Abstract: Interest in hurricane risk usually focuses on landfalling events of the highest intensity, which cause a disproportionate amount of hurricane-related damage. Yet assessing the long-term risk of the most intense landfalling ...

Abstract: odels that predict annual U.S. hurricane activity assume a Poisson distribution for the counts. Here the authors show that this assumption applied to Florida hurricanes leads to a forecast that underpredicts both the number ...

Abstract: The authors apply a procedure called Bayesian model averaging (BMA) for examining the utility of a set of covariates for predicting the distribution of U.S. hurricane counts and demonstrating a consensus model for seasonal ...

Abstract: Advances in hurricane climate science allow forecasts of seasonal landfall activity to be made. The authors begin with a review of the forecast methods available in the literature. They then reformulate the methods using ...

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 ...

Abstract: The authors build on their efforts to understand and predict coastal hurricane activity by developing statistical seasonal forecast models that can be used operationally. The modeling strategy uses May?June averaged values ...

Abstract: The rarity of severe coastal hurricanes implies that empirical estimates of extreme wind speed return levels will be unreliable. Here climatology models derived from extreme value theory are estimated using data from the ...

Abstract: The authors develop and apply a model that uses hurricane-experience data in counties along the U.S. hurricane coast to give annual exceedence probabilities to maximum tropical cyclone wind events. The model uses a maximum ...

Abstract: Hurricanes cause drastic social problems as well as generate huge economic losses. A reliable forecast of the level of hurricane activity covering the next several seasons has the potential to mitigate against such losses ...

Abstract: rs demonstrate a statistical model for the time it takes a manuscript to be accepted for publication. The manuscript received and accepted dates from published manuscripts with the term ?hurricane? in the title are obtained ...