A storm surge intensity classification based on extreme water level and concomitant wave height

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• 作者：Sheng Dong (1)
  Junguo Gao (1) (2)
  Xue Li (1)
  Yong Wei (3) (4)
  Liang Wang (1)
  
  1. College of Engineering ; Ocean University of China ; Qingdao ; 266100 ; P. R. China
  2. The First Institute of Oceanography ; SOS ; Qingdao ; 266061 ; P. R. China
  3. Pacific Marine Environmental Laboratory ; National Oceanic and Atmospheric Administration (NOAA) ; Seattle ; 98115 ; USA
  4. Joint Institute for the Study of Atmosphere and Ocean ; University of Washington ; Seattle ; WA ; 98105 ; USA
  
• 关键词：storm surge ; Poisson Bi ; variable Gumbel Logistic distribution ; Poisson Bi ; variable Log ; normal distribution ; intensity classification ; joint return period
• 刊名：Journal of Ocean University of China
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：14
• 期：2
• 页码：237-244
• 全文大小：552 KB
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• 刊物主题：Oceanography; Meteorology;
• 出版者：Springer Berlin Heidelberg
• ISSN：1993-5021

文摘

Storm surge is one of the predominant natural threats to coastal communities. Qingdao is located on the southern coast of the Shandong Peninsula in China. The storm surge disaster in Qingdao depends on various influencing factors such as the intensity, duration, and route of the passing typhoon, and thus a comprehensive understanding of natural coastal hazards is essential. In order to make up the defects of merely using the warning water level, this paper presents two statistical distribution models (Poisson Bi-variable Gumbel Logistic Distribution and Poisson Bi-variable Log-normal Distribution) to classify the intensity of storm surge. We emphasize the joint return period of typhoon-induced water levels and wave heights measured in the coastal area of Qingdao since 1949. The present study establishes a new criterion to classify the intensity grade of catastrophic storms using the typhoon surge estimated by the two models. A case study demonstrates that the new criterion is well defined in terms of probability concept, is easy to implement, and fits well the calculation of storm surge intensity. The procedures with the proposed statistical models would be useful for the disaster mitigation in other coastal areas influenced by typhoons.