In October, Hurricane Mitch claimed 9,000 lives when it dropped more than 50 inches of rain on Honduras. Their model uses historical data to map the likelihood of hurricane landfall at any location along the Gulf and East coasts of the United States, or along any other hurricane-threatened coastline around the world. Accurate estimates of the landfall probability of intense hurricanes are of use to insurers, emergency planners, government officials, populations in vulnerable coastal areas, and society as a whole.
Cat models are the main way that insurance companies apply scientific knowledge.
These models feature three basic components. A hazard component estimates the probability that a hazardous event will occur. The RPI model provides the hazard component only, but addresses some of the most challenging obstacles faced by the current generation of cat models. For example, the hazard components of existing cat models typically provide little sense of how uncertain their landfall probability estimates are, and they provide no independent means to verify their estimates for rare, intense storms like Mitch. The RPI model addresses the first problem by providing a range of uncertainty for each estimate of landfall probability, rather than giving a single number.