Evaluation of state-of-the-art GCMs in simulating Indian summer monsoon rainfall

Abstract

Seasonal prediction of Indian summer monsoon rainfall has been considered as one of the important factors to decide the social and economic aspect of India because of its multi-sectorial dependencies. This study evaluates the performance of seven state-of-the-art GCMs in simulating the summer monsoon rainfall on a seasonal scale over the period of 1982�2008 using the GCM reforecasts. The rainfall simulated by the models is compared with the IMD observed rainfall dataset at 0.25� � 0.25�. Preliminary analysis of spatial pattern and statistics shows that the models IITM-CFSv2, NCEP-CFSv2 and ECMWF are some of the prominent models that capture the seasonal rainfall pattern and possess good skill. ECMWF performs very well in simulating the rainfall pattern as well as the rainfall intensities. Comprehensive statistical analysis such as standard deviation ratio and skill scores concludes that the IITM-CFSv2 produces the rainfall pattern as well as the variability of the summer monsoon better than its counterparts. The multi-model simple mean also tends to improve with the addition of IITM-CFSv2. Though the rainfall trend and variance simulated by IITM-CFSv2 is quite in agreement with the observed, there lies a significant dry bias over the north-west India. The mean simulated rainfall is quite less with the CFSv2 models. Though the IITM-CFSv2 simulates lesser rainfall at all the four-lead times, it is quite capable in capturing the rainfall variability. The models ECMWF and GFDLA04 are well performers in terms of mean rainfall estimates whereas the models CFSv2 is better in terms of reproducing the rainfall variability. � 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.