Evaluation of WRF cumulus parameterization schemes for precipitation simulation in Talesh watershed, Iran

Extreme precipitation events frequently trigger destructive floods in mountainous regions with complex topography, where accurate rainfall prediction remains challenging. The Weather Research and Forecasting (WRF) model is widely used for high-resolution precipitation simulation; however, its performance strongly depends on the selected cumulus parameterization scheme. This study evaluates three widely used WRF cumulus parameterization schemes, namely Kain–Fritsch, modified Kain–Fritsch, and Grell 3D Ensemble, for simulating heavy precipitation events in the Talesh Watershed, Iran. Three major flood-producing rainfall events were selected and simulated using identical model configurations, differing only in the cumulus scheme. Simulated precipitation was evaluated against rain gauge observations using Root Mean Square Error (RMSE, mm) and Nash–Sutcliffe Efficiency (NSE, dimensionless). The reported statistics represent the average performance across the three events. Results show that the Kain–Fritsch scheme achieved the lowest RMSE (11.1 mm) and highest NSE (0.66), followed by the modified Kain–Fritsch (RMSE = 13.2 mm, NSE = 0.53) and Grell 3D Ensemble (RMSE = 14.9 mm, NSE = 0.37). The findings indicate that the Kain–Fritsch scheme provides the most reliable precipitation simulation for extreme rainfall events in this complex mountainous watershed. These results contribute to improving regional precipitation modeling and support more reliable flood forecasting and risk management in northern Iran.