Date of Award

5-2012

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Civil Engineering

Advisor

Pang, WeiChiang

Committee Member

Schiff , Scott

Committee Member

Nielson , Bryant

Abstract

This study presents the development of a new central pressure filling rate model to characterize the rate at which hurricanes or tropical storms decay after landfall. It has been shown that the post landfall decay rate of hurricanes is closely related to the time after landfall, the size of hurricane and proximity of the hurricane eye to the coastline. In addition, it has been observed that the decay rates of hurricanes are geographically dependent. Based on these observations, a set of simple empirical models expressed in
terms of exponential and linear equations are utilized to characterize the decay rate of hurricanes after landfall.
The filling rate model, which consists of a set of empirical equations, is organized according to the geographic region, the storm heading direction and proximity of the hurricane eye to the coastline. To account for the influence of the land terrain on the
decay rate of hurricanes, the North American continent is divided into seven regions: Gulf Coast, Florida, East Coast and Northeast Coast, Great Lakes, Inland and Mexico area. A new along-shore hurricane decay model is introduced to account for the decay
rate of hurricanes traveling along the coastline and with the hurricane eye relatively close to the coastline. In the new filling rate model, modeling parameters are determined through regression analysis using the hurricane database (HURDAT) maintained by the
National Hurricane Center for hurricane records from 1975 to 2011 (HRD 2012a). Based on the results of the regression analysis, it has been shown that the modeling uncertainty (or error term), which is defined as the difference between the model predicted and the actual observed decay rates, can be characterized using the unbounded Johnson distribution.
The new model is benchmarked against two current state-of-the-art models by comparing the simulated central pressures for historical hurricane events to that of the actual observations in HURDAT. The benchmark study has shown that the simulated results using the new decay model are generally more accurate and match reasonably well with the actual central pressures of historical storm events. The new decay model has been coded into a Matlab program and the codes are provided herein with this manuscript. The new decay model and the computer codes can be implemented into a stochastic hurricane simulation framework for long-term hurricane risk assessment or hurricane hazard mapping

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