[1]侯静惟,方伟华,程锰,等.基于Copula函数的海南热带气旋风雨联合概率特征分析[J].自然灾害学报,2019,28(03):054-64.[doi:10.13577/j.jnd.2019.0307]
 HOU Jingwei,FANG Weihua,CHENG Meng,et al.Joint probability analysis of tropical cyclone wind and rainfall for integrated hazard severity assessment in Hainan[J].,2019,28(03):054-64.[doi:10.13577/j.jnd.2019.0307]
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基于Copula函数的海南热带气旋风雨联合概率特征分析
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《自然灾害学报》[ISSN:/CN:23-1324/X]

卷:
28
期数:
2019年03期
页码:
054-64
栏目:
出版日期:
2019-06-28

文章信息/Info

Title:
Joint probability analysis of tropical cyclone wind and rainfall for integrated hazard severity assessment in Hainan
作者:
侯静惟12 方伟华12 程锰12 叶妍婷12 吴鹏3 韩轶男12
1. 北京师范大学环境演变与自然灾害教育部重点实验室, 北京 100875;
2. 应急管理部教育部减灾与应急管理研究院, 北京 100875;
3. 北京师范大学 统计学院, 北京 100875
Author(s):
HOU Jingwei12 FANG Weihua12 CHENG Meng12 YE Yanting12 WU Peng3 HAN Yinan12
1. Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;
2. Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management & Ministry of Education, Beijing 100875, China;
3. School of Statistics, Beijing Normal University, Beijing 100875, China
关键词:
热带气旋风雨联合概率Copula综合危险性
Keywords:
tropical cyclonejoint probabilityCopulaintegrated hazard intensity
分类号:
TU4;X43
DOI:
10.13577/j.jnd.2019.0307
摘要:
热带气旋灾害的主要致灾因子为大风和降水,易引发风暴潮、海浪、洪涝等次生灾害,具有典型的多灾种灾害链特征。大风和降水是热带气旋灾害的两个具有代表性的致灾因子,如何表达多个致灾因子的综合强度是一个关键性问题。本研究以海南岛为研究区域,以1951-2014年共298场历史热带气旋过程最大3s极值风速风场以及总降水量时间序列数据为基础,首先利用极值理论分别拟合了海南风雨两个单致灾因子的强度概率边缘分布,其次采用Clayton、Frank、Gumbel Copula函数计算了风雨二维联合概率。并通过K-S检验及AIC、BIC检验等方法优选了拟合函数,然后分别计算了风雨单个致灾因子超过阈值(RPor)和两个致灾因子同时超过阈值(RPand)两种联合重现期,最后基于影响海南的9场历史典型热带气旋损失归一化数据检验重现期计算结果的可靠性。结果表明:对于年极值分布拟合最大3s极值风速用Weibull分布、总降水量用Gumbel分布效果较好;对于边缘概率分布的连接函数,Clayton Copula函数的效果较好;联合重现期RPand相比于联合重现期RPor与历史热带气旋归一化损失率具有更好的相关性。
Abstract:
The wind and precipitation of tropical cyclones (TC) usually incur a variety of secondary hazards such as inland flood, storm surge and wave. It is of great importance to understand the integrated intensity of these hazards. By taking 3 s gust wind speed and total precipitation as the two representative hazard indicators, the joint probability of both TC wind and rainfall in Hainan of China are estimated. Firstly, the time series data of 3 s gust wind and total precipitation of the 298 TCs from 1951 to 2014 was obtained based on the modeling of past study. Secondly, the optimal marginal distributions of wind and rainfall are analyzed with five types of distribution models. Thirdly, Clayton Copula, Frank Copula and Gumbel Copula are used to construct joint probability distribution, and the optimal copula models are selected by K-S test and AIC, BIC test as well. Two types of joint return period, namely RPor and RPand, are computed. Finally, the normalized direct economic loss of 9 historical TCs are used to evaluate the reliability of the joint return periods results. It is found that for Hainan, Weibull and Gumbel are the most optimal distribution for gust wind speed and total precipitation respectively, and Clayton Copula is the best model for fitting joint hazard intensity of wind and rainfall. The joint return period RPor has a better relationship with the economic loss data.

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备注/Memo

备注/Memo:
收稿日期:2018-10-31;改回日期:2019-04-29。
基金项目:国家重点研发计划项目(2017YFA0604903,2018YFC1508803)
作者简介:侯静惟(1994-),女,硕士研究生,主要从事台风灾害研究.E-mail:jingwei.hou@mail.bnu.edu.cn
通讯作者:方伟华(1973-),男,教授,博士,主要从事台风灾害研究.E-mail:weihua.fang@bnu.edu.cn
更新日期/Last Update: 1900-01-01