Abstract
Hurricane warnings cause people and businesses in the predicted path of the cyclone to take actions that will reduce damage and/or loss of life. Sometimes these actions and their attendant costs are avoidable, since a larger section of the coast is alerted than that which the hurricane actually affects.
Using general population densities and the average damage costs due to storms, the authors present a combined game- and decision-theory approach to estimating the economic benefits of more accurate prediction. The potential savings to this economic sector for a substantial improvement in 24-hr forecasting accuracies (that is, the reduction of the average forecast error to one-half its present value) is shown to be at least $15.2 million in the first year. A general equation is presented for various combinations of improvement levels, population densities, percentage of those who protect, and number of warnings per season.
