Extreme precipitation events are among the most damaging hydroclimatic hazards, particularly in monsoon-dominated, topographically complex, and data-scarce regions of South Asia. Despite advances in global and regional climate modeling, accurate simulations of such extreme events remain challenging due to the nonlinear interactions between deep convection, orography, and large-scale circulation. This study evaluates the performance of the Regional Climate Model RegCM5, developed by the Abdus Salam International Centre for Theoretical Physics (ICTP), and reproduces two severe monsoon-driven precipitation events: July 2010 and August 2022. High-resolution simulations were conducted using convection-permitting (3 km) non-hydrostatic cores (MOLOCH and MM5) and are compared with coarser hydrostatic (12 km, MM4) simulations employing parameterized convection. Model outputs were validated against ERA5 and ERA5-Land reanalysis, satellite-based GPM precipitation, the Gloh2 ensemble product, and in-situ observations. Results indicate that the 3 km MOLOCH configuration significantly improves the simulation of precipitation intensity, spatial distribution, and temporal variability relative to hydrostatic runs. Notably, RegCM5-MOLOCH effectively captures the 500 hPa geopotential height patterns associated with the extreme event of the 2010 Russian blocking ridge, underscoring its utility in resolving key synoptic drivers.

RegCM5-MOLOCH reproduces the large-scale moisture transport while capturing terrain-induced convergence along the Sulaiman mountain ranges of Balochistan. Diagnostics of Moisture Flux Convergence (MFC) and Integrated Vapor Transport (IVT) further reveal strong southwesterly moisture inflow from the Arabian Sea converging over Sindh and Balochistan during August 2022, consistent with the flood-affected areas. Furthermore, Spearman rank correlation analysis reveals robust linkages between simulated precipitation and sea surface temperature-related changes in La Niña and the Indian Ocean Dipole (IOD). This highlights the combined influence of large-scale ocean-atmosphere modes on monsoon extremes. Whilst, overall, convection-permitting simulations reduce biases, some persistent wet biases remain, likely due to the unresolved uncertainties in cloud microphysics, land–atmosphere coupling, and moisture transport. These findings enhance the application of high-resolution regional modeling for enhanced flood risk assessment, improved early warning systems, and more effective climate adaptation strategies in monsoon-affected regions.