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Assessing hurricane damage costs in the presence of vulnerability model uncertainty

Author

Listed:
  • Cao Wang

    (Tsinghua University
    The University of Sydney)

  • Hao Zhang

    (The University of Sydney)

  • Kairui Feng

    (Tsinghua University)

  • Quanwang Li

    (Tsinghua University)

Abstract

Probability-based assessment of hurricane damage costs for coastal communities is vital for policy-makers and insurers. The uncertainties associated with hurricane damage costs include both the inherent uncertainty due to the random nature of hurricane process and the model uncertainty of the mathematical representation of hurricane damage (vulnerability model). The hurricane vulnerability model has traditionally been modeled as a deterministic function of hurricane wind speed in the literature, without considering the effect of vulnerability model uncertainty on hurricane damage assessment. This paper develops two methods to assess the hurricane damage costs in the presence of vulnerability model uncertainty. To account for the non-stationarity in hurricane actions due to the potential impact of climate change, the hurricane occurrence process is modeled as a non-stationary Poisson process and the hurricane intensity is assumed to vary in time with time-variant statistical parameters of hurricane wind speed. A case study of Miami-Dade County, Florida, is conducted to illustrate the proposed methods and to investigate the impact of vulnerability model uncertainty on hurricane damage costs.

Suggested Citation

  • Cao Wang & Hao Zhang & Kairui Feng & Quanwang Li, 2017. "Assessing hurricane damage costs in the presence of vulnerability model uncertainty," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(3), pages 1621-1635, February.
  • Handle: RePEc:spr:nathaz:v:85:y:2017:i:3:d:10.1007_s11069-016-2651-z
    DOI: 10.1007/s11069-016-2651-z
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    References listed on IDEAS

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    1. James B. Elsner & James P. Kossin & Thomas H. Jagger, 2008. "The increasing intensity of the strongest tropical cyclones," Nature, Nature, vol. 455(7209), pages 92-95, September.
    2. Dai, Hongzhe & Zhang, Boyi & Wang, Wei, 2015. "A multiwavelet support vector regression method for efficient reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 132-139.
    3. Elliott, Robert J.R. & Strobl, Eric & Sun, Puyang, 2015. "The local impact of typhoons on economic activity in China: A view from outer space," Journal of Urban Economics, Elsevier, vol. 88(C), pages 50-66.
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    Cited by:

    1. Li, Yaohan & Dong, You & Qian, Jing, 2020. "Higher-order analysis of probabilistic long-term loss under nonstationary hazards," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

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