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

Flooding episodes caused by a heavy rainfall event has become more frequent especially during the rainfall season in Botswana, this poses some socio-economic and environmental risks. This study investigates the capability of Weather Research and Forecasting (WRF) in simulating a heavy rainfall event which occurred on the 26th of December 2023 in Mahalapye District, Botswana. This event is one amongst many which has had 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 6-class) on a two-way nested domain (9 km and 3 km grid-spacing) and was initialized with GFS dataset. Gauged station data was used for validation alongside synoptic charts from GFS and 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 concludes 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.