• Berliner, L. M., C. K. Wikle, and N. Cressie, 2000: Long-lead prediction of Pacific SSTs via Bayesian dynamic modeling. J. Climate, 13 , 39533968.

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

    • Search Google Scholar
    • Export Citation
  • Buckley, B. W., L. M. Leslie, and M. S. Speer, 2003: The impact of observational technology on climate database quality: Tropical cyclones in the Tasman Sea. J. Climate, 16 , 26402645.

    • Search Google Scholar
    • Export Citation
  • Carlin, B. P., and T. A. Louis, 2000: Bayes and Empirical Bayes Methods for Data Analysis. Chapman & Hall/CRC, 419 pp.

  • Carlin, B. P., A. E. Gelfand, and A. F. M. Smith, 1992: Hierarchical Bayesian analysis of change point problems. Appl. Stat, 41 , 389405.

    • Search Google Scholar
    • Export Citation
  • Chen, M-H., Q-M. Shao, and J. G. Ibrahim, 2000: Monte Carlo Methods in Bayesian Computation. Springer, 386 pp.

  • Coles, S., 2001: An Introduction to Statistical Modeling of Extreme Values. Springer, 208 pp.

  • Congdon, P., 2003: Applied Bayesian Modelling. John Wiley & Sons, 530 pp.

  • Cook, E. R., R. D. D'Arrigo, and K. R. Briffa, 1998: A reconstruction of the North Atlantic Oscillation using tree-ring chronologies from North America and Europe. Holocene, 8 , 917.

    • Search Google Scholar
    • Export Citation
  • Deser, C., and J. M. Wallace, 1987: El Niño events and their relation to the Southern Oscillation: 1925–1986. J. Geophys. Res, 92 , 1418914196.

    • Search Google Scholar
    • Export Citation
  • Deser, C., and J. M. Wallace, 1990: Large-scale atmospheric circulation features of warm and cold episodes in the tropical Pacific. J. Climate, 3 , 12541281.

    • Search Google Scholar
    • Export Citation
  • Donnelly, J. P., and Coauthors, 2001: A 700-year sedimentary record of intense hurricane landfalls in southern New England. Geol. Soc. Amer. Bull, 113 , 714727.

    • Search Google Scholar
    • Export Citation
  • Efron, B., and R. J. Tibsharini, 1993: An Introduction to the Bootstrap. Chapman & Hall, 436 pp.

  • Elsner, J. B., 2003: Tracking hurricanes. Bull. Amer. Meteor. Soc, 84 , 353356.

  • Elsner, J. B., and C. P. Schmertmann, 1993: Improving extended-range seasonal predictions of intense Atlantic hurricane activity. Wea. Forecasting, 8 , 345351.

    • Search Google Scholar
    • Export Citation
  • Elsner, J. B., and A. B. Kara, 1999: Hurricanes of the North Atlantic: Climate and Society. Oxford University Press, 488 pp.

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

  • Elsner, J. B., and B. H. Bossak, 2004: Hurricane landfall probability and climate. Hurricanes and Typhoons: Past, Present, and Future, R. Murnane and K.-B. Liu, Eds., Columbia University Press, in press.

    • Search Google Scholar
    • Export Citation
  • Elsner, J. B., A. B. Kara, and M. A. Owens, 1999: Fluctuations in North Atlantic hurricanes. J. Climate, 12 , 427437.

  • Elsner, J. B., T. Jagger, and X. Niu, 2000a: Shifts in the rates of major hurricane activity over the North Atlantic during the 20th century. Geophys. Res. Lett, 27 , 17431746.

    • Search Google Scholar
    • Export Citation
  • Elsner, J. B., K-B. Liu, and B. Kocher, 2000b: Spatial variations in major U.S. hurricane activity: Statistics and a physical mechanism. J. Climate, 13 , 22932305.

    • Search Google Scholar
    • Export Citation
  • Elsner, J. B., B. H. Bossak, and X-F. Niu, 2001: Secular changes to the ENSO–U.S. hurricane relationship. Geophys. Res. Lett, 28 , 41234126.

    • Search Google Scholar
    • Export Citation
  • Elsner, J. B., X-F. Niu, and T. H. Jagger, 2004: Detecting shifts in hurricane rates using a Markov chain Monte Carlo approach. J. Climate, 17 , 26522666.

    • 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
  • Fernández-Partagás, J., and H. F. Diaz, 1996: Atlantic hurricanes in the second half of the nineteenth century. Bull. Amer. Meteor. Soc, 77 , 28992906.

    • Search Google Scholar
    • Export Citation
  • Folland, C. K., and D. E. Parker, 1995: Correction of instrumental biases in historical sea surface temperature data. Quart. J. Roy. Meteor. Soc, 121 , 319367.

    • Search Google Scholar
    • Export Citation
  • Gilks, W. R., A. Thomas, and D. J. Spiegelhalter, 1994: A language and program for complex Bayesian modelling. Statistician, 43 , 169178.

    • Search Google Scholar
    • Export Citation
  • Gilks, W. R., S. Richardson, and D. J. Spiegelhalter, 1996: Markov Chain Monte Carlo in Practice. Chapman & Hall/CRC, 486 pp.

  • Goldenberg, S. B., C. W. Landsea, A. M. Mestas-Nuñez, and W. M. Gray, 2001: The recent increase in Atlantic hurricane activity: Causes and implications. Science, 239 , 474479.

    • Search Google Scholar
    • Export Citation
  • Gray, W. M., C. W. Landsea, P. W. Mielke Jr., and K. J. Berry, 1992: Predicting Atlantic seasonal hurricane activity 6–11 months in advance. Wea. Forecasting, 7 , 440455.

    • Search Google Scholar
    • Export Citation
  • Hess, J. C., J. B. Elsner, and N. E. LaSeur, 1995: Improving seasonal hurricane predictions for the Atlantic basin. Wea. Forecasting, 10 , 425432.

    • Search Google Scholar
    • Export Citation
  • Jagger, T., J. B. Elsner, and X. Niu, 2001: A dynamic probability model of hurricane winds in coastal counties of the United States. J. Appl. Meteor, 40 , 853863.

    • Search Google Scholar
    • Export Citation
  • 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, Coral Gables, FL, 21 pp.

    • Search Google Scholar
    • Export Citation
  • Jones, G. L., and J. P. Hobert, 2001: Honest exploration of intractable probability distributions via Markov chain Monte Carlo. Stat. Sci, 4 , 312324.

    • Search Google Scholar
    • Export Citation
  • Jones, P. D., T. Jónsson, and D. Wheeler, 1997: Extension to the North Atlantic Oscillation using early instrumental pressure observations from Gibraltar and South-West Iceland. Int. J. Climatol, 17 , 14331450.

    • Search Google Scholar
    • Export Citation
  • Katz, R. W., 2002: Techniques for estimating uncertainty in climate change scenarios and impact studies. Climate Res, 20 , 167185.

  • Landsea, C. W., and Coauthors, 2004: The Atlantic hurricane database re-analysis project documentation for 1851–1910: Alterations and additions to the HURDAT database. Hurricanes and Typhoons: Past, Present, and Future, R. J. Murnane and K.-B. Liu, Eds., Columbia University Press, in press.

    • Search Google Scholar
    • Export Citation
  • Lehmiller, G. S., T. B. Kimberlain, and J. B. Elsner, 1997: Seasonal prediction models for North Atlantic basin hurricane location. Mon. Wea. Rev, 125 , 17801791.

    • Search Google Scholar
    • Export Citation
  • Liu, K-B., and M. L. Fearn, 1993: Lake-sediment record of late Holocene hurricane activities from coastal Alabama. Geology, 21 , 793796.

    • Search Google Scholar
    • Export Citation
  • Liu, K-B., and M. L. Fearn, 2000: Reconstruction of prehistoric landfall frequencies of catastrophic hurricanes in northwestern Florida from lake sediment records. Quart. Res, 54 , 238245.

    • Search Google Scholar
    • Export Citation
  • Ludlum, D. M., 1963: Early American Hurricanes, 1492–1870. Amer. Meteor. Soc., 198 pp.

  • McCullagh, P., and J. A. Nelder, 1989: Generalized Linear Models. Chapman and Hall, 511 pp.

  • Michaels, A., D. Malmquist, A. Knap, and A. Close, 1997: Climate science and insurance risk. Nature, 389 , 225227.

  • Murnane, R. J., and Coauthors, 2000: Model estimates hurricane wind speed probabilities. Eos, Trans. Amer. Geophys. Union, 81 , 433,. 438.

    • Search Google Scholar
    • Export Citation
  • Neumann, C. J., B. R. Jarvinen, C. J. McAdie, and G. R. Hammer, 1999: Tropical Cyclones of the North Atlantic Ocean, 1871– 1998. National Oceanic and Atmospheric Administration, 206 pp.

    • Search Google Scholar
    • Export Citation
  • Parisi, F., and R. Lund, 2000: Seasonality and return periods of landfalling Atlantic basin hurricanes. Aust. N. Z. J. Stat, 42 , 271282.

    • Search Google Scholar
    • Export Citation
  • Solow, A. R., and L. Moore, 2000: Testing for a trend in a partially incomplete hurricane record. J. Climate, 13 , 36963699.

  • Spiegelhalter, D. J., N. G. Best, W. R. Gilks, and H. Inskip, 1996: Hepatitis B: A case study in MCMC methods. Markov Chain Monte Carlo in Practice, W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, Eds., Chapman & Hall/CRC, 45–58.

    • Search Google Scholar
    • Export Citation
  • Venables, W. N., and B. D. Ripley, 1999: Modern Applied Statistics with S-PLUS. Springer, 501 pp.

  • Wikle, C. K., 2000: Hierarchical space–time dynamic models. Lecture Notes in Statistics: Studies in the Atmospheric Sciences, L. M. Berliner, D. Nychka, and T. Hoar, Eds., Springer-Verlag, 199 pp.

    • Search Google Scholar
    • Export Citation
  • Wikle, C. K., and C. J. Anderson, 2003: Climatological analysis of tornado report counts using a hierarchical Bayesian spatiotemporal model. J. Geophys. Res.,108, 9005, doi:10.1029/2002JD002806.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., J. M. Wallace, and D. S. Battisti, 1997: ENSO-like interdecadal variability: 1900–93. J. Climate, 10 , 10041020.

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A Hierarchical Bayesian Approach to Seasonal Hurricane Modeling

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  • 1 Department of Geography, The Florida State University, Tallahassee, Florida
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Abstract

A hierarchical Bayesian strategy for modeling annual U.S. hurricane counts from the period 1851–2000 is illustrated. The approach is based on a separation of the reliable twentieth-century records from the less precise nineteenth-century records and makes use of Poisson regression. The work extends a recent climatological analysis of U.S. hurricanes by including predictors (covariates) in the form of indices for the El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Model integration is achieved through a Markov chain Monte Carlo algorithm. A Bayesian strategy that uses only hurricane counts from the twentieth century together with noninformative priors compares favorably to a traditional (frequentist) approach and confirms a statistical relationship between climate patterns and coastal hurricane activity. Coinciding La Niña and negative NAO conditions significantly increase the probability of a U.S. hurricane. Hurricane counts from the nineteenth century are bootstrapped to obtain informative priors on the model parameters. The earlier records, though less reliable, allow for a more precise description of U.S. hurricane activity. This translates to a greater certainty in the authors' belief about the effects of ENSO and NAO on coastal hurricane activity. Similar conclusions are drawn when annual U.S. hurricane counts are disaggregated into regional counts. Contingent on the availability of values for the covariates, the models can be used to make predictive inferences about the hurricane season.

Corresponding author address: James B. Elsner, Dept. of Geography, The Florida State University, Tallahassee, FL 32306. Email: jelsner@garnet.fsu.edu

Abstract

A hierarchical Bayesian strategy for modeling annual U.S. hurricane counts from the period 1851–2000 is illustrated. The approach is based on a separation of the reliable twentieth-century records from the less precise nineteenth-century records and makes use of Poisson regression. The work extends a recent climatological analysis of U.S. hurricanes by including predictors (covariates) in the form of indices for the El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Model integration is achieved through a Markov chain Monte Carlo algorithm. A Bayesian strategy that uses only hurricane counts from the twentieth century together with noninformative priors compares favorably to a traditional (frequentist) approach and confirms a statistical relationship between climate patterns and coastal hurricane activity. Coinciding La Niña and negative NAO conditions significantly increase the probability of a U.S. hurricane. Hurricane counts from the nineteenth century are bootstrapped to obtain informative priors on the model parameters. The earlier records, though less reliable, allow for a more precise description of U.S. hurricane activity. This translates to a greater certainty in the authors' belief about the effects of ENSO and NAO on coastal hurricane activity. Similar conclusions are drawn when annual U.S. hurricane counts are disaggregated into regional counts. Contingent on the availability of values for the covariates, the models can be used to make predictive inferences about the hurricane season.

Corresponding author address: James B. Elsner, Dept. of Geography, The Florida State University, Tallahassee, FL 32306. Email: jelsner@garnet.fsu.edu

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