Dependency of U.S. Hurricane Economic Loss on Maximum Wind Speed and   Storm Size
  Many empirical hurricane economic loss models consider only wind speed and neglect storm size. These models may be inadequate in accurately predicting the losses of super-sized storms, such as Hurricane Sandy in 2012. In this study, we examined the dependencies of normalized U.S. hurricane loss on both wind speed and storm size for 73 tropical cyclones that made landfall in the U.S. from 1988 to 2012. A multi-variate least squares regression is used to construct a hurricane loss model using both wind speed and size as predictors. Using maximum wind speed and size together captures more variance of losses than using wind speed or size alone. It is found that normalized hurricane loss (L) approximately follows a power law relation with maximum wind speed (Vmax) and size (R). Assuming L=10^c Vmax^a R^b, c being a scaling factor, the coefficients, a and b, generally range between 4-12 and 2-4, respectively. Both a and b tend to increase with stronger wind speed. For large losses, a weighted regression model, with a being 4.28 and b being 2.52, produces a reasonable fitting to the actual losses. Hurricane Sandy's size was about 3.4 times of the average size of the 73 storms analyzed. Based on the weighted regression model, Hurricane Sandy's loss would be 21 times smaller if its size were of the average size with maximum wind speed unchanged. It is important to revise conventional empirical hurricane loss models to include both maximum wind speed and size as predictors. 
Alice R. Zhai and Jonathan H. Jiang
physics.ao-ph