4.5 Article

Spatiotemporal distribution of landing tropical cyclones and disaster impact analysis in coastal China during 1990-2016

期刊

PHYSICS AND CHEMISTRY OF THE EARTH
卷 115, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pce.2019.102830

关键词

Disaster indices; Disaster risk; Economic loss; Tropical cyclone; Entropy method

资金

  1. National Key Research and Development Program of China [2018YFA150903, 2016YFA0602703]
  2. National Natural Science Foundation of China [41575001]

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To assess the impact of tropical cyclones (hereafter as TCs) along the southeast coast of China, this study analyzed the spatiotemporal variation of TC-induced disasters, interannual variability of disasters and their intensities by using the data during 1990-2016. Economic losses were calculated by using the three disaster indices: based on the area of affected crops, number of collapsed buildings, and direct economic losses. Entropy method was used to improve the comprehensive disaster index impact model for the first time and use it in tropical cyclone disaster assessment. It is found that there was no obvious interannual variation in the total number of TCs affecting China, although low-intensity TCs decreased and high-intensity TCs increased significantly. Conditions in 2015 were used as a reference to convert the loss index. Results show that 1997 was a turning point in the combined disaster index. Moreover, interannual fluctuations were severe in the former period, but lower in the latter and smoother. According to the economic calculations from the three disaster indices, the economic value of collapsed buildings and affected crops tended to decrease over the interdecadal period, whereas there was an obvious increasing interdecadal trend in direct economic losses. This result indicates that the tropical cyclone induced disasters has gradually shifted from primary industry to secondary and tertiary industry. Results from this paper will provide science based support to policy makers to reduce the economic losses in natural disasters.

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