Abstract: On September 16^th, 2024, Typhoon Bebinca (2413) made landfall in Shanghai at severe typhoon intensity, and maintained intensity as a severe tropical storm for 18 hours, triggering disastrous weather events like heavy rainfall and strong winds across Shanghai and Jiangsu areas. Based on land surface observations, the performances of two global models, i.e., the European Center for Medium-Range Weather Forecasts (ECMWF) model, the Global Forecast System (GFS) model, and a regional model, i.e., the Jiangsu grid operational Weather Research and Forecasting (JWRF) model, were compared in forecasting the typhoon-caused rainfall and wind by the metrics of threat score, the prediction accuracy of precipitation location, and extreme values; meanwhile, the maintaining mechanism of Bebinca was investigated based on the JWRF regional model’s forecasts. The main findings are as follows: 1) All three models accurately predicted the spatial distribution and intensity of heavy rainfall and the spatial distribution of wind speeds, but showed southward biases in their forecasts of the location of heavy rainfall and overestimation of the wind speed magnitude. 2) The JWRF model outperformed the other two global models in forecasting the location of heavy rainfall, especially torrential rainfall, maximum precipitation, and the wind speed magnitude. 3) In the 24-h lead time forecasts, the GFS and JWRF models adjusted the location of torrential rainfall northwards, reaching higher accuracy than their 36-h lead time forecasts. 4) Further diagnostic analysis identified the brown ocean effect and water vapor transport from the East China Sea as the main causes for the typhoon’s maintaining presence. The research results contribute to improving and enhancing multi-scenario forecasting capabilities for typhoons and other severe weather events.