Assessing the Performance of WRF Model in Simulating Heavy Precipitation Events over East Africa Using Satellite-Based Precipitation Product

This study investigated the capability of Weather Research and Forecasting (WRF) model to simulate seven different heavy precipitation (PRE) events that occurred across East Africa in summer 2020. The WRF outputs were evaluated against high-resolution satellite-based observations, which obtained from prior evaluations several satellite observations with 30 stations’ data. synoptic conditions accompanying also determine are conducive PRE. verification output was carried out using area-related root mean square error (RMSE)-based fuzzy method. method quantifies similarity PRE intensity distribution between forecast observation at spatial scales. results showed reproduced magnitudes ranging 6 >30 mm/day. pattern Precipitation Estimation Remotely Sensed Information Artificial Neural Networks-Cloud Classification-Climate Data Record (PERSIANN-CCS-CDR) close output. RMSE respect tended reduce as scale increased for all events. data had an obvious advantage when validating demonstrated may be used forecasting over high resolutions subsequent simulation setups used.