Estimating Probabilities of Hurricane Wind Speeds Using a Large-Scale Empirical Model

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  • 1 Institute for Constructive Mathematics. University of South Florida, Tampa, Florida
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Abstract

A new method is presented for estimating the probability of exceeding a given wind speed in 1 year at any given location in the Atlantic tropical cyclone basin. The method is especially appropriate for wind speeds with return periods of 100 years or more, for which on-the-spot data are inadequate. The relative intensity of a tropical cyclone at any point in time is the actual central pressure drop divided by the greatest possible central pressure drop that mean seasonal climatic conditions allow. The empirical distribution of relative intensity as a function of time is derived from all Atlantic cyclone data. By combining this with information about the distribution of time from cyclone inception to closest approach to the site, and other steps, probabilities for various wind speeds at the site are obtained. Unlike other methods, this one does not attempt to fit data to any extreme value distribution, and it performs all integrations by discretizing and summing explicitly, never by simulation. The results at the Turkey Point Power Plant site in south Florida am in good agreement at lower wind speeds with National Hurricane Center estimates using local data for 1886–1988.

Abstract

A new method is presented for estimating the probability of exceeding a given wind speed in 1 year at any given location in the Atlantic tropical cyclone basin. The method is especially appropriate for wind speeds with return periods of 100 years or more, for which on-the-spot data are inadequate. The relative intensity of a tropical cyclone at any point in time is the actual central pressure drop divided by the greatest possible central pressure drop that mean seasonal climatic conditions allow. The empirical distribution of relative intensity as a function of time is derived from all Atlantic cyclone data. By combining this with information about the distribution of time from cyclone inception to closest approach to the site, and other steps, probabilities for various wind speeds at the site are obtained. Unlike other methods, this one does not attempt to fit data to any extreme value distribution, and it performs all integrations by discretizing and summing explicitly, never by simulation. The results at the Turkey Point Power Plant site in south Florida am in good agreement at lower wind speeds with National Hurricane Center estimates using local data for 1886–1988.

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