Does increasing the spatial resolution in dynamical downscaling impact climate change projection of Indian summer monsoon, population and GDP?

High-resolution regional climate model (RCM) simulations are found to be very useful in deriving realistic change projection information. This study uses high-resolution dynamical downscaling framework (CCSM4-WRF) for India. To delineate the advantage of high resolution, we compared results 9-km resolution CCSM4-WRF against 50-km RCM under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) program. Quantitative estimations show that majority CORDEX-SA models exhibit large dry bias (< − 4 mm/day) and low pattern correlation coefficient (PCC) over Western Ghats (WG). Mean climatology Indian summer monsoon (ISM) rainfall simulated by outperforms RCMs with negative biases (~ 1 PCC (≥ 0.755). skill provides better confidence its future at local scale. projects intensification most parts India reduction southern WG, which is consistent recent observed trends, but none could simulate this reduction. For all-India rainfall, ensemble mean an increase 1.3 ± 0.9 mm/day 0.67 mm/day. Projected changes socioeconomic variables such as population gross domestic product (GDP) enhancement spatial heterogeneity. Shared pathways scenarios pronounced growth coastal areas productivity urban areas. Therefore, information ISM together enhanced GDP, taking necessary steps adaptation mitigation a sustainable manner.