Impact of landfalling tropical cyclones in mainland China

被引:16
|
作者
Zhang QingHong [1 ]
Wei Qing [2 ]
Chen LianShou [3 ]
机构
[1] Peking Univ, Sch Phys, Dept Atmospher & Ocean Sci, Beijing 100871, Peoples R China
[2] Chinese Meteorol Agcy, Meteorol Ctr, Beijing 100081, Peoples R China
[3] Chinese Acad Meteorol Sci, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
tropical cyclones; impact index; water vapor; economic loss;
D O I
10.1007/s11430-010-4034-8
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Tropical cyclones (TCs) have a significant impact on mainland China. The purpose of this study is to develop an impact index which correlates with both the strong wind and heavy rainfall/flood damage caused by TCs in mainland China. By considering the radius of TCs, we first define the total destructiveness index (TDI) and total column water vapor index (TVI). Economic loss is used to represent the impact of landfalling TCs. The analysis is based on 30 landfalling TCs between 2001 and 2007, and identified significant correlations between the impact of landfalling TCs and the TVI (TDI). The correlations between the impact of landfalling TCs and TVI, TDI and maximum wind speed of TCs before landfall are 0.751, 0.59 and 0.345, respectively. This study also shows that landfalling TCs with a higher TVI usually bring heavier rainfall, and result in more economic losses in China. A TC impact index is defined as a function of TVI and TDI. The correlation between TC impact index and economic loss was found to be significant (r=0.769). Tropical storm Bilis in 2006 is classified as the landfalling TC with the highest impact index between 2001 and 2007 and Matsa, in 2005, as the second highest impact index in this same interval. Using a system cluster analysis method, 30 landfalling TCs in this study were graded into five categories according to their impact indices. Category 5, which is the highest level, included only one TC, which constituted 4% of the total TCs studied. Category 4 included three TCs (10%). Categories 3 and 2 included seven TCs each (23%) and Category 1 included 12 TCs (40%).
引用
下载
收藏
页码:1559 / 1564
页数:6
相关论文
共 50 条
  • [31] Risk Assessment of Landfalling Tropical Cyclones in China Based on Hazard Risk Theory
    Xu, Jin
    Xue, Xinyue
    Yang, Bo
    Wang, Wen
    Wu, Wenxiang
    Ji, Xiaodong
    APPLIED SCIENCES-BASEL, 2024, 14 (12):
  • [32] Characteristics of Landfalling Tropical Cyclones in North Carolina
    Kehoe, Jennifer
    Raman, Sethu
    Boyles, Ryan
    MARINE GEODESY, 2010, 33 (04) : 394 - 411
  • [33] El Nino Onset Time Affects the Intensity of Landfalling Tropical Cyclones in China
    Yang, Jinyi
    Xu, Feng
    Tu, Shifei
    Han, Liguo
    Zhang, Shaojing
    Zheng, Meiying
    Li, Yongchi
    Zhang, Shihan
    Wan, Yishun
    ATMOSPHERE, 2023, 14 (04)
  • [34] Latitudinal distribution of landing tropical cyclones over mainland China
    Zhang Han
    Guan Yu-Ping
    ACTA PHYSICA SINICA, 2012, 61 (16)
  • [35] Mean structure of tropical cyclones making landfall in mainland China
    Lina Bai
    Hui Yu
    Yinglong Xu
    Yuan Wang
    Journal of Meteorological Research, 2014, 28 : 407 - 419
  • [36] Mean Structure of Tropical Cyclones Making Landfall in Mainland China
    Bai Lina
    Yu Hui
    Xu Yinglong
    Wang Yuan
    JOURNAL OF METEOROLOGICAL RESEARCH, 2014, 28 (03) : 407 - 419
  • [37] THE IMPACT OF TROPICAL CYCLONES ON CHINA IN 2016
    HUA GU
    CHUANHAI QIAN
    SHUANZHU GAO
    CHUNYI XIANG
    Tropical Cyclone Research and Review, 2017, (Z1) : 1 - 12
  • [38] THE IMPACT OF TROPICAL CYCLONES ON CHINA IN 2015
    Su, Hang
    Qian, Chuanhai
    Gu, Hua
    Wang, Qian
    TROPICAL CYCLONE RESEARCH AND REVIEW, 2016, 5 (1-2) : 1 - 11
  • [39] THE IMPACT OF TROPICAL CYCLONES ON CHINA IN 2015
    HANG SU
    CHUANHAI QIAN
    HUA GU
    QIAN WANG
    Tropical Cyclone Research and Review, 2016, (Z1) : 1 - 11
  • [40] Possible Linkage Between Tropical Indian Ocean SST Anomalies and the Date of First and Last Tropical Cyclones Landfalling in the Chinese Mainland
    周群
    魏立新
    李敏
    Journal of Tropical Meteorology, 2022, (01) : 71 - 81