Reliable projection of future rainfall at local and regional scales is crucial for climate impact assessments, agricultural planning, and water resource management, particularly in monsoon-dependent regions like India. However, the coarse spatial resolution and inherent uncertainties of General Circulation Model (GCM) outputs limit their direct applicability for regional-scale analyses and necessitate their downscaling. The present study uses a chaos theory-based local approximation approach for downscaling of rainfall from future GCM projections. The outputs from five CMIP6 GCMs (CMCC-ESM2, CESM2-WACCM, EC-Earth3-Veg, CMCC-CM2-SR5, and BCC-CSM2-MR) are used to downscale monthly rainfall at a finer resolution (0.25° × 0.25°) across India. For each GCM, eight climate variables (eastward wind, northward wind, relative humidity, specific humidity, surface temperature, air temperature, sea level pressure, and geopotential height) are considered as predictors. The effectiveness of the downscaling framework is first demonstrated on the historical period (1961–2014) for all five GCMs, with observed precipitation data from the India Meteorological Department (IMD) as the predictand. Future rainfall (2015–2099) is downscaled under four different shared socioeconomic pathways scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Changes in future rainfall, relative to the baseline period of 1961–2014, are analyzed across three different timeframes: the 2020s (2020–2039) – the near-future; 2040s (2040–2069) – the mid-future; and 2070s (2070–2099) – the far-future. Future projections indicate a notable decline in southwest monsoon rainfall across eastern India and the Western Ghats, particularly under high-emission scenarios (SSP3-7.0 and SSP5-8.5), with some regions in western India also expected to experience an increase in southwest monsoon rainfall. The northeast monsoon is expected to increase in the northern, northeastern, and Western Ghats regions, especially in the far-future under high-emission scenarios. This indicates a potential shift in seasonal water availability that could impact regional water management strategies.
Deepthi et al. (Sun,) studied this question.