.03</div><input id='attrs-05714eb5-c13d-422d-ae29-d8bd4e251aa7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05714eb5-c13d-422d-ae29-d8bd4e251aa7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3017ca1d-8057-44de-a709-1a8e277b0a7a' class='xr-var-data-in' type='checkbox'><label for='data-3017ca1d-8057-44de-a709-1a8e277b0a7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.724244, -299.476198, -299.22815 , ...,   59.531631,   59.77967 ,\n",
-       "         60.027712])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.39 -80.31 ... 89.84 89.95</div><input id='attrs-d219ac98-9b8e-4144-9520-9be82566be95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d219ac98-9b8e-4144-9520-9be82566be95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7af750ac-cca8-420d-9165-e2f07fb6a5a6' class='xr-var-data-in' type='checkbox'><label for='data-7af750ac-cca8-420d-9165-e2f07fb6a5a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.389238, -80.308075, -80.226911, ...,  89.729781,  89.837868,\n",
-       "        89.945956])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.6 -299.3 ... 59.91 60.16</div><input id='attrs-1cee2e8a-8501-4ff6-839c-bb62c02661f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cee2e8a-8501-4ff6-839c-bb62c02661f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0d49fe0-b852-4a6f-8510-6561db6299f5' class='xr-var-data-in' type='checkbox'><label for='data-c0d49fe0-b852-4a6f-8510-6561db6299f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.594355, -299.346385, -299.098412, ...,   59.661746,   59.90971 ,\n",
-       "         60.157676])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.35 -80.27 -80.19 ... 89.89 90.0</div><input id='attrs-d2362a0c-dd39-416f-8fa1-321358702450' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2362a0c-dd39-416f-8fa1-321358702450' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-000c293c-a499-4b27-8b3e-4710a8040bcb' class='xr-var-data-in' type='checkbox'><label for='data-000c293c-a499-4b27-8b3e-4710a8040bcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.348657, -80.267493, -80.186329, ...,  89.783825,  89.891912,\n",
-       "        90.      ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9b85ba76-42b0-4380-b790-9a6e611689f6' class='xr-section-summary-in' type='checkbox'  ><label for='section-9b85ba76-42b0-4380-b790-9a6e611689f6' class='xr-section-summary' >Data variables: <span>(30)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ssu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fbf9cabd-57bd-4a64-ba5f-17c083e1e7c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fbf9cabd-57bd-4a64-ba5f-17c083e1e7c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f545c48c-244a-4e22-a55d-a21251c52e81' class='xr-var-data-in' type='checkbox'><label for='data-f545c48c-244a-4e22-a55d-a21251c52e81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Zonal Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yh:mean xq:point time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a999596-c9f4-49f6-addb-a90d0a360c2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a999596-c9f4-49f6-addb-a90d0a360c2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53ab9232-e034-4675-928a-046e38181c7e' class='xr-var-data-in' type='checkbox'><label for='data-53ab9232-e034-4675-928a-046e38181c7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Meridional Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yq:point xh:mean time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zos</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-69e3ec3e-1ebc-4739-b893-839ad833cc63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69e3ec3e-1ebc-4739-b893-839ad833cc63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1c9fe22-92e2-4d91-b057-09c726decdb1' class='xr-var-data-in' type='checkbox'><label for='data-f1c9fe22-92e2-4d91-b057-09c726decdb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea surface height above geoid</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>standard_name :</span></dt><dd>sea_surface_height_above_geoid</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Coriolis</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-69a01b79-beae-4c34-b92d-23db289ba647' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69a01b79-beae-4c34-b92d-23db289ba647' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29144f36-0446-4918-ae20-4a6838be2325' class='xr-var-data-in' type='checkbox'><label for='data-29144f36-0446-4918-ae20-4a6838be2325' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Coriolis parameter at corner (Bu) points</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cdbdabf9-efd5-4a5a-93db-42976f6140cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cdbdabf9-efd5-4a5a-93db-42976f6140cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec3f0266-525d-4e27-a4bd-27aec186cd7b' class='xr-var-data-in' type='checkbox'><label for='data-ec3f0266-525d-4e27-a4bd-27aec186cd7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_bu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dd4dd2b0-d072-459f-bc93-5c868ad8b418' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd4dd2b0-d072-459f-bc93-5c868ad8b418' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b45b8f1-9ab1-4961-8eb7-595fc3d32f88' class='xr-var-data-in' type='checkbox'><label for='data-7b45b8f1-9ab1-4961-8eb7-595fc3d32f88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd712cfc-8635-468c-9de5-193f45438c56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd712cfc-8635-468c-9de5-193f45438c56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b853b50-efe4-46bd-b96e-a9db23df3deb' class='xr-var-data-in' type='checkbox'><label for='data-7b853b50-efe4-46bd-b96e-a9db23df3deb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-26788cc0-bf16-4118-97a8-401fe81254fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26788cc0-bf16-4118-97a8-401fe81254fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fc85f4d-bdaf-4cb7-b87d-380b0b08dd3f' class='xr-var-data-in' type='checkbox'><label for='data-9fc85f4d-bdaf-4cb7-b87d-380b0b08dd3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>deptho</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aae4d39a-abe7-4a53-8998-1e06969f1c2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aae4d39a-abe7-4a53-8998-1e06969f1c2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cae630fc-3270-49e4-90e9-d2d5c524d53e' class='xr-var-data-in' type='checkbox'><label for='data-cae630fc-3270-49e4-90e9-d2d5c524d53e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Floor Depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>standard_name :</span></dt><dd>sea_floor_depth_below_geoid</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1bac1a5d-e940-4bb2-8be0-53a3642a1b11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bac1a5d-e940-4bb2-8be0-53a3642a1b11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6096b604-d2a1-480b-b6e3-8bfed0994c67' class='xr-var-data-in' type='checkbox'><label for='data-6096b604-d2a1-480b-b6e3-8bfed0994c67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9f90045e-ec5b-4e0b-891a-4e90570fee4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f90045e-ec5b-4e0b-891a-4e90570fee4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00f6295f-c9d4-4f02-a2c0-895a8e967b73' class='xr-var-data-in' type='checkbox'><label for='data-00f6295f-c9d4-4f02-a2c0-895a8e967b73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-633369ca-3ea3-49f9-8524-5ebd0e57956b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-633369ca-3ea3-49f9-8524-5ebd0e57956b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adafe5f0-2566-4749-bc36-d6b80969edf9' class='xr-var-data-in' type='checkbox'><label for='data-adafe5f0-2566-4749-bc36-d6b80969edf9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-721b45db-02d0-4740-9f22-5bd7b68c33a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-721b45db-02d0-4740-9f22-5bd7b68c33a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e40e6070-08c7-4e1b-8849-87a4b4f24b3e' class='xr-var-data-in' type='checkbox'><label for='data-e40e6070-08c7-4e1b-8849-87a4b4f24b3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6b029242-b240-46d3-93e9-d0f0b9ca0de7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b029242-b240-46d3-93e9-d0f0b9ca0de7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f2ad1c8-21d6-476e-846a-f93381be2e9a' class='xr-var-data-in' type='checkbox'><label for='data-5f2ad1c8-21d6-476e-846a-f93381be2e9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-542c6d2f-1c23-470b-ba40-d30c9cc30af1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-542c6d2f-1c23-470b-ba40-d30c9cc30af1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e190c5b4-91a6-42ed-8ab5-547cd392838d' class='xr-var-data-in' type='checkbox'><label for='data-e190c5b4-91a6-42ed-8ab5-547cd392838d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c1c79a64-9222-4882-bdba-d3d081e35a82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1c79a64-9222-4882-bdba-d3d081e35a82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54614c0e-8e92-481c-bdeb-db886eb46149' class='xr-var-data-in' type='checkbox'><label for='data-54614c0e-8e92-481c-bdeb-db886eb46149' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f0766899-1b3f-4ed2-9308-18a212b2e1b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0766899-1b3f-4ed2-9308-18a212b2e1b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3efd6c01-a0a5-4a03-a567-83dcc5d5f852' class='xr-var-data-in' type='checkbox'><label for='data-3efd6c01-a0a5-4a03-a567-83dcc5d5f852' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7e1ae093-2a25-4bff-80cc-c3a7b171ea2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e1ae093-2a25-4bff-80cc-c3a7b171ea2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c784a566-8808-4de8-afdf-315bbf5914d0' class='xr-var-data-in' type='checkbox'><label for='data-c784a566-8808-4de8-afdf-315bbf5914d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a40927c0-4b49-4d52-a0a1-54754438d2ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a40927c0-4b49-4d52-a0a1-54754438d2ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2412e505-35fa-422a-9d2f-07e91eee5190' class='xr-var-data-in' type='checkbox'><label for='data-2412e505-35fa-422a-9d2f-07e91eee5190' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8014d317-2333-4caf-b097-19ff3002e53d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8014d317-2333-4caf-b097-19ff3002e53d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c7c300f-725a-438f-98ef-2679d20c37a4' class='xr-var-data-in' type='checkbox'><label for='data-9c7c300f-725a-438f-98ef-2679d20c37a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aec834d2-cfd9-4264-a2c3-4ace9aa8ef97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aec834d2-cfd9-4264-a2c3-4ace9aa8ef97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-526a446f-e874-4a1c-9ac1-2a86a821017e' class='xr-var-data-in' type='checkbox'><label for='data-526a446f-e874-4a1c-9ac1-2a86a821017e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9fd189c5-f79d-4efc-9822-f36dabf7794c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fd189c5-f79d-4efc-9822-f36dabf7794c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54a004b5-cb26-4e3c-ba7f-18048766ce47' class='xr-var-data-in' type='checkbox'><label for='data-54a004b5-cb26-4e3c-ba7f-18048766ce47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c0ba9625-94ff-49a4-99c0-da13e2a7debb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0ba9625-94ff-49a4-99c0-da13e2a7debb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b063849d-af03-4314-a6d4-97b5b8b08a80' class='xr-var-data-in' type='checkbox'><label for='data-b063849d-af03-4314-a6d4-97b5b8b08a80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hfgeou</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b3ab4e2-087e-4bb9-9467-b102bade04e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b3ab4e2-087e-4bb9-9467-b102bade04e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f1ddbaa-1eb9-4e6d-8abd-00f411026a96' class='xr-var-data-in' type='checkbox'><label for='data-9f1ddbaa-1eb9-4e6d-8abd-00f411026a96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Upward geothermal heat flux at sea floor</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>upward_geothermal_heat_flux_at_sea_floor</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftof</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6059e462-03ca-454e-ab1e-45e0578d14bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6059e462-03ca-454e-ab1e-45e0578d14bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1bef8c6-41e1-495a-944a-b4d2ecca604b' class='xr-var-data-in' type='checkbox'><label for='data-e1bef8c6-41e1-495a-944a-b4d2ecca604b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Area Fraction</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>SeaAreaFraction</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f5493b4-d09e-46bc-aa90-bc30974c864e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f5493b4-d09e-46bc-aa90-bc30974c864e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e99d69e5-b952-41b2-90a7-bb4049c31e3f' class='xr-var-data-in' type='checkbox'><label for='data-e99d69e5-b952-41b2-90a7-bb4049c31e3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at tracer points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c464853-1f92-471c-b455-2185eeb5347a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c464853-1f92-471c-b455-2185eeb5347a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5ba92ee-dde9-4e63-be3a-83b98fbc5865' class='xr-var-data-in' type='checkbox'><label for='data-e5ba92ee-dde9-4e63-be3a-83b98fbc5865' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c9a4bab5-37f4-4b1b-8b4b-5eac07de1e9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9a4bab5-37f4-4b1b-8b4b-5eac07de1e9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8243f84d-3efe-48d9-98ec-db4e58aabb99' class='xr-var-data-in' type='checkbox'><label for='data-8243f84d-3efe-48d9-98ec-db4e58aabb99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ae0727d3-cdd5-4775-8d8e-c2bb023f4b41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae0727d3-cdd5-4775-8d8e-c2bb023f4b41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81dd878c-b98c-4cf3-9e68-5fe9ee423252' class='xr-var-data-in' type='checkbox'><label for='data-81dd878c-b98c-4cf3-9e68-5fe9ee423252' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zeta</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-39a00561-f2ca-479d-ba53-eb737f7ddabf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-39a00561-f2ca-479d-ba53-eb737f7ddabf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7b74f24-d405-4c8c-b96d-518c3078ddd2' class='xr-var-data-in' type='checkbox'><label for='data-f7b74f24-d405-4c8c-b96d-518c3078ddd2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb40dea4-9dfa-45c9-8394-49428328455d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eb40dea4-9dfa-45c9-8394-49428328455d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "    zeta          (yq, xq) float32 ...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d769d752-61ab-4c19-b5fe-7b9cd3beb49e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d769d752-61ab-4c19-b5fe-7b9cd3beb49e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>xh</span>: 1440</li><li><span class='xr-has-index'>xq</span>: 1440</li><li><span class='xr-has-index'>yh</span>: 1080</li><li><span class='xr-has-index'>yq</span>: 1080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4f7bdbfb-ad36-4c6c-9566-03f65ee1cdea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4f7bdbfb-ad36-4c6c-9566-03f65ee1cdea' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b7712a24-9614-4e67-a15f-ae7ed0356537' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7712a24-9614-4e67-a15f-ae7ed0356537' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16afb20c-26ce-4770-a1b4-cbfeb27e8e5b' class='xr-var-data-in' type='checkbox'><label for='data-16afb20c-26ce-4770-a1b4-cbfeb27e8e5b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>NOLEAP</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array(cftime.DatetimeNoLeap(101, 1, 1, 12, 0, 0, 0), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.7 -299.5 ... 59.78 60.03</div><input id='attrs-c805de49-6bde-482e-a208-bc6eb5350815' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c805de49-6bde-482e-a208-bc6eb5350815' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87330929-a568-4ab0-a358-c0841e8a1b17' class='xr-var-data-in' type='checkbox'><label for='data-87330929-a568-4ab0-a358-c0841e8a1b17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.724244, -299.476198, -299.22815 , ...,   59.531631,   59.77967 ,\n",
+       "         60.027712])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.39 -80.31 ... 89.84 89.95</div><input id='attrs-1f28f6d8-611f-40f0-90f6-5f8ba6889fcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f28f6d8-611f-40f0-90f6-5f8ba6889fcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82dcf70a-cfc4-4813-9455-a2fe7cd3121f' class='xr-var-data-in' type='checkbox'><label for='data-82dcf70a-cfc4-4813-9455-a2fe7cd3121f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.389238, -80.308075, -80.226911, ...,  89.729781,  89.837868,\n",
+       "        89.945956])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-299.6 -299.3 ... 59.91 60.16</div><input id='attrs-9468cec7-2511-488f-8429-7c4b17a30e6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9468cec7-2511-488f-8429-7c4b17a30e6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6acb4275-8f72-40c2-bfcf-0e199154a00e' class='xr-var-data-in' type='checkbox'><label for='data-6acb4275-8f72-40c2-bfcf-0e199154a00e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-299.594355, -299.346385, -299.098412, ...,   59.661746,   59.90971 ,\n",
+       "         60.157676])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.35 -80.27 -80.19 ... 89.89 90.0</div><input id='attrs-e143f33a-6061-49ff-a769-e3aec1e83818' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e143f33a-6061-49ff-a769-e3aec1e83818' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f00c538-b36c-4df4-8eca-937dd246ed3d' class='xr-var-data-in' type='checkbox'><label for='data-3f00c538-b36c-4df4-8eca-937dd246ed3d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-80.348657, -80.267493, -80.186329, ...,  89.783825,  89.891912,\n",
+       "        90.      ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab5de473-10ae-4df1-a932-babc68c805f5' class='xr-section-summary-in' type='checkbox'  ><label for='section-ab5de473-10ae-4df1-a932-babc68c805f5' class='xr-section-summary' >Data variables: <span>(30)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ssu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1f99f0ea-2092-4dbb-962c-085a9bff2a04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f99f0ea-2092-4dbb-962c-085a9bff2a04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1abb356c-edaf-4f7c-bf5f-cb0704e8602c' class='xr-var-data-in' type='checkbox'><label for='data-1abb356c-edaf-4f7c-bf5f-cb0704e8602c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Zonal Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yh:mean xq:point time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-652e4072-48ad-4e7a-9955-289ef5776d03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-652e4072-48ad-4e7a-9955-289ef5776d03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0885e085-c762-4947-9566-0ab2ea364e64' class='xr-var-data-in' type='checkbox'><label for='data-0885e085-c762-4947-9566-0ab2ea364e64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Meridional Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yq:point xh:mean time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zos</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1aa3fa72-28b0-4903-922b-2c8feefa1e26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1aa3fa72-28b0-4903-922b-2c8feefa1e26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4e3f989-9dbd-4cfc-b5cd-fc09053c30d4' class='xr-var-data-in' type='checkbox'><label for='data-b4e3f989-9dbd-4cfc-b5cd-fc09053c30d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea surface height above geoid</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>standard_name :</span></dt><dd>sea_surface_height_above_geoid</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Coriolis</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6da9f9b9-9266-45f9-bd2e-46e0039d2b4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6da9f9b9-9266-45f9-bd2e-46e0039d2b4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cd9c9b3-d328-4bac-97f1-f4784e31b3c1' class='xr-var-data-in' type='checkbox'><label for='data-1cd9c9b3-d328-4bac-97f1-f4784e31b3c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Coriolis parameter at corner (Bu) points</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-568f4d66-4e92-4282-826f-1b431dc10d2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-568f4d66-4e92-4282-826f-1b431dc10d2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0971c1a4-e9ba-487b-bd2b-75fe6b56409d' class='xr-var-data-in' type='checkbox'><label for='data-0971c1a4-e9ba-487b-bd2b-75fe6b56409d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_bu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f9b71565-2292-4f60-991d-ac25805232d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9b71565-2292-4f60-991d-ac25805232d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10123193-c9e4-4ff0-8caa-897fbce16e5e' class='xr-var-data-in' type='checkbox'><label for='data-10123193-c9e4-4ff0-8caa-897fbce16e5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6508453e-eab1-412a-9a14-12809a5dd5b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6508453e-eab1-412a-9a14-12809a5dd5b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30cf0a7a-4cce-4865-baf3-819187312fd1' class='xr-var-data-in' type='checkbox'><label for='data-30cf0a7a-4cce-4865-baf3-819187312fd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello_cv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ed8e6b0d-ed26-45c1-8d59-58aa3f6bd069' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed8e6b0d-ed26-45c1-8d59-58aa3f6bd069' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eed7fe39-969d-454f-b394-36736a9b04ba' class='xr-var-data-in' type='checkbox'><label for='data-eed7fe39-969d-454f-b394-36736a9b04ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Ocean Grid-Cell Area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>deptho</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b07bf675-5deb-4c61-9929-ed9d124c135a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b07bf675-5deb-4c61-9929-ed9d124c135a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de3a87c1-958c-431b-bc4c-ec054af596e8' class='xr-var-data-in' type='checkbox'><label for='data-de3a87c1-958c-431b-bc4c-ec054af596e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Floor Depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>standard_name :</span></dt><dd>sea_floor_depth_below_geoid</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fc124b91-6cff-4a96-b6c1-ff049e3094ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc124b91-6cff-4a96-b6c1-ff049e3094ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f61c9fa-64d0-4f45-9e4f-43d9980f8029' class='xr-var-data-in' type='checkbox'><label for='data-3f61c9fa-64d0-4f45-9e4f-43d9980f8029' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-81b43511-a095-409c-b448-5930ac63b4f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81b43511-a095-409c-b448-5930ac63b4f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc8ecb8a-d3f6-4598-85d3-b3f8e02868f8' class='xr-var-data-in' type='checkbox'><label for='data-fc8ecb8a-d3f6-4598-85d3-b3f8e02868f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d6215717-d7a7-49f4-9b16-6f787bda3642' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6215717-d7a7-49f4-9b16-6f787bda3642' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf374505-2cff-4955-8831-85a62209bb27' class='xr-var-data-in' type='checkbox'><label for='data-bf374505-2cff-4955-8831-85a62209bb27' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-61856447-a8aa-4186-be08-d106dba1e3ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61856447-a8aa-4186-be08-d106dba1e3ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-288fb7d7-8958-490f-8dfd-993514e53e12' class='xr-var-data-in' type='checkbox'><label for='data-288fb7d7-8958-490f-8dfd-993514e53e12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-daa9f9a9-0e0a-4dfe-b908-9747f468a990' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-daa9f9a9-0e0a-4dfe-b908-9747f468a990' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fcd343b-f0f9-473c-843e-50be04ad2f76' class='xr-var-data-in' type='checkbox'><label for='data-1fcd343b-f0f9-473c-843e-50be04ad2f76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyt</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4a935c3a-a19f-485e-9d40-47052daa69ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a935c3a-a19f-485e-9d40-47052daa69ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91d130eb-0269-45fd-8a44-df3554db9729' class='xr-var-data-in' type='checkbox'><label for='data-91d130eb-0269-45fd-8a44-df3554db9729' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at thickness/tracer points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0577c5a9-a91b-42a4-a00d-f5cba68c8b88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0577c5a9-a91b-42a4-a00d-f5cba68c8b88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62dadfb0-4b75-42b1-9c26-d0ac2e559be3' class='xr-var-data-in' type='checkbox'><label for='data-62dadfb0-4b75-42b1-9c26-d0ac2e559be3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f06bbc29-5abc-494a-98e1-e11d77dcac74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f06bbc29-5abc-494a-98e1-e11d77dcac74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f8c9519-e42f-43df-9afe-4dd32135bbd1' class='xr-var-data-in' type='checkbox'><label for='data-1f8c9519-e42f-43df-9afe-4dd32135bbd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bf5fda4b-e6d7-4054-9e55-44a42c67fae9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf5fda4b-e6d7-4054-9e55-44a42c67fae9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fb5cffc-bb75-4706-8f85-55b4dfa83f4d' class='xr-var-data-in' type='checkbox'><label for='data-5fb5cffc-bb75-4706-8f85-55b4dfa83f4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-52d996f3-2b9b-42b2-97cd-1cd89dd5a633' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52d996f3-2b9b-42b2-97cd-1cd89dd5a633' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0ba833b-46f5-4512-9f9e-ace6b3531987' class='xr-var-data-in' type='checkbox'><label for='data-c0ba833b-46f5-4512-9f9e-ace6b3531987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-edd54dbb-7bcd-4a74-9204-733754a7696f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edd54dbb-7bcd-4a74-9204-733754a7696f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ce2e74a-c8f4-4bd0-af58-025e29a25f7f' class='xr-var-data-in' type='checkbox'><label for='data-7ce2e74a-c8f4-4bd0-af58-025e29a25f7f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1c78f3db-908b-479a-84b1-f463b491a541' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c78f3db-908b-479a-84b1-f463b491a541' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2754089d-5331-40c0-8fc1-affe56fa9f8f' class='xr-var-data-in' type='checkbox'><label for='data-2754089d-5331-40c0-8fc1-affe56fa9f8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of corner (Bu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-14c09140-1a00-49e1-a2e2-5ca92c17f426' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14c09140-1a00-49e1-a2e2-5ca92c17f426' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba371b95-6f08-48c0-b750-65d64bad17b1' class='xr-var-data-in' type='checkbox'><label for='data-ba371b95-6f08-48c0-b750-65d64bad17b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-90b366b0-d502-4dff-ae9f-ff3a3d31e56a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90b366b0-d502-4dff-ae9f-ff3a3d31e56a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-441866bc-1a62-40c3-be92-6e02c0e3cf1a' class='xr-var-data-in' type='checkbox'><label for='data-441866bc-1a62-40c3-be92-6e02c0e3cf1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hfgeou</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5330f879-e7eb-419c-b29f-d0ab650514e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5330f879-e7eb-419c-b29f-d0ab650514e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48a5d70c-e641-4e91-b10a-87a1458d857a' class='xr-var-data-in' type='checkbox'><label for='data-48a5d70c-e641-4e91-b10a-87a1458d857a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Upward geothermal heat flux at sea floor</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>upward_geothermal_heat_flux_at_sea_floor</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftof</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1a27bd2a-0861-46c4-ab9e-ec89a06e9e23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a27bd2a-0861-46c4-ab9e-ec89a06e9e23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baf572f1-d8f7-4832-a21e-68f78e19140e' class='xr-var-data-in' type='checkbox'><label for='data-baf572f1-d8f7-4832-a21e-68f78e19140e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Area Fraction</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: point</dd><dt><span>standard_name :</span></dt><dd>SeaAreaFraction</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7f26dba8-2711-464d-8a0d-25249297eb4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f26dba8-2711-464d-8a0d-25249297eb4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-163f5a14-2e09-495c-8f49-eb8f17eee045' class='xr-var-data-in' type='checkbox'><label for='data-163f5a14-2e09-495c-8f49-eb8f17eee045' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at tracer points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-94d2d0bb-2aaf-4d18-9a45-137e7bbc9c92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94d2d0bb-2aaf-4d18-9a45-137e7bbc9c92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35d2a6e5-addb-4645-ae12-86cc1f39ac1e' class='xr-var-data-in' type='checkbox'><label for='data-35d2a6e5-addb-4645-ae12-86cc1f39ac1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-500cb3e1-46dd-4091-9ccb-e50375a4b78c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-500cb3e1-46dd-4091-9ccb-e50375a4b78c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76a6a5fa-0917-4381-ab0c-83bb4939f690' class='xr-var-data-in' type='checkbox'><label for='data-76a6a5fa-0917-4381-ab0c-83bb4939f690' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fb717410-2ff4-42a4-97ec-7592c51901d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb717410-2ff4-42a4-97ec-7592c51901d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6188432c-b590-4b38-9292-5f9ce4afa6b6' class='xr-var-data-in' type='checkbox'><label for='data-6188432c-b590-4b38-9292-5f9ce4afa6b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zeta</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-afd65a47-9279-4f8b-9b6f-d9847f516a5c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-afd65a47-9279-4f8b-9b6f-d9847f516a5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e23d5799-2795-4e59-9623-db4e1f6ff4d1' class='xr-var-data-in' type='checkbox'><label for='data-e23d5799-2795-4e59-9623-db4e1f6ff4d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1555200 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7814c460-e939-4be0-827e-f1116027c6f9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7814c460-e939-4be0-827e-f1116027c6f9' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -1511,7 +1515,7 @@
        "    zeta          (yq, xq) float32 ..."
       ]
      },
-     "execution_count": 20,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1528,7 +1532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1539,16 +1543,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.TRIPOLAR_REGULAR_WITH_LAND: 4>)"
+       "Filter(filter_scale=10, dx_min=1, filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=11, grid_type=<GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND: 6>)"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1562,8 +1566,8 @@
     "    filter_scale=factor,\n",
     "    dx_min=dx_min,\n",
     "    filter_shape=filter_shape,\n",
-    "    grid_type=gcm_filters.GridType.REGULAR_WITH_LAND,\n",
-    "    grid_vars={'wet_mask': wet_mask}\n",
+    "    grid_type=gcm_filters.GridType.TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
     ")\n",
     "filter_regular_with_land\n",
     "\n",
@@ -1571,36 +1575,36 @@
     "    filter_scale=factor,\n",
     "    dx_min=1,\n",
     "    filter_shape=filter_shape,\n",
-    "    grid_type=gcm_filters.GridType.TRIPOLAR_REGULAR_WITH_LAND,\n",
-    "    grid_vars={'wet_mask': wet_mask}\n",
+    "    grid_type=gcm_filters.GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND,\n",
+    "    grid_vars={'area': area, 'wet_mask': wet_mask}\n",
     ")\n",
     "filter_tripolar_regular_with_land"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 363 ms, sys: 24.8 ms, total: 388 ms\n",
-      "Wall time: 391 ms\n",
-      "CPU times: user 421 ms, sys: 24 ms, total: 444 ms\n",
-      "Wall time: 446 ms\n"
+      "CPU times: user 395 ms, sys: 26.4 ms, total: 421 ms\n",
+      "Wall time: 496 ms\n",
+      "CPU times: user 417 ms, sys: 24.2 ms, total: 441 ms\n",
+      "Wall time: 482 ms\n"
      ]
     }
    ],
    "source": [
-    "%time zeta_filtered_regular_with_land = filter_regular_with_land.apply(ds2['zeta'] * area, dims=['yq', 'xq'])/area\n",
-    "%time zeta_filtered_tripolar_regular_with_land = filter_tripolar_regular_with_land.apply(ds2['zeta'] * area, dims=['yq', 'xq'])/area"
+    "%time zeta_filtered_regular_with_land = filter_regular_with_land.apply(ds2['zeta'], dims=['yq', 'xq'])\n",
+    "%time zeta_filtered_tripolar_regular_with_land = filter_tripolar_regular_with_land.apply(ds2['zeta'], dims=['yq', 'xq'])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1626,7 +1630,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -1641,9 +1645,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1296x432 with 8 Axes>"
+       "<Figure size 1800x432 with 8 Axes>"
       ]
      },
      "metadata": {
@@ -1658,7 +1662,7 @@
     "zeta = ds2['zeta'].assign_coords({'geolat_c': ds2['geolat_c'], 'geolon_c': ds2['geolon_c']})\n",
     "\n",
     "grid1 = plt.GridSpec(1, 4, wspace=0.1, hspace=0.1)\n",
-    "fig = plt.figure(figsize=[18,6])\n",
+    "fig = plt.figure(figsize=[25,6])\n",
     "\n",
     "max_z = 0.4e-5\n",
     "subplot_kws=dict(projection=ccrs.NorthPolarStereo(central_longitude=-30.0),facecolor='grey')\n",
@@ -1669,11 +1673,11 @@
     "\n",
     "ax = fig.add_subplot(grid1[0, 1], projection=ccrs.NorthPolarStereo(central_longitude=-30.0),facecolor='grey')\n",
     "_ = plot_map(ax, zeta_reg, vmin=-max_z, vmax=max_z, \n",
-    "                   lon='geolon_c', lat='geolat_c', cmap='RdBu_r', title=r'REGULAR_WITH_LAND')\n",
+    "                   lon='geolon_c', lat='geolat_c', cmap='RdBu_r', title=r'TRANSFORMED_TO_REGULAR_WITH_LAND')\n",
     "\n",
     "ax = fig.add_subplot(grid1[0, 2], projection=ccrs.NorthPolarStereo(central_longitude=-30.0),facecolor='grey')\n",
     "_ = plot_map(ax, zeta_tripole, vmin=-max_z, vmax=max_z, \n",
-    "                   lon='geolon_c', lat='geolat_c', cmap='RdBu_r', title=r'TRIPOLAR_REGULAR_WITH_LAND')\n",
+    "                   lon='geolon_c', lat='geolat_c', cmap='RdBu_r', title=r'TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND')\n",
     "\n",
     "ax = fig.add_subplot(grid1[0, 3], projection=ccrs.NorthPolarStereo(central_longitude=-30.0),facecolor='grey')\n",
     "_ = plot_map(ax, zeta_tripole - zeta_reg, vmin=-max_z*0.1, vmax=max_z*0.1, \n",
@@ -1684,7 +1688,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The two methods give different answers along the horizontal line (passing through the pole), which is the longitudinal boundary of the model grid. This is because the `TRIPOLAR_REGULAR_WITH_LAND` Laplacian correctly handles tripolar exchanges, but the `REGULAR_WITH_LAND` Laplacian does not."
+    "The two methods give different answers along the horizontal line (passing through the pole), which is the longitudinal boundary of the model grid. This is because the `TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND` Laplacian correctly handles tripolar exchanges, but the `TRANSFORMED_TO_REGULAR_WITH_LAND` Laplacian does not."
    ]
   },
   {
diff --git a/docs/tutorial_vector_laplacian.ipynb b/docs/tutorial_vector_laplacian.ipynb
index ea27504..f925147 100644
--- a/docs/tutorial_vector_laplacian.ipynb
+++ b/docs/tutorial_vector_laplacian.ipynb
@@ -36,11 +36,13 @@
      "data": {
       "text/plain": [
        "[<GridType.REGULAR: 1>,\n",
-       " <GridType.REGULAR_WITH_LAND: 2>,\n",
-       " <GridType.IRREGULAR_WITH_LAND: 3>,\n",
-       " <GridType.TRIPOLAR_REGULAR_WITH_LAND: 4>,\n",
-       " <GridType.TRIPOLAR_POP_WITH_LAND: 5>,\n",
-       " <GridType.VECTOR_C_GRID: 6>]"
+       " <GridType.TRANSFORMED_TO_REGULAR: 2>,\n",
+       " <GridType.REGULAR_WITH_LAND: 3>,\n",
+       " <GridType.TRANSFORMED_TO_REGULAR_WITH_LAND: 4>,\n",
+       " <GridType.IRREGULAR_WITH_LAND: 5>,\n",
+       " <GridType.TRIPOLAR_TRANSFORMED_TO_REGULAR_WITH_LAND: 6>,\n",
+       " <GridType.TRIPOLAR_POP_WITH_LAND: 7>,\n",
+       " <GridType.VECTOR_C_GRID: 8>]"
       ]
      },
      "execution_count": 2,
@@ -459,14 +461,14 @@
        "    area_u    (yh, xq) float32 ...\n",
        "    area_v    (yq, xh) float32 ...\n",
        "    dxBu      (yq, xq) float64 ...\n",
-       "    dyBu      (yq, xq) float64 ...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3adb515c-4a21-4a6d-b8c8-d11040453d6e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3adb515c-4a21-4a6d-b8c8-d11040453d6e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 31</li><li><span class='xr-has-index'>xh</span>: 3600</li><li><span class='xr-has-index'>xq</span>: 3600</li><li><span class='xr-has-index'>yh</span>: 2400</li><li><span class='xr-has-index'>yq</span>: 2400</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5661d8d3-b3b9-4bc9-9cea-1a9a85cdb437' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5661d8d3-b3b9-4bc9-9cea-1a9a85cdb437' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.1 -110.0</div><input id='attrs-71127bdb-ec85-494e-a622-64c5fba79bd4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-71127bdb-ec85-494e-a622-64c5fba79bd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0c20258-2754-4f83-a28a-414a134cba9d' class='xr-var-data-in' type='checkbox'><label for='data-d0c20258-2754-4f83-a28a-414a134cba9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-109.900002, -109.800003, -109.699997, ..., -110.199997, -110.099998,\n",
-       "       -110.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-e13f6de2-4dda-4b96-ab06-8785f8b9f7a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e13f6de2-4dda-4b96-ab06-8785f8b9f7a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3a9d67f-49b0-4c1d-93f6-a459f05f8600' class='xr-var-data-in' type='checkbox'><label for='data-a3a9d67f-49b0-4c1d-93f6-a459f05f8600' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cartesian_axis :</span></dt><dd>N</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.666e+03 7.666e+03 ... 7.696e+03</div><input id='attrs-d8fc47dd-cb5c-4d2c-adcf-c4332362a550' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8fc47dd-cb5c-4d2c-adcf-c4332362a550' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1bd7dcb-b7fa-4b24-afb3-1896c9725cd4' class='xr-var-data-in' type='checkbox'><label for='data-f1bd7dcb-b7fa-4b24-afb3-1896c9725cd4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>NOLEAP</dd><dt><span>calendar :</span></dt><dd>NOLEAP</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([7665.5, 7666.5, 7667.5, 7668.5, 7669.5, 7670.5, 7671.5, 7672.5, 7673.5,\n",
+       "    dyBu      (yq, xq) float64 ...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-81bcb551-ce5c-4ae7-bfa5-27f0d8e5864f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-81bcb551-ce5c-4ae7-bfa5-27f0d8e5864f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 31</li><li><span class='xr-has-index'>xh</span>: 3600</li><li><span class='xr-has-index'>xq</span>: 3600</li><li><span class='xr-has-index'>yh</span>: 2400</li><li><span class='xr-has-index'>yq</span>: 2400</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e24f1d46-ff9d-45ae-a004-77f1fbb4f649' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e24f1d46-ff9d-45ae-a004-77f1fbb4f649' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.1 -110.0</div><input id='attrs-3fbeee83-6047-4670-9582-17133805ae6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fbeee83-6047-4670-9582-17133805ae6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab5909d2-d875-465d-bfea-ec5fec7e1286' class='xr-var-data-in' type='checkbox'><label for='data-ab5909d2-d875-465d-bfea-ec5fec7e1286' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-109.900002, -109.800003, -109.699997, ..., -110.199997, -110.099998,\n",
+       "       -110.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-d585fbd3-96a9-419e-adb8-0279bba655d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d585fbd3-96a9-419e-adb8-0279bba655d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25551888-c188-4348-9676-83b89a73dd07' class='xr-var-data-in' type='checkbox'><label for='data-25551888-c188-4348-9676-83b89a73dd07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cartesian_axis :</span></dt><dd>N</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.666e+03 7.666e+03 ... 7.696e+03</div><input id='attrs-6c730f0a-d0e7-4c0b-90a6-ad9d0736e9d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c730f0a-d0e7-4c0b-90a6-ad9d0736e9d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d926f488-5dbd-4281-9867-d2cb076a22ec' class='xr-var-data-in' type='checkbox'><label for='data-d926f488-5dbd-4281-9867-d2cb076a22ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>NOLEAP</dd><dt><span>calendar :</span></dt><dd>NOLEAP</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([7665.5, 7666.5, 7667.5, 7668.5, 7669.5, 7670.5, 7671.5, 7672.5, 7673.5,\n",
        "       7674.5, 7675.5, 7676.5, 7677.5, 7678.5, 7679.5, 7680.5, 7681.5, 7682.5,\n",
        "       7683.5, 7684.5, 7685.5, 7686.5, 7687.5, 7688.5, 7689.5, 7690.5, 7691.5,\n",
-       "       7692.5, 7693.5, 7694.5, 7695.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.2 -110.1</div><input id='attrs-dcaa73cc-1f47-473e-b4e3-b083d26d9ae1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcaa73cc-1f47-473e-b4e3-b083d26d9ae1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfbe38ef-68e2-4510-949d-4121e6531cc3' class='xr-var-data-in' type='checkbox'><label for='data-dfbe38ef-68e2-4510-949d-4121e6531cc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-109.949997, -109.849998, -109.75    , ..., -110.25    , -110.150002,\n",
-       "       -110.050003])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.47 -78.43 ... 89.92 89.97</div><input id='attrs-4be7daa3-50a1-4f98-b69d-93a599f99120' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4be7daa3-50a1-4f98-b69d-93a599f99120' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d77fb15-493c-4623-aa60-0af5ad7bd40c' class='xr-var-data-in' type='checkbox'><label for='data-7d77fb15-493c-4623-aa60-0af5ad7bd40c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-78.472862, -78.430603, -78.388336, ...,  89.876877,  89.92424 ,\n",
-       "        89.967903])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.45 -78.41 -78.37 ... 89.95 90.0</div><input id='attrs-74a65dc8-d603-4606-bcd7-84e5d75ea4ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74a65dc8-d603-4606-bcd7-84e5d75ea4ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2eecc14c-62bf-4c5b-8726-f7ba642b980d' class='xr-var-data-in' type='checkbox'><label for='data-2eecc14c-62bf-4c5b-8726-f7ba642b980d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-78.451729, -78.409462, -78.367203, ...,  89.902946,  89.951477,\n",
-       "        89.999992])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-35448127-6868-4350-9762-9f5f0e79af9d' class='xr-section-summary-in' type='checkbox'  ><label for='section-35448127-6868-4350-9762-9f5f0e79af9d' class='xr-section-summary' >Data variables: <span>(23)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>SSU</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-80d007d1-9429-4d23-b927-d19c0bed0c2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80d007d1-9429-4d23-b927-d19c0bed0c2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1bfe2314-004e-433e-9ce5-4d322da233f7' class='xr-var-data-in' type='checkbox'><label for='data-1bfe2314-004e-433e-9ce5-4d322da233f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Zonal Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yh:mean xq:point time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SSV</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-220a253b-b586-437b-967b-28a628b9275a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-220a253b-b586-437b-967b-28a628b9275a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74dbc929-6334-4977-9adb-81af23c4f5ca' class='xr-var-data-in' type='checkbox'><label for='data-74dbc929-6334-4977-9adb-81af23c4f5ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Meridional Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yq:point xh:mean time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a397e0e2-a16f-4829-ba3d-a62652654ea4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a397e0e2-a16f-4829-ba3d-a62652654ea4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ef3442b-5bf6-4da7-9f33-fd766023312c' class='xr-var-data-in' type='checkbox'><label for='data-9ef3442b-5bf6-4da7-9f33-fd766023312c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-26010071-e296-4c3c-baba-0732872bb398' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26010071-e296-4c3c-baba-0732872bb398' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f6c577c-c8cc-4033-a0f2-1f021cbfc9e9' class='xr-var-data-in' type='checkbox'><label for='data-9f6c577c-c8cc-4033-a0f2-1f021cbfc9e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-33e8ab83-f2c2-4eae-b715-e25cfcd1e80e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33e8ab83-f2c2-4eae-b715-e25cfcd1e80e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f38f1d23-182c-4585-8115-a5a25105d115' class='xr-var-data-in' type='checkbox'><label for='data-f38f1d23-182c-4585-8115-a5a25105d115' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-468a9145-d697-4f45-b842-09bc6b4ce31b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-468a9145-d697-4f45-b842-09bc6b4ce31b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-caaebccb-926e-4bf5-bc7c-de150e331d36' class='xr-var-data-in' type='checkbox'><label for='data-caaebccb-926e-4bf5-bc7c-de150e331d36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fa10ee86-58ec-4f77-a675-a2bfd2f8fddc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa10ee86-58ec-4f77-a675-a2bfd2f8fddc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c77fc498-4627-4b72-abac-dfe9ede37e64' class='xr-var-data-in' type='checkbox'><label for='data-c77fc498-4627-4b72-abac-dfe9ede37e64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-73eda312-f7fa-4673-967e-fba08d3f4ab4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73eda312-f7fa-4673-967e-fba08d3f4ab4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f89c586d-4be8-410e-8157-239a8ff51bfd' class='xr-var-data-in' type='checkbox'><label for='data-f89c586d-4be8-410e-8157-239a8ff51bfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxT</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-471e8f11-418f-4fc4-8ee7-795cfd5d20e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-471e8f11-418f-4fc4-8ee7-795cfd5d20e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e73b05e-924c-4400-944e-3c3d033243cc' class='xr-var-data-in' type='checkbox'><label for='data-5e73b05e-924c-4400-944e-3c3d033243cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyT</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6830549b-a68f-4c90-9cf0-addf0c6ddaa4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6830549b-a68f-4c90-9cf0-addf0c6ddaa4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3c5ff81-ea26-45d7-adda-993b1724196d' class='xr-var-data-in' type='checkbox'><label for='data-a3c5ff81-ea26-45d7-adda-993b1724196d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6a62250c-f5d7-44bd-adc2-b64171f2e237' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a62250c-f5d7-44bd-adc2-b64171f2e237' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03ece00f-1034-403a-957e-19dedcbf64b7' class='xr-var-data-in' type='checkbox'><label for='data-03ece00f-1034-403a-957e-19dedcbf64b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b6055527-9b73-4400-be24-dea4b7ebec9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6055527-9b73-4400-be24-dea4b7ebec9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8577a5e6-6cae-4f9c-ae5b-b67393a7137e' class='xr-var-data-in' type='checkbox'><label for='data-8577a5e6-6cae-4f9c-ae5b-b67393a7137e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6be8bc77-805a-4426-af32-956f2eeadc4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6be8bc77-805a-4426-af32-956f2eeadc4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2106d88b-5df0-46d3-a010-44fa164b8938' class='xr-var-data-in' type='checkbox'><label for='data-2106d88b-5df0-46d3-a010-44fa164b8938' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c7ff0ca-0c01-49ac-9e6a-5d8921dbed56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c7ff0ca-0c01-49ac-9e6a-5d8921dbed56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef10a1af-0cae-425f-8a92-f7674f2dd291' class='xr-var-data-in' type='checkbox'><label for='data-ef10a1af-0cae-425f-8a92-f7674f2dd291' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-85401279-7c8a-4b24-97b8-360f2c4bb782' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85401279-7c8a-4b24-97b8-360f2c4bb782' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb326986-2a4c-490a-96e2-fda9a4c762fb' class='xr-var-data-in' type='checkbox'><label for='data-bb326986-2a4c-490a-96e2-fda9a4c762fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at tracer points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>cell_measures :</span></dt><dd>area: area_t</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-87ff60a8-5875-4120-8a3f-100e32c33573' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87ff60a8-5875-4120-8a3f-100e32c33573' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0084ad95-7d64-4ee9-877b-9c2dd0f066a1' class='xr-var-data-in' type='checkbox'><label for='data-0084ad95-7d64-4ee9-877b-9c2dd0f066a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-adc29d53-2ed4-4bd9-b793-a18dab1e1f82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-adc29d53-2ed4-4bd9-b793-a18dab1e1f82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3666fe88-d51d-4803-a10b-197e358e4da1' class='xr-var-data-in' type='checkbox'><label for='data-3666fe88-d51d-4803-a10b-197e358e4da1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bd2d73f1-f839-4584-ae2f-7644b04ed98c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd2d73f1-f839-4584-ae2f-7644b04ed98c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e28acd7-6aab-4054-b1db-f3e0230dea6a' class='xr-var-data-in' type='checkbox'><label for='data-3e28acd7-6aab-4054-b1db-f3e0230dea6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_t</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8b99eb8d-ccd6-4ca7-81ef-bb388cde6a11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b99eb8d-ccd6-4ca7-81ef-bb388cde6a11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b73f14d6-ed8e-4781-bb60-c761c81a7067' class='xr-var-data-in' type='checkbox'><label for='data-b73f14d6-ed8e-4781-bb60-c761c81a7067' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface area of tracer (T) cells</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b74d7f79-2c46-45a5-b545-50bdb20a8460' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b74d7f79-2c46-45a5-b545-50bdb20a8460' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-223b9ee5-a023-406b-87ab-dbffa66f897b' class='xr-var-data-in' type='checkbox'><label for='data-223b9ee5-a023-406b-87ab-dbffa66f897b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface area of x-direction flow (U) cells</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-50f94a84-56c5-486c-81f0-a92e1395b6d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50f94a84-56c5-486c-81f0-a92e1395b6d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce7a139d-217d-4724-b987-2081c94ec515' class='xr-var-data-in' type='checkbox'><label for='data-ce7a139d-217d-4724-b987-2081c94ec515' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface area of y-direction flow (V) cells</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxBu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ed507975-0c85-442b-8b8b-1f36c3353fec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed507975-0c85-442b-8b8b-1f36c3353fec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65c95f73-d74b-45d8-a77e-741f2976f246' class='xr-var-data-in' type='checkbox'><label for='data-65c95f73-d74b-45d8-a77e-741f2976f246' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Zonal grid spacing at q points</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyBu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-64a7db78-e4e4-4dbb-aa62-f4d25e598444' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64a7db78-e4e4-4dbb-aa62-f4d25e598444' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8139e0a-ab24-476a-a732-6f3aaff99401' class='xr-var-data-in' type='checkbox'><label for='data-e8139e0a-ab24-476a-a732-6f3aaff99401' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Meridional grid spacing at q points</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3c9857af-1035-484c-b30f-ae09639cf4ff' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3c9857af-1035-484c-b30f-ae09639cf4ff' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "       7692.5, 7693.5, 7694.5, 7695.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.2 -110.1</div><input id='attrs-844fdfeb-08ab-4b77-b4e3-668fce4675af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-844fdfeb-08ab-4b77-b4e3-668fce4675af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13b3e891-1ee4-4dbb-9cfa-f8fd8e3e40b3' class='xr-var-data-in' type='checkbox'><label for='data-13b3e891-1ee4-4dbb-9cfa-f8fd8e3e40b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-109.949997, -109.849998, -109.75    , ..., -110.25    , -110.150002,\n",
+       "       -110.050003])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.47 -78.43 ... 89.92 89.97</div><input id='attrs-363d7457-255f-491b-b75a-7f834864bc98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-363d7457-255f-491b-b75a-7f834864bc98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dea4c198-acbf-4deb-838d-38005363ece2' class='xr-var-data-in' type='checkbox'><label for='data-dea4c198-acbf-4deb-838d-38005363ece2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-78.472862, -78.430603, -78.388336, ...,  89.876877,  89.92424 ,\n",
+       "        89.967903])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.45 -78.41 -78.37 ... 89.95 90.0</div><input id='attrs-9f94888d-3e98-47c1-9cee-071c7f2c4258' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f94888d-3e98-47c1-9cee-071c7f2c4258' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9542d713-9ccb-45ed-8c21-9fa82834fa98' class='xr-var-data-in' type='checkbox'><label for='data-9542d713-9ccb-45ed-8c21-9fa82834fa98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-78.451729, -78.409462, -78.367203, ...,  89.902946,  89.951477,\n",
+       "        89.999992])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0aa77f03-4a3c-415b-baf3-fbca3784b67d' class='xr-section-summary-in' type='checkbox'  ><label for='section-0aa77f03-4a3c-415b-baf3-fbca3784b67d' class='xr-section-summary' >Data variables: <span>(23)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>SSU</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-16a13062-b84e-440c-b493-10e7786d9281' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16a13062-b84e-440c-b493-10e7786d9281' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d14d7f4-405c-4697-b1b9-863fe45193b3' class='xr-var-data-in' type='checkbox'><label for='data-4d14d7f4-405c-4697-b1b9-863fe45193b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Zonal Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yh:mean xq:point time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SSV</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4196b576-ab04-41cb-b5dd-5aa92af27742' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4196b576-ab04-41cb-b5dd-5aa92af27742' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07166bc9-2c88-4193-a01b-e1eecb1d29b2' class='xr-var-data-in' type='checkbox'><label for='data-07166bc9-2c88-4193-a01b-e1eecb1d29b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Meridional Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yq:point xh:mean time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9e707b98-022b-4ff1-9532-3763f462060e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e707b98-022b-4ff1-9532-3763f462060e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92655946-5e60-4043-bdf8-3482398f0f4c' class='xr-var-data-in' type='checkbox'><label for='data-92655946-5e60-4043-bdf8-3482398f0f4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-52d30d33-f600-43ba-91d4-59fff8654acc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52d30d33-f600-43ba-91d4-59fff8654acc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4aec756b-8197-4d00-96c4-92e8c7d9e59f' class='xr-var-data-in' type='checkbox'><label for='data-4aec756b-8197-4d00-96c4-92e8c7d9e59f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolon_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dafa4f7d-8d88-4a17-ac60-5fd4fc2a966f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dafa4f7d-8d88-4a17-ac60-5fd4fc2a966f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3d85f19-27ee-4811-8874-8c5c86ae4e94' class='xr-var-data-in' type='checkbox'><label for='data-d3d85f19-27ee-4811-8874-8c5c86ae4e94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1681dc7b-879e-43b5-8857-9af77ef7e16a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1681dc7b-879e-43b5-8857-9af77ef7e16a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8699f4e1-105b-4ee3-bcc3-7a8237fc739c' class='xr-var-data-in' type='checkbox'><label for='data-8699f4e1-105b-4ee3-bcc3-7a8237fc739c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of tracer (T) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c909c049-334f-4532-8b3f-7dc1180d2073' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c909c049-334f-4532-8b3f-7dc1180d2073' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f0d3b3e-078f-4a17-be3a-f01106b30876' class='xr-var-data-in' type='checkbox'><label for='data-8f0d3b3e-078f-4a17-be3a-f01106b30876' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geolat_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f4d93079-ae8b-4149-ad4d-9163b5d8227b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4d93079-ae8b-4149-ad4d-9163b5d8227b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-effbaaff-43ba-4e56-bfc9-523a1e37ed76' class='xr-var-data-in' type='checkbox'><label for='data-effbaaff-43ba-4e56-bfc9-523a1e37ed76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxT</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c45f066b-e086-4a57-928e-27e86550bf0f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c45f066b-e086-4a57-928e-27e86550bf0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff00bc09-efc2-482f-989d-63df0b734547' class='xr-var-data-in' type='checkbox'><label for='data-ff00bc09-efc2-482f-989d-63df0b734547' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyT</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-56301d14-61aa-42b4-994f-00a3d3348568' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56301d14-61aa-42b4-994f-00a3d3348568' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67a19f27-edff-4720-ba02-30b7258a23bf' class='xr-var-data-in' type='checkbox'><label for='data-67a19f27-edff-4720-ba02-30b7258a23bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f9157ac1-8e9f-4d9d-94eb-ac151e5e9f08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9157ac1-8e9f-4d9d-94eb-ac151e5e9f08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd73f2b1-6797-4be0-9498-861f8349a203' class='xr-var-data-in' type='checkbox'><label for='data-dd73f2b1-6797-4be0-9498-861f8349a203' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCu</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3ac1487c-6b84-465f-8621-07a8d12d46dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ac1487c-6b84-465f-8621-07a8d12d46dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fbf30d2-f32b-4a16-8357-4dd4c432e359' class='xr-var-data-in' type='checkbox'><label for='data-8fbf30d2-f32b-4a16-8357-4dd4c432e359' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at u points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3ef5d730-debb-4d05-a4dc-71091014b44c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ef5d730-debb-4d05-a4dc-71091014b44c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea5b9b86-669c-4a01-8cdf-8e10a5d526a4' class='xr-var-data-in' type='checkbox'><label for='data-ea5b9b86-669c-4a01-8cdf-8e10a5d526a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(x) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyCv</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-222876e2-1bb8-46f8-9287-026a7f0e149a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-222876e2-1bb8-46f8-9287-026a7f0e149a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e9e03c2-c4de-4875-aac4-87e64960069b' class='xr-var-data-in' type='checkbox'><label for='data-0e9e03c2-c4de-4875-aac4-87e64960069b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delta(y) at v points (meter)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e6ed0a53-cf1b-41ae-8150-f7a5d723a18f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6ed0a53-cf1b-41ae-8150-f7a5d723a18f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1e9019c-e25b-4343-8661-0f9c615e4df9' class='xr-var-data-in' type='checkbox'><label for='data-f1e9019c-e25b-4343-8661-0f9c615e4df9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at tracer points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>cell_measures :</span></dt><dd>area: area_t</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_c</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b9b59b85-5c97-480f-8a21-27b884e094dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9b59b85-5c97-480f-8a21-27b884e094dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef9a7d05-8e1d-49f5-9488-d6ecf107c587' class='xr-var-data-in' type='checkbox'><label for='data-ef9a7d05-8e1d-49f5-9488-d6ecf107c587' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at corner (Bu) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-499b4aa2-a3a2-43c4-b928-1c0987485570' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-499b4aa2-a3a2-43c4-b928-1c0987485570' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2329f7d-f9d6-4ff6-b480-6fb57b5d9ec9' class='xr-var-data-in' type='checkbox'><label for='data-f2329f7d-f9d6-4ff6-b480-6fb57b5d9ec9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at zonal velocity (Cu) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wet_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-39234f48-aa88-4180-abcc-8c9effa1372a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39234f48-aa88-4180-abcc-8c9effa1372a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc2d8d0a-1d0f-4a6a-90c5-643596e76d80' class='xr-var-data-in' type='checkbox'><label for='data-dc2d8d0a-1d0f-4a6a-90c5-643596e76d80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>0 if land, 1 if ocean at meridional velocity (Cv) points</dd><dt><span>units :</span></dt><dd>none</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_t</span></div><div class='xr-var-dims'>(yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d7c3c0b1-7019-4bfa-8d0a-f5f0e8e14e5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7c3c0b1-7019-4bfa-8d0a-f5f0e8e14e5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb788888-c8a0-4d05-89c9-0c09f4bec9f9' class='xr-var-data-in' type='checkbox'><label for='data-bb788888-c8a0-4d05-89c9-0c09f4bec9f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface area of tracer (T) cells</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xh:sum time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_u</span></div><div class='xr-var-dims'>(yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5eba3db3-5659-4e9e-8c0b-460a69c713de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5eba3db3-5659-4e9e-8c0b-460a69c713de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db47235b-58a0-4f0e-88ab-955c0d444193' class='xr-var-data-in' type='checkbox'><label for='data-db47235b-58a0-4f0e-88ab-955c0d444193' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface area of x-direction flow (U) cells</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yh:sum xq:sum time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_v</span></div><div class='xr-var-dims'>(yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-265224a1-6a1b-4819-a934-0146530caaeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-265224a1-6a1b-4819-a934-0146530caaeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48ad5620-a109-4077-a57a-dd8088833d7a' class='xr-var-data-in' type='checkbox'><label for='data-48ad5620-a109-4077-a57a-dd8088833d7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface area of y-direction flow (V) cells</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area:sum yq:sum xh:sum time: point</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxBu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bae11a43-b143-44ef-be58-6b805edf32cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bae11a43-b143-44ef-be58-6b805edf32cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eb20876-9aa2-448b-9fce-cf44216e560d' class='xr-var-data-in' type='checkbox'><label for='data-5eb20876-9aa2-448b-9fce-cf44216e560d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Zonal grid spacing at q points</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyBu</span></div><div class='xr-var-dims'>(yq, xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1748af08-09c8-4723-bb7d-e53ea07c5352' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1748af08-09c8-4723-bb7d-e53ea07c5352' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a65b2af6-9147-4356-934c-748a3c50cdb6' class='xr-var-data-in' type='checkbox'><label for='data-a65b2af6-9147-4356-934c-748a3c50cdb6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Meridional grid spacing at q points</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[8640000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a084b98-9a32-4f8c-8e84-c5f417c58c0d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a084b98-9a32-4f8c-8e84-c5f417c58c0d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -528,7 +530,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -550,7 +552,7 @@
        " 'kappa_aniso']"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -568,7 +570,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -599,7 +601,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -608,7 +610,7 @@
        "array(2245.78271484)"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -621,7 +623,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -630,7 +632,7 @@
        "array(11260.51171875)"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -652,7 +654,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -668,7 +670,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -692,16 +694,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=100000, dx_min=array(2245.78271484), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=49, grid_type=<GridType.VECTOR_C_GRID: 6>)"
+       "Filter(filter_scale=100000, dx_min=array(2245.78271484), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=49, grid_type=<GridType.VECTOR_C_GRID: 8>)"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -740,7 +742,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -753,7 +755,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -1120,9 +1122,9 @@
        "    units:          m s-1\n",
        "    cell_methods:   yh:mean xq:point time: mean\n",
        "    time_avg_info:  average_T1,average_T2,average_DT\n",
-       "    interp_method:  none</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>yh</span>: 2400</li><li><span class='xr-has-index'>xh</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3aaee31a-ae1f-4e7e-9a0c-86a6ead2b7de' class='xr-array-in' type='checkbox' checked><label for='section-3aaee31a-ae1f-4e7e-9a0c-86a6ead2b7de' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[8640000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-d9dfbf06-9f55-4a45-82c5-119e0f818d3f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9dfbf06-9f55-4a45-82c5-119e0f818d3f' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.47 -78.43 ... 89.92 89.97</div><input id='attrs-12bd45c6-746c-4bfe-a64e-fbfdbc7f53d1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12bd45c6-746c-4bfe-a64e-fbfdbc7f53d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf43ae80-a257-43f9-a042-416301c40e69' class='xr-var-data-in' type='checkbox'><label for='data-cf43ae80-a257-43f9-a042-416301c40e69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-78.472862, -78.430603, -78.388336, ...,  89.876877,  89.92424 ,\n",
-       "        89.967903])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.2 -110.1</div><input id='attrs-cdddb9fc-ba5d-4048-a202-20fdd4823ddb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cdddb9fc-ba5d-4048-a202-20fdd4823ddb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d93bf6fe-36a7-4f4c-8558-b20e16ac1697' class='xr-var-data-in' type='checkbox'><label for='data-d93bf6fe-36a7-4f4c-8558-b20e16ac1697' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-109.949997, -109.849998, -109.75    , ..., -110.25    , -110.150002,\n",
-       "       -110.050003])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bcf351a3-2789-4e14-862e-5a657ea8abb9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bcf351a3-2789-4e14-862e-5a657ea8abb9' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Zonal Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yh:mean xq:point time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div></li></ul></div></div>"
+       "    interp_method:  none</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>yh</span>: 2400</li><li><span class='xr-has-index'>xh</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6771fad1-3344-4b92-8273-ca22f39b0127' class='xr-array-in' type='checkbox' checked><label for='section-6771fad1-3344-4b92-8273-ca22f39b0127' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[8640000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-869a2198-ee99-4201-add7-8955eb8530cd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-869a2198-ee99-4201-add7-8955eb8530cd' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.47 -78.43 ... 89.92 89.97</div><input id='attrs-e613861a-533a-4cd6-8f07-f4d6c6ab602d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e613861a-533a-4cd6-8f07-f4d6c6ab602d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-992ccbfd-0f27-4b0f-8357-053c008f7dfb' class='xr-var-data-in' type='checkbox'><label for='data-992ccbfd-0f27-4b0f-8357-053c008f7dfb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-78.472862, -78.430603, -78.388336, ...,  89.876877,  89.92424 ,\n",
+       "        89.967903])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.2 -110.1</div><input id='attrs-360de901-70fc-4ad5-9e8c-e57ab2e7c8e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-360de901-70fc-4ad5-9e8c-e57ab2e7c8e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-299f42b5-1e3e-4e3c-8f9b-85733f195468' class='xr-var-data-in' type='checkbox'><label for='data-299f42b5-1e3e-4e3c-8f9b-85733f195468' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-109.949997, -109.849998, -109.75    , ..., -110.25    , -110.150002,\n",
+       "       -110.050003])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c1a0ffc1-5852-4581-b505-12daed46ed48' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c1a0ffc1-5852-4581-b505-12daed46ed48' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Zonal Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yh:mean xq:point time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'u' (yh: 2400, xh: 3600)>\n",
@@ -1138,7 +1140,7 @@
        "    interp_method:  none"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1149,7 +1151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -1516,9 +1518,9 @@
        "    units:          m s-1\n",
        "    cell_methods:   yq:point xh:mean time: mean\n",
        "    time_avg_info:  average_T1,average_T2,average_DT\n",
-       "    interp_method:  none</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'v'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>yh</span>: 2400</li><li><span class='xr-has-index'>xh</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a3536faa-f414-4020-860f-67ee6f47af59' class='xr-array-in' type='checkbox' checked><label for='section-a3536faa-f414-4020-860f-67ee6f47af59' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[8640000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-31ca337f-da06-4bd3-80df-546aad09dc88' class='xr-section-summary-in' type='checkbox'  checked><label for='section-31ca337f-da06-4bd3-80df-546aad09dc88' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.47 -78.43 ... 89.92 89.97</div><input id='attrs-535cd553-8ed3-491b-853f-c942d9565cb3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-535cd553-8ed3-491b-853f-c942d9565cb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b37de2e-9cb1-4257-8d5f-fa6410e4ea29' class='xr-var-data-in' type='checkbox'><label for='data-1b37de2e-9cb1-4257-8d5f-fa6410e4ea29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-78.472862, -78.430603, -78.388336, ...,  89.876877,  89.92424 ,\n",
-       "        89.967903])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.2 -110.1</div><input id='attrs-dd5f64dc-ee6b-4084-8577-39b810165510' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dd5f64dc-ee6b-4084-8577-39b810165510' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ff7b087-4cee-4d5e-a326-bc3211d2d5c0' class='xr-var-data-in' type='checkbox'><label for='data-7ff7b087-4cee-4d5e-a326-bc3211d2d5c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-109.949997, -109.849998, -109.75    , ..., -110.25    , -110.150002,\n",
-       "       -110.050003])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-affb4692-edbd-4cd0-ac4c-402850a90b2a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-affb4692-edbd-4cd0-ac4c-402850a90b2a' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Meridional Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yq:point xh:mean time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div></li></ul></div></div>"
+       "    interp_method:  none</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'v'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>yh</span>: 2400</li><li><span class='xr-has-index'>xh</span>: 3600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-dbfa6544-8fdc-482e-8e50-41af208236ea' class='xr-array-in' type='checkbox' checked><label for='section-dbfa6544-8fdc-482e-8e50-41af208236ea' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[8640000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-6fbc6a20-4273-4cb1-ba3b-3e21e8cb63d1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6fbc6a20-4273-4cb1-ba3b-3e21e8cb63d1' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.47 -78.43 ... 89.92 89.97</div><input id='attrs-3600c713-15fc-491c-b40b-d19ad67f2264' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3600c713-15fc-491c-b40b-d19ad67f2264' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fbb82fb-cdc8-4336-9be1-bebf53023df1' class='xr-var-data-in' type='checkbox'><label for='data-5fbb82fb-cdc8-4336-9be1-bebf53023df1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-78.472862, -78.430603, -78.388336, ...,  89.876877,  89.92424 ,\n",
+       "        89.967903])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-109.9 -109.8 ... -110.2 -110.1</div><input id='attrs-0ce25649-7a2b-4afa-bed5-2f750c5b7971' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ce25649-7a2b-4afa-bed5-2f750c5b7971' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8f52886-e3d1-49ac-8be9-ebbe7169ae85' class='xr-var-data-in' type='checkbox'><label for='data-a8f52886-e3d1-49ac-8be9-ebbe7169ae85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-109.949997, -109.849998, -109.75    , ..., -110.25    , -110.150002,\n",
+       "       -110.050003])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ce5f6364-cafc-4aaf-aa5b-63b8f7312655' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ce5f6364-cafc-4aaf-aa5b-63b8f7312655' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Meridional Velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>yq:point xh:mean time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>interp_method :</span></dt><dd>none</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'v' (yh: 2400, xh: 3600)>\n",
@@ -1534,7 +1536,7 @@
        "    interp_method:  none"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1545,15 +1547,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 25.3 s, sys: 17.3 s, total: 42.6 s\n",
-      "Wall time: 42.8 s\n"
+      "CPU times: user 23.6 s, sys: 16.7 s, total: 40.3 s\n",
+      "Wall time: 40.5 s\n"
      ]
     }
    ],
@@ -1570,7 +1572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1590,7 +1592,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1606,12 +1608,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "To be able to plot unfiltered and filterd using true longitude and latitude, we need to make geolon/geolat coordinates of our xarray.Datasets."
+    "To be able to plot unfiltered and filtered fields using true longitude and latitude, we need to make geolon/geolat coordinates of our xarray.Datasets."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1621,7 +1623,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1631,7 +1633,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1711,12 +1713,12 @@
     "\n",
     "resulting in `kappa_x = kappa_iso + kappa_aniso` and `kappa_y = kappa_iso`. Anisotropy in an arbitrary direction (not aligned with the grid directions) is not yet implemented for `VECTOR_C_GRID`, but could be added mimicking the implementation in MOM6 (following [Smith and McWilliams, 2003](https://www.sciencedirect.com/science/article/pii/S1463500302000161?via%3Dihub)). \n",
     "\n",
-    "To filter with a fixed factor of 10, we need the filter scale to be equal to **ten times $dx_{max}$**, together with $\\kappa_x = dx^2/dx_{max}^2$ and $\\kappa_y = dy^2/dx_{max}^2$, where $dx_{max}$ is the minimum grid spacing in the domain. (See Section 2.6 in [Grooms et al. (2021)](https://www.essoar.org/doi/10.1002/essoar.10506591.1) for more details)."
+    "To filter with a fixed factor of 10, we need the filter scale to be equal to **ten times $dx_{max}$**, together with $\\kappa_x = dx^2/dx_{max}^2$ and $\\kappa_y = dy^2/dx_{max}^2$, where $dx_{max}$ is the minimum grid spacing in the domain. (See the [Filter Theory](https://gcm-filters.readthedocs.io/en/latest/theory.html) or Section 2.6 in [Grooms et al. (2021)](https://www.essoar.org/doi/10.1002/essoar.10506591.1) for more details)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1734,7 +1736,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1744,7 +1746,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1809,16 +1811,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Filter(filter_scale=112605.1171875, dx_min=array(2245.78271484), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=56, grid_type=<GridType.VECTOR_C_GRID: 6>)"
+       "Filter(filter_scale=112605.1171875, dx_min=array(2245.78271484), filter_shape=<FilterShape.GAUSSIAN: 1>, transition_width=3.141592653589793, ndim=2, n_steps=56, grid_type=<GridType.VECTOR_C_GRID: 8>)"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1849,15 +1851,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 29 s, sys: 20 s, total: 48.9 s\n",
-      "Wall time: 49.1 s\n"
+      "CPU times: user 27.4 s, sys: 19.3 s, total: 46.7 s\n",
+      "Wall time: 46.8 s\n"
      ]
     }
    ],
@@ -1867,7 +1869,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1880,7 +1882,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1890,7 +1892,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -1974,7 +1976,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -1995,7 +1997,7 @@
        " 'neverworld_sixteenth_degree_stats']"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2015,7 +2017,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -2402,7 +2404,7 @@
        "    filename:          averages_00030002.nc\n",
        "    grid_tile:         N/A\n",
        "    grid_type:         regular\n",
-       "    title:             NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d239a8c0-48bd-444b-a3e5-6c5322d0a461' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d239a8c0-48bd-444b-a3e5-6c5322d0a461' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 241</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 561</li><li><span class='xr-has-index'>zi</span>: 16</li><li><span class='xr-has-index'>zl</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c0c24ef6-1505-4b44-ac93-54c5c0f58c3d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c0c24ef6-1505-4b44-ac93-54c5c0f58c3d' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-83817faf-8404-4e44-a317-ff40c90cb124' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83817faf-8404-4e44-a317-ff40c90cb124' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b0ca4d2-7874-4380-a89c-0019fd031fff' class='xr-var-data-in' type='checkbox'><label for='data-5b0ca4d2-7874-4380-a89c-0019fd031fff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-04badd3a-9e65-4beb-a9a1-8332da89898a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04badd3a-9e65-4beb-a9a1-8332da89898a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fa2199c-a15f-4c2e-9b5a-b5e1fe9cfb78' class='xr-var-data-in' type='checkbox'><label for='data-1fa2199c-a15f-4c2e-9b5a-b5e1fe9cfb78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
+       "    title:             NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-15f58a3c-5c5b-4b9a-b609-cc4f79e670aa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-15f58a3c-5c5b-4b9a-b609-cc4f79e670aa' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 241</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 561</li><li><span class='xr-has-index'>zi</span>: 16</li><li><span class='xr-has-index'>zl</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ae9adb3d-fc8c-454a-bb9d-25553bbc1b9e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ae9adb3d-fc8c-454a-bb9d-25553bbc1b9e' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-3fbe9a0d-bcde-4b20-a52e-48ac3f18bf7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fbe9a0d-bcde-4b20-a52e-48ac3f18bf7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8940df35-5af5-4d1f-8990-ac22135a0189' class='xr-var-data-in' type='checkbox'><label for='data-8940df35-5af5-4d1f-8990-ac22135a0189' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-7e084375-ecc6-46d6-ae71-eb6d65fe0489' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e084375-ecc6-46d6-ae71-eb6d65fe0489' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7dafc20-26b3-4257-b546-66f8e5655864' class='xr-var-data-in' type='checkbox'><label for='data-d7dafc20-26b3-4257-b546-66f8e5655864' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 13, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 18, 12, 0, 0, 0),\n",
@@ -2501,10 +2503,10 @@
        "       cftime.Datetime360Day(85, 9, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 13, 12, 0, 0, 0),\n",
-       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-0cc551af-dd06-40bb-8095-26cc8ecdef1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cc551af-dd06-40bb-8095-26cc8ecdef1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cd62085-d467-4281-a271-e1b0e2598407' class='xr-var-data-in' type='checkbox'><label for='data-0cd62085-d467-4281-a271-e1b0e2598407' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 59.5 59.75 60.0</div><input id='attrs-d09f7cb1-bfd7-4de5-b3bc-bc2d87a9be53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d09f7cb1-bfd7-4de5-b3bc-bc2d87a9be53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-035a55c1-2d0b-4e12-bc55-15e51beda4de' class='xr-var-data-in' type='checkbox'><label for='data-035a55c1-2d0b-4e12-bc55-15e51beda4de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.25,  0.5 , ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-f89f164e-ce38-4259-8672-65e402854c5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f89f164e-ce38-4259-8672-65e402854c5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45d20829-b72d-44be-9f0f-8776639d430d' class='xr-var-data-in' type='checkbox'><label for='data-45d20829-b72d-44be-9f0f-8776639d430d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-70.0 -69.75 -69.5 ... 69.75 70.0</div><input id='attrs-0d573b4e-1529-4e6d-9e88-c9ad218b1585' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d573b4e-1529-4e6d-9e88-c9ad218b1585' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d035d19f-0dac-43ad-bfc5-019aed62c4e1' class='xr-var-data-in' type='checkbox'><label for='data-d035d19f-0dac-43ad-bfc5-019aed62c4e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-70.  , -69.75, -69.5 , ...,  69.5 ,  69.75,  70.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zi</span></div><div class='xr-var-dims'>(zi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.022e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-18633f50-79b6-43be-a320-0067cf13ce92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18633f50-79b6-43be-a320-0067cf13ce92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b97f31f-9948-40bb-bc7c-b1bbd42ca5d8' class='xr-var-data-in' type='checkbox'><label for='data-2b97f31f-9948-40bb-bc7c-b1bbd42ca5d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Interface Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.495, 1022.705, 1023.005, 1023.47 , 1024.03 , 1024.61 , 1025.185,\n",
+       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-d3e9026b-f2ce-4f4a-b59f-0370e69eccdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3e9026b-f2ce-4f4a-b59f-0370e69eccdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e75d1d4f-0e82-4011-b719-7cc715f1a5c0' class='xr-var-data-in' type='checkbox'><label for='data-e75d1d4f-0e82-4011-b719-7cc715f1a5c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 59.5 59.75 60.0</div><input id='attrs-6f9089e2-b351-4f53-b992-42a598bfc522' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f9089e2-b351-4f53-b992-42a598bfc522' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42fadf0c-9098-4de3-8ddc-5dbac8ce7680' class='xr-var-data-in' type='checkbox'><label for='data-42fadf0c-9098-4de3-8ddc-5dbac8ce7680' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.25,  0.5 , ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-c87c6e68-e17e-425b-aff5-b2bf4a9456bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c87c6e68-e17e-425b-aff5-b2bf4a9456bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcfc33d0-712a-49f1-bb17-67244927719a' class='xr-var-data-in' type='checkbox'><label for='data-dcfc33d0-712a-49f1-bb17-67244927719a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-70.0 -69.75 -69.5 ... 69.75 70.0</div><input id='attrs-ea5eb170-ae56-4dbd-9acc-32fee48f6543' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea5eb170-ae56-4dbd-9acc-32fee48f6543' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e93efec4-3087-48bc-ac42-d3474e3caba8' class='xr-var-data-in' type='checkbox'><label for='data-e93efec4-3087-48bc-ac42-d3474e3caba8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-70.  , -69.75, -69.5 , ...,  69.5 ,  69.75,  70.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zi</span></div><div class='xr-var-dims'>(zi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.022e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-d4d65a7f-22f6-4898-8b06-0c3c94a3f435' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4d65a7f-22f6-4898-8b06-0c3c94a3f435' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a3c08c2-831e-419b-95ac-681103bee2c0' class='xr-var-data-in' type='checkbox'><label for='data-8a3c08c2-831e-419b-95ac-681103bee2c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Interface Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.495, 1022.705, 1023.005, 1023.47 , 1024.03 , 1024.61 , 1025.185,\n",
        "       1025.735, 1026.24 , 1026.69 , 1027.085, 1027.425, 1027.7  , 1027.905,\n",
-       "       1028.045, 1028.155])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-e99ba378-3e95-47f2-b658-e51264dbeddf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e99ba378-3e95-47f2-b658-e51264dbeddf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37fe8588-4617-4365-bfde-90cf5c18a7d3' class='xr-var-data-in' type='checkbox'><label for='data-37fe8588-4617-4365-bfde-90cf5c18a7d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
-       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-77cfda4e-da91-4486-a174-c87cc1727662' class='xr-section-summary-in' type='checkbox'  ><label for='section-77cfda4e-da91-4486-a174-c87cc1727662' class='xr-section-summary' >Data variables: <span>(33)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-4649a6cc-d923-4ec7-aedd-86190f6887a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4649a6cc-d923-4ec7-aedd-86190f6887a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf287b8d-ff37-4a14-869e-17f62c8569fe' class='xr-var-data-in' type='checkbox'><label for='data-cf287b8d-ff37-4a14-869e-17f62c8569fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "       1028.045, 1028.155])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-cd7ccd11-af4d-4d25-b56d-aaa147fb7025' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd7ccd11-af4d-4d25-b56d-aaa147fb7025' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d916e98-8a3c-4135-b83e-e65821e16f22' class='xr-var-data-in' type='checkbox'><label for='data-1d916e98-8a3c-4135-b83e-e65821e16f22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
+       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3a0a319f-0389-4cd8-9293-3b0918833c51' class='xr-section-summary-in' type='checkbox'  ><label for='section-3a0a319f-0389-4cd8-9293-3b0918833c51' class='xr-section-summary' >Data variables: <span>(33)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-10002a82-eb49-425a-bf04-d435b4970b6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10002a82-eb49-425a-bf04-d435b4970b6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a9ba51e-69b4-4f76-8ff1-49696fa39ea6' class='xr-var-data-in' type='checkbox'><label for='data-0a9ba51e-69b4-4f76-8ff1-49696fa39ea6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2587,7 +2589,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-0b316b77-971a-4139-b8c0-697fc0e99446' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b316b77-971a-4139-b8c0-697fc0e99446' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf67780f-4f5a-482f-88ba-277bbc8f9ee8' class='xr-var-data-in' type='checkbox'><label for='data-bf67780f-4f5a-482f-88ba-277bbc8f9ee8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-01bb3c2b-4511-41b9-a820-9f8c0cc44248' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01bb3c2b-4511-41b9-a820-9f8c0cc44248' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46c99a17-f8d3-45c8-9fa5-8b7453447b84' class='xr-var-data-in' type='checkbox'><label for='data-46c99a17-f8d3-45c8-9fa5-8b7453447b84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2670,7 +2672,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-49b00bc9-7ece-481b-bc4c-3b9b42a5fc57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49b00bc9-7ece-481b-bc4c-3b9b42a5fc57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8c74179-1681-44a9-b612-3dd94098dc88' class='xr-var-data-in' type='checkbox'><label for='data-b8c74179-1681-44a9-b612-3dd94098dc88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-fd7b580e-5945-4f7d-8026-36b16510a58b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd7b580e-5945-4f7d-8026-36b16510a58b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8d345d8-6dd6-4df0-9ca9-21093274672c' class='xr-var-data-in' type='checkbox'><label for='data-f8d345d8-6dd6-4df0-9ca9-21093274672c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2753,7 +2755,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_BT</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-1584ed19-07e3-4bc9-a2d8-bca0f74386d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1584ed19-07e3-4bc9-a2d8-bca0f74386d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f67182b5-8fe5-4849-97ad-b1a010a270ec' class='xr-var-data-in' type='checkbox'><label for='data-f67182b5-8fe5-4849-97ad-b1a010a270ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Barotropic contribution to Kinetic Energy</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_BT</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-d6bb8b12-ff01-46ab-9878-056eabd0fdb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6bb8b12-ff01-46ab-9878-056eabd0fdb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9ad277b-92a6-4f72-83b8-716118c4c80e' class='xr-var-data-in' type='checkbox'><label for='data-c9ad277b-92a6-4f72-83b8-716118c4c80e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Barotropic contribution to Kinetic Energy</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2836,7 +2838,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_CorAdv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-79737194-2864-45de-97c3-8254c2ff03d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79737194-2864-45de-97c3-8254c2ff03d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7fa774e-5e70-437c-b4f7-a600c2b00c06' class='xr-var-data-in' type='checkbox'><label for='data-f7fa774e-5e70-437c-b4f7-a600c2b00c06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Coriolis and Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_CorAdv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-4a9c33d7-6f3f-4962-b348-05ddb21dac62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a9c33d7-6f3f-4962-b348-05ddb21dac62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac04a5aa-ddfa-4f0b-9acb-46d44f53fc69' class='xr-var-data-in' type='checkbox'><label for='data-ac04a5aa-ddfa-4f0b-9acb-46d44f53fc69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Coriolis and Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -2919,7 +2921,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_adv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e18f2e1d-cff2-487b-b90f-54506313804f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e18f2e1d-cff2-487b-b90f-54506313804f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd26674d-e3bd-44d1-904e-047af43104f2' class='xr-var-data-in' type='checkbox'><label for='data-cd26674d-e3bd-44d1-904e-047af43104f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_adv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-347f7f8d-c777-4df2-a131-de338c506cba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-347f7f8d-c777-4df2-a131-de338c506cba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47328fe1-0fa9-43d9-b170-57cc6a2b6fc7' class='xr-var-data-in' type='checkbox'><label for='data-47328fe1-0fa9-43d9-b170-57cc6a2b6fc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3002,7 +3004,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_horvisc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-54256def-fe06-49f5-80e9-6a41f8186147' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54256def-fe06-49f5-80e9-6a41f8186147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b24a4de-135d-4367-b8c7-334186cce801' class='xr-var-data-in' type='checkbox'><label for='data-5b24a4de-135d-4367-b8c7-334186cce801' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_horvisc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-f7499323-2b9f-49b7-8db9-59ca35467ffb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7499323-2b9f-49b7-8db9-59ca35467ffb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce4f2efc-282b-43ad-bc08-fa954ef90f08' class='xr-var-data-in' type='checkbox'><label for='data-ce4f2efc-282b-43ad-bc08-fa954ef90f08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3085,7 +3087,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-7097737b-30de-4c8b-b86f-669b168b7f5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7097737b-30de-4c8b-b86f-669b168b7f5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-687800f8-9303-40e3-a34a-56483514c7b6' class='xr-var-data-in' type='checkbox'><label for='data-687800f8-9303-40e3-a34a-56483514c7b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Vertical Viscosity and Stresses</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-755fba06-1e57-40d0-9e32-6fe00497a5d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-755fba06-1e57-40d0-9e32-6fe00497a5d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6489b4ad-f499-474c-b7b0-c7daed35eb40' class='xr-var-data-in' type='checkbox'><label for='data-6489b4ad-f499-474c-b7b0-c7daed35eb40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Vertical Viscosity and Stresses</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3168,7 +3170,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PE_to_KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-a080b2c6-3ffc-45b1-95f8-f6d776e90721' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a080b2c6-3ffc-45b1-95f8-f6d776e90721' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-930b462f-a71c-4c4c-9b1d-b466efd09501' class='xr-var-data-in' type='checkbox'><label for='data-930b462f-a71c-4c4c-9b1d-b466efd09501' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Potential to Kinetic Energy Conversion of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PE_to_KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-ba98aab7-0b36-4353-8964-d48bb430d2c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba98aab7-0b36-4353-8964-d48bb430d2c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89759c00-88ba-4bee-a237-e9013ddf5dd8' class='xr-var-data-in' type='checkbox'><label for='data-89759c00-88ba-4bee-a237-e9013ddf5dd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Potential to Kinetic Energy Conversion of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3251,7 +3253,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-6e6ec849-002f-451f-8aee-40b6595bcf39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e6ec849-002f-451f-8aee-40b6595bcf39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-409ac96c-4ebb-4728-8a14-809df77f8da0' class='xr-var-data-in' type='checkbox'><label for='data-409ac96c-4ebb-4728-8a14-809df77f8da0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-55406682-c231-4c80-a16e-b28cd1703115' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55406682-c231-4c80-a16e-b28cd1703115' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd204bf4-d058-4a39-a4b6-4b3a1a25718a' class='xr-var-data-in' type='checkbox'><label for='data-cd204bf4-d058-4a39-a4b6-4b3a1a25718a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3334,7 +3336,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-a17fdb9c-ad88-4da0-8601-7e122fb1da93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a17fdb9c-ad88-4da0-8601-7e122fb1da93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c42c835-a762-4e58-a35d-824b7696c38c' class='xr-var-data-in' type='checkbox'><label for='data-1c42c835-a762-4e58-a35d-824b7696c38c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-4d689ba8-3e4e-43d2-a403-eaede6e9023b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d689ba8-3e4e-43d2-a403-eaede6e9023b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fd65dea-77d3-40c9-a3f8-62f7ab908504' class='xr-var-data-in' type='checkbox'><label for='data-0fd65dea-77d3-40c9-a3f8-62f7ab908504' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3417,7 +3419,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(time, zl, yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 241), meta=np.ndarray&gt;</div><input id='attrs-3c5b47af-dc78-4e3f-ad1d-48083e3394bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c5b47af-dc78-4e3f-ad1d-48083e3394bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e08490d9-1603-4a4c-9e7d-10ce3746b5f0' class='xr-var-data-in' type='checkbox'><label for='data-e08490d9-1603-4a4c-9e7d-10ce3746b5f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Potential Vorticity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m-1 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(time, zl, yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 241), meta=np.ndarray&gt;</div><input id='attrs-3d6ccb50-51e4-420d-a82e-a7c9e36a5358' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d6ccb50-51e4-420d-a82e-a7c9e36a5358' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7024a816-8527-44d2-bc50-645d35ed890e' class='xr-var-data-in' type='checkbox'><label for='data-7024a816-8527-44d2-bc50-645d35ed890e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Potential Vorticity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m-1 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3500,7 +3502,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd1</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-ad37a44b-a080-46d7-8193-132851f041eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad37a44b-a080-46d7-8193-132851f041eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-351f9e4d-8182-4aea-8c8e-e2f25327a2d9' class='xr-var-data-in' type='checkbox'><label for='data-351f9e4d-8182-4aea-8c8e-e2f25327a2d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>First baroclinic deformation radius</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd1</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-8b8e4343-f670-468d-98a0-ffcb1950f3e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b8e4343-f670-468d-98a0-ffcb1950f3e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70730c89-23d3-4e28-b0ea-fd35228d1e6e' class='xr-var-data-in' type='checkbox'><label for='data-70730c89-23d3-4e28-b0ea-fd35228d1e6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>First baroclinic deformation radius</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3558,7 +3560,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd_dx</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-d6dea721-749b-4e15-b39e-581b1bd2ee8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6dea721-749b-4e15-b39e-581b1bd2ee8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa8ddc1e-cadd-4475-a6d2-7cf506dcc076' class='xr-var-data-in' type='checkbox'><label for='data-aa8ddc1e-cadd-4475-a6d2-7cf506dcc076' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Ratio between deformation radius and grid spacing</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m m-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd_dx</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-ba17bc91-2ea0-4961-9876-9a52019078af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba17bc91-2ea0-4961-9876-9a52019078af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb01eb68-18c3-4044-8fa1-2ac97c13cab3' class='xr-var-data-in' type='checkbox'><label for='data-bb01eb68-18c3-4044-8fa1-2ac97c13cab3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Ratio between deformation radius and grid spacing</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m m-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3616,7 +3618,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-2512ec59-aade-41cb-a309-36b2c7d93f60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2512ec59-aade-41cb-a309-36b2c7d93f60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6412986-d0c4-4236-b5d0-9e2f93c05f49' class='xr-var-data-in' type='checkbox'><label for='data-a6412986-d0c4-4236-b5d0-9e2f93c05f49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>Length of average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-aa861e08-355e-46e3-b34a-317c78494ed2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa861e08-355e-46e3-b34a-317c78494ed2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-667bcf88-f973-4702-b154-48bf768198fe' class='xr-var-data-in' type='checkbox'><label for='data-667bcf88-f973-4702-b154-48bf768198fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>Length of average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3651,7 +3653,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-2a7247ea-abc6-42e9-970c-71af709f3310' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a7247ea-abc6-42e9-970c-71af709f3310' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8e28a69-4058-4117-853f-2f6a3d1cda16' class='xr-var-data-in' type='checkbox'><label for='data-e8e28a69-4058-4117-853f-2f6a3d1cda16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-b099ee6f-3482-4626-b181-eb4d2580c8ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b099ee6f-3482-4626-b181-eb4d2580c8ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6527b20-6037-4ffc-acd4-df61f03f9df7' class='xr-var-data-in' type='checkbox'><label for='data-d6527b20-6037-4ffc-acd4-df61f03f9df7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3686,7 +3688,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-42db9286-927d-4cbf-ad3d-f6b3ce3c7506' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42db9286-927d-4cbf-ad3d-f6b3ce3c7506' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c78a290b-f595-4f17-aee4-62c463c2ff73' class='xr-var-data-in' type='checkbox'><label for='data-c78a290b-f595-4f17-aee4-62c463c2ff73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>End time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-9763ae1f-b695-43d1-8d17-80bccf013f60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9763ae1f-b695-43d1-8d17-80bccf013f60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d254e9ce-4814-4693-a313-6031d9ddb425' class='xr-var-data-in' type='checkbox'><label for='data-d254e9ce-4814-4693-a313-6031d9ddb425' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>End time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3721,7 +3723,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dKE_dt</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-46c219b3-a53f-41cf-a110-fd3df9cf0867' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46c219b3-a53f-41cf-a110-fd3df9cf0867' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0210f015-5de7-4307-875e-2ba8bc28cf40' class='xr-var-data-in' type='checkbox'><label for='data-0210f015-5de7-4307-875e-2ba8bc28cf40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Tendency of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dKE_dt</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-f1bff2db-a361-4410-b84b-b856e0ca3348' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1bff2db-a361-4410-b84b-b856e0ca3348' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b093def5-da95-4de2-bfba-da25f2c105e8' class='xr-var-data-in' type='checkbox'><label for='data-b093def5-da95-4de2-bfba-da25f2c105e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Tendency of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3804,7 +3806,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-f5d2d091-71f9-4bc0-b8c5-d3221cbb446b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5d2d091-71f9-4bc0-b8c5-d3221cbb446b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a32a03b-c30c-488f-b686-ef9cf91e4b54' class='xr-var-data-in' type='checkbox'><label for='data-8a32a03b-c30c-488f-b686-ef9cf91e4b54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-4446c44e-d41b-430a-9bbb-df36e0f32933' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4446c44e-d41b-430a-9bbb-df36e0f32933' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ac01ce5-4dbb-42e7-b95a-a679d0ade585' class='xr-var-data-in' type='checkbox'><label for='data-5ac01ce5-4dbb-42e7-b95a-a679d0ade585' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3887,7 +3889,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-a8c5b149-27e0-4ecb-8e7e-81f54545e86a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8c5b149-27e0-4ecb-8e7e-81f54545e86a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9cb6f22-1a5a-4add-939e-8160ba2463cc' class='xr-var-data-in' type='checkbox'><label for='data-e9cb6f22-1a5a-4add-939e-8160ba2463cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-1cded6eb-187e-4f8d-9d24-d4397106c7c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cded6eb-187e-4f8d-9d24-d4397106c7c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d39a8f3-235a-4391-aa9f-65f9c6d681be' class='xr-var-data-in' type='checkbox'><label for='data-4d39a8f3-235a-4391-aa9f-65f9c6d681be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -3970,7 +3972,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>du_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-b28db82e-294b-4dae-8c9d-d626ad71ee55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b28db82e-294b-4dae-8c9d-d626ad71ee55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a6c0825-056a-4810-9bd1-047ef83258e9' class='xr-var-data-in' type='checkbox'><label for='data-6a6c0825-056a-4810-9bd1-047ef83258e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>du_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-5d7b6a5a-1929-445e-b20f-4d1ac407983b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d7b6a5a-1929-445e-b20f-4d1ac407983b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-caff72dd-fb70-4a5e-90ea-c8612ab5eff7' class='xr-var-data-in' type='checkbox'><label for='data-caff72dd-fb70-4a5e-90ea-c8612ab5eff7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4053,7 +4055,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dudt</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-78fcd873-61d2-4dd3-ae24-32238bf95728' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78fcd873-61d2-4dd3-ae24-32238bf95728' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3b1b1b7-a57d-4ad8-a31a-b2fef711914e' class='xr-var-data-in' type='checkbox'><label for='data-f3b1b1b7-a57d-4ad8-a31a-b2fef711914e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dudt</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-bc30b96e-baa5-4bc1-8374-1b9f6edce88e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc30b96e-baa5-4bc1-8374-1b9f6edce88e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6558f800-4003-4ebf-8887-f3fa44d24254' class='xr-var-data-in' type='checkbox'><label for='data-6558f800-4003-4ebf-8887-f3fa44d24254' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4136,7 +4138,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dv_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-f907570f-9dc6-40ca-aac2-aed97b2a5cd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f907570f-9dc6-40ca-aac2-aed97b2a5cd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e256af42-b37d-4eb0-9876-e82d19445a52' class='xr-var-data-in' type='checkbox'><label for='data-e256af42-b37d-4eb0-9876-e82d19445a52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dv_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-ae224b51-9944-4b8a-964b-c6f97f93a43c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae224b51-9944-4b8a-964b-c6f97f93a43c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f550ea2-ebb5-4175-9cf0-6b2f997edffa' class='xr-var-data-in' type='checkbox'><label for='data-3f550ea2-ebb5-4175-9cf0-6b2f997edffa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4219,7 +4221,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dvdt</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-ade4fa86-acd8-4926-b57f-275fa5dda833' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ade4fa86-acd8-4926-b57f-275fa5dda833' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05f991e9-2b92-48de-bd02-799467aafb7b' class='xr-var-data-in' type='checkbox'><label for='data-05f991e9-2b92-48de-bd02-799467aafb7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dvdt</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-8be4f921-1c39-4425-9941-692236b104b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8be4f921-1c39-4425-9941-692236b104b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2969202c-17e9-4826-a451-e1732e718553' class='xr-var-data-in' type='checkbox'><label for='data-2969202c-17e9-4826-a451-e1732e718553' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4302,7 +4304,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e2</span></div><div class='xr-var-dims'>(time, zi, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 16, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-90871991-2935-40a8-a74f-9e71a447fe2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90871991-2935-40a8-a74f-9e71a447fe2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa46252b-6d61-4100-b782-29d464b2d820' class='xr-var-data-in' type='checkbox'><label for='data-aa46252b-6d61-4100-b782-29d464b2d820' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zi:point yh:mean xh:mean time: mean_pow(2)</dd><dt><span>long_name :</span></dt><dd>Interface Height Relative to Mean Sea Level</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e2</span></div><div class='xr-var-dims'>(time, zi, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 16, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e8233999-f257-4d8a-8abd-8286c2c0abe7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8233999-f257-4d8a-8abd-8286c2c0abe7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14aa1bb3-dbbd-4fe4-9a02-289eae749930' class='xr-var-data-in' type='checkbox'><label for='data-14aa1bb3-dbbd-4fe4-9a02-289eae749930' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zi:point yh:mean xh:mean time: mean_pow(2)</dd><dt><span>long_name :</span></dt><dd>Interface Height Relative to Mean Sea Level</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4385,7 +4387,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-d0c3aff0-37e7-475f-b93c-72d270bef265' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0c3aff0-37e7-475f-b93c-72d270bef265' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56714446-8113-4e3a-aac4-e0433d0736ab' class='xr-var-data-in' type='checkbox'><label for='data-56714446-8113-4e3a-aac4-e0433d0736ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:sum yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer Thickness</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e4e407d6-9a6e-4425-8c01-4f07b633582b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4e407d6-9a6e-4425-8c01-4f07b633582b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-868972f7-f2d9-4f5d-820f-e4e681efda13' class='xr-var-data-in' type='checkbox'><label for='data-868972f7-f2d9-4f5d-820f-e4e681efda13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:sum yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer Thickness</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4468,7 +4470,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;</div><input id='attrs-00c60d90-ab55-4f97-b824-c7559f2b16f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00c60d90-ab55-4f97-b824-c7559f2b16f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd843f63-9e52-44e4-b842-a9a2c3faffeb' class='xr-var-data-in' type='checkbox'><label for='data-cd843f63-9e52-44e4-b842-a9a2c3faffeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>time axis boundaries</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;</div><input id='attrs-2bb046eb-353c-4f6c-b9d2-56b414a90a7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bb046eb-353c-4f6c-b9d2-56b414a90a7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de7ba653-018c-42d6-88cf-bdbed0ba9fc4' class='xr-var-data-in' type='checkbox'><label for='data-de7ba653-018c-42d6-88cf-bdbed0ba9fc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>time axis boundaries</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4503,7 +4505,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-f2ad09e3-d82d-42a2-a6de-45f85ac2e495' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2ad09e3-d82d-42a2-a6de-45f85ac2e495' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41146ddb-6337-4e3b-9f18-47faad4d5f22' class='xr-var-data-in' type='checkbox'><label for='data-41146ddb-6337-4e3b-9f18-47faad4d5f22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-ae3f07e4-733c-4fc3-bbdd-ae5b1da3f29e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae3f07e4-733c-4fc3-bbdd-ae5b1da3f29e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9dd7f280-5cac-4e3f-ac9b-dde193ec922c' class='xr-var-data-in' type='checkbox'><label for='data-9dd7f280-5cac-4e3f-ac9b-dde193ec922c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4586,7 +4588,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-482560d8-1a9a-4bc2-8eeb-799beb031308' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-482560d8-1a9a-4bc2-8eeb-799beb031308' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d014b48-2b63-4dd5-a05d-1838c08c611c' class='xr-var-data-in' type='checkbox'><label for='data-8d014b48-2b63-4dd5-a05d-1838c08c611c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-211fa116-88f5-4da3-ab3f-16324250cf64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-211fa116-88f5-4da3-ab3f-16324250cf64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff7369e4-2592-40e1-89ce-f66e691fb1af' class='xr-var-data-in' type='checkbox'><label for='data-ff7369e4-2592-40e1-89ce-f66e691fb1af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4669,7 +4671,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uh</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-85b3ade3-cbc1-4a50-ab84-93b4ecd54037' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85b3ade3-cbc1-4a50-ab84-93b4ecd54037' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ecef221-ffdb-4205-b533-a9e3157bc4ee' class='xr-var-data-in' type='checkbox'><label for='data-5ecef221-ffdb-4205-b533-a9e3157bc4ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yh:sum xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uh</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 241), meta=np.ndarray&gt;</div><input id='attrs-f39562bc-7851-4277-a396-94da9d04fe39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f39562bc-7851-4277-a396-94da9d04fe39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c177057-cd46-443a-bc4c-785ae0b72e3b' class='xr-var-data-in' type='checkbox'><label for='data-1c177057-cd46-443a-bc4c-785ae0b72e3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yh:sum xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4752,7 +4754,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-b62f2b40-6520-4c1c-a324-ffe9d0199abb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b62f2b40-6520-4c1c-a324-ffe9d0199abb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e1f576a-3d05-467f-9217-e992c93a83f9' class='xr-var-data-in' type='checkbox'><label for='data-4e1f576a-3d05-467f-9217-e992c93a83f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-e7114145-27f4-43d9-89a1-b6f98fbe5943' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7114145-27f4-43d9-89a1-b6f98fbe5943' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82d0cd36-75ae-43c3-9742-ef16966349d1' class='xr-var-data-in' type='checkbox'><label for='data-82d0cd36-75ae-43c3-9742-ef16966349d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4835,7 +4837,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-1160da43-13ab-4a70-9092-c707bf3062e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1160da43-13ab-4a70-9092-c707bf3062e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-193df89b-c7ad-4bd9-9355-8c27e5d91746' class='xr-var-data-in' type='checkbox'><label for='data-193df89b-c7ad-4bd9-9355-8c27e5d91746' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-5df90418-f934-4ab7-b4ea-f02c0702f932' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5df90418-f934-4ab7-b4ea-f02c0702f932' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-553db590-46b4-4a32-aaa6-cd4b03b83028' class='xr-var-data-in' type='checkbox'><label for='data-553db590-46b4-4a32-aaa6-cd4b03b83028' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -4918,7 +4920,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-6fd9a47f-6c41-4c78-89a7-564730a7de80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fd9a47f-6c41-4c78-89a7-564730a7de80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39127414-c8af-4140-b15b-9c22e2765c86' class='xr-var-data-in' type='checkbox'><label for='data-39127414-c8af-4140-b15b-9c22e2765c86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yq:point xh:sum time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 561, 240), meta=np.ndarray&gt;</div><input id='attrs-fc1fed23-9d32-4f09-beb4-4079d06a89c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc1fed23-9d32-4f09-beb4-4079d06a89c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-980b085a-eee6-4a4b-91a6-a906e1e6d7c4' class='xr-var-data-in' type='checkbox'><label for='data-980b085a-eee6-4a4b-91a6-a906e1e6d7c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yq:point xh:sum time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5001,7 +5003,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b59ea48-a09c-464a-a613-84bd28eea604' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b59ea48-a09c-464a-a613-84bd28eea604' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>associated_files :</span></dt><dd>area_t: static.nc</dd><dt><span>filename :</span></dt><dd>averages_00030002.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-19697d85-4240-4ea0-b627-161d3ebdccd0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-19697d85-4240-4ea0-b627-161d3ebdccd0' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>associated_files :</span></dt><dd>area_t: static.nc</dd><dt><span>filename :</span></dt><dd>averages_00030002.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -5037,7 +5039,7 @@
        "    title:             NeverWorld2"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5057,7 +5059,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -5444,7 +5446,7 @@
        "    filename:          averages_00030002.nc\n",
        "    grid_tile:         N/A\n",
        "    grid_type:         regular\n",
-       "    title:             NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-aa2a040b-460d-4af4-acd5-a5e6dae0bb9d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aa2a040b-460d-4af4-acd5-a5e6dae0bb9d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 240</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 560</li><li><span class='xr-has-index'>zi</span>: 16</li><li><span class='xr-has-index'>zl</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3a4ec9bc-7ae6-4713-a23a-5a82cc4bac3e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3a4ec9bc-7ae6-4713-a23a-5a82cc4bac3e' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-a3c37e39-5dd4-46f6-96ef-9acbe3298ffc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3c37e39-5dd4-46f6-96ef-9acbe3298ffc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2eb7bd0-c98c-4204-a339-4140a3eaf601' class='xr-var-data-in' type='checkbox'><label for='data-f2eb7bd0-c98c-4204-a339-4140a3eaf601' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-6dfd8b0c-3ac2-4821-847f-3cb9ad5d9d8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6dfd8b0c-3ac2-4821-847f-3cb9ad5d9d8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3ac0529-c11f-49b1-9dd6-19d2a31bd93d' class='xr-var-data-in' type='checkbox'><label for='data-b3ac0529-c11f-49b1-9dd6-19d2a31bd93d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
+       "    title:             NeverWorld2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3260314c-cf68-4348-b95f-96718d43cae5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3260314c-cf68-4348-b95f-96718d43cae5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>xh</span>: 240</li><li><span class='xr-has-index'>xq</span>: 240</li><li><span class='xr-has-index'>yh</span>: 560</li><li><span class='xr-has-index'>yq</span>: 560</li><li><span class='xr-has-index'>zi</span>: 16</li><li><span class='xr-has-index'>zl</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-15baebc4-b3a6-4eea-a12d-ba86fc91c976' class='xr-section-summary-in' type='checkbox'  checked><label for='section-15baebc4-b3a6-4eea-a12d-ba86fc91c976' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-29fb88c0-4778-4f0e-8583-306bb46463ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29fb88c0-4778-4f0e-8583-306bb46463ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8473d72-9f30-4623-a0e2-f85b7d5742f7' class='xr-var-data-in' type='checkbox'><label for='data-f8473d72-9f30-4623-a0e2-f85b7d5742f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0084-05-03 12:00:00 ... 0085-09-...</div><input id='attrs-c1242229-2ad8-4af0-acbb-f61b77b8e1be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1242229-2ad8-4af0-acbb-f61b77b8e1be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46e3dcc5-359c-4c5d-8b69-1daccd075030' class='xr-var-data-in' type='checkbox'><label for='data-46e3dcc5-359c-4c5d-8b69-1daccd075030' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>calendar_type :</span></dt><dd>THIRTY_DAY_MONTHS</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(84, 5, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 13, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(84, 5, 18, 12, 0, 0, 0),\n",
@@ -5543,10 +5545,10 @@
        "       cftime.Datetime360Day(85, 9, 3, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 8, 12, 0, 0, 0),\n",
        "       cftime.Datetime360Day(85, 9, 13, 12, 0, 0, 0),\n",
-       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-bf1f4289-8add-41a0-8126-25ee96134e9c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf1f4289-8add-41a0-8126-25ee96134e9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86cab067-6b65-4b21-aa50-4cb19b5822ae' class='xr-var-data-in' type='checkbox'><label for='data-86cab067-6b65-4b21-aa50-4cb19b5822ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.25 0.5 0.75 ... 59.5 59.75 60.0</div><input id='attrs-0fe6861f-5a10-4e65-86d3-1f8e708de055' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fe6861f-5a10-4e65-86d3-1f8e708de055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc68e5f5-37bf-46ec-9354-f57af8c2146b' class='xr-var-data-in' type='checkbox'><label for='data-dc68e5f5-37bf-46ec-9354-f57af8c2146b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.25,  0.5 ,  0.75, ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-7b94250f-1cf4-441f-8f1a-e494bb38f408' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b94250f-1cf4-441f-8f1a-e494bb38f408' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-075d647e-12f0-4783-bf31-a545779f0485' class='xr-var-data-in' type='checkbox'><label for='data-075d647e-12f0-4783-bf31-a545779f0485' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.75 -69.5 -69.25 ... 69.75 70.0</div><input id='attrs-a0fa0d98-69d8-4c42-9ef8-69a37d3c0a11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0fa0d98-69d8-4c42-9ef8-69a37d3c0a11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc20cca8-d089-4d03-b5f0-3d220e281fad' class='xr-var-data-in' type='checkbox'><label for='data-fc20cca8-d089-4d03-b5f0-3d220e281fad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.75, -69.5 , -69.25, ...,  69.5 ,  69.75,  70.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zi</span></div><div class='xr-var-dims'>(zi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.022e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-32213ac9-d71a-44a1-ac35-96e3f9cf5005' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32213ac9-d71a-44a1-ac35-96e3f9cf5005' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8fcd6fe-5473-41fe-bbdf-c22ed6d492c2' class='xr-var-data-in' type='checkbox'><label for='data-e8fcd6fe-5473-41fe-bbdf-c22ed6d492c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Interface Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.495, 1022.705, 1023.005, 1023.47 , 1024.03 , 1024.61 , 1025.185,\n",
+       "       cftime.Datetime360Day(85, 9, 18, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xh</span></div><div class='xr-var-dims'>(xh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.125 0.375 0.625 ... 59.62 59.88</div><input id='attrs-e52dabd5-0192-4b38-86c2-4a2cfdd8eee5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e52dabd5-0192-4b38-86c2-4a2cfdd8eee5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b63620d-97e9-42d6-bc0d-502200addceb' class='xr-var-data-in' type='checkbox'><label for='data-2b63620d-97e9-42d6-bc0d-502200addceb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>h point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.125,  0.375,  0.625, ..., 59.375, 59.625, 59.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xq</span></div><div class='xr-var-dims'>(xq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.25 0.5 0.75 ... 59.5 59.75 60.0</div><input id='attrs-424712c0-1941-493b-ad5a-dc4966f04efe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-424712c0-1941-493b-ad5a-dc4966f04efe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48f23749-50b1-4886-9d44-0e66b141a011' class='xr-var-data-in' type='checkbox'><label for='data-48f23749-50b1-4886-9d44-0e66b141a011' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>q point nominal longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 0.25,  0.5 ,  0.75, ..., 59.5 , 59.75, 60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yh</span></div><div class='xr-var-dims'>(yh)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.88 -69.62 ... 69.62 69.88</div><input id='attrs-adc8e9f3-8e41-48c0-a414-75f906158ec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-adc8e9f3-8e41-48c0-a414-75f906158ec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9075e1ec-f69f-406a-bcba-a007c9bb6ccb' class='xr-var-data-in' type='checkbox'><label for='data-9075e1ec-f69f-406a-bcba-a007c9bb6ccb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>h point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.875, -69.625, -69.375, ...,  69.375,  69.625,  69.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yq</span></div><div class='xr-var-dims'>(yq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-69.75 -69.5 -69.25 ... 69.75 70.0</div><input id='attrs-9302b90b-22a1-4387-9e97-b8e06e0c88a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9302b90b-22a1-4387-9e97-b8e06e0c88a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c157c1b-0086-421d-bcf1-6390b9807229' class='xr-var-data-in' type='checkbox'><label for='data-9c157c1b-0086-421d-bcf1-6390b9807229' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>q point nominal latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-69.75, -69.5 , -69.25, ...,  69.5 ,  69.75,  70.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zi</span></div><div class='xr-var-dims'>(zi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.022e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-5b42b029-d824-4d0f-ac7d-fca5ed8970e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b42b029-d824-4d0f-ac7d-fca5ed8970e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aca0a82a-88b1-48aa-a6c2-9bf945d5297f' class='xr-var-data-in' type='checkbox'><label for='data-aca0a82a-88b1-48aa-a6c2-9bf945d5297f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Interface Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.495, 1022.705, 1023.005, 1023.47 , 1024.03 , 1024.61 , 1025.185,\n",
        "       1025.735, 1026.24 , 1026.69 , 1027.085, 1027.425, 1027.7  , 1027.905,\n",
-       "       1028.045, 1028.155])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-83060dc3-6d61-4182-b7bc-ce436c19b209' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83060dc3-6d61-4182-b7bc-ce436c19b209' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b15421b-cf98-4aaf-96de-964d016e81c7' class='xr-var-data-in' type='checkbox'><label for='data-7b15421b-cf98-4aaf-96de-964d016e81c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
-       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7bcfbef6-a8fe-4a5e-ab53-97050d708994' class='xr-section-summary-in' type='checkbox'  ><label for='section-7bcfbef6-a8fe-4a5e-ab53-97050d708994' class='xr-section-summary' >Data variables: <span>(33)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-744e406b-846b-4ea2-bbc5-83374260ce77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-744e406b-846b-4ea2-bbc5-83374260ce77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeb39592-bdf4-48e3-b50b-113a9adc6fc5' class='xr-var-data-in' type='checkbox'><label for='data-eeb39592-bdf4-48e3-b50b-113a9adc6fc5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "       1028.045, 1028.155])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.028e+03</div><input id='attrs-8bafce2b-05be-4085-8cf3-307c4e2f4733' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8bafce2b-05be-4085-8cf3-307c4e2f4733' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb0bd3e8-34b7-4ed5-bd9d-8834770505a7' class='xr-var-data-in' type='checkbox'><label for='data-cb0bd3e8-34b7-4ed5-bd9d-8834770505a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>Layer Target Potential Density</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>kg m-3</dd></dl></div><div class='xr-var-data'><pre>array([1022.6 , 1022.81, 1023.2 , 1023.74, 1024.32, 1024.9 , 1025.47, 1026.  ,\n",
+       "       1026.48, 1026.9 , 1027.27, 1027.58, 1027.82, 1027.99, 1028.1 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-03b07497-3d0d-49d7-a99b-208a65212156' class='xr-section-summary-in' type='checkbox'  ><label for='section-03b07497-3d0d-49d7-a99b-208a65212156' class='xr-section-summary' >Data variables: <span>(33)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-2450351f-2b7e-400b-9734-04bac1bc2985' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2450351f-2b7e-400b-9734-04bac1bc2985' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeca4b95-1daf-4084-9a64-01dab5924c30' class='xr-var-data-in' type='checkbox'><label for='data-eeca4b95-1daf-4084-9a64-01dab5924c30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5629,7 +5631,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-0116aab4-bfc5-430b-86e5-53ad4b5173e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0116aab4-bfc5-430b-86e5-53ad4b5173e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f4333dc-f804-4442-bbd6-b9443219244e' class='xr-var-data-in' type='checkbox'><label for='data-9f4333dc-f804-4442-bbd6-b9443219244e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-22d3786b-c59b-4f26-a8be-8bf57249382e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22d3786b-c59b-4f26-a8be-8bf57249382e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-497d2474-54e9-4233-baf6-be484b778f69' class='xr-var-data-in' type='checkbox'><label for='data-497d2474-54e9-4233-baf6-be484b778f69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Coriolis and Advective Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5712,7 +5714,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-c45ab4da-ab51-4edd-bd63-589677907c0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c45ab4da-ab51-4edd-bd63-589677907c0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41651cec-823d-4729-ad74-f4918bd67a0a' class='xr-var-data-in' type='checkbox'><label for='data-41651cec-823d-4729-ad74-f4918bd67a0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-15e6b42e-d413-4276-abbf-4a834779002d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15e6b42e-d413-4276-abbf-4a834779002d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-494aaf7b-4520-4bf7-9b9a-44c57ebab542' class='xr-var-data-in' type='checkbox'><label for='data-494aaf7b-4520-4bf7-9b9a-44c57ebab542' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer kinetic energy per unit mass</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5795,7 +5797,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_BT</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-c8ccec46-f237-4067-a16f-1246f79cdac0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c8ccec46-f237-4067-a16f-1246f79cdac0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99d5505f-c025-48e8-a90b-062e3de8f4b0' class='xr-var-data-in' type='checkbox'><label for='data-99d5505f-c025-48e8-a90b-062e3de8f4b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Barotropic contribution to Kinetic Energy</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_BT</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-3306e6f1-cc81-4d8c-8201-1e7b89448b45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3306e6f1-cc81-4d8c-8201-1e7b89448b45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99cb0e23-977d-4e9c-bbaf-fca25983ed83' class='xr-var-data-in' type='checkbox'><label for='data-99cb0e23-977d-4e9c-bbaf-fca25983ed83' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Barotropic contribution to Kinetic Energy</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5878,7 +5880,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_CorAdv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-bd9b9430-a6a7-497f-88d2-3cb54eb5b2ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd9b9430-a6a7-497f-88d2-3cb54eb5b2ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e92ca41-5ed6-4d41-ade1-c53f2143d84b' class='xr-var-data-in' type='checkbox'><label for='data-5e92ca41-5ed6-4d41-ade1-c53f2143d84b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Coriolis and Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_CorAdv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-4bbd4c59-abb6-42c3-8e97-7576487f0c42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bbd4c59-abb6-42c3-8e97-7576487f0c42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bf3e4b2-541c-456e-8230-1f319ed33a31' class='xr-var-data-in' type='checkbox'><label for='data-9bf3e4b2-541c-456e-8230-1f319ed33a31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Coriolis and Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -5961,7 +5963,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_adv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-869ccb49-5d02-43ca-9ed7-f97748d48edd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-869ccb49-5d02-43ca-9ed7-f97748d48edd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3fe26a5-85cd-43aa-824c-a4d930d1d6ac' class='xr-var-data-in' type='checkbox'><label for='data-d3fe26a5-85cd-43aa-824c-a4d930d1d6ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_adv</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-5306d1ce-9a64-4b66-96e6-d64d286628f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5306d1ce-9a64-4b66-96e6-d64d286628f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89cbe8c7-b96d-4fc2-ad28-78b05ad368ce' class='xr-var-data-in' type='checkbox'><label for='data-89cbe8c7-b96d-4fc2-ad28-78b05ad368ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Advection</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6044,7 +6046,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_horvisc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-48e1bce2-baa7-4740-9efe-3dde6af20339' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48e1bce2-baa7-4740-9efe-3dde6af20339' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02ef195d-cea6-46d3-b29d-9a721c5b018f' class='xr-var-data-in' type='checkbox'><label for='data-02ef195d-cea6-46d3-b29d-9a721c5b018f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_horvisc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-24e79770-2f1b-486c-9ccb-0a3d2477eb2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24e79770-2f1b-486c-9ccb-0a3d2477eb2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2132b1ee-04d5-457a-ba70-af08a16d12f8' class='xr-var-data-in' type='checkbox'><label for='data-2132b1ee-04d5-457a-ba70-af08a16d12f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6127,7 +6129,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-9c8b6a52-1fcd-4a31-bcdd-8d59c855758f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c8b6a52-1fcd-4a31-bcdd-8d59c855758f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61b3ad8d-ad85-41ec-bb53-6d04e7bf8d80' class='xr-var-data-in' type='checkbox'><label for='data-61b3ad8d-ad85-41ec-bb53-6d04e7bf8d80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Vertical Viscosity and Stresses</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KE_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-b9c45197-7102-45d9-9f9c-85d517c15ee5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9c45197-7102-45d9-9f9c-85d517c15ee5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d92b51f7-88d9-452d-ad7d-7869de77b02d' class='xr-var-data-in' type='checkbox'><label for='data-d92b51f7-88d9-452d-ad7d-7869de77b02d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Source from Vertical Viscosity and Stresses</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6210,7 +6212,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PE_to_KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-054ef123-b93b-4f9f-bccd-93f20425dda4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-054ef123-b93b-4f9f-bccd-93f20425dda4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-289b6c56-7a3a-48df-939f-7d6e1523afe8' class='xr-var-data-in' type='checkbox'><label for='data-289b6c56-7a3a-48df-939f-7d6e1523afe8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Potential to Kinetic Energy Conversion of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PE_to_KE</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-163c315a-9192-4a40-b223-bca6c4ee2d30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-163c315a-9192-4a40-b223-bca6c4ee2d30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-267a418f-a3dd-4f47-90e0-4b24faa58185' class='xr-var-data-in' type='checkbox'><label for='data-267a418f-a3dd-4f47-90e0-4b24faa58185' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Potential to Kinetic Energy Conversion of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6293,7 +6295,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-d54f0ee8-2dad-464c-8ccd-e84280efc881' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d54f0ee8-2dad-464c-8ccd-e84280efc881' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0845177-a830-4186-92b0-75fca0a500b0' class='xr-var-data-in' type='checkbox'><label for='data-c0845177-a830-4186-92b0-75fca0a500b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-87d89095-6a35-4801-9050-c5c318a11793' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87d89095-6a35-4801-9050-c5c318a11793' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d440a23-1a62-45a6-b2c3-34cfe837a82a' class='xr-var-data-in' type='checkbox'><label for='data-6d440a23-1a62-45a6-b2c3-34cfe837a82a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6376,7 +6378,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e7e83fac-ec68-4759-84ff-5b3267cd269d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7e83fac-ec68-4759-84ff-5b3267cd269d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b527368d-374f-41f6-89e7-ee87c9d40527' class='xr-var-data-in' type='checkbox'><label for='data-b527368d-374f-41f6-89e7-ee87c9d40527' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PFv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-5dd1815e-1b10-4aea-9a54-2a2ec9266614' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dd1815e-1b10-4aea-9a54-2a2ec9266614' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3ac38f3-c6be-43ea-9f99-aa702b068a0a' class='xr-var-data-in' type='checkbox'><label for='data-a3ac38f3-c6be-43ea-9f99-aa702b068a0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Pressure Force Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6459,7 +6461,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(time, zl, yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-7b51c276-9658-42e4-bea7-383f63a4d9df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b51c276-9658-42e4-bea7-383f63a4d9df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-645d0341-991a-4b3c-99d9-e3848f7f6ab4' class='xr-var-data-in' type='checkbox'><label for='data-645d0341-991a-4b3c-99d9-e3848f7f6ab4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Potential Vorticity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m-1 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(time, zl, yq, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-c1ea87be-2329-4807-945c-7e934d124246' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1ea87be-2329-4807-945c-7e934d124246' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dda79a06-0daa-4b4f-b636-26668b64bad4' class='xr-var-data-in' type='checkbox'><label for='data-dda79a06-0daa-4b4f-b636-26668b64bad4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Potential Vorticity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m-1 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6542,7 +6544,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd1</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-6ed4e992-42f2-4414-a03d-12c6fb0f6335' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ed4e992-42f2-4414-a03d-12c6fb0f6335' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03cb78cc-e0b4-413b-8267-2647fbb306c2' class='xr-var-data-in' type='checkbox'><label for='data-03cb78cc-e0b4-413b-8267-2647fbb306c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>First baroclinic deformation radius</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd1</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-d866e775-8884-4a68-b19d-7b644615f4e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d866e775-8884-4a68-b19d-7b644615f4e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-702e59d2-e5c3-4f27-8517-3465cc512582' class='xr-var-data-in' type='checkbox'><label for='data-702e59d2-e5c3-4f27-8517-3465cc512582' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>First baroclinic deformation radius</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6600,7 +6602,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd_dx</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-61af3576-9355-4f93-80ec-a0380e227f00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61af3576-9355-4f93-80ec-a0380e227f00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5dd3ab0-bd7c-45b0-aea1-7ec54c121c71' class='xr-var-data-in' type='checkbox'><label for='data-b5dd3ab0-bd7c-45b0-aea1-7ec54c121c71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Ratio between deformation radius and grid spacing</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m m-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Rd_dx</span></div><div class='xr-var-dims'>(time, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-7a7036ed-ad17-4aa9-8237-2d6b88aa93cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a7036ed-ad17-4aa9-8237-2d6b88aa93cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a981f0b9-1b04-4b1f-9c7a-8a6276dc77f0' class='xr-var-data-in' type='checkbox'><label for='data-a981f0b9-1b04-4b1f-9c7a-8a6276dc77f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Ratio between deformation radius and grid spacing</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m m-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6658,7 +6660,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-6a820fce-0781-484f-849f-3736203f4da8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a820fce-0781-484f-849f-3736203f4da8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae4e9747-42d7-4130-a6b3-3cb2f4075010' class='xr-var-data-in' type='checkbox'><label for='data-ae4e9747-42d7-4130-a6b3-3cb2f4075010' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>Length of average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-d8d8cc20-4b8d-4cc6-af25-abe71e49ff54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8d8cc20-4b8d-4cc6-af25-abe71e49ff54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-915ad4d0-a7e5-49a2-a8bd-5636b542a350' class='xr-var-data-in' type='checkbox'><label for='data-915ad4d0-a7e5-49a2-a8bd-5636b542a350' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>Length of average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6693,7 +6695,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-bcff721a-fd06-42b1-bfbd-f6c181341657' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcff721a-fd06-42b1-bfbd-f6c181341657' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59372d8b-0387-499f-830e-b21610db62ab' class='xr-var-data-in' type='checkbox'><label for='data-59372d8b-0387-499f-830e-b21610db62ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-9948816f-caac-4333-b698-114960e52c15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9948816f-caac-4333-b698-114960e52c15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b32fe1e-fa1d-4e2a-bd4a-afbd418bdda8' class='xr-var-data-in' type='checkbox'><label for='data-4b32fe1e-fa1d-4e2a-bd4a-afbd418bdda8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6728,7 +6730,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-e9dd84ea-dbc0-4a53-8b88-297cf1bcc3e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9dd84ea-dbc0-4a53-8b88-297cf1bcc3e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92a333ac-6fd5-47dd-97ab-e970c7496021' class='xr-var-data-in' type='checkbox'><label for='data-92a333ac-6fd5-47dd-97ab-e970c7496021' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>End time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-95c0e2d0-c122-4232-bc81-b029105094d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95c0e2d0-c122-4232-bc81-b029105094d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17df3ef9-247d-4233-a78e-1de2c8c5685e' class='xr-var-data-in' type='checkbox'><label for='data-17df3ef9-247d-4233-a78e-1de2c8c5685e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>End time for average period</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6763,7 +6765,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dKE_dt</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-8961fa11-46b9-464d-a12e-61282dff1b08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8961fa11-46b9-464d-a12e-61282dff1b08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77966e2f-0d85-4489-a399-d9838d4c119c' class='xr-var-data-in' type='checkbox'><label for='data-77966e2f-0d85-4489-a399-d9838d4c119c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Tendency of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dKE_dt</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-f50b46dc-c837-432e-9007-e175cb8af295' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f50b46dc-c837-432e-9007-e175cb8af295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2afc691c-5094-4b84-ad1a-5c9401107790' class='xr-var-data-in' type='checkbox'><label for='data-2afc691c-5094-4b84-ad1a-5c9401107790' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:mean yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Kinetic Energy Tendency of Layer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-3</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6846,7 +6848,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-396cd600-18a4-4a3a-ae2c-bee003615b02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-396cd600-18a4-4a3a-ae2c-bee003615b02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8ffdb87-737e-410d-9c47-362af2c3ee82' class='xr-var-data-in' type='checkbox'><label for='data-a8ffdb87-737e-410d-9c47-362af2c3ee82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffu</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-a959f340-e95d-46ab-9875-74f119713089' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a959f340-e95d-46ab-9875-74f119713089' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66f07afe-6cb7-4c5a-b8b8-b0c593252279' class='xr-var-data-in' type='checkbox'><label for='data-66f07afe-6cb7-4c5a-b8b8-b0c593252279' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -6929,7 +6931,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-d0b16379-5136-425c-9205-a586ac592f5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0b16379-5136-425c-9205-a586ac592f5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8366fee7-41ac-44f4-92cf-9cb48838718f' class='xr-var-data-in' type='checkbox'><label for='data-8366fee7-41ac-44f4-92cf-9cb48838718f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diffv</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-b3f73783-267f-44c7-a107-61462fe02660' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3f73783-267f-44c7-a107-61462fe02660' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d31ffc31-0cc2-45fd-9744-134bd480028d' class='xr-var-data-in' type='checkbox'><label for='data-d31ffc31-0cc2-45fd-9744-134bd480028d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Horizontal Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7012,7 +7014,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>du_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-ff677f97-55a5-4fa9-a58c-cefce75ff85a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff677f97-55a5-4fa9-a58c-cefce75ff85a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5ce4387-d2ac-40d8-87b8-c56d0953925b' class='xr-var-data-in' type='checkbox'><label for='data-b5ce4387-d2ac-40d8-87b8-c56d0953925b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>du_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-726e0204-009e-4dd8-a78e-937e37d31b3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-726e0204-009e-4dd8-a78e-937e37d31b3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ea87468-5c26-4794-ab4e-ac6659425838' class='xr-var-data-in' type='checkbox'><label for='data-6ea87468-5c26-4794-ab4e-ac6659425838' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7095,7 +7097,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dudt</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-33b5836e-d765-4811-aade-4e1be4a2ce56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33b5836e-d765-4811-aade-4e1be4a2ce56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe653736-3ca2-4058-93fc-a310ad471a60' class='xr-var-data-in' type='checkbox'><label for='data-fe653736-3ca2-4058-93fc-a310ad471a60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dudt</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-c30024ee-2aae-42b1-a9e9-b99920a422bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c30024ee-2aae-42b1-a9e9-b99920a422bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ba670b5-ed58-4c68-8507-0701f76eb7f4' class='xr-var-data-in' type='checkbox'><label for='data-7ba670b5-ed58-4c68-8507-0701f76eb7f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7178,7 +7180,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dv_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-65373944-42b6-4c6f-a6ec-b0598db6d05a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65373944-42b6-4c6f-a6ec-b0598db6d05a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c36cfe00-4482-4dd6-a089-4cc7f866597b' class='xr-var-data-in' type='checkbox'><label for='data-c36cfe00-4482-4dd6-a089-4cc7f866597b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dv_dt_visc</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-7495c23c-0a91-49d1-9b6d-4d07c4a65cd7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7495c23c-0a91-49d1-9b6d-4d07c4a65cd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f36a26b1-f5b0-43bc-b92d-4c51061b7dc2' class='xr-var-data-in' type='checkbox'><label for='data-f36a26b1-f5b0-43bc-b92d-4c51061b7dc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration from Vertical Viscosity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7261,7 +7263,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dvdt</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-b5eff106-dc6b-44d2-84e5-aefcccfc63c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5eff106-dc6b-44d2-84e5-aefcccfc63c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c99b4e93-3b94-433f-862a-3d6cc15ae4f6' class='xr-var-data-in' type='checkbox'><label for='data-c99b4e93-3b94-433f-862a-3d6cc15ae4f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dvdt</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-f408f131-0732-4079-a96f-dcaf2c3a5d50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f408f131-0732-4079-a96f-dcaf2c3a5d50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bc5a53b-f60f-4794-ba9c-11cb70e6f552' class='xr-var-data-in' type='checkbox'><label for='data-8bc5a53b-f60f-4794-ba9c-11cb70e6f552' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7344,7 +7346,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e2</span></div><div class='xr-var-dims'>(time, zi, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 16, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-8e3d434b-b39a-44bd-8859-e994fcec7f9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e3d434b-b39a-44bd-8859-e994fcec7f9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-860e1ef0-15e5-4fed-a5c3-f0357b5d6bbd' class='xr-var-data-in' type='checkbox'><label for='data-860e1ef0-15e5-4fed-a5c3-f0357b5d6bbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zi:point yh:mean xh:mean time: mean_pow(2)</dd><dt><span>long_name :</span></dt><dd>Interface Height Relative to Mean Sea Level</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e2</span></div><div class='xr-var-dims'>(time, zi, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 16, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-6207e4f2-bf85-41e7-b15b-28e3b8c4ecd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6207e4f2-bf85-41e7-b15b-28e3b8c4ecd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d40af0d3-462b-48e3-a986-ff45f0619d98' class='xr-var-data-in' type='checkbox'><label for='data-d40af0d3-462b-48e3-a986-ff45f0619d98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zi:point yh:mean xh:mean time: mean_pow(2)</dd><dt><span>long_name :</span></dt><dd>Interface Height Relative to Mean Sea Level</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7427,7 +7429,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-b351dab3-82a7-4230-b380-1005c218eb12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b351dab3-82a7-4230-b380-1005c218eb12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ec942d1-f445-457d-b142-611162db14d4' class='xr-var-data-in' type='checkbox'><label for='data-2ec942d1-f445-457d-b142-611162db14d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:sum yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer Thickness</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h</span></div><div class='xr-var-dims'>(time, zl, yh, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-8fe62fce-1ce4-4b86-bf8e-1c543b38771c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fe62fce-1ce4-4b86-bf8e-1c543b38771c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6351b71f-359e-4b75-af95-050f8bc13d35' class='xr-var-data-in' type='checkbox'><label for='data-6351b71f-359e-4b75-af95-050f8bc13d35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: area_t</dd><dt><span>cell_methods :</span></dt><dd>area:mean zl:sum yh:mean xh:mean time: mean</dd><dt><span>long_name :</span></dt><dd>Layer Thickness</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7510,7 +7512,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;</div><input id='attrs-c82c7e59-7225-435f-a6ed-2f6106a37b1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c82c7e59-7225-435f-a6ed-2f6106a37b1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca7240c9-0188-4eeb-85a0-a690d399653e' class='xr-var-data-in' type='checkbox'><label for='data-ca7240c9-0188-4eeb-85a0-a690d399653e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>time axis boundaries</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;</div><input id='attrs-b2850e51-3fd5-4330-a053-c8b3e14dae18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2850e51-3fd5-4330-a053-c8b3e14dae18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b19c5227-f208-4457-92bd-4dad6d71e7e9' class='xr-var-data-in' type='checkbox'><label for='data-b19c5227-f208-4457-92bd-4dad6d71e7e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calendar :</span></dt><dd>360_day</dd><dt><span>long_name :</span></dt><dd>time axis boundaries</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7545,7 +7547,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-0bcf5eab-1969-4ed8-8275-e27f92ef7031' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bcf5eab-1969-4ed8-8275-e27f92ef7031' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58bcd64b-46e8-4806-8a73-3855ef84480a' class='xr-var-data-in' type='checkbox'><label for='data-58bcd64b-46e8-4806-8a73-3855ef84480a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-1ec62f0c-1f91-4876-b28b-6c46a3d0e7ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ec62f0c-1f91-4876-b28b-6c46a3d0e7ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3224e6df-e246-403e-b77d-c21e32c48734' class='xr-var-data-in' type='checkbox'><label for='data-3224e6df-e246-403e-b77d-c21e32c48734' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7628,7 +7630,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-1886dcc7-ab82-464e-8b87-deb3f47ef8f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1886dcc7-ab82-464e-8b87-deb3f47ef8f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4948b1e-a0e7-482a-8440-4a93e8efa501' class='xr-var-data-in' type='checkbox'><label for='data-a4948b1e-a0e7-482a-8440-4a93e8efa501' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-7060c16b-fc07-4651-8dd3-6a947bb65315' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7060c16b-fc07-4651-8dd3-6a947bb65315' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dc478ac-13ef-4b0e-8cc4-db815e0b264d' class='xr-var-data-in' type='checkbox'><label for='data-7dc478ac-13ef-4b0e-8cc4-db815e0b264d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yh:mean xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Zonal Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7711,7 +7713,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uh</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-cc56c0d9-0e97-448b-9918-08f7aed9db67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc56c0d9-0e97-448b-9918-08f7aed9db67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3329c5c-59d5-40b6-b39f-5c142231f593' class='xr-var-data-in' type='checkbox'><label for='data-a3329c5c-59d5-40b6-b39f-5c142231f593' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yh:sum xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uh</span></div><div class='xr-var-dims'>(time, zl, yh, xq)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-75c539b6-3b43-4407-9aac-93ce2d860913' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75c539b6-3b43-4407-9aac-93ce2d860913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9072a88f-c31b-43bb-a800-2979c0c468b2' class='xr-var-data-in' type='checkbox'><label for='data-9072a88f-c31b-43bb-a800-2979c0c468b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yh:sum xq:point time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Zonal Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7794,7 +7796,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-45d4e305-a50d-47bf-adb2-aacf516678f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45d4e305-a50d-47bf-adb2-aacf516678f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0555e7de-9687-4934-a1a4-4a66b759de11' class='xr-var-data-in' type='checkbox'><label for='data-0555e7de-9687-4934-a1a4-4a66b759de11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-b8f56795-61ea-4d7c-99d9-726cbdcae234' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8f56795-61ea-4d7c-99d9-726cbdcae234' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e65cb0a0-1467-4663-b3f0-ba4119dd9baf' class='xr-var-data-in' type='checkbox'><label for='data-e65cb0a0-1467-4663-b3f0-ba4119dd9baf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7877,7 +7879,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-e8ffb75a-095e-4f57-a530-fd9d74b4060c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8ffb75a-095e-4f57-a530-fd9d74b4060c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffc82b11-62bb-4f86-9d92-0c41a633bab8' class='xr-var-data-in' type='checkbox'><label for='data-ffc82b11-62bb-4f86-9d92-0c41a633bab8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_BT_accel</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-fab67847-130f-4526-bcd4-f307d0efbecb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fab67847-130f-4526-bcd4-f307d0efbecb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4c965ca-3be4-4764-872d-7c7fb234c59d' class='xr-var-data-in' type='checkbox'><label for='data-e4c965ca-3be4-4764-872d-7c7fb234c59d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:mean yq:point xh:mean time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Barotropic Anomaly Meridional Acceleration</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m s-2</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -7960,7 +7962,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-a172593b-06e2-4a8d-bc1f-306c00642fe4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a172593b-06e2-4a8d-bc1f-306c00642fe4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47e2bcaf-e910-46d3-b384-b40742b4053c' class='xr-var-data-in' type='checkbox'><label for='data-47e2bcaf-e910-46d3-b384-b40742b4053c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yq:point xh:sum time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(time, zl, yq, xh)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 15, 560, 240), meta=np.ndarray&gt;</div><input id='attrs-6892c840-91e5-4a7a-a851-84f08968d93e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6892c840-91e5-4a7a-a851-84f08968d93e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a00c2f35-246a-4dd5-bc12-feaeaa14d5ed' class='xr-var-data-in' type='checkbox'><label for='data-a00c2f35-246a-4dd5-bc12-feaeaa14d5ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>zl:sum yq:point xh:sum time: mean</dd><dt><span>interp_method :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Meridional Thickness Flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m3 s-1</dd></dl></div><div class='xr-var-data'><table>\n",
        "<tr>\n",
        "<td>\n",
        "<table>\n",
@@ -8043,7 +8045,7 @@
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-da42350d-c9db-4ef5-9b93-70f77b7bab55' class='xr-section-summary-in' type='checkbox'  checked><label for='section-da42350d-c9db-4ef5-9b93-70f77b7bab55' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>associated_files :</span></dt><dd>area_t: static.nc</dd><dt><span>filename :</span></dt><dd>averages_00030002.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa607362-9ee6-416a-9504-e83ace6c248b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa607362-9ee6-416a-9504-e83ace6c248b' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>associated_files :</span></dt><dd>area_t: static.nc</dd><dt><span>filename :</span></dt><dd>averages_00030002.nc</dd><dt><span>grid_tile :</span></dt><dd>N/A</dd><dt><span>grid_type :</span></dt><dd>regular</dd><dt><span>title :</span></dt><dd>NeverWorld2</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -8079,7 +8081,7 @@
        "    title:             NeverWorld2"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/gcm_filters/filter.py b/gcm_filters/filter.py
index 3c8e04d..db00211 100644
--- a/gcm_filters/filter.py
+++ b/gcm_filters/filter.py
@@ -12,7 +12,13 @@
 from scipy import interpolate
 
 from .gpu_compat import get_array_module
-from .kernels import ALL_KERNELS, BaseScalarLaplacian, BaseVectorLaplacian, GridType
+from .kernels import (
+    ALL_KERNELS,
+    AreaWeightedMixin,
+    BaseScalarLaplacian,
+    BaseVectorLaplacian,
+    GridType,
+)
 
 
 FilterShape = enum.Enum("FilterShape", ["GAUSSIAN", "TAPER"])
@@ -173,6 +179,11 @@ def filter_func(field, *args):
         laplacian = Laplacian(**grid_vars)
         np = get_array_module(field)
         field_bar = field.copy()  # Initalize the filtering process
+
+        # prepare field for filtering (this multiplies by area for simple fixed factor
+        # filters, and does nothing for all other filters)
+        field_bar = laplacian.prepare(field_bar)
+
         for i in range(filter_spec.n_steps_total):
             if filter_spec.is_laplacian[i]:
                 s_l = np.real(filter_spec.s[i])
@@ -186,6 +197,11 @@ def filter_func(field, *args):
                     temp_l * 2 * np.real(s_b) / np.abs(s_b) ** 2
                     + temp_b * 1 / np.abs(s_b) ** 2
                 )
+
+        # finalize filtering (this divides by area for simple fixed factor filters,
+        # and does nothing for all other filters)
+        field_bar = laplacian.finalize(field_bar)
+
         return field_bar
 
     return filter_func
@@ -209,6 +225,11 @@ def filter_func_vec(ufield, vfield, *args):
         np = get_array_module(ufield)
         ufield_bar = ufield.copy()  # Initalize the filtering process
         vfield_bar = vfield.copy()  # Initalize the filtering process
+
+        # prepare field for filtering (this multiplies by area for simple fixed factor
+        # filters, and does nothing for all other filters)
+        (ufield_bar, vfield_bar) = laplacian.prepare(ufield_bar, vfield_bar)
+
         for i in range(filter_spec.n_steps_total):
             if filter_spec.is_laplacian[i]:
                 s_l = np.real(filter_spec.s[i])
@@ -233,6 +254,11 @@ def filter_func_vec(ufield, vfield, *args):
                     vtemp_l * 2 * np.real(s_b) / np.abs(s_b) ** 2
                     + vtemp_b * 1 / np.abs(s_b) ** 2
                 )
+
+        # finalize filtering (this divides by area for simple fixed factor filters,
+        # and does nothing for all other filters)
+        (ufield_bar, vfield_bar) = laplacian.finalize(ufield_bar, vfield_bar)
+
         return (ufield_bar, vfield_bar)
 
     return filter_func_vec
@@ -262,7 +288,7 @@ class Filter:
     grid_type : GridType
         what sort of grid we are dealing with
     grid_vars : dict
-        dictionary of extra parameters used to initialize the grid laplacian
+        dictionary of extra parameters used to initialize the grid Laplacian
 
     Attributes
     ----------
@@ -280,6 +306,17 @@ class Filter:
 
     def __post_init__(self):
 
+        self.Laplacian = ALL_KERNELS[self.grid_type]
+
+        # Determine whether this is simple fixed factor filter; in that case we need dx_min = 1
+        if issubclass(self.Laplacian, AreaWeightedMixin):
+            if self.dx_min != 1:
+                raise ValueError(
+                    f"Provided Laplacian is for simple fixed factor filtering, "
+                    "where transformed field is filtered on a regular grid with dx = dy = 1. "
+                    "dx_min must be set to 1."
+                )
+
         # Get default number of steps
         filter_factor = self.filter_scale / self.dx_min
         if self.ndim > 2:
@@ -299,8 +336,8 @@ def __post_init__(self):
 
         if self.n_steps < n_steps_default:
             warnings.warn(
-                "Warning: You have set n_steps below the default. Results might not be accurate.",
-                UserWarning,
+                "You have set n_steps below the default. Results might not be accurate.",
+                stacklevel=2,
             )
 
         # Issue numerical stability warning, if needed
@@ -309,8 +346,9 @@ def __post_init__(self):
         ]
         if filter_factor >= max_filter_factor:
             warnings.warn(
-                "Warning: Filter scale much larger than grid scale -> numerical instability possible",
-                UserWarning,
+                "Filter scale much larger than grid scale -> numerical instability possible. "
+                "More information on numerical instability can be found at https://gcm-filters.readthedocs.io/en/latest/theory.html.",
+                stacklevel=2,
             )
 
         self.filter_spec = _compute_filter_spec(
@@ -323,7 +361,6 @@ def __post_init__(self):
         )
 
         # check that we have all the required grid aguments
-        self.Laplacian = ALL_KERNELS[self.grid_type]
 
         if not set(self.Laplacian.required_grid_args()) == set(self.grid_vars):
             raise ValueError(
@@ -369,7 +406,7 @@ def plot_shape(self, ax=None):
 
     def apply(self, field, dims):
         """Filter a field with scalar Laplacian across the dimensions specified by dims."""
-        if not issubclass(self.Laplacian, BaseScalarLaplacian):
+        if issubclass(self.Laplacian, BaseVectorLaplacian):
             raise ValueError(
                 f"Provided Laplacian {self.Laplacian} is a vector Laplacian. "
                 f"The ``.apply`` method is only suitable for scalar Laplacians."
@@ -388,6 +425,7 @@ def apply(self, field, dims):
             output_dtypes=[field.dtype],
             dask="parallelized",
         )
+
         return field_smooth
 
     def apply_to_vector(self, ufield, vfield, dims):
@@ -412,4 +450,5 @@ def apply_to_vector(self, ufield, vfield, dims):
             output_dtypes=[ufield.dtype, vfield.dtype],
             dask="parallelized",
         )
+
         return (ufield_smooth, vfield_smooth)
diff --git a/gcm_filters/kernels.py b/gcm_filters/kernels.py
index 1b90cc7..d179838 100644
--- a/gcm_filters/kernels.py
+++ b/gcm_filters/kernels.py
@@ -10,14 +10,15 @@
 from .gpu_compat import ArrayType, get_array_module
 
 
-# not married to the term "Cartesian"
 GridType = enum.Enum(
     "GridType",
     [
         "REGULAR",
+        "REGULAR_AREA_WEIGHTED",
         "REGULAR_WITH_LAND",
+        "REGULAR_WITH_LAND_AREA_WEIGHTED",
         "IRREGULAR_WITH_LAND",
-        "TRIPOLAR_REGULAR_WITH_LAND",
+        "TRIPOLAR_REGULAR_WITH_LAND_AREA_WEIGHTED",
         "TRIPOLAR_POP_WITH_LAND",
         "VECTOR_C_GRID",
     ],
@@ -38,9 +39,17 @@ def _prepare_tripolar_exchanges(field):
 
 @dataclass
 class BaseScalarLaplacian(ABC):
+    """̵Base class for scalar Laplacians."""
+
+    def prepare(self, field):
+        return field
+
     def __call__(self, field):
         pass  # pragma: no cover
 
+    def finalize(self, field):
+        return field
+
     # change to property when we are using python 3.9
     # https://stackoverflow.com/questions/128573/using-property-on-classmethods
     @classmethod
@@ -53,9 +62,17 @@ def required_grid_args(self):
 
 @dataclass
 class BaseVectorLaplacian(ABC):
+    """Base class for vector Laplacians."""
+
+    def prepare(self, ufield, vfield):
+        return (ufield, vfield)
+
     def __call__(self, ufield, vfield):
         pass  # pragma: no cover
 
+    def finalize(self, ufield, vfield):
+        return (ufield, vfield)
+
     # change to property when we are using python 3.9
     # https://stackoverflow.com/questions/128573/using-property-on-classmethods
     @classmethod
@@ -66,9 +83,27 @@ def required_grid_args(self):
             return []
 
 
+@dataclass
+class AreaWeightedMixin(ABC):
+    """Mixin to weight and deweight a field by the cell area.
+
+    Attributes
+    ----------
+    area: cell area
+    """
+
+    area: ArrayType
+
+    def prepare(self, field):
+        return field * self.area
+
+    def finalize(self, field):
+        return field / self.area
+
+
 @dataclass
 class RegularLaplacian(BaseScalarLaplacian):
-    """̵Laplacian for regularly spaced Cartesian grids."""
+    """̵Scalar Laplacian for regularly spaced Cartesian grids."""
 
     def __call__(self, field: ArrayType):
         np = get_array_module(field)
@@ -84,9 +119,30 @@ def __call__(self, field: ArrayType):
 ALL_KERNELS[GridType.REGULAR] = RegularLaplacian
 
 
+@dataclass
+class RegularLaplacianWithArea(AreaWeightedMixin, RegularLaplacian):
+    """̵Scalar Laplacian operating on a locally orthogonal grid in three steps:
+
+    1. :py:meth:`prepare`: Field is multiplied by the cell area. This corresponds to transforming the field from the original locally orthogonal grid to a regularly spaced Cartesian grid with dx = dy = 1.
+    2. :meth:`__call__`: Laplacian acts on regular Cartesian grid.
+    3. :meth:`finalize`: Diffused field is divided by the cell area of the original grid. This corresponds to transforming the field from the regular Cartesian grid back to the original grid.
+
+    Attributes
+    ----------
+    area: cell area of original grid
+    """
+
+    area: ArrayType
+
+    pass
+
+
+ALL_KERNELS[GridType.REGULAR_AREA_WEIGHTED] = RegularLaplacianWithArea
+
+
 @dataclass
 class RegularLaplacianWithLandMask(BaseScalarLaplacian):
-    """̵Laplacian for regularly spaced Cartesian grids with land mask.
+    """̵Scalar Laplacian for regularly spaced Cartesian grids with land mask.
 
     Attributes
     ----------
@@ -97,7 +153,6 @@ class RegularLaplacianWithLandMask(BaseScalarLaplacian):
 
     def __post_init__(self):
         np = get_array_module(self.wet_mask)
-
         self.wet_fac = (
             np.roll(self.wet_mask, -1, axis=-1)
             + np.roll(self.wet_mask, 1, axis=-1)
@@ -126,9 +181,36 @@ def __call__(self, field: ArrayType):
 ALL_KERNELS[GridType.REGULAR_WITH_LAND] = RegularLaplacianWithLandMask
 
 
+@dataclass
+class RegularLaplacianWithLandMaskAndArea(
+    AreaWeightedMixin, RegularLaplacianWithLandMask
+):
+    """̵Scalar Laplacian operating on a locally orthogonal grid with land mask in three steps:
+
+    1. :py:meth:`prepare`: Field is multiplied by the cell area. This corresponds to transforming the field from the original locally orthogonal grid to a regularly spaced Cartesian grid with dx = dy = 1.
+    2. :meth:`__call__`: Laplacian acts on regular Cartesian grid.
+    3. :meth:`finalize`: Diffused field is divided by the cell area of the original grid. This corresponds to transforming the field from the regular Cartesian grid back to the original grid.
+
+    Attributes
+    ----------
+    area: cell area of original grid
+    wet_mask: Mask array, 1 for ocean, 0 for land
+    """
+
+    area: ArrayType
+    wet_mask: ArrayType
+
+    pass
+
+
+ALL_KERNELS[
+    GridType.REGULAR_WITH_LAND_AREA_WEIGHTED
+] = RegularLaplacianWithLandMaskAndArea
+
+
 @dataclass
 class IrregularLaplacianWithLandMask(BaseScalarLaplacian):
-    """̵Laplacian for irregularly spaced Cartesian grids with land mask.
+    """̵Scalar Laplacian for locally orthogonal grids with land mask.
 
     Attributes
     ----------
@@ -193,14 +275,20 @@ def __call__(self, field: ArrayType):
 
 
 @dataclass
-class TripolarRegularLaplacianTpoint(BaseScalarLaplacian):
-    """̵Laplacian for fields defined at T-points on POP tripolar grid geometry with land mask, but assuming that dx = dy = 1
+class TripolarRegularLaplacianTpoint(AreaWeightedMixin, BaseScalarLaplacian):
+    """Scalar Laplacian operating on a locally orthogonal grid with land mask and a tripole boundary. There are three steps:
+
+    1. :py:meth:`prepare`: Field is multiplied by the cell area. This corresponds to transforming the field from the original locally orthogonal grid to a regularly spaced Cartesian grid with dx = dy = 1.
+    2. :meth:`__call__`: Laplacian acts on regular Cartesian grid.
+    3. :meth:`finalize`: Diffused field is divided by the cell area of the original grid. This corresponds to transforming the field from the regular Cartesian grid back to the original grid.
 
     Attributes
     ----------
+    area: cell area of original grid
     wet_mask: Mask array, 1 for ocean, 0 for land
     """
 
+    area: ArrayType
     wet_mask: ArrayType
 
     def __post_init__(self):
@@ -216,7 +304,7 @@ def __post_init__(self):
             + np.roll(wet_mask_extended, 1, axis=-1)
             + np.roll(wet_mask_extended, -1, axis=-2)
             + np.roll(wet_mask_extended, 1, axis=-2)
-        )  # todo: inherit this operation from CartesianLaplacianWithLandMask
+        )  # todo: inherit this operation from RegularLaplacianWithLandMask
 
     def __call__(self, field: ArrayType):
         np = get_array_module(field)
@@ -231,7 +319,7 @@ def __call__(self, field: ArrayType):
             + np.roll(data, 1, axis=-1)
             + np.roll(data, -1, axis=-2)
             + np.roll(data, 1, axis=-2)
-        )  # todo: inherit this operation from CartesianLaplacianWithLandMask
+        )  # todo: inherit this operation from RegularLaplacianWithLandMask
 
         out = out[..., :-1, :]  # disregard appended row
 
@@ -239,21 +327,23 @@ def __call__(self, field: ArrayType):
         return out
 
 
-ALL_KERNELS[GridType.TRIPOLAR_REGULAR_WITH_LAND] = TripolarRegularLaplacianTpoint
+ALL_KERNELS[
+    GridType.TRIPOLAR_REGULAR_WITH_LAND_AREA_WEIGHTED
+] = TripolarRegularLaplacianTpoint
 
 
 @dataclass
 class POPTripolarLaplacianTpoint(BaseScalarLaplacian):
-    """̵Laplacian for irregularly spaced Cartesian grids with land mask.
+    """̵Scalar Laplacian for locally orthogonal grid with land mask and tripole boundary condition, as for example used in the global POP configuration. This Laplacian works for scalar fields located at T-points.
 
     Attributes
     ----------
     wet_mask: Mask array, 1 for ocean, 0 for land; can be obtained via xr.where(KMT>0, 1, 0)
-    dxe: x-spacing centered at eastern T-cell edge, provided by model diagnostic HUS(nlat, nlon)
-    dye: y-spacing centered at eastern  T-cell edge, provided by model diagnostic HTE(nlat, nlon)
-    dxn: x-spacing centered at northern T-cell edge, provided by model diagnostic HTN(nlat, nlon)
-    dyn: y-spacing centered at northern T-cell edge, provided by model diagnostic HUW(nlat, nlon)
-    tarea: cell area, provided by model diagnostic TAREA(nlat, nlon)
+    dxe: x-spacing centered at eastern T-cell edge, provided by POP model diagnostic HUS(nlat, nlon)
+    dye: y-spacing centered at eastern  T-cell edge, provided by POP model diagnostic HTE(nlat, nlon)
+    dxn: x-spacing centered at northern T-cell edge, provided by POP model diagnostic HTN(nlat, nlon)
+    dyn: y-spacing centered at northern T-cell edge, provided by POP model diagnostic HUW(nlat, nlon)
+    tarea: cell area, provided by POP model diagnostic TAREA(nlat, nlon)
     """
 
     wet_mask: ArrayType
@@ -316,7 +406,7 @@ def __call__(self, field: ArrayType):
 
 @dataclass
 class CgridVectorLaplacian(BaseVectorLaplacian):
-    """̵Vector Laplacian on C-Grid.
+    """̵Vector Laplacian on C-Grid. The implementation follows the friction operator suggested by Griffies and Hallberg, 2000.
 
     Attributes
     ----------
@@ -424,8 +514,7 @@ def __call__(self, ufield: ArrayType, vfield: ArrayType):
 
 
 def required_grid_vars(grid_type: GridType):
-    """Utility function for figuring out the required grid variables
-    needed by each grid type.
+    """Utility function for figuring out the required grid variables needed by each grid type.
 
     Parameters
     ----------
diff --git a/tests/test_filter.py b/tests/test_filter.py
index bcab879..76ad4f5 100644
--- a/tests/test_filter.py
+++ b/tests/test_filter.py
@@ -29,6 +29,7 @@ def _check_equal_filter_spec(spec1, spec2):
                 filter_shape=FilterShape.GAUSSIAN,
                 transition_width=np.pi,
                 ndim=2,
+                grid_vars={},
             ),
             FilterSpec(
                 n_steps_total=10,
@@ -80,6 +81,7 @@ def _check_equal_filter_spec(spec1, spec2):
                 filter_shape=FilterShape.TAPER,
                 transition_width=np.pi,
                 ndim=1,
+                grid_vars={},
             ),
             FilterSpec(
                 n_steps_total=3,
@@ -114,6 +116,16 @@ def test_filter_spec(filter_args, expected_filter_spec):
 vector_grids = [gt for gt in GridType if gt.name in {"VECTOR_C_GRID"}]
 # all remaining grids are for scalar Laplacians
 scalar_grids = [gt for gt in GridType if gt not in vector_grids]
+scalar_transformed_regular_grids = [
+    gt
+    for gt in GridType
+    if gt.name
+    in {
+        "REGULAR_AREA_WEIGHTED",
+        "REGULAR_WITH_LAND_AREA_WEIGHTED",
+        "TRIPOLAR_REGULAR_WITH_LAND_AREA_WEIGHTED",
+    }
+]
 
 
 @pytest.fixture(scope="module", params=scalar_grids)
@@ -125,47 +137,64 @@ def grid_type_and_input_ds(request):
 
     grid_vars = {}
 
+    if grid_type == GridType.REGULAR_AREA_WEIGHTED:
+        area = 0.5 + np.random.rand(ny, nx)
+        da_area = xr.DataArray(area, dims=["y", "x"])
+        grid_vars = {"area": da_area}
     if grid_type == GridType.REGULAR_WITH_LAND:
         mask_data = np.ones_like(data)
         mask_data[: (ny // 2), : (nx // 2)] = 0
         da_mask = xr.DataArray(mask_data, dims=["y", "x"])
         grid_vars = {"wet_mask": da_mask}
+    if grid_type == GridType.REGULAR_WITH_LAND_AREA_WEIGHTED:
+        area = 0.5 + np.random.rand(ny, nx)
+        da_area = xr.DataArray(area, dims=["y", "x"])
+        mask_data = np.ones_like(data)
+        mask_data[: (ny // 2), : (nx // 2)] = 0
+        da_mask = xr.DataArray(mask_data, dims=["y", "x"])
+        grid_vars = {"area": da_area, "wet_mask": da_mask}
     if grid_type == GridType.IRREGULAR_WITH_LAND:
         mask_data = np.ones_like(data)
         mask_data[: (ny // 2), : (nx // 2)] = 0
         da_mask = xr.DataArray(mask_data, dims=["y", "x"])
-        grid_data = np.ones_like(data)
+        grid_data = 0.5 + np.random.rand(ny, nx)
         da_grid = xr.DataArray(grid_data, dims=["y", "x"])
+        da_area = xr.DataArray(grid_data * grid_data, dims=["y", "x"])
+        da_kappa = xr.DataArray(np.ones_like(data), dims=["y", "x"])
+
         grid_vars = {
             "wet_mask": da_mask,
             "dxw": da_grid,
             "dyw": da_grid,
             "dxs": da_grid,
             "dys": da_grid,
-            "area": da_grid,
-            "kappa_w": da_grid,
-            "kappa_s": da_grid,
+            "area": da_area,
+            "kappa_w": da_kappa,
+            "kappa_s": da_kappa,
         }
-    if grid_type == GridType.TRIPOLAR_REGULAR_WITH_LAND:
+    if grid_type == GridType.TRIPOLAR_REGULAR_WITH_LAND_AREA_WEIGHTED:
+        area = 0.5 + np.random.rand(ny, nx)
+        da_area = xr.DataArray(area, dims=["y", "x"])
         mask_data = np.ones_like(data)
         mask_data[: (ny // 2), : (nx // 2)] = 0
         mask_data[0, :] = 0  #  Antarctica
         da_mask = xr.DataArray(mask_data, dims=["y", "x"])
-        grid_vars = {"wet_mask": da_mask}
+        grid_vars = {"area": da_area, "wet_mask": da_mask}
     if grid_type == GridType.TRIPOLAR_POP_WITH_LAND:
         mask_data = np.ones_like(data)
         mask_data[: (ny // 2), : (nx // 2)] = 0
         mask_data[0, :] = 0  #  Antarctica
         da_mask = xr.DataArray(mask_data, dims=["y", "x"])
-        grid_data = np.ones_like(data)
+        grid_data = 0.5 + np.random.rand(ny, nx)
         da_grid = xr.DataArray(grid_data, dims=["y", "x"])
+        da_area = xr.DataArray(grid_data * grid_data, dims=["y", "x"])
         grid_vars = {
             "wet_mask": da_mask,
             "dxe": da_grid,
             "dye": da_grid,
             "dxn": da_grid,
             "dyn": da_grid,
-            "tarea": da_grid,
+            "tarea": da_area,
         }
 
     da = xr.DataArray(data, dims=["y", "x"])
@@ -264,9 +293,13 @@ def test_diffusion_filter(grid_type_and_input_ds, filter_args):
     filtered = filter.apply(da, dims=["y", "x"])
 
     # check conservation
-    # this would need to be replaced by a proper area-weighted integral
-    da_sum = da.sum()
-    filtered_sum = filtered.sum()
+    area = 1
+    for k, v in grid_vars.items():
+        if "area" in k:
+            area = v
+            break
+    da_sum = (da * area).sum()
+    filtered_sum = (filtered * area).sum()
     xr.testing.assert_allclose(da_sum, filtered_sum)
 
     # check that we get an error if we pass scalar Laplacian to .apply_to vector,
@@ -294,13 +327,19 @@ def test_diffusion_filter(grid_type_and_input_ds, filter_args):
     # check that we get a warning if n_steps < n_steps_default
     bad_filter_args["ndim"] = 2
     bad_filter_args["n_steps"] = 3
-    with pytest.warns(UserWarning, match=r"Warning: You have set n_steps .*"):
+    with pytest.warns(UserWarning, match=r"You have set n_steps .*"):
         filter = Filter(grid_type=grid_type, grid_vars=grid_vars, **bad_filter_args)
     # check that we get a warning if numerical instability possible
     bad_filter_args["n_steps"] = 0
     bad_filter_args["filter_scale"] = 1000
-    with pytest.warns(UserWarning, match=r"Warning: Filter scale much larger .*"):
+    with pytest.warns(UserWarning, match=r"Filter scale much larger .*"):
         filter = Filter(grid_type=grid_type, grid_vars=grid_vars, **bad_filter_args)
+    # check that we get an error if we pass dx_min != 1 to a regular scalar Laplacian
+    if grid_type in scalar_transformed_regular_grids:
+        bad_filter_args["filter_scale"] = 3  # restore good value for filter scale
+        bad_filter_args["dx_min"] = 3
+        with pytest.raises(ValueError, match=r"Provided Laplacian .*"):
+            filter = Filter(grid_type=grid_type, grid_vars=grid_vars, **bad_filter_args)
 
 
 #################### Visosity-based filter tests ########################################
diff --git a/tests/test_kernels.py b/tests/test_kernels.py
index 699b894..d91a4f9 100644
--- a/tests/test_kernels.py
+++ b/tests/test_kernels.py
@@ -3,7 +3,13 @@
 import numpy as np
 import pytest
 
-from gcm_filters.kernels import ALL_KERNELS, GridType, required_grid_vars
+from gcm_filters.kernels import (
+    ALL_KERNELS,
+    AreaWeightedMixin,
+    BaseScalarLaplacian,
+    GridType,
+    required_grid_vars,
+)
 
 
 # define (for now: hard-code) which grids are associated with vector Laplacians
@@ -19,23 +25,34 @@ def grid_type_field_and_extra_kwargs(request):
     data = np.random.rand(ny, nx)
 
     extra_kwargs = {}
+    if grid_type == GridType.REGULAR_AREA_WEIGHTED:
+        area = 0.5 + np.random.rand(ny, nx)
+        extra_kwargs["area"] = area
     if grid_type == GridType.REGULAR_WITH_LAND:
         mask_data = np.ones_like(data)
         mask_data[: (ny // 2), : (nx // 2)] = 0
         extra_kwargs["wet_mask"] = mask_data
+    if grid_type == GridType.REGULAR_WITH_LAND_AREA_WEIGHTED:
+        area = 0.5 + np.random.rand(ny, nx)
+        extra_kwargs["area"] = area
+        mask_data = np.ones_like(data)
+        mask_data[: (ny // 2), : (nx // 2)] = 0
+        extra_kwargs["wet_mask"] = mask_data
     if grid_type == GridType.IRREGULAR_WITH_LAND:
         mask_data = np.ones_like(data)
         mask_data[: (ny // 2), : (nx // 2)] = 0
         extra_kwargs["wet_mask"] = mask_data
-        grid_data = np.ones_like(data)
+        grid_data = 0.5 + np.random.rand(ny, nx)
         extra_kwargs["dxw"] = grid_data
         extra_kwargs["dyw"] = grid_data
         extra_kwargs["dxs"] = grid_data
         extra_kwargs["dys"] = grid_data
-        extra_kwargs["area"] = grid_data
-        extra_kwargs["kappa_w"] = grid_data
-        extra_kwargs["kappa_s"] = grid_data
-    if grid_type == GridType.TRIPOLAR_REGULAR_WITH_LAND:
+        extra_kwargs["area"] = grid_data * grid_data
+        extra_kwargs["kappa_w"] = np.ones_like(data)
+        extra_kwargs["kappa_s"] = np.ones_like(data)
+    if grid_type == GridType.TRIPOLAR_REGULAR_WITH_LAND_AREA_WEIGHTED:
+        area = 0.5 + np.random.rand(ny, nx)
+        extra_kwargs["area"] = area
         mask_data = np.ones_like(data)
         mask_data[: (ny // 2), : (nx // 2)] = 0
         mask_data[0, :] = 0  #  Antarctica
@@ -45,12 +62,12 @@ def grid_type_field_and_extra_kwargs(request):
         mask_data[: (ny // 2), : (nx // 2)] = 0
         mask_data[0, :] = 0  #  Antarctica
         extra_kwargs["wet_mask"] = mask_data
-        grid_data = np.ones_like(data)
+        grid_data = 0.5 + np.random.rand(ny, nx)
         extra_kwargs["dxe"] = grid_data
         extra_kwargs["dye"] = grid_data
         extra_kwargs["dxn"] = grid_data
         extra_kwargs["dyn"] = grid_data
-        extra_kwargs["tarea"] = grid_data
+        extra_kwargs["tarea"] = grid_data * grid_data
 
     return grid_type, data, extra_kwargs
 
@@ -61,7 +78,18 @@ def test_conservation(grid_type_field_and_extra_kwargs):
 
     LaplacianClass = ALL_KERNELS[grid_type]
     laplacian = LaplacianClass(**extra_kwargs)
-    res = laplacian(data)
+    area = 1  # default value for regular Cartesian grids
+    # - Laplacians that belong to AreaWeithedMixin class
+    #   act on (transformed) regular grid with dx = dy = 1;
+    #   --> test with area = 1
+    # - all other Laplacians  act on potentially irregular grid
+    #   --> need area information
+    if not issubclass(LaplacianClass, AreaWeightedMixin):
+        for k, v in extra_kwargs.items():
+            if "area" in k:
+                area = v
+                break
+    res = laplacian(data) * area
     np.testing.assert_allclose(res.sum(), 0.0, atol=1e-12)
 
 
@@ -187,9 +215,40 @@ def test_flux_in_x_direction(grid_type_field_and_extra_kwargs):
 tripolar_grids = [gt for gt in GridType if gt.name.startswith("TRIPOLAR")]
 
 
-def test_for_antarctica(grid_type_field_and_extra_kwargs):
+@pytest.fixture(scope="module", params=tripolar_grids)
+# the following test data mirrors a regular grid because
+# these are the assumptions of test_tripolar_exchanges
+def tripolar_grid_type_field_and_extra_kwargs(request):
+    grid_type = request.param
+    ny, nx = (128, 256)
+    data = np.random.rand(ny, nx)
+
+    extra_kwargs = {}
+    if grid_type == GridType.TRIPOLAR_REGULAR_WITH_LAND_AREA_WEIGHTED:
+        area = np.ones_like(data)
+        extra_kwargs["area"] = area
+        mask_data = np.ones_like(data)
+        mask_data[: (ny // 2), : (nx // 2)] = 0
+        mask_data[0, :] = 0  #  Antarctica
+        extra_kwargs["wet_mask"] = mask_data
+    if grid_type == GridType.TRIPOLAR_POP_WITH_LAND:
+        mask_data = np.ones_like(data)
+        mask_data[: (ny // 2), : (nx // 2)] = 0
+        mask_data[0, :] = 0  #  Antarctica
+        extra_kwargs["wet_mask"] = mask_data
+        grid_data = np.ones_like(data)
+        extra_kwargs["dxe"] = grid_data
+        extra_kwargs["dye"] = grid_data
+        extra_kwargs["dxn"] = grid_data
+        extra_kwargs["dyn"] = grid_data
+        extra_kwargs["tarea"] = grid_data * grid_data
+
+    return grid_type, data, extra_kwargs
+
+
+def test_for_antarctica(tripolar_grid_type_field_and_extra_kwargs):
     """This test checks that we get an error if southernmost row of wet_mask has entry not equal to zero."""
-    grid_type, _, extra_kwargs = grid_type_field_and_extra_kwargs
+    grid_type, _, extra_kwargs = tripolar_grid_type_field_and_extra_kwargs
 
     if grid_type in tripolar_grids:
         nx = np.shape(extra_kwargs["wet_mask"])[1]
@@ -202,9 +261,9 @@ def test_for_antarctica(grid_type_field_and_extra_kwargs):
             laplacian = LaplacianClass(**bad_kwargs)
 
 
-def test_tripolar_exchanges(grid_type_field_and_extra_kwargs):
+def test_tripolar_exchanges(tripolar_grid_type_field_and_extra_kwargs):
     """This test checks that Laplacian exchanges across northern boundary seam line of tripolar grid are correct."""
-    grid_type, data, extra_kwargs = grid_type_field_and_extra_kwargs
+    grid_type, data, extra_kwargs = tripolar_grid_type_field_and_extra_kwargs
 
     if grid_type in tripolar_grids:
         LaplacianClass = ALL_KERNELS[grid_type]
@@ -216,9 +275,12 @@ def test_tripolar_exchanges(grid_type_field_and_extra_kwargs):
         random_loc = np.random.randint(1, nx // 2 - 2)
         delta[-1, random_loc] = 1
 
+        regular_kwargs = copy.deepcopy(extra_kwargs)
+        regular_kwargs["wet_mask"][0, random_loc] = 1
+
         diffused = laplacian(delta)
-        # check that delta function gets diffused isotropically across northern boundary
-        # this would need to be replaced once we provide irregular grid data in fixture
+        # check that delta function gets diffused isotropically across northern boundary;
+        # this assumes regular grid data in fixture
         np.testing.assert_allclose(
             diffused[-2, random_loc], diffused[-1, nx - random_loc - 1], atol=1e-12
         )