Comparison of CMIP6 and CMIP5 Models in Projections of Precipitation and Temperature over Central India

The South Asian monsoon is a lifeline of over two billion inhabitants of the Indian subcontinent. Hence, a reliable monsoon prediction system is essential for the operation of weather and climate over the region. The state-of-art General Circulation Models (GCMs) are powerful tools for monsoon prediction and assessing the effects of climate change on precipitation and temperature in rising extreme events such as floods, storms, heatwaves, and drought. However, selecting appropriate GCMs is a grand challenge for assessing climate change projections due to their significant uncertainties. The present study will evaluate the relative performance of GCMs of phases 5 and 6 of the Coupled Model Intercomparison Project dataset based on their multi-model mean (MMM) ability to project rainfall and temperature during the summer season (JJAS) over central India. In addition to the spatial patterns under the Shared Socioeconomic Pathways (SSPs), the study will also examine the model's ability to simulate interannual variability. The present research aims to determine the most reliable CMIP6 and CMIP5 datasets model and their comparison in simulation and projection of seasonal temperature and precipitation. The seasonal climatological mean of GCMs simulated rainfall and temperature shows variability at different scales over central India. CMIP6 multi-model mean demonstrate a reasonably well performance than CMIP5 in the seasonal mean cycle simulation with a better representation of the rainfall. The present study will also investigate the changes in sources of projection uncertainty and future precipitation indices. Finally, the current research will discuss the highlights of comparing the CMIP6 and CMIP5 datasets and their representations of better simulation performances based on the skill score metrics of precipitation and temperature indices.

KEYWORDS. CMIP6, CMIP5, MMM precipitation and temperature, Projection