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14 May 2020 Analysis of Wave Fields under Tropical Cyclones in the South China Sea
Wenxuan Sun, Zhuxiao Shao, Bingchen Liang, Huijun Gao
Author Affiliations +
Abstract

Sun, W.; Shao, Z.; Liang, B., and Gao, H., 2020. Analysis of wave fields under tropical cyclones in the South China Sea. In: Zheng, C.W.; Wang, Q.; Zhan, C., and Yang, S.B. (eds.), Air-Sea Interaction and Coastal Environments of the Maritime and Polar Silk Roads. Journal of Coastal Research, Special Issue No. 99, pp. 126–130. Coconut Creek (Florida), ISSN 0749-0208.

The study of wave fields under extreme weather conditions, such as tropical cyclones, is becoming increasingly important for ocean engineering. In this work, wave simulation under a tropical cyclone is carried out in the South China Sea (SCS). The SWAN model is driven by the blended wind field. In this model, the wind input term and whitecapping dissipation term are specifically studied to obtain a reliable model result. During tropical cyclones Doksuri and Kai-tak in 2012, the waves are simulated in the SCS, and the simulated significant wave heights are validated by the measured data at buoys B1, B2 and B3. The validation results show that the simulated values match the measured values well. By the simulated significant wave heights, the wave field is analyzed during the tropical cyclone. In the mean and maximal conditions, the wave fields are studied with the tropical cyclone track. The maximal significant wave heights at the buoy locations are associated with the corresponding spatial distribution of significant wave heights in the SCS, which can reflect the effect of the tropical cyclone on the wave at a specified point.

©Coastal Education and Research Foundation, Inc. 2020
Wenxuan Sun, Zhuxiao Shao, Bingchen Liang, and Huijun Gao "Analysis of Wave Fields under Tropical Cyclones in the South China Sea," Journal of Coastal Research 99(sp1), 126-130, (14 May 2020). https://doi.org/10.2112/SI99-018.1
Received: 21 July 2019; Accepted: 9 December 2019; Published: 14 May 2020
KEYWORDS
mean and maximal conditions
South China Sea
spatial distribution
SWAN model
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