Modelling extreme wind speeds in regions prone to hurricanes

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.