Comprehensive evaluation and ranking of CMIP6 global climate models for simulating climate extreme indices across diverse hydrological and geographical regions of Nepal

Nepal This study develops an integrated performance-based framework to evaluate Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on their ability to simulate climate extremes in Nepal over the historical period (1981–2014) using raw (not bias-corrected or downscaled) GCM outputs. Eleven extreme climate indices, five precipitation-based and six temperature-based, were selected in alignment with Nepal’s National Adaptation Plan (2019) . Model performance was assessed using Kling–Gupta Efficiency, Correlation Coefficient, and Normalized RMSE. These metrics were aggregated into a single composite score (Utility Value), using an entropy weight method at the pixel level. A Group Decision-Making approach was then applied across the spatial domain to rank the GCMs based on their performance across multiple pixels. The proposed framework is novel in its multi-criteria, multi-scale evaluation across national, river basin, and physiographic levels. The results reveal significant spatial variation in GCM performance across Nepal, with no single model performing best in all regions or for all indices. The top three GCMs overall were IPSL-CM6A-LR, GFDL-ESM4, and ACCESS-CM2. Rankings were also developed for major river basins and physiographic zones, providing localized guidance for climate impact modeling. The proposed framework is scalable and transferable to other regions with complex climatic and topographic variations, enhancing the robustness of climate model selection for impact studies. • Comprehensive evaluation of CMIP6 GCMs using climate extreme indices. • Spatially explicit model rankings across Nepal’s basins and physiographic zones. • Model recommendations and high-resolution dataset to support future climate risk assessments.