Accuracy of historical precipitation from CMIP6 global climate models under diversified climatic features over India

The importance of global climate models (GCMs) is increasingly recognized due to their excellent ability to accurately predict climatic factors. These capabilities prove invaluable to water resources engineers as they facilitate effective planning and strategic decision -making. Finally, evaluating the performance of GCMs is very important because it allows us to simulate and predict different climate scenarios, empowering us to make informed choices. Therefore, the purpose of this study is to determine the degree of discordance between historical simulated data produced by the CMIP6 models and historical observational data over different climate zones of India. The ability of 24 different GCMs to reproduce the geographical and seasonal distribution of Indian precipitation has been tested by analyzing the daily historical precipitation forecasts from these models. These models have been used to estimate the degree of uncertainty associated with the spatiotemporal variability of precipitation forecasts. More than 20% percent bias (PBIAS) is observed to occur predominantly in four climate classifications: polar tundra, temperate, cold, and tropical monsoon. In some regions of India, the CMIP6 models produce overestimated or underestimated results. The locations identified indicate that there have been changes of more than 20% PBIAS near Sivalik Range, Naga Hills, and Western Ghats. The precipitations of those regions that have been underestimated also imply that those locations have different climatic conditions. This study also highlights that CMIP6 GCMs are yet to produce better results near several Indian mountainous regions depending upon climates. The outcomes of this study will be very useful for reconstructing modeled data for that specific regions.