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Modelling extreme wind speeds in regions prone to hurricanes

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  • D. Walshaw

Abstract

Extreme wind speeds can arise as the result of a simple pressure differential, or a complex dynamic system such as a tropical storm. When sets of record values comprise a mixture of two or more different types of event, the standard models for extremes based on a single limiting distribution are not applicable. We develop a mixture model for extreme winds arising from two distinct processes. Working with sequences of annual maximum speeds obtained at hurricane prone locations in the USA, we take a Bayesian approach to inference, which allows the incorporation of prior information obtained from other sites. We model the extremal behaviour for the contrasting wind climates of Boston and Key West, and show that the standard models can give misleading results at such locations.

Suggested Citation

  • D. Walshaw, 2000. "Modelling extreme wind speeds in regions prone to hurricanes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(1), pages 51-62.
    • Handle: RePEc:bla:jorssc:v:49:y:2000:i:1:p:51-62
    DOI: 10.1111/1467-9876.00178
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    Cited by:

    1. Thomas Jagger & James Elsner & R. Burch, 2011. "Climate and solar signals in property damage losses from hurricanes affecting the United States," 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. 58(1), pages 541-557, July.
    2. Li, Gong & Shi, Jing, 2012. "Applications of Bayesian methods in wind energy conversion systems," Renewable Energy, Elsevier, vol. 43(C), pages 1-8.
    3. M. Ivette Gomes & Armelle Guillou, 2015. "Extreme Value Theory and Statistics of Univariate Extremes: A Review," International Statistical Review, International Statistical Institute, vol. 83(2), pages 263-292, August.

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