Impact of Aerosol–Cloud Interactions and SST Updates on the Simulation of the 31 May 2025 Convective Storm over Alexandria with WRF-Chem

Abstract:
Extreme rainfall events in coastal cities such as Alexandria, Egypt, are challenging to forecast due to the combined influences of local convection, sea surface conditions, and aerosol interactions. The convective storm of 31 May 2025 caused intense rainfall over Alexandria, which was poorly predicted by most operational weather models.

In this study, the WRF-Chem model was configured to investigate this event, focusing on the role of aerosols and dust in modifying cloud microphysics and precipitation. The model setup included the MOSAIC 4-bin aerosol scheme (chem_opt=300), dust emissions (dust_opt=1), and the Morrison two-moment microphysics scheme (mp_physics=10). A sea surface temperature (SST) update was applied to better represent the evolving surface conditions over the Mediterranean. Sensitivity experiments were performed to assess the effects of aerosol–cloud interactions and aerosol–radiation feedback on convective development.

The results indicate that WRF-Chem successfully reproduced the timing, location, and intensity of the observed rainfall, outperforming typical operational forecasts. Aerosols and desert dust increased cloud condensation nuclei (CCN), which enhanced cloud water content, delayed precipitation onset, and intensified convection. The SST update was also found to play a critical role in triggering and sustaining the convective cells over coastal regions.

This study demonstrates that coupling aerosol chemistry with advanced microphysics and SST updates can significantly improve the predictability of extreme weather events in complex coastal environments.