Benchmarking Regional Climate Variability in CMIP6 over India in the Recent Accelerated Global Warming Epoch

This study evaluated 30 CMIP6 models and their Multi-Model Mean (M3) with observations in capturing India’s regional climate variability and extremes during 2015–2024, a period when global temperatures reached approximately 1.5°C above pre-industrial levels. The mean state of the climate and Expert Team on Climate Change Detection and Indices (ETCCDI)-based extremes in models are compared against observations from the Indian Meteorological Department (IMD). The M3 showed notable skill-pattern correlations of up to 0.96 for rainfall and greater than 0.9 for temperature; Kling-Gupta Efficiency (KGE) scores also typically exceeded 0.8 for temperature and 0.6 for rainfall, especially over central and eastern India. However, substantial uncertainties remain; dry spells were underestimated by up to 8 spells/year in arid and southern India, and warm, wet days by as much as 16 days/year in key regions. Individual models struggled with daily extremes and with matching observed precipitation trends. Persistent regional errors, particularly in orographic and coastal zones, limit direct use of projections for adaptation in the coming decades. Future work should prioritise improved simulation of extremes, robust bias correction/downscaling, and advanced representation of monsoon dynamics and teleconnections. This study highlights that benchmarking climate models against high-resolution regional observational data is essential for meaningful regional risk management.