Comparison of Local and Basinwide Methods for Risk Assessment of Tropical Cyclone Landfall

Timothy M. Hall NASA Goddard Institute for Space Studies, New York, New York

Search for other papers by Timothy M. Hall in
Current site
Google Scholar
PubMed
Close
and
Stephen Jewson Risk Management Solutions, London, United Kingdom

Search for other papers by Stephen Jewson in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Two statistical methods for predicting the number of tropical cyclones (TCs) making landfall on sections of the North American coastline are compared. The first method—the “local model”—is derived exclusively from historical landfalls on the particular coastline section. The second method—the “track model”—involves statistical modeling of TC tracks from genesis to lysis, and is based on historical observations of such tracks. Identical scoring schemes are used for each model, derived from the out-of-sample likelihood of a Bayesian analysis of the Poisson landfall number distribution. The track model makes better landfall rate predictions on most coastal regions, when coastline sections at a scale of several hundred kilometers or smaller are considered. The reduction in sampling error due to the use of the much larger dataset more than offsets any bias in the track model. When larger coast sections are considered, there are more historical landfalls, and the local model scores better. This is the first clear justification for the use of track models for the assessment of TC landfall risk on regional and smaller scales.

Corresponding author address: Timothy Hall, NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025. Email: thall@giss.nasa.gov

Abstract

Two statistical methods for predicting the number of tropical cyclones (TCs) making landfall on sections of the North American coastline are compared. The first method—the “local model”—is derived exclusively from historical landfalls on the particular coastline section. The second method—the “track model”—involves statistical modeling of TC tracks from genesis to lysis, and is based on historical observations of such tracks. Identical scoring schemes are used for each model, derived from the out-of-sample likelihood of a Bayesian analysis of the Poisson landfall number distribution. The track model makes better landfall rate predictions on most coastal regions, when coastline sections at a scale of several hundred kilometers or smaller are considered. The reduction in sampling error due to the use of the much larger dataset more than offsets any bias in the track model. When larger coast sections are considered, there are more historical landfalls, and the local model scores better. This is the first clear justification for the use of track models for the assessment of TC landfall risk on regional and smaller scales.

Corresponding author address: Timothy Hall, NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025. Email: thall@giss.nasa.gov

Save
  • Aldrich, J., 1997: R. A. Fisher and the making of maximum likelihood 1912–1922. Stat. Sci., 12 , 162176.

  • Bove, M. C., J. B. Elsner, C. W. Landsea, X. Niu, and J. J. O’Brien, 1998: Effect of El Niño of U.S. landfalling hurricanes, revisited. Bull. Amer. Meteor. Soc., 79 , 24772482.

    • Search Google Scholar
    • Export Citation
  • Elsner, J. B., and B. H. Bossak, 2001: Bayesian analysis of U.S. hurricane climate. J. Climate, 14 , 43414350.

  • Emanuel, K. A., S. Ravela, E. Vivant, and C. Risi, 2006: A statistical deterministic approach to hurricane risk assessment. Bull. Amer. Meteor. Soc., 87 , 299314.

    • Search Google Scholar
    • Export Citation
  • Epstein, E. S., 1985: Statistical Inference and Prediction in Climatology: A Bayesian Approach. Meteor. Monogr. No. 42, Amer. Meteor. Soc., 199 pp.

    • Search Google Scholar
    • Export Citation
  • Hall, T. M., and S. Jewson, 2007: Statistical modeling of North Atlantic tropical cyclone tracks. Tellus, 59A , 486498.

  • James, M. K., and L. B. Mason, 2005: Synthetic tropical cyclone database. J. Waterway, Port, Coastal, Ocean Eng., 131 , 181192.

  • Jarvinen, B. R., C. J. Neumann, and M. A. S. Davis, 1984: A tropical cyclone data tape for the North Atlantic Basin, 1886–1983, contents, limitations, and uses. NOAA Tech. Memo. NWS NHC 22, Miami, FL, 21 pp.

  • Quenouille, M., 1949: Approximate tests of correlation in time series. J. Roy. Stat. Soc., 11B , 1884.

  • Tartaglione, C. A., S. R. Smith, and J. J. O’Brien, 2003: ENSO impact on hurricane landfall probabilities for the Caribbean. J. Climate, 16 , 29252931.

    • Search Google Scholar
    • Export Citation
  • Tukey, J. M., 1958: Bias and confidence in not quite large samples. Ann. Math. Stat., 29 , 614.

  • Vickery, P. J., P. Skerlj, and L. Twisdale, 2000: Simulation of hurricane risk in the US using an empirical track model. J. Structural Eng., 126 , 12221237.

    • Search Google Scholar
    • Export Citation
  • Webster, P. J., G. J. Holland, J. A. Curry, and H-R. Chang, 2005: Changes in tropical cyclone number, duration, and intensity in a warming environment. Science, 309 , 18441846.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 283 78 4
PDF Downloads 207 52 4