Kilometer Scale Climate Modeling of Extremes: Evaluation of the NonHydrostatic Regional Climate Model (NHRCM) over Pakistan

Rising global warming is accelerating climate extremes at regional scales worldwide. Capturing these extremes at the regional level requires high resolution climate modeling capable of representing complex topography and strong land atmosphere interactions. In this study, a high-resolution Non-Hydrostatic Regional Climate Model (NHRCM) is configured at a kilometer scale resolution (5 km) through dynamic downscaling of the MRI AGCM 3.2 outputs developed by the Meteorological Research Institute of Japan (MRI). Daily precipitation and temperature (maximum and minimum) data are generated at 5 km resolution for the historical period (1980–2000) and the future period (2081–2100) under the high emission climate scenario SSP585. The performance of the downscaled climate variables is evaluated against ERA5 Land data after resampling to the same resolution as the NHRCM. Statistical metrics and extreme climate indices are used to quantify model skill and biases at regional and sub regional scales over Pakistan. The results reveal a strong correlation in high elevation regions of Pakistan compared to the plains. After evaluating model performance, precipitation and temperature extreme indices are calculated for both historical and future periods. The findings indicate an increase in precipitation in the southern regions of Pakistan, accompanied by rising temperatures. These trends are also associated with an increase in short-duration intense rainfall events during summer and prolonged dry conditions in winter. Furthermore, the frequency of heatwaves is expected to rise by the end of the century across Pakistan, along with increasing temperatures in snow fed regions. Overall, this study highlights the added value of high-resolution nonhydrostatic regional climate modeling in understanding and assessing climate extremes over Pakistan, providing a robust foundation for future climate impact assessments and adaptation planning.