Multi-model prediction of disastrous weather events caused by Typhoon Bebinca and analysis of the brown ocean effect

On September 16th, 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 rain and strong winds across Shanghai and Jiangsu. Based on land surface observations, the performance of two global models, i.e., the European Center for Medium-Range Weather Forecasts (ECMWF) model, the Global Forecast System (GFS) model, and one regional model, i.e., the Jiangsu Weather Research and Forecasting (JWRF) model, was compared in forecasting the typhoon-caused rain 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 rain and the spatial distribution of wind speeds, but showed southward biases in their forecasts of the location of heavy rain and overestimation of the wind magnitude. 2) The JWRF model outperformed the other two global models in forecasting the location of heavy rain, especially torrential rain, maximum precipitation, and the wind magnitude. 3) In the 24-h lead time forecasts, the GFS and JWRF models adjusted the location of torrential rain 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.