Typhoon wind and wave numerical forecasting optimization in the South China Sea based on observation data

Dong Jiang, Bigui Huang, Qingsheng Miao, Hang Sun and Zhifeng Wang ()
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Dong Jiang: Ocean University of China
Bigui Huang: CNOOC Research Institute Ltd.
Qingsheng Miao: National Marine Data and Information Service
Hang Sun: CNOOC Research Institute Ltd.
Zhifeng Wang: Ocean University of China

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 8, No 27, 9653-9677

Abstract: Abstract In this study, the Weather Research and Forecasting (WRF) model is used to optimize 36 combination of physical parameterization schemes for typhoon forecasts in the South China Sea(SCS) based on 20 typhoons from 2011 to 2022.Considering both typhoon intensity and track, Thompson_KF_YSU schemes achieved the best simulation results with root-mean-square errors (RMSE) of 3.85 m/s, 3.268 hPa,5.786 m/s, 11.112 hPa and 114.915 km for 10 m wind, sea level pressure (SLP), 10 m maximum surface wind (Max wind), minimum sea level pressure (Min SLP) and typhoon track, ranking 2nd, 1st, 4th, 4th, and 2nd respectively across all schemes. Based on the (Simulating WAves Nearshore) SWAN model and using wind fields obtained from the optimized Thompson_KF_YSU schemes, the WSM6_Tiedtke_YSU schemes (recommended by Hurricane applications of WRF4.3 Users Guide) and the ensemble prediction from 36 experiments to simulate the typhoon wave forecasts in the SCS. Thompson_KF_YSU schemes forecasts wind field driven typhoon wave forecasts with smallest overall error in terms of significant wave height (Hs) and mean period (Tm), with RMSE of 1.256 m and 1.230 s, respectively. The results can be used as a reference for the forecasting of typhoon, disaster prevention and mitigation in offshore engineering, and typhoon research.

Keywords: Typhoon wind; Typhoon wave; Numerical simulation; Physical combinatorial optimization (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07126-1

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