A simplified index to assess the combined impact of tropical cyclone precipitation and wind on China

  • Peiyan ChenEmail author
  • Hui Yu
  • Ming Xu
  • Xiaotu Lei
  • Feng Zeng
Research Article


Relationships between tropical cyclone (TC) precipitation, wind, and storm damage are analyzed for China based on TCs over the period from 1984 to 2013. The analysis shows that the maximum daily areal precipitation from stations with daily precipitation of ⩾ 50 mm and the sum of wind gusts of ⩾ 13.9 m/s can be used to estimate the main damage caused by TCs, and an index combining the precipitation and wind gust of a TC (IPWT) is defined to assess the severity of the combined impact of precipitation and wind. The correlation coefficient between IPWT and the damage index for affecting TCs is 0.80, which is higher than that for only precipitation or wind. All TCs with precipitation and wind affecting China are divided into five categories, Category 0 to Category 4, based on IPWT, where higher categories refer to higher combined impacts of precipitation and wind. The combined impact category is closely related to damage category and it can be used to estimate the potential damage category in operational work. There are 87.7%, 72.9%, 69.8%, and 73.4% of cases that have the same or one category difference between damage category and combined impact category for Categories 1, 2, 3, and 4, respectively. IPWT and its classification can be used to assess the severity of the TC impact and of combined precipitation and wind conveniently and accurately, and the potential damage caused by TCs. The result will be a good supplementary data for TC intensity, precipitation, wind, and damage. In addition, IPWT can be used as an index to judge the reliability of damage data. Further analysis of the annual frequency of combined precipitation-wind impact categories reveals no significant increasing or decreasing trend in impact over China over the past 30 years.


tropical cyclone impact precipitation wind 


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This study was sponsored by the National Basic Research Program of China (Grant No. 2015CB452806), the National Natural Science Foundations of China (Grant Nos. 41475082 and 41875114), Shanghai Science & Technology Research Program (Grant No. 19dz1200101), and the Fundamental Research Funds of the STI/CMA (Grant No. 2019JB06).


  1. Chen H Y, Yu H, Ye G J, Xu M, Yang Q Z (2019). Return period and the trend of extreme disastrous rainstorm events in Zhejiang Province. J Trop Meteorol, 25: 192–200Google Scholar
  2. Chen P Y, Lei X T, Ying M (2013). Introduction and application of a new comprehensive assessment index for damage caused by tropical cyclones. Trop Cyclone Res Rev, 2: 176–183Google Scholar
  3. Chen P Y, Yang Y H, Lei X T, Qian Y Z (2009). Cause analysis and preliminary hazard estimate of typhoon disaster in China. J Nat Disast, 18: 64–73 (in Chinese)Google Scholar
  4. Easterling D R, Peterson T C, Karl T R (1996). On the development and use of homogenized climate datasets. J Clim, 9(6): 1429–1434CrossRefGoogle Scholar
  5. Emanuel K (2005). Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436(7051): 686–688CrossRefGoogle Scholar
  6. GB/T 19201-2006 (2006). Grade of tropical cyclones. Beijing: Standards Press of ChinaGoogle Scholar
  7. Kantha L (2006). Time to replace the Saffir-Simpson hurricane scale? Eos (Wash DC), 87(1): 3–6CrossRefGoogle Scholar
  8. Kantha L (2013). Classification of hurricanes: lessons from Katrina, Ike, Irene, Isaac and Sandy. Ocean Eng, 70: 124–128CrossRefGoogle Scholar
  9. Lei X T, Chen P Y, Yang Y H, Qian Y Z (2009). Characters and objective assessment of disasters caused by typhoons in China. Acta Meteorol Sin, 67: 875–883 (in Chinese)Google Scholar
  10. Liang B Q, Fan Q, Yang J, Wang T M (1999). A fuzzy mathematic evaluation of the disaster by tropical cyclones. J Trop Meteorol, 15: 305–311 (in Chinese)Google Scholar
  11. Lin Q W, Lu C J (1987). An analysis on satellite cloud imageries and radar echoes from the tropical depression “8.27”. J Guangxi Meteor: 13–16 (in Chinese)Google Scholar
  12. Lou W P, Chen H Y, Qiu X F, Tang Q Y, Zheng F (2012). Assessment of economic losses from tropical cyclone disasters based on PCA-BP. Nat Hazards, 60(3): 819–829CrossRefGoogle Scholar
  13. Lu W F (1995). Assessment and prediction of disastrous losses due to tropical cyclones in Shanghai. J Nat Disast, 4: 40–45 (in Chinese)Google Scholar
  14. Lu X Q, Yu H, Ying M, Qi L B (2018a). The effects of station network density on statistical analyses oftropical cyclone precipitation. J Trop Meteorol, 24(4): 421–431Google Scholar
  15. Lu Y, Ren F M, Zhu W J (2018b). Risk zoning of typhoon disasters in Zhejiang Province, China. Nat Hazards Earth Syst Sci, 18(11): 2921–2932CrossRefGoogle Scholar
  16. Ma Q Y, Li G Y, Wang X R, Wang W G, Gao L Y (2008). A fuzzy synthetic evaluation model for typhoon disaster. Meteor Mon, 34: 20–25 (in Chinese)Google Scholar
  17. Pielke R A Jr, Gratz J, Landsea C W, Collins D, Saunders M A, Musulin R (2008). Normalized hurricane damage in the United States:1900–2005. Nat Hazards Rev, 9(1): 29–42CrossRefGoogle Scholar
  18. Powell M D, Reinhold T A (2007). Tropical cyclone destructive potential by integrated kinetic energy. Bull Am Meteorol Soc, 879(2): 219–221Google Scholar
  19. Ren F M, Gleason B, Easterling D (2001). A numerical technique for partitioning cyclone troical precipitation. J Trop Meteorol, 17(3): 308–313 (in Chinese)Google Scholar
  20. Rezapour M, Baldock T E (2014). Classification of hurricane hazards: the importance of rainfall. Weather Forecast, 29(6): 1319–1331CrossRefGoogle Scholar
  21. STI/CMA (2006). Climatological Atlas for Tropical Cyclones Affecting China (1951–2000). Beijing: Science Press (in Chinese)Google Scholar
  22. STI/CMA (2017). Climatological Atlas of Tropical Cyclones over the Western North Pacific (1981–2010). Beijing: Science PressGoogle Scholar
  23. Van Oldenborgh G J, van der Wiel K, Sebastian A, Singh R, Arrighi J, Otto F, Haustein K, Li S, Vecchi G, Cullen H (2017). Attribution of extreme rainfall from Hurricane Harvey, August 2017. Environ Res Lett, 12(12): 124009CrossRefGoogle Scholar
  24. Wang Y J, Wen S S, Li X C, Thomas F, Su B D, Wang R, Jiang T (2016). Spatiotemporal distributions of influential tropical cyclones and associated economic losses in China in 1984–2015. Nat Hazards, 84(3): 2009–2030CrossRefGoogle Scholar
  25. Wu H Y, Kang L H, Chen L L, Ma X M (2007). Effect of meteorological observation environment variability on homogeneity of temperature series in Zhiejiang Province. Mater Sci Technol, 35(1): 152–156 (in Chinese)Google Scholar
  26. Xiao F J, Yin Y Z, Luo Y, Song L C, Ye D X (2011). Tropical cyclone hazards analysis based on tropical cyclone potential impact index. J Geosci (Prague), 21: 791–800Google Scholar
  27. Xu H S, Lian J J, Bin L L, Xu K (2018). Joint distribution of muliple typhoon hazard factors. Scientia Geographica Sinica, 38(12): 2118–2124 (in Chinese)Google Scholar
  28. Xu Q, Wei L, Jin Y, Zhao Q Y, Cao J (2015). A dynamically constrained method for determining the vortex centers of tropical cyclones predicted by high-resolution models. J Atmos Sci, 72(1): 88–103CrossRefGoogle Scholar
  29. Yang Q Z, Xu M (2010). Preliminary study of the assessment of methods for disaster-inducing risks by TCs using sample events of TCs that affected Shanghai. J Trop Meteorol, 16: 299–304Google Scholar
  30. Ying M, Zhang W, Yu H, Lu X Q, Feng J X, Fan Y, Zhu Y, Chen D (2014). An overview of the China Meteorological Administration tropical cyclone database. J Atmos Ocean Technol, 31(2): 287–301CrossRefGoogle Scholar
  31. Zhang Q, Wu L G, Liu Q F (2009). Tropical cyclone damages in China 1983–2006. Bull Am Meteorol Soc, 90(4): 489–496CrossRefGoogle Scholar
  32. Zhang Q H, Wei Q, Chen L S (2010). Impact of landfalling tropical cyclones in mainland China. Sci China Earth Sci, 53(10): 1559–1564 (in Chinese)CrossRefGoogle Scholar
  33. Zhao S S, Ren F M, Gao G, Huang D P (2015). Characteristics of Chinese tropical cyclone disaster in the past 10 years. J Trop Meteorol, 31(03): 424–432 (in Chinese)Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Peiyan Chen
    • 1
    • 2
    Email author
  • Hui Yu
    • 1
    • 3
  • Ming Xu
    • 1
  • Xiaotu Lei
    • 4
  • Feng Zeng
    • 2
    • 5
  1. 1.Shanghai Typhoon Institute, China Meteotological AdministrationShanghaiChina
  2. 2.The Joint Laboratory for Typhoon Forecasting Technique Applications between Shanghai Typhoon Institute and Wenzhou Meteorological BureauWenzhouChina
  3. 3.Key Laboratory of Numerical Modeling for Tropical CycloneChina Meteotological AdministrationShanghaiChina
  4. 4.Shanghai Meteorological ServiceShanghaiChina
  5. 5.Wenzhou Meteorological BureauWenzhouChina

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