Figure number: 3.13 From the IPCC Working Group I Contribution to the Sixth Assessment Report: Chapter 3
Annual-mean precipitation rate (mm day–1) for the period 1995–2014. (a) Multi- model (ensemble) mean constructed with one realization of the CMIP6 historical experiments from each model. (b) Multi- model mean bias, defined as the difference between the CMIP6 multi-model mean and precipitation analyses from the Global Precipitation Climatology Project (GPCP) version 2.3 (Adler et al., 2003). (c) Multi-model mean of the root mean square error calculated over all months separately and averaged with respect to the precipitation analyses from GPCP v2.3. (d) Multi-model-mean bias, calculated as the difference between the CMIP6 multi-model mean and the precipitation analyses from GPCP v2.3. Also shown is the multi-model mean bias as the difference between the multi-model mean of (e) high resolution and (f) low resolution simulations of four HighResMIP models and the precipitation analyses from GPCP v2.3. Uncertainty is represented using the advanced approach: No overlay indicates regions with robust signal, where ≥66% of models show change greater than variability threshold and ≥80% of all models agree on sign of change; diagonal lines indicate regions with no change or no robust signal, where <66% of models show a change greater than the variability threshold; crossed lines indicate regions with conflicting signal, where ≥66% of models show change greater than variability threshold and <80% of all models agree on sign of change. For more information on the advanced approach, please refer to the Cross-Chapter Box Atlas.1. Stippling in panel e) marks areas where the bias in high resolution versions of the HighResMIP models is lower in at least 3 out of 4 models than in the corresponding low resolution versions.
- Bock, L.: DLR, Germany; lisa.bock@dlr.de
- Barreiro, M.: Universidad de la República, Uruguay
- Eyring, V.: DLR., Germany
Bock, L., Lauer, A., Schlund, M., Barreiro, M., Bellouin, N., Jones, C., Predoi, V., Meehl, G., Roberts, M., and Eyring, V.: Quantifying progress across different CMIP phases with the ESMValTool, Journal of Geophysical Research: Atmospheres, 125, e2019JD032321. https://doi.org/10.1029/2019JD032321
- ESMValTool-AR6-OriginalCode-FinalFigures: ar6_chapter_3
- ESMValCore-AR6-OriginalCode-FinalFigures: fix_cmip6_models_newcore
Recipes used:
- recipes/ipccwg1ar6ch3/recipe_ipccwg1ar6ch3_atmosphere.yml
- recipes/ipccwg1ar6ch3/recipe_ipccwg1ar6ch3_highres.yml
Diagnostics used:
- diag_scripts/ipcc_ar5/ch12_calc_IAV_for_stippandhatch.ncl
- diag_scripts/ipcc_ar6/model_bias.ncl
- diag_scripts/ipcc_ar6/model_bias_diff.ncl
- recipe_ipccwg1ar6ch3_atmosphere_YYYYMMDD_HHMMSS/plots/fig_3_13_cmip5/fig_3_13/model_bias_pr_annualclim_CMIP5.eps
- recipe_ipccwg1ar6ch3_atmosphere_YYYYMMDD_HHMMSS/plots/fig_3_13_cmip6/fig_3_13/model_bias_pr_annualclim_CMIP6.eps
- ESMValTool environment file: IPCC_environments/ar6_newcore_lisa_conda_environment.yml
- pip file: IPCC_environments/ar6_newcore_lisa_pip_environment.txt
Machine used: Mistral