Tropical cyclone-generated storm surge frequently causes catastrophic damage in communities along the Gulf of Mexico. The prediction of landfalling or hypothetical storm surge magnitudes in U.S. Gulf Coast regions remains problematic, in part, because of the dearth of historic event parameter data, including accurate records of storm surge magnitude (elevation) at locations along the coast from hurricanes. While detailed historical records exist that describe hurricane tracks, these data have rarely been correlated with the resulting storm surge, limiting our ability to make statistical inferences, which are needed to fully understand the vulnerability of the U.S. Gulf Coast to hurricane-induced storm surge hazards.
This dissertation addresses the need for reliable statistical storm surge estimation by proposing a probabilistic geodatabase-assisted methodology to generate a storm surge surface based on hurricane location and intensity parameters on a single desktop computer. The proposed methodology draws from a statistically representative synthetic tropical cyclone dataset to estimate hurricane track patterns and storm surge elevations. The proposed methodology integrates four modules: tropical cyclone genesis, track propagation, storm surge estimation, and a geodatabase. Implementation of the developed methodology will provide a means to study and improve long-term tropical cyclone activity patterns and predictions.
Specific contributions are made to the current state of the art through each of the four modules. In the genesis module, improved representative data from historical genesis populations are achieved through implementation of a stratified-Monte-Carlo sampling method to simulate genesis locations for the North Atlantic Basin, avoiding potential non-representative clustering of sampled genesis locations. In the track module, the improved synthetic genesis locations are used as the starting point for a track location and intensity methodology that incorporates storm strength parameters into the synthetic tracks and improves the positional quality of synthetic tracks. In the surge module, high-resolution, computationally intensive storm surge model results are probabilistically integrated in a computationally fast-running platform. In the geodatabase module, historic and synthetic tropical cyclone genesis, track, and surge elevation data are combined for efficient storage and retrieval of storm surge data.
| Identifer | oai:union.ndltd.org:LSU/oai:etd.lsu.edu:etd-01162013-060632 |
| Date | 23 January 2013 |
| Creators | BINSELAM, SAIT AHMET |
| Contributors | DSa, Eurico J., Knapp, Gerald M., Leitner, Michael, Levitan, Marc L., Friedland, Carol J. |
| Publisher | LSU |
| Source Sets | Louisiana State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lsu.edu/docs/available/etd-01162013-060632/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached herein a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to LSU or its agents the non-exclusive license to archive and make accessible, under the conditions specified below and in appropriate University policies, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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