The Capabilities of WRF in Simulating Extreme Rainfall over the Mahalapye District of Botswana

Flooding episodes caused by a heavy rainfall event have become more frequent, especially during the rainfall season in Botswana, which poses some socio-economic and environmental risks. This study investigates the capability of the Weather Research and Forecasting (WRF) model in simulating a heavy rainfall event that occurred on 26 December 2023 in Mahalapye District, Botswana. This event is one among many that have negatively impacted the lives and infrastructures in Botswana. The WRF model was configured using the tropical-suite physics schemes, i.e., (Rapid Radiative Transfer Model, Yonsei University planetary boundary layer scheme, Unified Noah land surface model, New Tiedtke, Weather Research and Forecasting Single-Moment six-class) on a two-way nested domain (9 km and 3 km grid spacing) and was initialized with the GFS dataset. Gauged station data was used for verification alongside synoptic charts generated using ECMWF ERA5 dataset. The results show that the WRF model simulation using the tropical-suite physics schemes is able to reproduce the spatial and temporal patterns of the observed rainfall but with some notable biases. Performance metrics, including RMSE, correlation coefficient, and KGE, showed moderate to good agreement, highlighting the model’s sensitivity to physical parameterization and resolution. The results of this study conclude that the WRF model demonstrates promising potential in forecasting extreme rainfall events in Botswana, but more sensitivity tests to different parameterization schemes are needed in order to integrate the model into the early warning systems to enhance disaster preparedness and response.