Evaluation of microphysics and boundary layer schemes for simulating extreme rainfall events over Saudi Arabia using WRF-ARW

Extreme Rainfall Events (EREs) and resulting flash floods in Saudi Arabia pose major threats, frequently causing fatalities and significant economic losses. Accurate ERE simulations are crucial for weather forecasting, climate change assessment, and disaster management. This study evaluates planetary boundary layer (PBL) and cloud microphysics (MP) schemes to simulate EREs in the Arabian Peninsula (AP) using the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model V4.4. Thirty-six combinations of four PBL and nine MP schemes were tested across 17 EREs at a convection-permitting 3 km resolution and compared with IMERG gridded satellite data for rainfall and station observations for temperature, humidity, and wind speed. The Kling–Gupta Efficiency (KGE), which incorporates correlation, variability, and bias, was used as performance metric. We found a good agreement between observed and simulated rainfall patterns, though some over- and underestimations were present. Among the PBL schemes, Yonsei University (YSU; BL1) tended to perform best in terms of rainfall, while Thompson (MP8) ranked the highest among the MP schemes. Goddard (MP7) also delivered strong results. Among all 36 combinations, the Thompson-YSU (MP8_BL1) combination produced the highest mean KGE across the 17 EREs for rainfall, performing statistically significantly better than 21 other combinations. While MP8_BL1 also performed best for the other three meteorological variables, performance rankings varied across variables, likely because different physical processes govern the simulation of different variables. This study highlights the complexity of scheme evaluation and the importance of analyzing multiple EREs with high-quality reference data. The results offer practical guidance for scheme selection and lay the foundation for improving ERE forecasting and regional climate modeling over the AP.