Create scatterplots for the REF

doc/sphinx/source/recipes/recipe_ref.rst

@@ -16,7 +16,10 @@ Available recipes
 Recipes are stored in recipes/ref
 
 * recipe_ref_cre.yml:
-    Maps and zonal means of longwave and shortwave cloud radiative effect
+   Maps and zonal means of longwave and shortwave cloud radiative effect.
+
+* recipe_ref_scatterplot.yml
+   2D histograms with focus on clouds.
 
 
 Example plots:
@@ -36,3 +39,17 @@ Example plots:
    Zonal averages of the climatological mean longwave cloud radiative
    effect from CERES-EBAF Ed4.2 (solid black), ESACCI-CLOUD (dashed black), 
    ISCCP-FH (dotted black) and the MPI-ESM1-2-LR model (blue).
+
+.. _fig_ref_3:
+.. figure::  /recipes/figures/ref/seaborn_jointplot.png
+   :align:   center
+
+   2D histogram of total cloud fraction and longwave cloud radiative
+   effect from CESM2-WACCM for the years 2002-2014 with 1D histograms attached.
+
+.. _fig_ref_4:
+.. figure::  /recipes/figures/ref/seaborn_displot.png
+   :align:   center
+
+   2D histogram of total cloud fraction and longwave cloud radiative
+   effect from CESM2-WACCM and ESACCI-CLOUD for the years 2002-2014.

esmvaltool/diag_scripts/seaborn_diag.py

@@ -148,6 +148,7 @@ def _create_plot(
         plot_func_str,
         _get_str_from_kwargs(plot_kwargs),
     )
+
     plot_obj = plot_func(data=data_frame, **plot_kwargs)
 
     # Adjust plot appearance
@@ -443,6 +444,14 @@ def _set_legend_title(plot_obj, legend_title: str) -> None:
         legend = plot_obj.get_legend()
     elif hasattr(plot_obj, 'legend'):  # FacetGrid, PairGrid
         legend = plot_obj.legend
+    elif isinstance(plot_obj, sns.axisgrid.JointGrid):  # JointGrid
+        # Manually create a legend if needed in JointGrid
+        handles, labels = plot_obj.ax_joint.get_legend_handles_labels()
+        if handles and labels:
+            legend = plot_obj.ax_joint.legend(handles=handles, labels=labels,
+                                              title=legend_title)
+        else:
+            legend = None
     else:
         raise ValueError(
             f"Cannot set legend title, `{type(plot_obj).__name__}` does not "

esmvaltool/recipes/ref/recipe_ref_scatterplot.yml

@@ -0,0 +1,113 @@
+# ESMValTool
+---
+documentation:
+  title: Model evaluation with focus on clouds.
+  description: >
+    Plot scatter plots of two different variables using the Seaborn diagnostic 
+    in ESMValTool.
+  authors:
+    - bock_lisa
+    - lauer_axel
+  maintainer:
+    - bock_lisa
+
+timerange_for_models: &time_period
+  timerange: '2005/2014'  # can be specified, this is just an example
+
+diagnostics:
+  plot_joint_clt_lwcre:
+    description: Scatterplot clt vs lwcre.
+    variables:
+      clt:
+        mip: Amon
+        exp: historical
+        ensemble: r1i1p1
+        <<: *time_period
+      lwcre:
+        mip: Amon
+        derive: true
+        force_derivation: false
+        exp: historical
+        ensemble: r1i1p1
+        <<: *time_period
+    additional_datasets:
+      - {dataset: CESM2-WACCM, project: CMIP6, grid: gn, ensemble: r1i1p1f1}
+    scripts:
+      plot:
+        script: seaborn_diag.py
+        seaborn_func: jointplot
+        title: 
+        seaborn_kwargs:
+          kind: hist
+          x: clt
+          y: lwcre
+          bins: 20                    # Adjust binning for histograms
+          stat: probability
+          cmap: YlGnBu
+          marginal_ticks: True
+          marginal_kws:
+            color: darkturquoise
+            bins: 20
+            fill: True
+            stat: probability
+        add_aux_coords: true
+        dropna_kwargs:
+          axis: 0
+          how: any
+        plot_object_methods:
+          set_axis_labels:
+            xlabel: 'clt [%]'
+            ylabel: 'lwcre [W m-2]'
+        seaborn_settings:
+          style: ticks
+          rc:
+            axes.titlepad: 15.0
+
+  plot_hist_with_ref_clt_lwcre:
+    description: Scatterplot clt vs swcre with reference.
+    variables:
+      clt:
+        mip: Amon
+        exp: historical
+        ensemble: r1i1p1
+        <<: *time_period
+      lwcre:
+        mip: Amon
+        derive: true
+        force_derivation: false
+        exp: historical
+        ensemble: r1i1p1
+        <<: *time_period
+    additional_datasets:
+      - {dataset: ESACCI-CLOUD, project: OBS, type: sat, version: AVHRR-AMPM-fv3.0, tier: 2, alias: ESACCI-CLOUD}
+      - {dataset: CESM2-WACCM, project: CMIP6, grid: gn, ensemble: r1i1p1f1, alias: CESM2-WACCM}
+    scripts:
+      plot:
+        script: seaborn_diag.py
+        seaborn_func: displot
+        seaborn_kwargs:
+          kind: hist
+          col: alias                # Creates side-by-side plots for each dataset
+          x: clt
+          y: lwcre
+          bins: 20                    # Adjust binning for histograms
+          height: 5                   # Set height of each subplot
+          aspect: 1.2                 # Set aspect ratio
+          stat: probability 
+          common_norm: True
+          cmap: YlGnBu
+          cbar: True                  # Includes a color bar
+          cbar_kws:
+            label: "Probability"
+        add_aux_coords: true
+        dropna_kwargs:
+          axis: 0
+          how: any
+        plot_object_methods:
+          set_axis_labels:
+            xlabel: 'clt [%]'
+            ylabel: 'swcre [W m-2]'
+        seaborn_settings:
+          style: ticks
+          rc:
+            axes.titlepad: 15.0