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Evolution of the Indian summer monsoon rainfall simulations from CMIP3 to CMIP6 models

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Abstract

Systematic biases in simulation of the mean and variability of Indian summer monsoon rainfall (ISMR) and its teleconnection with the El Nino and Southern Oscillation (ENSO) by climate models have proven to be roadblocks for improving the seasonal prediction skill of the ISMR. Yet, the improvements of these biases in simulating the ISMR by coupled ocean–atmosphere general circulation models (CGCMs) have been slow. Here, we investigate the progress made by the latest CMIP6 models in simulating the mean and variability of the ISMR including its multi-decadal variability in comparison to the earlier CMIP3 and CMIP5 models and unravel key common and persisting biases. That the number of models simulating the pattern of climatological mean summer rainfall over the region with fidelity has increased from less than 10% in CMIP3 to more than 50% in CMIP6 is a notable progress. The CMIP6 models also indicate notable progress in simulating the inter-annual, multi-decadal variability and marginal improvement in simulating the ENSO-ISMR correlations. In addition to consolidating these advances in simulating the ISMR in more climate models, future developments must focus on improving the following three persisting biases namely; (1) most models, including those in CMIP6, tend to simulate the mean location of the continental ITCZ during June–September (JJAS) about 10° south of the observed location of ~ 22° N, (2) with the ensemble mean 21-year moving correlation between ISMR and JJAS mean Nino3.4 sea surface temperature for all models being ~ − 0.3 compared to observed ~ − 0.65, almost all models simulate significantly weaker ENSO-monsoon relationship and (3) the number of models simulating the observed variance and periodicity of the multi-decadal variability of ISMR remains small even in CMIP6. We argue that the position bias in simulating the continental ITCZ may be related to the large and significant biases in simulating the JJAS SST over the tropical Indian Ocean, persistent even in the best of CMIP6 CGCMs making the improvement of SST biases (and associated heat transport across the equator) another area where future model developments need to focus.

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Acknowledgements

BNG is grateful to the Science and Engineering Research Board (SERB), Government of India for Fellowship and Research Grant supporting PVR, BAC and YZ. The authors are grateful to three anonymous reviewers for their constructive comments and suggestion that improved the presentation and clarity of the manuscript significantly. The CMIP data are downloaded from https://esgf-node.llnl.gov/projects/cmip6/, https://esgf-node.llnl.gov/projects/cmip5/, https://esgf-node.llnl.gov/projects/cmip3/. The authors thank the organizations responsible for making them freely available.

Funding

The research is supported by funding from Science and Engineering Research Board (SERB), Government of India. Science and Engineering Research Board, Diary No. SERBIF/ 3707 12020-21 dated 25/09/2020.

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  1. Department of Physics, Cotton University, Guwahati, 781001, India

    B. Abida Choudhury, P. V. Rajesh, Yasmin Zahan & B. N. Goswami

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  1. B. Abida Choudhury
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BNG conceived the study while BAC carried out most analysis with contributions from RPV. The first draft of the manuscript prepared by BNG and is improved with a major contribution from BAC also with some critical feedbacks from RPV and YZ.

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Correspondence to B. Abida Choudhury.

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The observed rainfall data sources are– http://aphrodite.st.hirosaki-u.ac.jp/products.html (APHRODITE), https://tropmet.res.in/static_pages.php?page_id=53 (Obs1), https://www.tropmet.res.in/Data%20Archival-52-Page#data (Obs3), https://psl.noaa.gov/data/gridded/data.gpcp.html (GPCP). The SST (observation) data is obtained from– https://psl.noaa.gov/data/gridded/data.cobe.html (COBE). The CMIPs data are obtained from https://esgf-node.llnl.gov/projects/cmip6/, https://esgf-node.llnl.gov/projects/cmip5/, https://esgf-node.llnl.gov/projects/cmip3/.

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Choudhury, B.A., Rajesh, P.V., Zahan, Y. et al. Evolution of the Indian summer monsoon rainfall simulations from CMIP3 to CMIP6 models. Clim Dyn 58, 2637–2662 (2022). https://doi.org/10.1007/s00382-021-06023-0

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