Natural Hazards

, Volume 71, Issue 2, pp 1053–1065 | Cite as

China’s tropical cyclone disaster risk source analysis based on the gray density clustering

  • L. J. Zhang
  • H. Y. Zhu
  • X. J. Sun
Original Paper


In recent years, tropical cyclones on the Pacific Northwest have decreased. We cannot infer that tropical cyclones impact China have reduced, because the Pacific Northwest is not homogeneous, and the variation characteristics of tropical cyclones in different sea areas are not clear. This paper uses gray relational density clustering algorithm to cluster tropical cyclone data sets between 1949 and 2008, according to the generated position of tropical cyclones, generated density and the possibility of landing. The Pacific Northwest is divided into different sea areas. Then, we analyze the risk of tropical cyclones generated in these sea areas. The results show that the probability of tropical cyclones landing generated in some sea areas is very high, reached 74 %, but the probability of tropical cyclones landing generated in other sea areas is only 2 %. Tropical cyclones generated in some sea areas are more likely to develop into typhoons, strong typhoons and so on, but the intensity of tropical cyclones generated in other sea areas is lower, there is little risk for China. Finally, according to the climate change stage trends, we divide the period 1949–2008 into three stages and analyze the tropical cyclone risk of each sea areas.


Density clustering algorithm Gray relational Tropical cyclones Risk source 



This work was financially supported by the National Natural Science Foundation of China (No. 71173116), the National Natural Science Foundation of China (No. 71171115), the Project Funded by China Institute of Manufacturing Development (SK20120200-3), and the Project Funded by China Institute of Manufacturing Development (SK20120200-7). A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1. China Institute of Manufacturing DevelopmentNanjing University of Information Science and TechnologyNanjingChina

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