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  • 标题:A Methodological Study on AMH Copula-Based Joint Exceedance Probabilities and Applications for Assessing Tropical Cyclone Impacts and Disaster Risks (Part I)
  • 本地全文:下载
  • 作者:Qiuzhen Yang ; Ming Xu ; Xiaotu Lei
  • 期刊名称:Tropical Cyclone Research and Review
  • 印刷版ISSN:2225-6032
  • 出版年度:2014
  • 卷号:3
  • 期号:1
  • 页码:53-62
  • DOI:10.6057/2014TCRR01.05
  • 出版社:Elsevier BV
  • 摘要:A disaster induced by a tropical cyclone (TC) is a complex non-linear process, involving interactions of multiple factors. Assuming that the resilience to TC disasters remains basically unchanged, the disaster-causing risk is usually consistent with intensities of the TC-induced rainstorms and wind. When an area is hit by a low probability TC, the rainstorm and wind intensities are higher, and the likelihood for causing a disaster is greater. Therefore, criteria for the impact of a TC and disaster risk assessments can be established based on the probable intensities of the TC-associated rainstorms and wind. In this study, an AMH Copula-based function is introduced to investigate the joint risk probabilities of TC rainstorms and wind. In line with the equivalence principle of the distribution of a stochastic atmospheric phenomenon in both time and space, and taking the impact on Shanghai of TC Haikui as an example, the Copula-based joint probability distribution model is developed to assess the impacts of TC rainstorms and wind, based on the marginal distributions of the maximum daily rainfall and extreme gust velocity. The joint exceedance probabilities of TC rainstorms and wind derived from the model can be used as criteria to measure the risk levels. As our findings show, this approach captures the TC risks well, especially in high-risk areas. The aim of the study is to provide a practically useful concept for making more accurate assessments of the risk level of an extreme weather event using observational data, and objective criteria for risk avoidance and transfer.
  • 关键词:TC impact ; joint distribution ; joint exceedance probability ; risk assessment ; spatial distribution
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