Quantifying Extreme Hurricane Risk in the North Atlantic and Gulf of Mexico

• Other Authors: Trepanier, Jill, 1985- (authoraut)
• Format: Others
• Language: English; English
• Published: Florida State University
• Subjects: Geography
• Online Access: http://purl.flvc.org/fsu/fd/FSU_migr_etd-5234

Hurricanes threaten the United States every year. It is important to quantify the risk of these events for emergency managers. Extreme value statistics are used to model hurricane characteristics at different locations. Using wind speeds over a specified threshold, the risk of extreme winds are estimated in twelve Florida cities. The risk estimates are provided as statistical return periods, or the expected frequency of specific hurricane magnitudes. Results show that the city of Miami can expect to see hurricane winds blowing at 50 ms-1 (45.5-54.5) [90% CI] or stronger, on average, once every 12 years. In comparison, the city of Pensacola can expect to see hurricane winds of 50 ms-1 (46.9-53.1) [90% CI] or stronger once every 24 years. Hurricanes in the vicinity of Florida are found to be increasing in intensity over time as a product of higher offshore intensification rates. The risk of hurricane strikes can be further understood by including an additional variable, storm surge. Using observational data, the joint probability distribution of hurricane wind speeds and storm surge is found at three Air Force Bases along the U. S. Gulf coast. The quartile pointwise uncertainty is quantified using a Monte Carlo procedure. Eglin Air Force Base can expect wind speeds blowing at 50 ms-1 and surge heights of 3 m, on average, once every 28 years (23-36). MacDill Air Force Base can expect wind speeds blowing at 50 ms-1 and surge heights of 3 m, on average, once every 27 years (22-34). Keesler Air Force Base can expect wind speeds blowing at 50 ms-1 and surge heights of 3 m, on average, once every 15 years (13-18). Utilizing a spatial tessellation across the North Atlantic and Gulf of Mexico provides additional insight into the risk of hurricane strikes. Parameters from the extreme value model are mapped across space to visualize patterns. Sea surface temperature is included as a covariate in a geographically weighted regression model with each parameter. It is found that as sea surface temperatures increase, the expected hurricane wind speed for a given return period also increases. === A Dissertation submitted to the Department of Geography in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Spring Semester, 2012. === March 15, 2012. === Extreme Value, Hurricane, Risk === Includes bibliographical references. === James Elsner, Professor Directing Dissertation; Joseph Donoghue, University Representative; Victor Mesev, Committee Member; Tingting Zhao, Committee Member.