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Estimation of extreme wave heights and wind speeds in the South China Sea


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1 College of Science, China University of Petroleum, Qingdao – 266580, China

Extreme events have significant impacts on the coastal and offshore regions. In the present paper, the return values of significant wave height and wind speed are estimated based on three different models namely generalized extreme value distribution, generalized Pareto distribution and polynomial approximation to acquire a universal and trustworthy model estimate. Here, six sites in the South China Sea with diverse geographical characteristics are considered to perform the extreme value analysis and the datasets used in the experiments were derived from the ERA-Interim reanalysis. Then the advantages and shortcomings of three different methods are discussed and analyzed in detail. The polynomial approximation method is analyzed and compared with the other methods, and it is found that this new method predominantly resolves the drawbacks encountered by the other typical extreme value estimation methods and it is suitable for estimating the return values in the South China Sea.
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  • Estimation of extreme wave heights and wind speeds in the South China Sea

Abstract Views: 132  | 

Authors

J C Wang
College of Science, China University of Petroleum, Qingdao – 266580, China
S D Zang
College of Science, China University of Petroleum, Qingdao – 266580, China
Y J Ji
College of Science, China University of Petroleum, Qingdao – 266580, China
Y H Zhang
College of Science, China University of Petroleum, Qingdao – 266580, China

Abstract


Extreme events have significant impacts on the coastal and offshore regions. In the present paper, the return values of significant wave height and wind speed are estimated based on three different models namely generalized extreme value distribution, generalized Pareto distribution and polynomial approximation to acquire a universal and trustworthy model estimate. Here, six sites in the South China Sea with diverse geographical characteristics are considered to perform the extreme value analysis and the datasets used in the experiments were derived from the ERA-Interim reanalysis. Then the advantages and shortcomings of three different methods are discussed and analyzed in detail. The polynomial approximation method is analyzed and compared with the other methods, and it is found that this new method predominantly resolves the drawbacks encountered by the other typical extreme value estimation methods and it is suitable for estimating the return values in the South China Sea.