Abstract Submission: The Kuma River watershed, situated in southern Japan, is frequently subjected to severe storms. Notably, in July 2020, an exceptionally intense storm impacted the watershed. This event resulted in substantial property damage and approximately 70 fatalities. For storm disaster mitigation and prevention, it is imperative to reconstruct past extreme storm events and analyze their underlying physical mechanisms. Furthermore, considering the implications of global warming, it is essential to project future extreme storms under changing climatic conditions. This necessitates the accurate tuning of a regional atmospheric model for the Kuma River watershed. In this study, we focused on calibrating the Weather Research and Forecasting (WRF) model for the Kuma River watershed. Utilizing nested domains, we implemented a high-resolution grid of 2 km for the innermost domain. Various combinations of parameterization schemes were evaluated to identify the optimal configuration. Model accuracy was assessed by comparing simulated and observed precipitation at the sub-watershed scale. The results demonstrated that precise calibration of the WRF model can achieve high accuracy. However, the model exhibited limitations in reproducing peak rainfall values. This suggests that model calibration may need to be event-specific to accurately capture peak rainfall during extreme events.
