Numerical evaluation of WRF microphysics parameterizations for a major rainfall event over an arid region

This study examines how cloud microphysical parameterizations in the Weather Research and Forecasting (WRF) model influence the simulation of rainfall over Kuwait during November 2018, with particular focus on the extreme event of 14 November. The WRF model was configured at 4-km resolution and dynamically downscaled from the Community Climate System Model version 4 (CCSM4) to evaluate the performance of four bulk microphysics schemes: WSM6, Lin, Thompson, and Morrison. Model output was evaluated against observations from the Kuwait Automatic Weather Station (29.22°N, 47.96°E) using cumulative and distributional rainfall characteristics, event-scale analysis, and standard statistical metrics (RMSE, MAE, bias, and correlation). All schemes reproduced the timing of rainfall events, while notable differences were found in simulated rainfall intensity. WSM6 produced rainfall amounts closest to observations, with the lowest error values and a small positive bias. Lin showed moderate overestimation, Thompson produced larger overestimation during heavy-rain periods, and Morrison consistently underestimated rainfall totals. For the 14 November event, which recorded 79.0 mm at the station, simulated totals ranged from 55.6 to 91.6 mm across the schemes, indicating that inter-scheme differences were dominated by rainfall magnitude rather than timing. These results highlight the sensitivity of convection-permitting rainfall simulations in arid regions to microphysical formulation. Evaluation using additional events and seasons is needed to assess whether these results extend beyond the period examined.