Figure number: Figure 10.19 From the IPCC Working Group I Contribution to the Sixth Assessment Report: Chapter 10
Changes in the Indian summer monsoon in the historical and future periods. (a) Observational uncertainty demonstrated by a snapshot of rain-gauge density (% of 0.05°-subgrid boxes containing at least one gauge) in the APHRO-MA 0.5° daily precipitation dataset for June to September 1956. (b) Multi-model ensemble (MME)-mean bias of 34 CMIP6 models for June to September precipitation (mm day-1) compared to CRU TS observations for the 1985‒2010 period. (c) Maps of rainfall trends (mm day-1 per decade) in CRU TS observations (1950‒2000), the CMIP6 MME-mean of SSP5-8.5 future projections for 2015‒2100 (34 models), the CMIP6 hist-GHG and hist-aer runs, both measured over 1950 to 2000. (d) Low-pass filtered time series of June to September precipitation anomalies (%, relative to 1995‒2014 baseline) averaged over the central India box shown in panel (b). The averaging region (20°N‒28°N, 76°E‒87°E) follows other works (Bollasina, Ming, & Ramaswamy, 2011; Huang et al., 2020; Jin & Wang, 2017). Time series are shown for CRU TS (brown), GPCC (dark blue), REGEN (green), APHRO-MA (light brown) observational estimates and the IITM all-India rainfall product (light blue) in comparison with the CMIP6 mean of 13 models for the all-forcings historical (pink) the aerosol-only (hist-aer, grey) and greenhouse gas-only (hist-GHG, blue). Dark red and blue lines show low-pass filtered MME-mean change in the CMIP6 historical/SSP5-8.5 (34 models) and CMIP5 historical/RCP8.5 (41 models) experiments for future projections to 2100. The filter is the same as that used in Figure 10.11(d). To the right, box-and-whisker plots show the 2081‒2100 change averaged over the CMIP5 (blue) and CMIP6 (dark red) ensembles. Note that some models exceed the plotting range (CMIP5: GISS-E2-R-CC, GISS-E2-R & IPSL-CM5B-LRl and CMIP6: CanESM5-CanOE, CanESM5 & GISS-E2-1-G). (e) Precipitation linear trend (% per decade) over central India for historical 1950‒2000 (left) and future 2015‒2100 (right) periods in Indian monsoon rainfall in observed estimates (black crosses), the CMIP5 historical-RCP8.5 simulations (blue), the CMIP6 ensemble (dark red) for historical all-forcings experiment and SSP5-8.5 future projection, the CMIP6 hist-GHG (light blue triangles), hist-aer (grey triangles) and historical all-forcings (same sample as for hist-aer and hist-GHG, pink circles). Ensemble means are also shown. Box-and-whisker plots show the trend distribution of the three coupled and the d4PDF atmosphere-only (for past period only) SMILEs used throughout Chapter 10 and follow the methodology used in Figure 10.6. (f) Example spread of trends (mm day -1 per decade) out to the near term (2016‒2045) in RCP8.5 SMILE experiments of the MPI-ESM model, showing the difference between the three driest and three wettest trends among ensemble members over central India. All trends are estimated using ordinary least-squares regression. Further details on data sources and processing are available in the chapter data table (Table 10.SM.11).
- Jury, M.W.: BSC, Spain; martin.w.jury@gmail.com; githubid: mwjury
- Turner, A.: University of Reading, UK
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- ESMValTool-AR6-OriginalCode-FinalFigures: ar6_chapter_10
- ESMValCore-AR6-OriginalCode-FinalFigures: working_cordex_2.2
Recipe used: recipes/ar6_wgi_ch10/recipe_IndianMonsoon.yml
Diagnostic used: diag_scripts/ar6_wgi_ch10/diagnostic_IPCC_AR6_CH10.py
This is the path of the image relative to the automatically generated ESMValTool output location:
- recipe_IndianMonsoon_YYYYMMDD_HHMMSS/plots/ch_10/fig_19/Fig_19.png
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'external' data has been included in ESMValTool totalling ~11KB
- IITM obs timeseries (11KB): esmvaltool/diag_scripts/ar6_wgi_ch10/CH10_additional_data/ATurner_SouthAsia/iitm-regionrf_all_india.csv
- ESMValTool environment file: IPCC_environments/ar6_chapter_10_conda_environment.yml
- pip file: IPCC_environments/ar6_chapter_10_pip_environment.txt
Internal Wegener Center (University of Graz, Austria) machine wegc203128.
** The documentation was created by Chapter 10 Chapter Scientist Martin W. Jury (email: martin.w.jury@gmail.com, githubid: mwjury). Please, contact Martin in case any questions in documentation arise.