Merge branch 'main' of https://github.com/ESMValGroup/ESMValTool

Author: valeriupredoi

.zenodo.json

@@ -461,6 +461,11 @@
       "affiliation": "DLR, Germany",
       "name": "Debeire, Kevin",
       "orcid": "0000-0001-6006-8750"
+    },
+    {
+      "affiliation": "BSC, Spain",
+      "name": "Ghosh, Supriyo",
+      "orcid": "0000-0003-0581-9907"
     }
   ],
   "description": "ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP.",

CITATION.cff

@@ -457,9 +457,14 @@ authors:
     family-names: Debeire
     given-names: Kevin
     orcid: "https://orcid.org/0000-0001-6006-8750"
+  -
+    affiliation: "BSC, Spain"
+    family-names: Ghosh
+    given-names: Supriyo
+    orcid: "https://orcid.org/0000-0003-0581-9907"
 
 cff-version: 1.2.0
-date-released: 2026-07-17
+date-released: 2026-07-28
 doi: "10.5281/zenodo.3401363"
 license: "Apache-2.0"
 message: "If you use this software, please cite it using these metadata."

doc/sphinx/source/community/release_strategy/release_strategy.rst

@@ -68,23 +68,23 @@ Upcoming releases
 | 2027 Q4    | BSC                   | 2.19.0           |
 +------------+-----------------------+------------------+
 
+Past releases
+^^^^^^^^^^^^^
+
 - 2.15.0 (Release Manager: `Felicity Chun`_, `Romain Beucher`_)
 
 +------------+------------+----------------------------------------+-------------------------------------+
 |  Planned   |    Done    |            Event                       |             Changelog               |
 +============+============+========================================+=====================================+
-| 2026-06-19 |            | ESMValCore `Feature Freeze`_           |                                     |
+| 2026-06-19 | 2026-06-22 | ESMValCore `Feature Freeze`_           |                                     |
 +------------+------------+----------------------------------------+-------------------------------------+
-| 2026-06-26 |            | ESMValTool `Feature Freeze`_           |                                     |
+| 2026-06-26 | 2026-07-13 | ESMValTool `Feature Freeze`_           |                                     |
 +------------+------------+----------------------------------------+-------------------------------------+
-| 2026-07-03 |            | ESMValCore Release 2.15.0              |                                     |
+| 2026-07-03 | 2026-07-15 | :esmvalcore-release:`v2.15.0` released | :ref:`esmvalcore:changelog-v2-15-0` |
 +------------+------------+----------------------------------------+-------------------------------------+
-| 2026-07-17 |            | ESMValTool Release 2.15.0              |                                     |
+| 2026-07-17 | 2026-07-28 | :release:`v2.15.0` released            |     :ref:`changelog-v2-15-0`        |
 +------------+------------+----------------------------------------+-------------------------------------+
 
-Past releases
-^^^^^^^^^^^^^
-
 - 2.14.0 (Release Manager: `Manuel Schlund`_)
 
 +------------+------------+----------------------------------------+-------------------------------------+

doc/sphinx/source/input.rst

@@ -21,13 +21,10 @@ as used in the various
 
 .. note::
 
-    CORDEX support is still
-    work in progress.
-    Contributions, in the form of
-    :ref:`pull request reviews <reviewing>` or
-    :ref:`pull requests <esmvalcore:contributing>`
-    are most welcome. We are particularly interested in contributions from
-    people with good understanding of the CORDEX project and its standards.
+    CORDEX support is available for selected domains and variables.
+    An example workflow for CORDEX-CMIP5 EUR-11 models is described in the
+    :ref:`perfmetrics documentation <nml_perfmetrics>`.
+    Contributions improving CORDEX data handling and coverage are welcome.
 
 This section provides an introduction to getting (access to) climate data
 for use with ESMValTool.

doc/sphinx/source/recipes/figures/perfmetrics/cordex_cmip5_portrait.png

@@ -33,6 +33,7 @@ Recipes are stored in recipes/
 * recipe_perfmetrics_CMIP5.yml
 * recipe_perfmetrics_CMIP5_4cds.yml
 * recipe_perfmetrics_land_CMIP5.yml
+* recipe_perfmetrics_CORDEX-CMIP5.yml
 
 Diagnostics are stored in diag_scripts/perfmetrics/
 
@@ -49,6 +50,8 @@ Diagnostics are stored in diag_scripts/perfmetrics/
   different options for normalization.
 * collect.ncl: collects and plots the metrics previously calculated by
   cycle_latlon.ncl.
+* ``portrait_plot.py``: portrait plot of relative RMSE (used by
+  ``recipe_perfmetrics_CORDEX-CMIP5.yml``; see :ref:`recipe_portrait`)
 
 User settings in recipe
 -----------------------
@@ -182,6 +185,16 @@ Variables
     * et (land, monthly mean, longitude latitude time)
     * rlus, rlds, rsus, rdsd (atmos, monthly mean, longitude latitude time)
 
+#. recipe_perfmetrics_CORDEX-CMIP5.yml
+
+    * clivi, clt, prw, rlut, rsus (atmos, daily mean, EUR-11)
+    * lwp (atmos, daily mean, EUR-11; derived from ``clwvi`` and ``clivi`` for CORDEX
+      models, native ``lwp`` for the ESACCI-CLOUD reference)
+    * sic (sea ice, daily mean, EUR-11)
+    * snw (land, daily mean, EUR-11)
+    * lst, sst (CORDEX ``ts`` with land/sea masking; compared to ESACCI-LST / ESACCI-SST,
+      daily mean, EUR-11)
+
 Observations and reformat scripts
 ---------------------------------
 
@@ -222,6 +235,21 @@ for downloading and processing instructions.
     * Landschuetzer2016 (fgco2 - esmvaltool/cmorizers/data/formatters/datasets/landschuetzer2016.py)
     * MTE (gpp - esmvaltool/cmorizers/data/formatters/datasets/mte.py)
 
+#. recipe_perfmetrics_CORDEX-CMIP5.yml
+
+    * ESACCI-CLOUD (clivi, clt, lwp, rlut, rsus -
+      esmvaltool/cmorizers/data/formatters/datasets/esacci_cloud.py)
+    * ESACCI-WATERVAPOUR (prw -
+      esmvaltool/cmorizers/data/formatters/datasets/esacci_watervapour.py)
+    * ESACCI-SEAICE (sic -
+      esmvaltool/cmorizers/data/formatters/datasets/esacci_seaice.py)
+    * ESACCI-SNOW (snw -
+      esmvaltool/cmorizers/data/formatters/datasets/esacci_snow.py)
+    * ESACCI-LST (ts -
+      esmvaltool/cmorizers/data/formatters/datasets/esacci_lst.py)
+    * ESACCI-SST (tos -
+      esmvaltool/cmorizers/data/formatters/datasets/esacci_sst.py)
+
 References
 ----------
 
@@ -273,3 +301,11 @@ Example plots
    A diagonal split of a grid square shows the relative error with respect to the reference data set
    (lower right triangle) and the alternative data set (upper left triangle).
    White boxes are used when data are not available for a given model and variable.
+
+.. figure:: /recipes/figures/perfmetrics/cordex_cmip5_portrait.png
+   :width: 70%
+   :align: center
+
+   Relative RMSE (centered median normalization) of CORDEX-CMIP5 EUR-11 models
+   against ESA CCI reference data for 2003–2005, produced by
+   ``recipe_perfmetrics_CORDEX-CMIP5.yml`` using ``portrait_plot.py``.

doc/sphinx/source/recipes/recipe_perfmetrics.rst

@@ -254,6 +254,10 @@ authors:
     name: Gettelman, Andrew
     institute: NCAR, USA
     orcid: https://orcid.org/0000-0002-8284-2599
+  ghosh_supriyo:
+    name: Ghosh, Supriyo
+    institute: BSC, Spain
+    orcid: https://orcid.org/0000-0003-0581-9907
   gier_bettina:
     name: Gier, Bettina
     institute: University of Bremen, Germany

esmvaltool/config-references.yml

@@ -786,7 +786,11 @@ def plot_settings(self) -> dict[str, dict[str, Any]]:
             },
             "map": {
                 "function": partial(self.create_2d_plot, "map"),
-                "coords": (["longitude", "latitude"],),
+                "coords": (
+                    ["longitude", "latitude"],
+                    ["grid_longitude", "grid_latitude"],
+                    ["projection_x_coordinate", "projection_y_coordinate"],
+                ),
                 "provenance": {
                     "authors": ["schlund_manuel"],
                     "caption": "Map plot of {long_name} of dataset {alias}.",

esmvaltool/diag_scripts/monitor/multi_datasets.py

@@ -402,7 +402,7 @@ def plot(cfg, data):
         axes_pad=0.1,
     )
     # remap colorbar to 10 discrete steps
-    cmap = mpl.cm.get_cmap(cfg["plot_kwargs"]["cmap"], 10)
+    cmap = plt.get_cmap(cfg["plot_kwargs"]["cmap"], 10)
     cfg["plot_kwargs"]["cmap"] = cmap
     for i in range(group_count):
         group = data.isel({cfg["group_by"]: i})