Cloud properties and their projected changes in CMIP models with low to high climate sensitivity

Overview

The recipes recipe_bock24acp_*.yml reproduce figures (Fig. 3, 4, 6 and 7) from the publication Bock and Lauer, 2024 investigating cloud properties and their projected changes in CMIP models with low to high climate sensitivity.

Available recipes and diagnostics

Recipes are stored in recipes/clouds

• recipe_bock24acp_fig3-4_maps.yml

• recipe_bock24acp_fig6_zonal.yml

• recipe_bock24acp_fig7_boxplots.yml

Diagnostics are stored in diag_scripts/

Fig. 3 and 4:

• clouds/clouds_ecs_groups_maps.py: Geographical maps of the multi-year annual means for group means of historical CMIP simulations from all three ECS groups.

Fig. 6:

• clouds/clouds_ecs_groups_zonal.py: Zonally averaged group means.

Fig. 7:

• clouds/clouds_ecs_groups_boxplots.py: Boxplots of relative changes for all groups.

User settings in recipe

1. Script clouds_ecs_groups_maps.py

   Required settings (scripts)

   reference: if true, a reference dataset is given within ‘variable_group’ equal ‘OBS’

   Optional settings (scripts)

   plot_each_model: one figure for each single model

2. Script clouds/clouds_ecs_groups_zonal.py

   Required settings (scripts)

   group_by: list of ‘variable_group’s to have the order plot_type: ‘zonal’ and ‘height’ plots are available

   Optional settings (scripts)

   filename_attach: attachment to the output files

3. Script clouds/clouds_ecs_groups_boxplots.py

   Required settings (scripts)

   exclude_datasets: list of datasets which are not used for the statistics, default is [‘MultiModelMean’, ‘MultiModelP5’, ‘MultiModelP95’] group_by: list of ‘variable_group’s to have the order plot_type: ‘zonal’ and ‘height’ plots are available

   Optional settings (scripts)

   filename_attach: attachment to the output files title: set title of figure y_range: set range of the y-axes

Variables

• clt (atmos, monthly, longitude latitude time)

• clivi (atmos, monthly, longitude latitude time)

• clwvi (atmos, monthly, longitude latitude time)

• rlut (atmos, monthly, longitude latitude time)

• rsut (atmos, monthly, longitude latitude time)

• rlutcs (atmos, monthly, longitude latitude time)

• rsutcs (atmos, monthly, longitude latitude time)

• tas (atmos, monthly, longitude latitude time)

Observations and reformat scripts

• CERES-EBAF (Ed4.2) - TOA radiation fluxes (used for calculation of the cloud radiative effects)

  Reformat script: cmorizers/data/formatters/datasets/ceres_ebaf.py

References

• Bock, L. and Lauer, A.: Cloud properties and their projected changes in CMIP models with low to high climate sensitivity, Atmos. Chem. Phys., 24, 1587–1605, https://doi.org/10.5194/acp-24-1587-2024, 2024.

Example plots

Fig. 141 Geographical map of the multi-year annual mean net cloud radiative effect from (a) CERES–EBAF Ed4.2 (OBS) and (b–d) group means of historical CMIP simulations from all three ECS groups (Fig. 4).

Fig. 142 The upper panel show the zonally averaged group means of total cloud fraction from historical simulations (solid lines) and RCP8.5/SSP5-8.5 scenarios (dashed lines) for the three different ECS groups. Lower panels show the corresponding relative differences of all zonally averaged group means between the RCP8.5/SSP5-8.5 scenarios and the corresponding historical simulations. Shading indicates the 5 % and 95 % quantiles of the single model results (Fig. 6a).

Fig. 143 Relative change (calculated as the difference between the scenario value and the historical value divided by the historical value) of total cloud fraction (clt), ice water path (iwp), liquid water path (lwp), and net cloud radiative effect (netcre) per degree of warming averaged over the Southern Ocean (30–65°S). In the box plot, each box indicates the range from the first quartile to the third quartile, the vertical line shows the median, and the whiskers the minimum and maximum values, excluding the outliers. Outliers are defined as being outside 1.5 times the interquartile range (Fig. 7b).