Increase in Indian summer monsoon precipitation as a response to doubled atmospheric CO2: CMIP6 simulations and projections

Indian summer monsoon (ISM) inter-annual variability on spatial and temporal scale is evaluated with CMIP6 models based on historical simulations. We have selected the best ten models based on the model’s ability to represent mean seasonal precipitation, annual cycle of precipitation, and coefficient of variation. For these selected models, historical simulation of JJAS (June–September) total precipitation is also evaluated. We found that CMIP6 models depict better pattern correlation (with observation) in representing mean monsoon. Ensemble mean of models has greater skill. Further, total precipitation bifurcation of convective and large-scale rain is also investigated. Model depicts overestimation of convective precipitation and underestimation of stratiform precipitation. Ensemble mean is also depicting overestimation of convective precipitation although it is better than individual models. Model simulated total cloud fraction depict pattern correlation of above 0.6 with respect to observation. In case of multi-model ensemble, pattern correlation of total cloud fraction reaches to 0.85. Further, selected CMIP6 models are used for the estimation of future projections of rainfall in the warming scenario (1 percent increase in CO2 concentration: 1pctCO2). Models depict increased precipitation over Indian land region in future scenarios, and variability is also supposed to be increased due to projected increase in standard deviation of precipitation.