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Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. T.N. Krishnamurti, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (Jan. 20, 2005). Includes bibliographical references.

Scientific literature is concerned with the impact that climate change will have on natural disasters in the near future. These events disrupt our daily lives and can cause damage that may never be repaired. Merging science and social science, the study of vulnerability looks at how human systems will be impacted by these natural disasters. In the United States, hurricanes in the Gulf Coast are projected to increase in intensity as well as have an increased capacity for damage with a rise in sea level. Therefore, it is important to understand who is systematically vulnerable to these impacts of natural disasters and how we can mitigate this damage. Through this thesis, I argue that these impacts of hurricanes will put already vulnerable populations at a greater risk for damage caused by these events in the future. I will briefly outline the scientific basis on which the claims of increased hurricane activity are founded, as well as outline concepts of vulnerability. I examine case studies of Hurricanes Andrew and Katrina, both of which can inform how social disparities delineate vulnerability in the United States. Based upon this historical understanding that recovery from a storm is highly contingent upon social and economic resources available to an individual or community, I argue that vulnerable communities must be highlighted. I then project vulnerability based upon demographic characteristics of communities within the Gulf Coast in order to highlight these areas of necessary attention.

We consider the impact that various shocks and stresses have on the reliability of networks with radial topology, such as an electrical power grid. We incorporate the effects of aging, geographical risk, and local dependence between components into a model of overall system reliability. We also simulate how the system fares under extreme weather events, such as hurricanes. Our model gives a flexible and general understanding of how outside forces affect network reliability and can be adapted to a range of specific uses. We run a simulation using this model which yields realistic results.

Five statistical and dynamical tropical cyclone intensity guidance techniques available at the National Hurricane Center during the 2003 and 2004 Atlantic and Eastern North Pacific seasons were evaluated within three intensity phases: (I) formation; (II early intensification; and (III) decay. During the formation phase, the Decay Statistical Hurricane Intensity Prediction (DSHIPS) technique was the best technique in both basins. When the forecast errors during formation exceed +/- 10 kt, the statistical techniques tend to over-forecast and the dynamical models tend to under-forecast. Whereas DSHIPS was also the best technique in the Atlantic during the early intensification stage, the Geophysical Fluid Dynamics Laboratory model was the best in the Eastern North Pacific. All techniques under-forecast periods of rapid intensification and the peak intensity, and have an overall poor performance during decay-reintensification cycles in both basins. Whereas the DSHIPS was the best technique in the Atlantic during decay, none of the techniques excelled during the decay phase in the eastern North Pacific. All techniques tend to decay the tropical cyclones in both basins too slowly, except that the DSHIPS performed well (13 of 15) during rapid decay events in the Atlantic. Similar error characteristics had been found in the western North Pacific.

CHDS State/Local / Hurricane Katrina highlighted serious deficiencies in America's national approach to emergency management of Incidents of National Significance (IoNS). Although Homeland Security Presidential Directive Five identifies a broad, unified effort to respond to domestic incidents, barriers to the achievement of this goal exist in our culture, policies and processes. When viewing our national response from the perspective of network theory and knowledge management, specific gaps are identified in doctrine, organizational composition and technological capability. An agenda for change to the National Response Plan and National Incident Management System should integrate the strengths of the network design and address the critical role that knowledge plays in shaping response efforts at all levels. A comprehensive strategy to change the culture and approach of our response community includes streamlining organizational roles of the Unified Command and local Emergency Operations Centers, expanding the Unified Command to include the private sector and NGOs as equal partners, implementing a Knowledge Management Annex to the National Response Plan and deploying a mesh network communications system as part of the proactive federal response. / Commander, U.S. Coast Guard

Hurricanes rapidly destroy large expanses land in coastal Louisiana marsh. Research shows that freshwater marsh with organic soils experience increased destruction during hurricanes compared to other marsh. A relevant question surfaces, do some restoration projects create marsh similar to marshes that are more susceptible to hurricane damage. This study analyzes soil, bulk density, plant composition, and buoyancy of restoration projects and sites adjacent to those that experienced land loss during Hurricanes Katrina and Rita. Results indicate that high organic matter percentages in marsh soil increases hurricane susceptibility attributed to decreased bulk density and increased buoyancy. Buoyancy is episodic and is highest during late summer months when soil temperature and decomposition are highest. Late summer is typically when most intense hurricanes occur. If marsh is less dense, decomposing, and buoyant when strongest hurricanes hit, then potential for destruction during a hurricane increases. Samples were collected from August 2009 to October 2009.

During the 1979 Atlantic hurricane season a tropical wave left the west coast of Africa and continued westward where satellite and ship observation indicated strengthening to a tropical depression from which Hurricane Frederic developed. This particular tropical disturbance has an interesting history. In its westward progression it intensified to hurricane strength lasting less than 24 hours followed by a weakening east of the Lesser Antilles. Continuing westward, this disturbance became extratropical over Southeast Cuba, but quickly reintensified to hurricane strength over Northwest Cuba, tracking through the warm Gulf waters and eventually making landfall near Mobile, Alabama. A number of experiments were carried out on a multi-level primitive equation (PE) model, a one-level PE model, and a higher resolution multi-level PE model (T63) in order to simulate the progression and intensification from a wave to a hurricane over a specified limited domain. Although previous experiments using this model with its comprehensive physical processes exhibit a reasonable predictive rate of success, the early experiments during this case study produced poor results. The most successful forecasts will be examined carefully and discussed entirely. There is strong indication that for mesoscale features a higher resolution model would achieve better results. / Typescript. / "Submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science." / Advisor: T. N. Krishnamurti, Professor Directing Thesis. / Includes bibliographical references (leaves 165-167).

A significant minority of at risk residents in the USA do not evacuate from an approaching hurricane when they are advised to by local authorities. This causes unnecessary deaths, injuries and suffering; a situation which is likely to intensify under predicted climate change. This thesis argues that non-evacuation is not fully understood as both the academic and policy framing of the decision to evacuate is centred around technical and socio-economic approaches which assume that risk is objective and “rational” people will evacuate if they have the material means to do so. This thesis argues that rationalities are differentiated and decision making is also a process which is influenced by members of a social network. Therefore there is a need for a more constructivist approach to get a deeper understanding of the subjectivity of hurricane evacuation. In this thesis, the theory of reasoned action is used as the framework of decision making as it highlights the importance of subjective attitudes and subjective norms on behaviour. A mixed methods case study of Hurricane Ike is used to analyse the evacuation of Galveston Island, Texas. Firstly a “Q” study was undertaken with 40 residents of Galveston, which unveiled four distinct subjective evacuation attitudes, demonstrating that people understand hurricane risk in different ways which impact on their decision to evacuate. The results of the Q study were then used to parameterise an agent based model, designed to investigate community level evacuation. The model showed that it is possible to explain island-level evacuation through the combination of subjective evacuation attitudes and subjective norms which can interact to produce emergent, or unpredicted behaviour. This thesis represents a fundamental challenge to positivist approaches and clearly demonstrates the value of a more constructivist approach to understanding hurricane evacuation based on subjective evacuation attitudes and subjective norms.

This thesis presents a technique for storm surge forecasting. Storm surge is the water that is pushed toward the shore by the force of the winds swirling around the storm. This advancing surge combines with the normal tides to create the hurricane storm tide, which can increase the mean water level by almost 20 feet. Numerical modeling is an important tool used for storm surge forecast. Numerical model ADCIRC (Advanced Circulation model; Luettich et al, 1992) is used in this thesis for simulating hurricanes. A statistical technique, EST (Empirical Statistical Technique) is used to generate life cycle storm surge values from the simulated hurricanes. These two models have been applied to Freeport, TX. The thesis also compares the results with the model SLOSH (Sea, Lake, and Overland Surges from Hurricanes), which is currently used for evacuation and planning. The present approach of classifying hurricanes according to their maximum sustained winds is analyzed. This approach is not found to applicable in all the cases and more research needs to be done. An alternate approach is suggested for hurricane storm surge estimation.