Abstract

In response to the 2004 and 2005 hurricane seasons, surge risk assessment approaches have been re-evaluated to develop more rapid, reliable methods for predicting the risk associated with extreme hurricanes. Here, the development of dimensionless surge response functions relating surge to hurricane meteorological parameters is presented. Such response functions present an opportunity to maximize surge data usage and to improve statistical estimates of surge probability by providing a means for defining continuous probability density functions. A numerical modeling investigation was carried out for the Texas, USA coastline to develop physical scaling laws relating storm surge response with hurricane parameters including storm size, intensity, and track. It will be shown that these scaling laws successfully estimate the surge response at any arbitrary location for any arbitrary storm track within the study region. Such a prediction methodology has the potential to decrease numerical computation requirements by 75% for hurricane risk assessment studies.

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