Published online by Cambridge University Press: 14 September 2009
Condensed summary
Coastal hurricanes generate huge financial losses within the insurance industry. The relative infrequency of severe coastal hurricanes implies that empirical probability estimates of the next big loss will be unreliable. Hurricane climatologists have recently developed statistical models to forecast the level of coastal hurricane activity based on climate conditions prior to the season. Motivated by the usefulness of such models, in this chapter we analyze and model a catalog of normalized insured losses caused by hurricanes affecting the United States. The catalog of losses dates back through the twentieth century. The purpose of this work is to demonstrate a preseason forecast tool that can be used for insurance applications. Although wind speed is directly related to damage potential, the amount of damage depends on both storm intensity and storm size. As anticipated, we found that climate conditions prior to a hurricane season provide information about possible future insured hurricane losses. The models exploit this information to predict the distribution of likely annual losses and the distribution of a worst-case catastrophic loss aggregated over the entire US coast.
Introduction
Coastal hurricanes are a serious social and economic concern for the United States. Strong winds, heavy rainfall, and storm surge kill people and destroy property. The destructive power of hurricanes rivals that of earthquakes. On August 28, 2005, Hurricane Katrina's winds reached 78 meters per second (m s− 1) in the central Gulf of Mexico, making it one of the strongest Atlantic hurricanes ever recorded.
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