Accurate regional climate information is vital for hydrological applications, impact studies, and adaptation planning. However, Global Climate Model (GCM) outputs are constrained by coarse resolution and systematic biases, limiting their utility over the climatically diverse and topographically complex Indian subcontinent. To address this, we present INDRA-CMIP6, a high-resolution (0.1° × 0.1°) daily dataset of precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) for the historical period (1951–2014) and future projections (2015–2100) under four emission scenarios (SSP126, SSP245, SSP370, SSP585). The dataset, derived from 14 CMIP6 GCMs and their multi-model ensemble (MME) mean, was developed using the Double Bias-Corrected Constructed Analogue (DBCCA) approach with MSWEP and MSWX as reference datasets. Evaluation against reference data shows reduced warm and cold biases and improved representation of regional climate. INDRA-CMIP6 enables assessments of climate extremes and supports water resource planning.
Mandal et al. (Thu,) studied this question.