Environment, Development and Sustainability

, Volume 21, Issue 6, pp 3077–3092 | Cite as

Tropical cyclone damages in Mainland China over 2005–2016: losses analysis and implications

  • Hong Wang
  • Min Xu
  • Anselem Onyejuruwa
  • Yanjun Wang
  • Shanshan Wen
  • Andrew E. Gao
  • Yubin LiEmail author


This study analyzed the annual variation and provincial distribution of the number of landfalling tropical cyclones (TCs) and the associated losses in respect of direct economic losses, collapsed buildings, casualties, evacuated population, affected population, and the affected agricultural area in mainland China during 2005–2016. The numbers of western North Pacific TCs and landfall TCs were 24 and 7.5, respectively. The annual mean losses of TC disasters included 36.7 million affected people, 69.5 billion Yuan direct economic losses, and 254 deaths. For an average landfalling TC, the numbers were 4.9 million people, 9.3 billion Yuan, and 33.9 deaths, respectively. Most of the damages were caused by the small numbers of destructive TCs, and the top 10 TCs contributed to 48% of direct economic losses, 71% of deaths, and 66% of building damages. Among the provinces affected by TC disasters, Zhejiang, Guangdong, and Fujian took the majority of the losses. Nevertheless, the casualties per landfalling TC were highest in Hunan (63.3 deaths), while mortalities (the rate of casualties to the evacuated population) in Henan (200.0 per 105 persons) and Yunnan (116.7 per 105 persons) were significantly higher than the other provinces (below 30 per 105 persons), indicating more population needed to be evacuated in future TC disasters in these provinces. The larger the number of landfalling TCs in a year or higher the wind force scale of a landfalling TC did not necessary lead to larger losses. However, stronger rainfall and/or a northeast-recurving track played a role in increasing the TC disaster losses.


Annual variation Influential factors Mainland China Provincial distribution Tropical cyclone disaster 



This work is supported by the National Key Research and Development Program of China (2018YFC1506405), the National Program on Global Change and Air-Sea Interaction (GASI-IPOVAI-04) and the National Natural Science Foundation of China (41675009). The authors thank the China Meteorological Administration for providing the tropical cyclone best-track dataset and the tropical cyclone disaster data. We also appreciate the National Bureau of Statistics of China and EconStats for the GDP data.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric PhysicsNanjing University of Information Science and TechnologyNanjingChina
  2. 2.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)ZhuhaiChina
  3. 3.School of Geographical SciencesNanjing University of Information Science and TechnologyNanjingChina
  4. 4.Edgemont Junior – Senior High SchoolNew YorkUSA

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