auxiliary_data_dir -> auxiliary_data_dir

doc/sphinx/source/recipes/recipe_climwip.rst

@@ -44,7 +44,8 @@ Using shapefiles for cutting scientific regions
 To use shapefiles for selecting SREX or AR6 regions by name it is necessary to download them, e.g.,
 from the sources below and reference the file using the `shapefile` parameter. This can either be a
 absolute or a relative path. In the example recipes they are stored in a subfolder `shapefiles`
-in the :ref:`configuration option <esmvalcore:config_options>` `auxiliary_data_dir`.
+in the :ref:`configuration option <esmvalcore:config_options>`
+``auxiliary_data_dir``.
 
 SREX regions (AR5 reference regions): http://www.ipcc-data.org/guidelines/pages/ar5_regions.html
 

doc/sphinx/source/recipes/recipe_ipccwg1ar6ch3.rst

@@ -45,7 +45,7 @@ To reproduce Fig. 3.9 you need the shapefile of the `AR6 reference regions
 Please download the file `IPCC-WGI-reference-regions-v4_shapefile.zip
 <https://github.com/SantanderMetGroup/ATLAS/blob/v1.6/reference-regions/IPCC-WGI-reference-regions-v4_shapefile.zip>`_,
 unzip and store it in `<auxiliary_data_dir>/IPCC-regions/` (where
-`auxiliary_data_dir` is given as :ref:`configuration option
+``auxiliary_data_dir`` is given as :ref:`configuration option
 <esmvalcore:config_options>`).
 
 .. _`Eyring et al., 2021`: https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-3/

doc/sphinx/source/recipes/recipe_rainfarm.rst

@@ -32,7 +32,7 @@ User settings
 * nf: number of subdivisions for downscaling (e.g. 8 will produce output fields with linear resolution increased by a factor 8)
 * conserv_glob: logical, if to conserve precipitation over full domain
 * conserv_smooth: logical, if to conserve precipitation using convolution (if neither conserv_glob or conserv_smooth is chosen, box conservation is used)
-* weights_climo: set to false or omit if no orographic weights are to be used, else set it to the path to a fine-scale precipitation climatology file. If a relative file path is used, `auxiliary_data_dir` will be searched for this file. The file is expected to be in NetCDF format and should contain at least one precipitation field. If several fields at different times are provided, a climatology is derived by time averaging. Suitable climatology files could be for example a fine-scale precipitation climatology from a high-resolution regional climate model (see e.g. Terzago et al. 2018), a local high-resolution gridded climatology from observations, or a reconstruction such as those which can be downloaded from the WORLDCLIM (http://www.worldclim.org) or CHELSA (http://chelsa-climate.org) websites. The latter data will need to be converted to NetCDF format before being used (see for example the GDAL tools (https://www.gdal.org).
+* weights_climo: set to false or omit if no orographic weights are to be used, else set it to the path to a fine-scale precipitation climatology file. If a relative file path is used, ``auxiliary_data_dir`` will be searched for this file. The file is expected to be in NetCDF format and should contain at least one precipitation field. If several fields at different times are provided, a climatology is derived by time averaging. Suitable climatology files could be for example a fine-scale precipitation climatology from a high-resolution regional climate model (see e.g. Terzago et al. 2018), a local high-resolution gridded climatology from observations, or a reconstruction such as those which can be downloaded from the WORLDCLIM (http://www.worldclim.org) or CHELSA (http://chelsa-climate.org) websites. The latter data will need to be converted to NetCDF format before being used (see for example the GDAL tools (https://www.gdal.org).
 
 
 Variables
@@ -60,4 +60,4 @@ Example plots
 .. figure:: /recipes/figures/rainfarm/rainfarm.png
    :width: 14cm
 
-   Example of daily cumulated precipitation from the CMIP5 EC-EARTH model on a specific day, downscaled using RainFARM from its original resolution (1.125°) (left panel), increasing spatial resolution by a factor of 8 to 0.14°; Two stochastic realizations are shown (central and right panel). A fixed spectral slope of s=1.7 was used. Notice how the downscaled fields introduce fine scale precipitation structures, while still maintaining on average the original coarse-resolution precipitation. Different stochastic realizations are shown to demonstrate how an ensemble of realizations can be used to reproduce unresolved subgrid variability. (N.B.: this plot was not produced by ESMValTool - the recipe output is netcdf only). 
+   Example of daily cumulated precipitation from the CMIP5 EC-EARTH model on a specific day, downscaled using RainFARM from its original resolution (1.125°) (left panel), increasing spatial resolution by a factor of 8 to 0.14°; Two stochastic realizations are shown (central and right panel). A fixed spectral slope of s=1.7 was used. Notice how the downscaled fields introduce fine scale precipitation structures, while still maintaining on average the original coarse-resolution precipitation. Different stochastic realizations are shown to demonstrate how an ensemble of realizations can be used to reproduce unresolved subgrid variability. (N.B.: this plot was not produced by ESMValTool - the recipe output is netcdf only).