Among natural disasters affecting the United States, North Atlantic tropical cyclones (TCs) and hurricanes are responsible for the highest economic losses and are one of the main causes of fatalities. Although we cannot prevent these storms from occurring, skillful seasonal predictions of the North Atlantic TC activity and associated impacts can provide basic information critical to our improved preparedness. Unfortunately, it is not yet possible to predict heavy rainfall and flooding associated with these storms several months in advance, and the lead time is limited to few days at the most. On the other hand, overall North Atlantic TC activity can be potentially predicted with a six- to nine-month lead time. This thesis focuses on the evaluation of the skill in predicting basin-wide North Atlantic TC activity with a long lead time and rainfall with a short lead time. For the seasonal forecast of TC activity, we develop statistical-dynamical forecasting systems for different quantities related to the frequency and intensity of North Atlantic TCs using only tropical Atlantic and tropical mean sea surface temperatures (SSTs) as covariates. Our results show that skillful predictions of North Atlantic TC activity are possible starting from November for a TC season that peaks in the August-October months. The short term forecasting of rainfall associated with TC activity is based on five numerical weather prediction (NWP) models. Our analyses focused on 15 North Atlantic TCs that made landfall along the U.S. coast over the period of 2007-2012. The skill of the NWP models is quantified by visual examination of the distribution of the errors for the different lead-times, and numerical examination of the first three moments of the error distribution. Based on our results, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead times up to 48 hours, without a consistently best or worst NWP model.

This dissertation, "Camille Was No Lady But Katrina Was A Bitch: Gender, Hurricanes & Popular Culture," uses the history of the hurricane naming process to compare the shifting environmental, scientific, and cultural changes taking place throughout the world during the twentieth century. It argues four major points: first, once gender is assigned to an object and adopted publicly en mass, it cannot be removed. Second, hurricane names have segregated hurricanes from other natural disasters in public consciousness. From "witches" and "bitches" to "monsters" and "menaces," the hurricane in popular memory calls forward explicitly gendered imagery; earthquakes, typhoons, dust bowls, plagues of insects, and other natural disasters do not carry the same sort of gendered associations. Third, by tracing the development and acceptance of the U.S. state-implemented hurricane naming process, it is possible to trace the spread of American gendered terms throughout the world. As illustrated throughout, gendered American meteorological terms are also found in global references to storms proving that hurricane names and descriptions are a form of both ecological and soft-power cultural imperialism. Finally, and most importantly, the socio-political implications tied to name and descriptive choices used with hurricanes have had a profound impact on storm perception globally. Introduced in 1954 by the U.S. Weather Bureau as a female-only hurricane naming system, hurricane names were rapidly adopted by other countries under U.S. meteorological control in the post-World War II era. With fears over Cold War politics both abroad and at home, the feminized hurricane was not just a weapon of mass destruction to be harnessed but also a potential tool of cultural domination through descriptive means. By the 1970s, with a discussion of feminism worldwide, references to the female-named storms helped produce dualistic images of "stormy women" and the "Women's Lib Storm" that were politically useful to men and the state when they felt threatened by feminism. Meanwhile, today's references to Hurricane Katrina, and later Sandy, as a "bitch" on Twitter reappear in blogs around the world. Due to this, the feminization of hurricanes has created and sustained a misogynistic, pervasively American form of vilification of women in media portrayals that continues to this day. / acase@tulane.edu

Hurricanes and earthquakes have caused extensive property damage to wood-frame residential construction in the past two decades in the United States. In order to improve residential building performance and mitigate losses from hurricane and earthquake hazards, there is an urgent need for better understanding of building performance and improvements in design and evaluation tools. In this study, a fragility analysis methodology is developed for assessing the response of light-frame wood construction exposed to extreme hurricane winds and earthquakes. The fragility is a conditional limit state probability, presented as a function of the 3-second gust wind speed (hurricanes) or spectral acceleration at the fundamental period of the building (earthquakes), leading to a relation between damage state probability and the hazard stipulated in ASCE Standard 7. A fully coupled probabilistic framework is proposed to assess reliability of the residential construction through convolution of the structural fragility model with hazard models. Finally, a comparative risk assessment addresses the similarities and differences in competing hurricane and earthquake hazards. The tools above can be used to evaluate new and existing building products, model the uncertainties that are inherent to the prediction of building performance, and manage the risk that is consequent to these uncertainties economically

Flooding inundation during hurricanes has been very costly and dangerous. However, the impact of climate change on hurricane flooding is not well understood at present. As sea surface temperatures increase, it is expected that hurricane intensity will increase and sea levels will rise. It is further hypothesized that climate change will increase hurricane flooding inundation, which would increase property damages and adversely affect a greater number of people. This thesis presents a case study of Corpus Christi, Texas, which analyzes the impact of climate change on hurricane flooding. Sea level rise projections and intensification of historical hurricanes were considered in this study. Storm surges were determined with the ADCIRC numerical model, while GIS was used to estimate area flooded, property damages, and population affected. Flooding inundation, property damages, and number of people affected by flooding increases as the intensity of the hurricane increases. As hurricane intensity increases and sea levels rise, the depth of flooding also increases dramatically. Based on two historical hurricanes and one shifted historical hurricane, on average the inundated area increases about 11 km2 per degree Celsius of sea surface temperature rise, the property damages increase by about $110 million per degree Celsius of sea surface temperature rise, and the number of people affected by flooding inundation increases by about 4,900 per degree Celsius of sea surface temperature rise. These results indicate that it may become necessary to consider the effects of climate change when building future coastal communities and adapting the protection of existing communities.

Thesis (M. P. A.)--Texas State University-San Marcos, 2009. / "Fall 2009." Includes bibliographical references (leaves 104-109).

Thesis (M.S.)--University of Akron, Dept. of Geology, 2008. / "December, 2008." Title from electronic thesis title page (viewed 12/13/2009) Advisor, Lisa E. Park; Faculty Readers, Ira D. Sasowsky, John Peck; Department Chair, John P. Szabo; Dean of the College, Ronald F. Levant; Dean of the Graduate School, George R. Newkome. Includes bibliographical references.

The purpose of this study was to describe the predictors of evacuation intention among coastal residents in the State of Florida and to determine if there are meaningful segments of the population who intend to evacuate when told to do so by governmental officials because of a major hurricane. In the America’s and the Caribbean, 75,000 deaths have been attributed to hurricanes in the 20 th century. A well planned evacuation can reduce injury and death, yet many people do not have an evacuation plan and do not intend to evacuate when told to do so. The study used secondary data from the Harvard School of Public Health, Hurricane in High Risk Areas study, a random sample of 5,046 non-institutionalized persons age 18 and older in coastal counties of Texas, Louisiana, Mississippi, Alabama, Georgia, North Carolina, South Carolina and Florida. Surveys for the State of Florida were segregated and used in this analysis, resulting in a study sample of 1,006 surveys from 42 counties. When asked if they would evacuate in the future if told to by government officials, 59.1% of Floridians surveyed said they would leave, 35.2% said they would not leave and 5.6% said it would depend. In Florida, 65.7% of the population had been threatened or hit by a major hurricane in the last three years and 26.6% of those had left their homes because of the hurricane. Of those whose communities were threatened by a hurricane, 83.3% of the communities were damaged and 33.8% experienced major flooding associated with the hurricane. Bivariate statistics and logistic regression were used to explore the interactions of predictors and evacuation intention. The best predictor of evacuation intention was prior evacuation from a hurricane (chi-square= 45.48, p < .01, Cramer’s V = 0.266). Significant relationships were also demonstrated between evacuation intention and worry a future hurricane would hit the community (chi-square = 22.75, p < .01, Cramer’s V = 0.11), the presence of pets (chi-square = 6.57, p < .01, Cramer’s V = 0.084), concern the home would be damaged (chi-square = 19.41, p < .01, Cramer’s V = 0.10), belief the home would withstand a major hurricane (chi-square = 19.55, p < .01, Cramer’s V = 0.10), length of time in the community (chi-square = 26.59, p < .01, Cramer’s V = 0.12), having children in the household (chi-square = 11.13, p < .01, Cramer’s V = 0.11), having a generator (chi-square = 17.12, p < .01, Cramer’s V = 0.13), age (chi-square = 24, p < .01, Cramer’s V = 0.16) and race (chi-square = 12.21, p = .02, Cramer’s V = 0.12). Logistic regression of the predictors of evacuation intention resulted in significant relationships with previous evacuation experience (OR = 4.99, p < .001), age 30 to 49 compared to age over 65 (OR = 2.776, p < .01), the presence of a generator (OR = .447, p < .01), having a home not very likely to be damaged compared to a home very likely to be damaged (OR =.444, p = .018), and experiencing poor prior government and voluntary agency response to previous hurricanes compared to excellent response (OR = .386, p < .027). Chi-squared Automatic Interaction Detection (CHAID) was used to identify segments of the population most likely and least likely to evacuate when told to do so. Those most likely to evacuate had evacuated due to a previous hurricane. Those least likely to evacuate when told to do so had not evacuated in a previous storm, do not own a generator and are over the age of 65. Information from this study can be used in planning for evacuation response by governmental entities. Available demographic information can be used to determine numbers of persons likely to evacuate before a storm. The results of this study can be used to inform a marketing strategy by government officials to encourage evacuation among those who say they would not evacuate when told to do so. Further research is needed to determine additional characteristics of the populations who say they will and will not evacuate when told to do so.

Using hydraulic modeling and Geographic Information System (GIS) software, the 100-year flood was delineated for the municipality of Avon Park located in Highlands County, Florida. A detailed and rigorous approach was undertaken to first collect and develop an extensive spatial database to store the data collected that is pertinent to the model. This analysis combined ArcGIS version 8.3 and the Interconnected Channel and Pond Routing (ICPR) model version 3.02 to develop hydraulic models that assigned regulatory flood elevation within the watershed. The model results were post processed and brought into GIS to delineate the 100-year flood.The steps outlined in this thesis with respect to the use of GIS as a tool in model pre and post-processing are applicable to many models. Hence, the methodology outlined in this thesis adds to the existing pool of knowledge about the use of GIS in hydraulic modeling. By documenting all the steps related to data acquisition, data processing and manipulation, the model interface and GIS, and the post processing of the model results, this thesis can serve as resources for future studies that utilize both GIS and hydraulic modeling.

Hurricanes pose a challenge for residents and communities of the United States Gulf Coast. The people that live in the region must adapt and respond to these storms, as do the social institutions that provide support during disasters and their aftermath. This is complicated by the longstanding and ongoing relationship between the oil and gas industry and gulf coastal communities, especially as activities associated with oil and gas development alter the local environments and regional landscapes in ways that increase vulnerability. These vulnerabilities layer onto existing social inequalities and make management and protection of regional populations difficult, and complicate recovery efforts. In this dissertation I explore the relationships between people, communities, industry, and social institutions. I trace the recent history of gulf coast storms in the region, emergent and developing strategies for preparation and recovery, and ongoing contention embedded within policy and governance issues. I also consider the complex interaction between social and natural systems, the role of government and support networks in providing assistance, and the locus of responsibility in mitigating vulnerability and providing support, before, during, and after a disaster.

The power of natural disasters to significantly and drastically alter the lives of the people they touch is vast, and the response rate of the provided aid can be the difference between a successful recovery and not. This study examines the relationship between natural disasters and volunteerism. The analysis makes use of panel data measurements on volunteer rate and volunteer hours per resident as well as FEMA measurements of major natural disasters from 2005 – 2012. I find that states that experience a natural disaster in the current year experience a significant and positive increase in volunteer rate in the year following the disaster. The findings highlight the importance of policy focused on harnessing volunteer labor in the wake of natural disasters.