文献类型：期刊文献

英文题名：Refined Assessment and Future Projections of Indian Summer Monsoon Rainfall Using CMIP6 Models

作者：Li, Jiahao[1];Fan, Lingli[1];Chen, Xuzhe[1];Lin, Chunqiao[1];Song, Luchi[1];Xu, Jianjun[2]

机构：[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang 524088, Peoples R China;[2]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen 518120, Peoples R China

年份：2023

卷号：15

期号：24

外文期刊名：WATER

收录：SCI-EXPANDED(收录号：WOS:001130614900001)、、Scopus(收录号：2-s2.0-85180217181)、WOS

基金：We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (https://esgf-index1.ceda.ac.uk/search/cmip6-ceda/) for producing and making available their model output.

语种：英文

外文关键词：Indian summer monsoon rainfall; CMIP6; model assessment; projected rainfall trend

外文摘要：Analyzing and forecasting the Indian Summer Monsoon Rainfall (ISMR) is vital for South Asia's socio-economic stability. Using 35 climate models from the latest generation of the Coupled Model Intercomparison Project (CMIP6) to simulate and project ISMR, we integrated statistical methods, such as Taylor diagrams, comprehensive rating indicators, and interannual variability scores, to compare performance differences between various models and analyze influencing mechanisms. The results show that the majority of models effectively simulate the climatology of the ISMR. However, they exhibit limitations in accurately capturing its interannual variability. Importantly, we observed no significant correlation between a model's ability to simulate ISMR's general climatology and its accuracy in representing annual variability. After a comprehensive assessment, models, like BCC-ESM1, EC-Earth3-Veg, GFDL-CM4, INM-CM5-0, and SAM0-UNICON were identified as part of the prime model mean ensemble (pMME), demonstrating superior performance in spatiotemporal simulations. The pMME can accurately simulate the sea surface temperature changes in the North Indian Ocean and the atmospheric circulation characteristics of South Asia. This accuracy is pivotal for CMIP6's prime models to precisely simulate ISMR climatic variations. CMIP6 projections suggest that, by the end of the 21st century, ISMR will increase under low, medium, and high emission scenarios, with a significant rise in rainfall under the high emission scenario, especially in the western and northern parts of India. Among the pMME, the projected increase in rainfall across India is more moderate, with an estimated increase of 30%. The findings of this study suggest that selecting the best models for regional climate downscaling research will project regional climate changes more accurately. This provides valuable recommendations for model improvements in the Indian region.