In this study, a comparison of 17 Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets with Indian Meteorological Department (IMD) data in terms of finding out extreme precipitation indices obtained by the Expert Team on Climate Change Detection and Indices (ETCCDI) is done. The extreme indices considered were the consecutive dry days (CDD), consecutive wet days (CWD), maximum 1-day precipitation (RX1DAY), maximum 5-day precipitation (RX5DAY), precipitation > 2.5 mm (RR2.5), heavy precipitation > 10 mm (R10MM), very heavy precipitation > 20 mm (R20MM), and simple daily intensity (SDII) that have been calculated for 17 CMIP6 datasets from 1950 to 2014 with IMD-gridded precipitation datasets over India. Rankings were assigned using the TOPSIS method with evaluation metrics as CC and RMSE as conditions. Almost all datasets performed well for indices, i.e., CWD, R10MM, R20MM, and RR2.5. The top 5 performing models are EC-Earth3, EC-Earth3-Veg, MRI-ESM2-0, GFDL-ESM4, and MIROC6 which were ensembled and projected for future periods in the near (2015-2040), middle (2041-2070), and far future (2070-2100), and extreme indices were calculated under Shared Socioeconomic Pathways 126 (SSP126), SSP245, SSP370, and SSP585 scenarios. The ensemble mean shows that RX1DAY, RX5DAY, R10MM, R20MM, and CWD are observed to increase in western ghats and northeastern regions of India. Central India exhibits a dynamic influence on precipitation indices in different climate change scenarios. The temporal variation for the SSP585 scenario predicts significant increases of about 45.41%, 149.40%, 52.26%, and 45.92% in R10MM, R20MM, RX1DAY, and RX5DAY over the current climate. Future extreme precipitation indices help flood modelers and hydrologists with watershed management.
Keywords: CMIP6; ETCCDI; Extreme precipitation indices; India; SSP; TOPSIS.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.