Abstract
Using data from 62 tropical cyclones (TCs) that made landfall in Guangdong Province (China) between 2000 and 2019, we selected six indices—minimum central pressure, maximum wind speed, maximum rainstorm ratio, cumulative surface rainfall, tropical cyclone (TC) track length, lifetime—and constructed a projection pursuit dynamic cluster (PPDC) model to assess TC damage risk. Although a single index may provide correct information on the intensity of certain types of damage, a comprehensive damage risk assessment cannot be obtained from individual indices alone. The PPDC model is a stable tool for TC damage risk assessment, especially in terms of economic loss, agricultural disaster area and disaster-affected population. Model validation improved the correlation of each of the indices. Output from the PPDC model for disaster-affected population and agricultural disaster-affected area also improved after model validation. We examined the limitations of the single indices using data from three TCs. Output from the PPDC model can closely reflect the intensity of the damage caused by the cyclones. Projection pursuit dynamic clustering is a new objective method for TC damage risk assessment, which can provide the scientific basis to support disaster prevention and mitigation.
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The TC best-track dataset related to this article can be found at [http://tcdata.typhoon.org.cn], hosted by the Shanghai Typhoon Institute of the China Meteorological Administration (Ying et al. 2014).
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Acknowledgements
We thank Tina Tin, PhD, from Liwen Bianji (Edanz) (www.liwenbianji.cn/), for editing the English text of a draft of this manuscript.
Funding
This study was supported by the Fundamental Research Funds of the Special Program for Key Research and Development of Guangdong Province (Grant No. 2019B111101002), Guangzhou Science and Technology Planning Project (Grant No. 201903010036), China Postdoctoral Science Foundation (Grant No. 2020M683021), National Natural Science Foundation of China (Grant Nos. 42075004, 41875021, and 41830533).
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Conceptualization was contributed by SC, WL; Methodology was contributed by CN; Formal analysis and investigation were contributed by ZZ; Writing—original draft preparation—was contributed by CT; Writing—review and editing—was contributed by CT, SC; Funding acquisition was contributed by SC, WL; Supervision was contributed by SC.
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Tu, C., Chen, S., Zhao, Z. et al. Damage assessment for tropical cyclones landing in Guangdong Province of China by using a projection pursuit dynamic cluster model. Nat Hazards 114, 475–493 (2022). https://doi.org/10.1007/s11069-022-05398-5
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DOI: https://doi.org/10.1007/s11069-022-05398-5