rtofs_global.ipynb

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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                           (MT: 1, Y: 3298, X: 4500)\n",
       "Coordinates:\n",
       "  * MT                                (MT) datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date                              (MT) float64 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "  * Y                                 (Y) int32 1 2 3 4 ... 3295 3296 3297 3298\n",
       "  * X                                 (X) int32 1 2 3 4 ... 4497 4498 4499 4500\n",
       "    Latitude                          (Y, X) float32 dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;\n",
       "    Longitude                         (Y, X) float32 dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;\n",
       "Data variables:\n",
       "    ssh                               (MT, Y, X) float32 dask.array&lt;chunksize=(1, 825, 1125), meta=np.ndarray&gt;\n",
       "    u_barotropic_velocity             (MT, Y, X) float32 dask.array&lt;chunksize=(1, 825, 1125), meta=np.ndarray&gt;\n",
       "    v_barotropic_velocity             (MT, Y, X) float32 dask.array&lt;chunksize=(1, 825, 1125), meta=np.ndarray&gt;\n",
       "    surface_boundary_layer_thickness  (MT, Y, X) float32 dask.array&lt;chunksize=(1, 825, 1125), meta=np.ndarray&gt;\n",
       "    mixed_layer_thickness             (MT, Y, X) float32 dask.array&lt;chunksize=(1, 825, 1125), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:  CF-1.0\n",
       "    title:        HYCOM ATLb2.00\n",
       "    institution:  National Centers for Environmental Prediction\n",
       "    source:       HYCOM archive file\n",
       "    experiment:   92.8\n",
       "    history:      archv2ncdf2d</pre><div class='xr-wrap' style='display:none'><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-d7e45b3a-7718-4d9c-97c3-68c35e094640' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d7e45b3a-7718-4d9c-97c3-68c35e094640' 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'>MT</span>: 1</li><li><span class='xr-has-index'>Y</span>: 3298</li><li><span class='xr-has-index'>X</span>: 4500</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5faae54e-ed29-4933-ae24-6d77fabeb6d7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5faae54e-ed29-4933-ae24-6d77fabeb6d7' 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'>MT</span></div><div class='xr-var-dims'>(MT)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-09-21T10:00:00</div><input id='attrs-c1f635ea-0833-4dd6-9dc3-de69389aabaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1f635ea-0833-4dd6-9dc3-de69389aabaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71564486-67e0-420f-b586-320fb2c0b085' class='xr-var-data-in' type='checkbox'><label for='data-71564486-67e0-420f-b586-320fb2c0b085' title='Show/Hide data repr'><svg class='icon xr-icon-database'><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></dl></div><div class='xr-var-data'><pre>array([&#x27;2023-09-21T10:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Date</span></div><div class='xr-var-dims'>(MT)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-5b4b3aca-d1fa-4956-8995-2af21093b7d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b4b3aca-d1fa-4956-8995-2af21093b7d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00f605be-1a9d-4873-a434-5966013438c7' class='xr-var-data-in' type='checkbox'><label for='data-00f605be-1a9d-4873-a434-5966013438c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>date</dd><dt><span>units :</span></dt><dd>day as %Y%m%d.%f</dd><dt><span>C_format :</span></dt><dd>%13.4f</dd><dt><span>FORTRAN_format :</span></dt><dd>(f13.4)</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
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       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 3295 3296 3297 3298</div><input id='attrs-f9d8cdda-31c6-4b2f-a17a-3da034e3056b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9d8cdda-31c6-4b2f-a17a-3da034e3056b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efacadee-b087-4fc1-8edf-331ff1f9e661' class='xr-var-data-in' type='checkbox'><label for='data-efacadee-b087-4fc1-8edf-331ff1f9e661' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 3296, 3297, 3298], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 4497 4498 4499 4500</div><input id='attrs-0f408627-2dec-4a73-91ad-15ec4fcb8818' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f408627-2dec-4a73-91ad-15ec4fcb8818' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e63c51d-2cdc-41b2-bd6c-05179484bd09' class='xr-var-data-in' type='checkbox'><label for='data-6e63c51d-2cdc-41b2-bd6c-05179484bd09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 4498, 4499, 4500], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;</div><input id='attrs-295b9d29-8162-4480-84a9-4cc9a9c9cacc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-295b9d29-8162-4480-84a9-4cc9a9c9cacc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4b96e5e-6b6b-46fe-87e3-75b8c970a6a8' class='xr-var-data-in' type='checkbox'><label for='data-f4b96e5e-6b6b-46fe-87e3-75b8c970a6a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 56.61 MiB </td>\n",
       "                        <td> 3.54 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (825, 1125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Longitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;</div><input id='attrs-d51423f3-5a47-4f5d-bcd2-65682ca98505' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d51423f3-5a47-4f5d-bcd2-65682ca98505' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d43a8776-6663-4376-8ef2-fe08534d9f52' class='xr-var-data-in' type='checkbox'><label for='data-d43a8776-6663-4376-8ef2-fe08534d9f52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>modulo :</span></dt><dd>360 degrees</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 56.61 MiB </td>\n",
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       "                        <td> (825, 1125) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-44577244-99b3-4678-874e-299fcf9d7bc7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-44577244-99b3-4678-874e-299fcf9d7bc7' class='xr-section-summary' >Data variables: <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>ssh</span></div><div class='xr-var-dims'>(MT, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 825, 1125), meta=np.ndarray&gt;</div><input id='attrs-dd5da940-adb6-48ce-87b3-d82317263f9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd5da940-adb6-48ce-87b3-d82317263f9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cf4999b-c0a7-4a9b-a461-adc6271d7124' class='xr-var-data-in' type='checkbox'><label for='data-0cf4999b-c0a7-4a9b-a461-adc6271d7124' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_elevation</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>valid_range :</span></dt><dd>[-1.9011002  1.5169019]</dd><dt><span>long_name :</span></dt><dd> sea surf. height  [92.8H]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 56.61 MiB </td>\n",
       "                        <td> 3.54 MiB </td>\n",
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       "                        <td> (1, 825, 1125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_barotropic_velocity</span></div><div class='xr-var-dims'>(MT, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 825, 1125), meta=np.ndarray&gt;</div><input id='attrs-e7ba9532-8915-470e-861a-9ec35a6d7657' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7ba9532-8915-470e-861a-9ec35a6d7657' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6cb36d0-0eab-478e-8718-58d59a0fb835' class='xr-var-data-in' type='checkbox'><label for='data-d6cb36d0-0eab-478e-8718-58d59a0fb835' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>barotropic_eastward_sea_water_velocity</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>valid_range :</span></dt><dd>[-1.1866853  1.1786588]</dd><dt><span>long_name :</span></dt><dd>    baro. u-vel.   [92.8H]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 56.61 MiB </td>\n",
       "                        <td> 3.54 MiB </td>\n",
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       "                    <tr>\n",
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       "                        <td> (1, 3298, 4500) </td>\n",
       "                        <td> (1, 825, 1125) </td>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> 16 chunks in 2 graph layers </td>\n",
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       "  <line x1=\"114\" y1=\"14\" x2=\"114\" y2=\"102\" />\n",
       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"102\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,102.89526461642106 24.9485979497544,102.89526461642106\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"84.948598\" y=\"122.895265\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4500</text>\n",
       "  <text x=\"164.948598\" y=\"58.921931\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,58.921931)\">3298</text>\n",
       "  <text x=\"7.474299\" y=\"115.420966\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,115.420966)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-e41558d8-b0ef-4a63-a2bc-2e69d93b7dff' class='xr-section-summary-in' type='checkbox'  ><label for='section-e41558d8-b0ef-4a63-a2bc-2e69d93b7dff' class='xr-section-summary' >Indexes: <span>(3)</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-index-name'><div>MT</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c044512c-7058-40a0-ab46-d4201096305e' class='xr-index-data-in' type='checkbox'/><label for='index-c044512c-7058-40a0-ab46-d4201096305e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2023-09-21 10:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;MT&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b463220d-88ea-40ec-a589-ea80a7f185c2' class='xr-index-data-in' type='checkbox'/><label for='index-b463220d-88ea-40ec-a589-ea80a7f185c2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       3289, 3290, 3291, 3292, 3293, 3294, 3295, 3296, 3297, 3298],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;Y&#x27;, length=3298))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>X</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-80c3ff3c-088a-4eed-ba22-c8184747f7e0' class='xr-index-data-in' type='checkbox'/><label for='index-80c3ff3c-088a-4eed-ba22-c8184747f7e0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       4491, 4492, 4493, 4494, 4495, 4496, 4497, 4498, 4499, 4500],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;X&#x27;, length=4500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1c1ad1f-5df5-4933-9856-c5332cff367b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f1c1ad1f-5df5-4933-9856-c5332cff367b' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.0</dd><dt><span>title :</span></dt><dd>HYCOM ATLb2.00</dd><dt><span>institution :</span></dt><dd>National Centers for Environmental Prediction</dd><dt><span>source :</span></dt><dd>HYCOM archive file</dd><dt><span>experiment :</span></dt><dd>92.8</dd><dt><span>history :</span></dt><dd>archv2ncdf2d</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                           (MT: 1, Y: 3298, X: 4500)\n",
       "Coordinates:\n",
       "  * MT                                (MT) datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date                              (MT) float64 dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "  * Y                                 (Y) int32 1 2 3 4 ... 3295 3296 3297 3298\n",
       "  * X                                 (X) int32 1 2 3 4 ... 4497 4498 4499 4500\n",
       "    Latitude                          (Y, X) float32 dask.array<chunksize=(825, 1125), meta=np.ndarray>\n",
       "    Longitude                         (Y, X) float32 dask.array<chunksize=(825, 1125), meta=np.ndarray>\n",
       "Data variables:\n",
       "    ssh                               (MT, Y, X) float32 dask.array<chunksize=(1, 825, 1125), meta=np.ndarray>\n",
       "    u_barotropic_velocity             (MT, Y, X) float32 dask.array<chunksize=(1, 825, 1125), meta=np.ndarray>\n",
       "    v_barotropic_velocity             (MT, Y, X) float32 dask.array<chunksize=(1, 825, 1125), meta=np.ndarray>\n",
       "    surface_boundary_layer_thickness  (MT, Y, X) float32 dask.array<chunksize=(1, 825, 1125), meta=np.ndarray>\n",
       "    mixed_layer_thickness             (MT, Y, X) float32 dask.array<chunksize=(1, 825, 1125), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:  CF-1.0\n",
       "    title:        HYCOM ATLb2.00\n",
       "    institution:  National Centers for Environmental Prediction\n",
       "    source:       HYCOM archive file\n",
       "    experiment:   92.8\n",
       "    history:      archv2ncdf2d"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import cf_xarray\n",
    "import xarray as xr\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "ds = xr.open_dataset('rtofs_glo_2ds_f034_diag.nc', chunks={})\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x135e14ac0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.ssh.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x13d0f4be0>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ssh = ds.ssh.isel(MT=0)\n",
    "lng = ssh.cf['longitude']\n",
    "mask = xr.where(lng < 500, True, False)\n",
    "new_mask = mask & mask.shift(Y=1, fill_value=True) & mask.shift(X=1, fill_value=True) & mask.shift(Y=-1, fill_value=True) & mask.shift(X=-1, fill_value=True)\n",
    "ssh.where(new_mask == 1).cf.plot(x='longitude', y='latitude')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".xr-text-repr-fallback {\n",
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       ".xr-section-item input {\n",
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       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (Y: 3298, X: 4500)&gt;\n",
       "dask.array&lt;where, shape=(3298, 4500), dtype=float32, chunksize=(825, 1125), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * Y          (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X          (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500\n",
       "    MT         datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date       float64 dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
       "    Latitude   (Y, X) float32 dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;\n",
       "    Longitude  (Y, X) float32 dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><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'>Y</span>: 3298</li><li><span class='xr-has-index'>X</span>: 4500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c06908fb-4659-4c0d-b8e9-0f1587a4311c' class='xr-array-in' type='checkbox' checked><label for='section-c06908fb-4659-4c0d-b8e9-0f1587a4311c' 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=(825, 1125), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 56.61 MiB </td>\n",
       "                        <td> 3.54 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (3298, 4500) </td>\n",
       "                        <td> (825, 1125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 9 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"137\" 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=\"22\" x2=\"120\" y2=\"22\" />\n",
       "  <line x1=\"0\" y1=\"44\" x2=\"120\" y2=\"44\" />\n",
       "  <line x1=\"0\" y1=\"65\" x2=\"120\" y2=\"65\" />\n",
       "  <line x1=\"0\" y1=\"87\" x2=\"120\" y2=\"87\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"87\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"87\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"87\" />\n",
       "  <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"87\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"87\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,87.94666666666666 0.0,87.94666666666666\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"107.946667\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4500</text>\n",
       "  <text x=\"140.000000\" y=\"43.973333\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,43.973333)\">3298</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-4d7f89e2-8770-4d54-9731-9ada15ea55a2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4d7f89e2-8770-4d54-9731-9ada15ea55a2' 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'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 3295 3296 3297 3298</div><input id='attrs-8c5a0522-89e9-4717-9be9-9e40802565b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c5a0522-89e9-4717-9be9-9e40802565b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-daa3295c-89de-4a52-8a41-3e32067579b6' class='xr-var-data-in' type='checkbox'><label for='data-daa3295c-89de-4a52-8a41-3e32067579b6' title='Show/Hide data 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([   1,    2,    3, ..., 3296, 3297, 3298], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 4497 4498 4499 4500</div><input id='attrs-3ac8edc4-7c2e-4ea1-b970-b738c232725e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ac8edc4-7c2e-4ea1-b970-b738c232725e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d626ba49-db97-464f-85c0-ecafdf22e3a0' class='xr-var-data-in' type='checkbox'><label for='data-d626ba49-db97-464f-85c0-ecafdf22e3a0' title='Show/Hide data 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([   1,    2,    3, ..., 4498, 4499, 4500], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MT</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-09-21T10:00:00</div><input id='attrs-e2f3655e-832c-423f-90bf-56dd22443f4f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e2f3655e-832c-423f-90bf-56dd22443f4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ad0150c-4eca-4fae-8387-0a97bf1d0c5d' class='xr-var-data-in' type='checkbox'><label for='data-8ad0150c-4eca-4fae-8387-0a97bf1d0c5d' title='Show/Hide data 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(&#x27;2023-09-21T10:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Date</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-a0c29ef0-ff77-42e5-ad1b-838a9e3f1d1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0c29ef0-ff77-42e5-ad1b-838a9e3f1d1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e502ca2-cf6e-464a-a02b-4d6ec0139efd' class='xr-var-data-in' type='checkbox'><label for='data-4e502ca2-cf6e-464a-a02b-4d6ec0139efd' title='Show/Hide data 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;</div><input id='attrs-89b50603-36f0-4a8b-b558-7de1f9ec2f0d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89b50603-36f0-4a8b-b558-7de1f9ec2f0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e44f1f8c-edb9-4e74-a9f7-a696f258162b' class='xr-var-data-in' type='checkbox'><label for='data-e44f1f8c-edb9-4e74-a9f7-a696f258162b' title='Show/Hide data 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 56.61 MiB </td>\n",
       "                        <td> 3.54 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (3298, 4500) </td>\n",
       "                        <td> (825, 1125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"137\" 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",
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       "  <line x1=\"0\" y1=\"44\" x2=\"120\" y2=\"44\" />\n",
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       "\n",
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       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"87\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"87\" />\n",
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       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"107.946667\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4500</text>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Longitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(825, 1125), meta=np.ndarray&gt;</div><input id='attrs-d19e6ea0-1ad9-475f-8258-9501e117b557' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d19e6ea0-1ad9-475f-8258-9501e117b557' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f68f0a76-f64d-44a6-8a73-e5f00d9ebd0e' class='xr-var-data-in' type='checkbox'><label for='data-f68f0a76-f64d-44a6-8a73-e5f00d9ebd0e' title='Show/Hide data 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 56.61 MiB </td>\n",
       "                        <td> 3.54 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (3298, 4500) </td>\n",
       "                        <td> (825, 1125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"137\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "\n",
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       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"87\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"87\" />\n",
       "  <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"87\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"87\" style=\"stroke-width:2\" />\n",
       "\n",
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       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,87.94666666666666 0.0,87.94666666666666\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"107.946667\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4500</text>\n",
       "  <text x=\"140.000000\" y=\"43.973333\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,43.973333)\">3298</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4885cb06-0909-4c01-97cf-14c76d463590' class='xr-section-summary-in' type='checkbox'  ><label for='section-4885cb06-0909-4c01-97cf-14c76d463590' class='xr-section-summary' >Indexes: <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-index-name'><div>Y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f8724958-d112-442a-a2b6-169c8b1a9a95' class='xr-index-data-in' type='checkbox'/><label for='index-f8724958-d112-442a-a2b6-169c8b1a9a95' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       3289, 3290, 3291, 3292, 3293, 3294, 3295, 3296, 3297, 3298],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;Y&#x27;, length=3298))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>X</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a70466b4-c5bf-46d7-aa29-1a084bd5f6b0' class='xr-index-data-in' type='checkbox'/><label for='index-a70466b4-c5bf-46d7-aa29-1a084bd5f6b0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       4491, 4492, 4493, 4494, 4495, 4496, 4497, 4498, 4499, 4500],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;X&#x27;, length=4500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c357396d-b3c4-44a3-9838-8ede39bb0afb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c357396d-b3c4-44a3-9838-8ede39bb0afb' 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 (Y: 3298, X: 4500)>\n",
       "dask.array<where, shape=(3298, 4500), dtype=float32, chunksize=(825, 1125), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * Y          (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X          (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500\n",
       "    MT         datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date       float64 dask.array<chunksize=(), meta=np.ndarray>\n",
       "    Latitude   (Y, X) float32 dask.array<chunksize=(825, 1125), meta=np.ndarray>\n",
       "    Longitude  (Y, X) float32 dask.array<chunksize=(825, 1125), meta=np.ndarray>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = xr.where(mask == 1, ssh, np.nan)\n",
    "mask\n",
    "# mask[:-1,:] = mask[:-1,:].where(mask[1:,:] == 1, 0)\n",
    "# mask[:,:-1] = mask[:,:-1].where(mask[:,1:] == 1, 0)\n",
    "# mask[1:,:] = mask[1:,:].where(mask[:-1,:] == 1, 0)\n",
    "# mask[:,1:] = mask[:,1:].where(mask[:,:-1] == 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "cannot align objects with join='exact' where index/labels/sizes are not equal along these coordinates (dimensions): 'Y' ('Y',)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m/Users/matthewiannucci/Developer/ocean-notebooks/rtofs_global.ipynb Cell 5\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> <a href='vscode-notebook-cell:/Users/matthewiannucci/Developer/ocean-notebooks/rtofs_global.ipynb#X12sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m mask[:\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m,:] \u001b[39m=\u001b[39m mask[:\u001b[39m-\u001b[39;49m\u001b[39m1\u001b[39;49m,:]\u001b[39m.\u001b[39;49mwhere(mask[\u001b[39m1\u001b[39;49m:,:] \u001b[39m==\u001b[39;49m \u001b[39m1\u001b[39;49m, \u001b[39m0\u001b[39;49m)\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/common.py:1184\u001b[0m, in \u001b[0;36mDataWithCoords.where\u001b[0;34m(self, cond, other, drop)\u001b[0m\n\u001b[1;32m   1181\u001b[0m     \u001b[39mself\u001b[39m \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39misel(\u001b[39m*\u001b[39m\u001b[39m*\u001b[39mindexers)\n\u001b[1;32m   1182\u001b[0m     cond \u001b[39m=\u001b[39m cond\u001b[39m.\u001b[39misel(\u001b[39m*\u001b[39m\u001b[39m*\u001b[39mindexers)\n\u001b[0;32m-> 1184\u001b[0m \u001b[39mreturn\u001b[39;00m ops\u001b[39m.\u001b[39;49mwhere_method(\u001b[39mself\u001b[39;49m, cond, other)\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/ops.py:179\u001b[0m, in \u001b[0;36mwhere_method\u001b[0;34m(self, cond, other)\u001b[0m\n\u001b[1;32m    177\u001b[0m \u001b[39m# alignment for three arguments is complicated, so don't support it yet\u001b[39;00m\n\u001b[1;32m    178\u001b[0m join \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39minner\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mif\u001b[39;00m other \u001b[39mis\u001b[39;00m dtypes\u001b[39m.\u001b[39mNA \u001b[39melse\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mexact\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m--> 179\u001b[0m \u001b[39mreturn\u001b[39;00m apply_ufunc(\n\u001b[1;32m    180\u001b[0m     duck_array_ops\u001b[39m.\u001b[39;49mwhere_method,\n\u001b[1;32m    181\u001b[0m     \u001b[39mself\u001b[39;49m,\n\u001b[1;32m    182\u001b[0m     cond,\n\u001b[1;32m    183\u001b[0m     other,\n\u001b[1;32m    184\u001b[0m     join\u001b[39m=\u001b[39;49mjoin,\n\u001b[1;32m    185\u001b[0m     dataset_join\u001b[39m=\u001b[39;49mjoin,\n\u001b[1;32m    186\u001b[0m     dask\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mallowed\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m    187\u001b[0m     keep_attrs\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[1;32m    188\u001b[0m )\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/computation.py:1249\u001b[0m, in \u001b[0;36mapply_ufunc\u001b[0;34m(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, meta, dask_gufunc_kwargs, on_missing_core_dim, *args)\u001b[0m\n\u001b[1;32m   1247\u001b[0m \u001b[39m# feed DataArray apply_variable_ufunc through apply_dataarray_vfunc\u001b[39;00m\n\u001b[1;32m   1248\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39many\u001b[39m(\u001b[39misinstance\u001b[39m(a, DataArray) \u001b[39mfor\u001b[39;00m a \u001b[39min\u001b[39;00m args):\n\u001b[0;32m-> 1249\u001b[0m     \u001b[39mreturn\u001b[39;00m apply_dataarray_vfunc(\n\u001b[1;32m   1250\u001b[0m         variables_vfunc,\n\u001b[1;32m   1251\u001b[0m         \u001b[39m*\u001b[39;49margs,\n\u001b[1;32m   1252\u001b[0m         signature\u001b[39m=\u001b[39;49msignature,\n\u001b[1;32m   1253\u001b[0m         join\u001b[39m=\u001b[39;49mjoin,\n\u001b[1;32m   1254\u001b[0m         exclude_dims\u001b[39m=\u001b[39;49mexclude_dims,\n\u001b[1;32m   1255\u001b[0m         keep_attrs\u001b[39m=\u001b[39;49mkeep_attrs,\n\u001b[1;32m   1256\u001b[0m     )\n\u001b[1;32m   1257\u001b[0m \u001b[39m# feed Variables directly through apply_variable_ufunc\u001b[39;00m\n\u001b[1;32m   1258\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39many\u001b[39m(\u001b[39misinstance\u001b[39m(a, Variable) \u001b[39mfor\u001b[39;00m a \u001b[39min\u001b[39;00m args):\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/computation.py:292\u001b[0m, in \u001b[0;36mapply_dataarray_vfunc\u001b[0;34m(func, signature, join, exclude_dims, keep_attrs, *args)\u001b[0m\n\u001b[1;32m    289\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mxarray\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mcore\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mdataarray\u001b[39;00m \u001b[39mimport\u001b[39;00m DataArray\n\u001b[1;32m    291\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(args) \u001b[39m>\u001b[39m \u001b[39m1\u001b[39m:\n\u001b[0;32m--> 292\u001b[0m     args \u001b[39m=\u001b[39m deep_align(\n\u001b[1;32m    293\u001b[0m         args, join\u001b[39m=\u001b[39;49mjoin, copy\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m, exclude\u001b[39m=\u001b[39;49mexclude_dims, raise_on_invalid\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m\n\u001b[1;32m    294\u001b[0m     )\n\u001b[1;32m    296\u001b[0m objs \u001b[39m=\u001b[39m _all_of_type(args, DataArray)\n\u001b[1;32m    298\u001b[0m \u001b[39mif\u001b[39;00m keep_attrs \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mdrop\u001b[39m\u001b[39m\"\u001b[39m:\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/alignment.py:847\u001b[0m, in \u001b[0;36mdeep_align\u001b[0;34m(objects, join, copy, indexes, exclude, raise_on_invalid, fill_value)\u001b[0m\n\u001b[1;32m    844\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    845\u001b[0m         out\u001b[39m.\u001b[39mappend(variables)\n\u001b[0;32m--> 847\u001b[0m aligned \u001b[39m=\u001b[39m align(\n\u001b[1;32m    848\u001b[0m     \u001b[39m*\u001b[39;49mtargets,\n\u001b[1;32m    849\u001b[0m     join\u001b[39m=\u001b[39;49mjoin,\n\u001b[1;32m    850\u001b[0m     copy\u001b[39m=\u001b[39;49mcopy,\n\u001b[1;32m    851\u001b[0m     indexes\u001b[39m=\u001b[39;49mindexes,\n\u001b[1;32m    852\u001b[0m     exclude\u001b[39m=\u001b[39;49mexclude,\n\u001b[1;32m    853\u001b[0m     fill_value\u001b[39m=\u001b[39;49mfill_value,\n\u001b[1;32m    854\u001b[0m )\n\u001b[1;32m    856\u001b[0m \u001b[39mfor\u001b[39;00m position, key, aligned_obj \u001b[39min\u001b[39;00m \u001b[39mzip\u001b[39m(positions, keys, aligned):\n\u001b[1;32m    857\u001b[0m     \u001b[39mif\u001b[39;00m key \u001b[39mis\u001b[39;00m no_key:\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/alignment.py:783\u001b[0m, in \u001b[0;36malign\u001b[0;34m(join, copy, indexes, exclude, fill_value, *objects)\u001b[0m\n\u001b[1;32m    587\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m    588\u001b[0m \u001b[39mGiven any number of Dataset and/or DataArray objects, returns new\u001b[39;00m\n\u001b[1;32m    589\u001b[0m \u001b[39mobjects with aligned indexes and dimension sizes.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    773\u001b[0m \n\u001b[1;32m    774\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m    775\u001b[0m aligner \u001b[39m=\u001b[39m Aligner(\n\u001b[1;32m    776\u001b[0m     objects,\n\u001b[1;32m    777\u001b[0m     join\u001b[39m=\u001b[39mjoin,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    781\u001b[0m     fill_value\u001b[39m=\u001b[39mfill_value,\n\u001b[1;32m    782\u001b[0m )\n\u001b[0;32m--> 783\u001b[0m aligner\u001b[39m.\u001b[39;49malign()\n\u001b[1;32m    784\u001b[0m \u001b[39mreturn\u001b[39;00m aligner\u001b[39m.\u001b[39mresults\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/alignment.py:568\u001b[0m, in \u001b[0;36mAligner.align\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    566\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfind_matching_unindexed_dims()\n\u001b[1;32m    567\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39massert_no_index_conflict()\n\u001b[0;32m--> 568\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49malign_indexes()\n\u001b[1;32m    569\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39massert_unindexed_dim_sizes_equal()\n\u001b[1;32m    571\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mjoin \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39moverride\u001b[39m\u001b[39m\"\u001b[39m:\n",
      "File \u001b[0;32m~/Developer/ocean-notebooks/env/lib/python3.10/site-packages/xarray/core/alignment.py:415\u001b[0m, in \u001b[0;36mAligner.align_indexes\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    413\u001b[0m \u001b[39mif\u001b[39;00m need_reindex:\n\u001b[1;32m    414\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mjoin \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mexact\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[0;32m--> 415\u001b[0m         \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[1;32m    416\u001b[0m             \u001b[39m\"\u001b[39m\u001b[39mcannot align objects with join=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mexact\u001b[39m\u001b[39m'\u001b[39m\u001b[39m where \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    417\u001b[0m             \u001b[39m\"\u001b[39m\u001b[39mindex/labels/sizes are not equal along \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    418\u001b[0m             \u001b[39m\"\u001b[39m\u001b[39mthese coordinates (dimensions): \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    419\u001b[0m             \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m, \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mjoin(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mname\u001b[39m!r}\u001b[39;00m\u001b[39m \u001b[39m\u001b[39m{\u001b[39;00mdims\u001b[39m!r}\u001b[39;00m\u001b[39m\"\u001b[39m \u001b[39mfor\u001b[39;00m name, dims \u001b[39min\u001b[39;00m key[\u001b[39m0\u001b[39m])\n\u001b[1;32m    420\u001b[0m         )\n\u001b[1;32m    421\u001b[0m     joiner \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_index_joiner(index_cls)\n\u001b[1;32m    422\u001b[0m     joined_index \u001b[39m=\u001b[39m joiner(matching_indexes)\n",
      "\u001b[0;31mValueError\u001b[0m: cannot align objects with join='exact' where index/labels/sizes are not equal along these coordinates (dimensions): 'Y' ('Y',)"
     ]
    }
   ],
   "source": [
    "mask[:-1,:] = mask[:-1,:].where(mask[1:,:] == 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/b2/s20v34y16hg9263q_zf2y1740000gn/T/ipykernel_20527/66957572.py:13: 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",
      "  plt.pcolormesh(lon, lat, ssh, edgecolor='none')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x13cf9f400>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ssh = ds.ssh.isel(MT=0)\n",
    "lon = ssh.Longitude\n",
    "lat = ds.Latitude\n",
    "\n",
    "# Masking according to https://oceanpython.org/2012/11/29/global-rtofs-real-time-ocean-forecast-system/\n",
    "mask = lon > 500\n",
    "ssh = np.ma.masked_where(mask == True, ssh)\n",
    "ssh[:-1,:] = np.ma.masked_where(mask[1:,:] == True, ssh[:-1,:])\n",
    "ssh[:,:-1] = np.ma.masked_where(mask[:,1:] == True, ssh[:,:-1])\n",
    "ssh[1:,:] = np.ma.masked_where(mask[:-1,:] == True, ssh[1:,:])\n",
    "ssh[:,1:] = np.ma.masked_where(mask[:,:-1] == True, ssh[:,1:])\n",
    "\n",
    "plt.pcolormesh(lon, lat, ssh, edgecolor='none')\n",
    "plt.xlim(74.160034, 434.11987)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14832007"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ssh.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;Longitude&#x27; (Y: 3298, X: 4500)&gt;\n",
       "array([[ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       ...,\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ..., False, False, False],\n",
       "       [ True,  True,  True, ..., False, False, False]])\n",
       "Coordinates:\n",
       "  * Y        (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X        (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'Longitude'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Y</span>: 3298</li><li><span class='xr-has-index'>X</span>: 4500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6a79a879-37c1-4546-9229-5aeb789b2390' class='xr-array-in' type='checkbox' checked><label for='section-6a79a879-37c1-4546-9229-5aeb789b2390' 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>True True True True True True ... False False False False False False</span></div><div class='xr-array-data'><pre>array([[ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       ...,\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ..., False, False, False],\n",
       "       [ True,  True,  True, ..., False, False, False]])</pre></div></div></li><li class='xr-section-item'><input id='section-84de0d1a-3048-4e9b-acba-5283abc4914d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-84de0d1a-3048-4e9b-acba-5283abc4914d' 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'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 3295 3296 3297 3298</div><input id='attrs-7606e9ba-2051-48a0-b9a2-8427f86f2a6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7606e9ba-2051-48a0-b9a2-8427f86f2a6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89cca078-916f-48fc-b51b-8484c2668141' class='xr-var-data-in' type='checkbox'><label for='data-89cca078-916f-48fc-b51b-8484c2668141' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 3296, 3297, 3298], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 4497 4498 4499 4500</div><input id='attrs-3ce10387-7007-438f-b4e9-aa32b625917f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ce10387-7007-438f-b4e9-aa32b625917f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36306522-4e69-497f-b08d-4787d649fda6' class='xr-var-data-in' type='checkbox'><label for='data-36306522-4e69-497f-b08d-4787d649fda6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 4498, 4499, 4500], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b6ed526a-d105-45c9-b0db-3ddd44bf98f4' class='xr-section-summary-in' type='checkbox'  ><label for='section-b6ed526a-d105-45c9-b0db-3ddd44bf98f4' class='xr-section-summary' >Indexes: <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-index-name'><div>Y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-92203f21-4f7b-4893-8cb4-924ca7a16f73' class='xr-index-data-in' type='checkbox'/><label for='index-92203f21-4f7b-4893-8cb4-924ca7a16f73' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       3289, 3290, 3291, 3292, 3293, 3294, 3295, 3296, 3297, 3298],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;Y&#x27;, length=3298))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>X</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bd6917ac-63e6-48dd-8524-519e0f1633cc' class='xr-index-data-in' type='checkbox'/><label for='index-bd6917ac-63e6-48dd-8524-519e0f1633cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       4491, 4492, 4493, 4494, 4495, 4496, 4497, 4498, 4499, 4500],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;X&#x27;, length=4500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bbf56345-7872-4757-8b15-3797eddef551' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bbf56345-7872-4757-8b15-3797eddef551' 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 'Longitude' (Y: 3298, X: 4500)>\n",
       "array([[ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       ...,\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ..., False, False, False],\n",
       "       [ True,  True,  True, ..., False, False, False]])\n",
       "Coordinates:\n",
       "  * Y        (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X        (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = ds.cf['longitude'] < 500\n",
    "mask.persist()\n",
    "mask[:-1,:] = mask[:-1,:].where(mask[1:,:].values, False)\n",
    "mask[:,:-1] = mask[:,:-1].where(mask[:,1:].values, False)\n",
    "mask[1:,:] = mask[1:,:].where(mask[:-1,:].values, False)\n",
    "mask[:,1:] = mask[:,1:].where(mask[:,:-1].values, False)\n",
    "mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;ssh&#x27; (Y: 3298, X: 4500)&gt;\n",
       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)\n",
       "Coordinates:\n",
       "    MT         datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date       float64 2.023e+07\n",
       "  * Y          (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X          (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500\n",
       "    Latitude   (Y, X) float32 -78.64 -78.64 -78.64 -78.64 ... 47.15 47.1 47.04\n",
       "    Longitude  (Y, X) float32 74.16 74.24 74.32 74.4 ... 794.1 794.1 794.1 794.1\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_elevation\n",
       "    units:          m\n",
       "    valid_range:    [-1.9011002  1.5169019]\n",
       "    long_name:       sea surf. height  [92.8H]</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ssh'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Y</span>: 3298</li><li><span class='xr-has-index'>X</span>: 4500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d36bd415-c425-46a6-b145-b4ac9506546a' class='xr-array-in' type='checkbox' checked><label for='section-d36bd415-c425-46a6-b145-b4ac9506546a' 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>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-326da7e5-62d5-43f1-bd9f-e166f188a4d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-326da7e5-62d5-43f1-bd9f-e166f188a4d8' 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>MT</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-09-21T10:00:00</div><input id='attrs-d442f023-6b37-4dbf-9b55-21b2f9e1fdda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d442f023-6b37-4dbf-9b55-21b2f9e1fdda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba349453-41f8-4f7a-ae88-51cf0315a73d' class='xr-var-data-in' type='checkbox'><label for='data-ba349453-41f8-4f7a-ae88-51cf0315a73d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><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></dl></div><div class='xr-var-data'><pre>array(&#x27;2023-09-21T10:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Date</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.023e+07</div><input id='attrs-3ae940f0-0989-4b08-a310-d308cfe8d519' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ae940f0-0989-4b08-a310-d308cfe8d519' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3817405-e1bc-497b-882c-566870a7bf93' class='xr-var-data-in' type='checkbox'><label for='data-a3817405-e1bc-497b-882c-566870a7bf93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>date</dd><dt><span>units :</span></dt><dd>day as %Y%m%d.%f</dd><dt><span>C_format :</span></dt><dd>%13.4f</dd><dt><span>FORTRAN_format :</span></dt><dd>(f13.4)</dd></dl></div><div class='xr-var-data'><pre>array(20230921.416667)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 3295 3296 3297 3298</div><input id='attrs-26c46698-1837-4950-9a33-a634a2b95ff1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26c46698-1837-4950-9a33-a634a2b95ff1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c61f9a7-696a-453d-a348-7c130e30af8f' class='xr-var-data-in' type='checkbox'><label for='data-4c61f9a7-696a-453d-a348-7c130e30af8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 3296, 3297, 3298], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 4497 4498 4499 4500</div><input id='attrs-5dc534ee-35af-4c90-ae71-465c7b159b91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dc534ee-35af-4c90-ae71-465c7b159b91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3a5b254-616d-4d3a-b539-a9536c6fd446' class='xr-var-data-in' type='checkbox'><label for='data-a3a5b254-616d-4d3a-b539-a9536c6fd446' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 4498, 4499, 4500], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-78.64 -78.64 -78.64 ... 47.1 47.04</div><input id='attrs-7dea4f97-5e66-4cb3-a50f-a3d9c387b0f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7dea4f97-5e66-4cb3-a50f-a3d9c387b0f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44e12e27-a7db-4d2e-87e2-7a8ca560d42b' class='xr-var-data-in' type='checkbox'><label for='data-44e12e27-a7db-4d2e-87e2-7a8ca560d42b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-78.64    , -78.64    , -78.64    , ..., -78.64    , -78.64    ,\n",
       "        -78.64    ],\n",
       "       [-78.608   , -78.608   , -78.608   , ..., -78.608   , -78.608   ,\n",
       "        -78.608   ],\n",
       "       [-78.576   , -78.576   , -78.576   , ..., -78.576   , -78.576   ,\n",
       "        -78.576   ],\n",
       "       ...,\n",
       "       [ 47.041878,  47.096367,  47.1508  , ...,  47.1508  ,  47.096367,\n",
       "         47.041878],\n",
       "       [ 47.041878,  47.096367,  47.150803, ...,  47.150803,  47.096367,\n",
       "         47.041878],\n",
       "       [ 47.041878,  47.096367,  47.150803, ...,  47.150803,  47.096367,\n",
       "         47.041878]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Longitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>74.16 74.24 74.32 ... 794.1 794.1</div><input id='attrs-74222bce-bcc5-4a82-b635-5e831c4b813e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74222bce-bcc5-4a82-b635-5e831c4b813e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80e34052-5ffc-4dbe-99f2-2deeb21cfd9c' class='xr-var-data-in' type='checkbox'><label for='data-80e34052-5ffc-4dbe-99f2-2deeb21cfd9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>modulo :</span></dt><dd>360 degrees</dd></dl></div><div class='xr-var-data'><pre>array([[ 74.160034,  74.23999 ,  74.31995 , ..., 433.92004 , 434.      ,\n",
       "        434.07996 ],\n",
       "       [ 74.160034,  74.23999 ,  74.31995 , ..., 433.92004 , 434.      ,\n",
       "        434.07996 ],\n",
       "       [ 74.160034,  74.23999 ,  74.31995 , ..., 433.92004 , 434.      ,\n",
       "        434.07996 ],\n",
       "       ...,\n",
       "       [ 74.12012 ,  74.12024 ,  74.12036 , ..., 434.11963 , 434.11975 ,\n",
       "        434.11987 ],\n",
       "       [ 74.119995,  74.12012 ,  74.12012 , ..., 434.11987 , 434.11987 ,\n",
       "        434.12    ],\n",
       "       [ 74.119995, 434.11987 , 434.11987 , ..., 794.1201  , 794.1201  ,\n",
       "        794.12    ]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bba6c1c6-eb0b-4b86-8a14-9c70531070a9' class='xr-section-summary-in' type='checkbox'  ><label for='section-bba6c1c6-eb0b-4b86-8a14-9c70531070a9' class='xr-section-summary' >Indexes: <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-index-name'><div>Y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-930d3c63-6bda-4d0b-bdb8-3f66af5df5ac' class='xr-index-data-in' type='checkbox'/><label for='index-930d3c63-6bda-4d0b-bdb8-3f66af5df5ac' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       3289, 3290, 3291, 3292, 3293, 3294, 3295, 3296, 3297, 3298],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;Y&#x27;, length=3298))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>X</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4bffc81f-6826-4291-8981-c3169612ebaf' class='xr-index-data-in' type='checkbox'/><label for='index-4bffc81f-6826-4291-8981-c3169612ebaf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       4491, 4492, 4493, 4494, 4495, 4496, 4497, 4498, 4499, 4500],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;X&#x27;, length=4500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6fe5d056-e64b-4c50-8e68-e27982c972cf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6fe5d056-e64b-4c50-8e68-e27982c972cf' 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>standard_name :</span></dt><dd>sea_surface_elevation</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>valid_range :</span></dt><dd>[-1.9011002  1.5169019]</dd><dt><span>long_name :</span></dt><dd> sea surf. height  [92.8H]</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'ssh' (Y: 3298, X: 4500)>\n",
       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)\n",
       "Coordinates:\n",
       "    MT         datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date       float64 2.023e+07\n",
       "  * Y          (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X          (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500\n",
       "    Latitude   (Y, X) float32 -78.64 -78.64 -78.64 -78.64 ... 47.15 47.1 47.04\n",
       "    Longitude  (Y, X) float32 74.16 74.24 74.32 74.4 ... 794.1 794.1 794.1 794.1\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_elevation\n",
       "    units:          m\n",
       "    valid_range:    [-1.9011002  1.5169019]\n",
       "    long_name:       sea surf. height  [92.8H]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da = ds.ssh.isel(MT=0).where(mask == True)\n",
    "da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
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       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;ssh&#x27; (Y: 3298, X: 4500)&gt;\n",
       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)\n",
       "Coordinates:\n",
       "    MT         datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date       float64 2.023e+07\n",
       "  * Y          (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X          (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500\n",
       "    Latitude   (Y, X) float32 -78.64 -78.64 -78.64 -78.64 ... 47.15 47.1 47.04\n",
       "    Longitude  (Y, X) float32 74.16 74.24 74.32 74.4 ... 794.1 794.1 794.1 794.1\n",
       "    longitude  (Y, X) float32 74.16 74.24 74.32 74.4 ... 74.12 74.12 74.12 74.12\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_elevation\n",
       "    units:          m\n",
       "    valid_range:    [-1.9011002  1.5169019]\n",
       "    long_name:       sea surf. height  [92.8H]</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ssh'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Y</span>: 3298</li><li><span class='xr-has-index'>X</span>: 4500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-739c1398-dd30-4e9b-a57a-88c4b5cd92e7' class='xr-array-in' type='checkbox' checked><label for='section-739c1398-dd30-4e9b-a57a-88c4b5cd92e7' 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>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-01b333b7-ca77-4831-9e3c-887c35a5677e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01b333b7-ca77-4831-9e3c-887c35a5677e' class='xr-section-summary' >Coordinates: <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>MT</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-09-21T10:00:00</div><input id='attrs-1bbbd6b6-c1c9-4840-9154-a17e24600d17' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bbbd6b6-c1c9-4840-9154-a17e24600d17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47c0ea95-cb04-4c11-a765-a2866798e8e6' class='xr-var-data-in' type='checkbox'><label for='data-47c0ea95-cb04-4c11-a765-a2866798e8e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><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></dl></div><div class='xr-var-data'><pre>array(&#x27;2023-09-21T10:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Date</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.023e+07</div><input id='attrs-3459119f-b9de-4a99-b3aa-be74c0a6ff28' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3459119f-b9de-4a99-b3aa-be74c0a6ff28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3dc079e-5172-41d3-bda7-aa28edfbb9c7' class='xr-var-data-in' type='checkbox'><label for='data-c3dc079e-5172-41d3-bda7-aa28edfbb9c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>date</dd><dt><span>units :</span></dt><dd>day as %Y%m%d.%f</dd><dt><span>C_format :</span></dt><dd>%13.4f</dd><dt><span>FORTRAN_format :</span></dt><dd>(f13.4)</dd></dl></div><div class='xr-var-data'><pre>array(20230921.416667)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 3295 3296 3297 3298</div><input id='attrs-91b008ed-3a59-402c-a47f-5ad631ba8b09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91b008ed-3a59-402c-a47f-5ad631ba8b09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d23e4d53-bb96-410a-af99-5f9592517aed' class='xr-var-data-in' type='checkbox'><label for='data-d23e4d53-bb96-410a-af99-5f9592517aed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 3296, 3297, 3298], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 ... 4497 4498 4499 4500</div><input id='attrs-55493aa2-7ab1-4b27-bea6-e49efa9af75f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55493aa2-7ab1-4b27-bea6-e49efa9af75f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-733227cc-92e2-478c-937e-edb303fb0d75' class='xr-var-data-in' type='checkbox'><label for='data-733227cc-92e2-478c-937e-edb303fb0d75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>point_spacing :</span></dt><dd>even</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3, ..., 4498, 4499, 4500], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-78.64 -78.64 -78.64 ... 47.1 47.04</div><input id='attrs-58a21abc-fa63-444f-b8b3-e54a98f24a44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58a21abc-fa63-444f-b8b3-e54a98f24a44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31d89589-b29f-436d-9ef3-683871ce3923' class='xr-var-data-in' type='checkbox'><label for='data-31d89589-b29f-436d-9ef3-683871ce3923' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-78.64    , -78.64    , -78.64    , ..., -78.64    , -78.64    ,\n",
       "        -78.64    ],\n",
       "       [-78.608   , -78.608   , -78.608   , ..., -78.608   , -78.608   ,\n",
       "        -78.608   ],\n",
       "       [-78.576   , -78.576   , -78.576   , ..., -78.576   , -78.576   ,\n",
       "        -78.576   ],\n",
       "       ...,\n",
       "       [ 47.041878,  47.096367,  47.1508  , ...,  47.1508  ,  47.096367,\n",
       "         47.041878],\n",
       "       [ 47.041878,  47.096367,  47.150803, ...,  47.150803,  47.096367,\n",
       "         47.041878],\n",
       "       [ 47.041878,  47.096367,  47.150803, ...,  47.150803,  47.096367,\n",
       "         47.041878]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Longitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>74.16 74.24 74.32 ... 794.1 794.1</div><input id='attrs-bcf01cb8-26c2-4002-8ea3-ca3d74365e48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcf01cb8-26c2-4002-8ea3-ca3d74365e48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bef22631-baf1-43be-be10-badf828a8d8f' class='xr-var-data-in' type='checkbox'><label for='data-bef22631-baf1-43be-be10-badf828a8d8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>modulo :</span></dt><dd>360 degrees</dd></dl></div><div class='xr-var-data'><pre>array([[ 74.160034,  74.23999 ,  74.31995 , ..., 433.92004 , 434.      ,\n",
       "        434.07996 ],\n",
       "       [ 74.160034,  74.23999 ,  74.31995 , ..., 433.92004 , 434.      ,\n",
       "        434.07996 ],\n",
       "       [ 74.160034,  74.23999 ,  74.31995 , ..., 433.92004 , 434.      ,\n",
       "        434.07996 ],\n",
       "       ...,\n",
       "       [ 74.12012 ,  74.12024 ,  74.12036 , ..., 434.11963 , 434.11975 ,\n",
       "        434.11987 ],\n",
       "       [ 74.119995,  74.12012 ,  74.12012 , ..., 434.11987 , 434.11987 ,\n",
       "        434.12    ],\n",
       "       [ 74.119995, 434.11987 , 434.11987 , ..., 794.1201  , 794.1201  ,\n",
       "        794.12    ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>74.16 74.24 74.32 ... 74.12 74.12</div><input id='attrs-d52d2cb0-1e6c-4706-bda2-121a76682688' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d52d2cb0-1e6c-4706-bda2-121a76682688' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9ee5991-9c0a-48bd-8b0e-34da84417ef9' class='xr-var-data-in' type='checkbox'><label for='data-a9ee5991-9c0a-48bd-8b0e-34da84417ef9' title='Show/Hide data 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([[74.160034, 74.23999 , 74.31995 , ..., 73.920044, 74.      ,\n",
       "        74.079956],\n",
       "       [74.160034, 74.23999 , 74.31995 , ..., 73.920044, 74.      ,\n",
       "        74.079956],\n",
       "       [74.160034, 74.23999 , 74.31995 , ..., 73.920044, 74.      ,\n",
       "        74.079956],\n",
       "       ...,\n",
       "       [74.12012 , 74.12024 , 74.12036 , ..., 74.11963 , 74.11975 ,\n",
       "        74.11987 ],\n",
       "       [74.119995, 74.12012 , 74.12012 , ..., 74.11987 , 74.11987 ,\n",
       "        74.119995],\n",
       "       [74.119995, 74.11987 , 74.11987 , ..., 74.12012 , 74.12012 ,\n",
       "        74.119995]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7bb1a2d3-7c84-41ed-924e-6af47e055548' class='xr-section-summary-in' type='checkbox'  ><label for='section-7bb1a2d3-7c84-41ed-924e-6af47e055548' class='xr-section-summary' >Indexes: <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-index-name'><div>Y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-59bf00d9-e8b2-4d7b-8269-1a09bbb00b2e' class='xr-index-data-in' type='checkbox'/><label for='index-59bf00d9-e8b2-4d7b-8269-1a09bbb00b2e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       3289, 3290, 3291, 3292, 3293, 3294, 3295, 3296, 3297, 3298],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;Y&#x27;, length=3298))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>X</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4c159cca-a787-4c01-8b2b-e43915e2906a' class='xr-index-data-in' type='checkbox'/><label for='index-4c159cca-a787-4c01-8b2b-e43915e2906a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   1,    2,    3,    4,    5,    6,    7,    8,    9,   10,\n",
       "       ...\n",
       "       4491, 4492, 4493, 4494, 4495, 4496, 4497, 4498, 4499, 4500],\n",
       "      dtype=&#x27;int32&#x27;, name=&#x27;X&#x27;, length=4500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3a227864-c11f-4de0-8bdb-91c3d9f892e6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3a227864-c11f-4de0-8bdb-91c3d9f892e6' 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>standard_name :</span></dt><dd>sea_surface_elevation</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>valid_range :</span></dt><dd>[-1.9011002  1.5169019]</dd><dt><span>long_name :</span></dt><dd> sea surf. height  [92.8H]</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'ssh' (Y: 3298, X: 4500)>\n",
       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)\n",
       "Coordinates:\n",
       "    MT         datetime64[ns] 2023-09-21T10:00:00\n",
       "    Date       float64 2.023e+07\n",
       "  * Y          (Y) int32 1 2 3 4 5 6 7 8 ... 3292 3293 3294 3295 3296 3297 3298\n",
       "  * X          (X) int32 1 2 3 4 5 6 7 8 ... 4494 4495 4496 4497 4498 4499 4500\n",
       "    Latitude   (Y, X) float32 -78.64 -78.64 -78.64 -78.64 ... 47.15 47.1 47.04\n",
       "    Longitude  (Y, X) float32 74.16 74.24 74.32 74.4 ... 794.1 794.1 794.1 794.1\n",
       "    longitude  (Y, X) float32 74.16 74.24 74.32 74.4 ... 74.12 74.12 74.12 74.12\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_elevation\n",
       "    units:          m\n",
       "    valid_range:    [-1.9011002  1.5169019]\n",
       "    long_name:       sea surf. height  [92.8H]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da = da.assign_coords(longitude=(((da.cf['longitude'] + 180) % 360) - 180))\n",
    "da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ssh"
   ]
  }
 ],
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