Hurricane Ivan struck the Gulf Coast in September 2004. Ivan was classified as a category five storm on the Saffir-Simpson scale of Hurricane Intensity before it made landfall in the U.S. with winds around 165 miles per hour. Its intensity dropped to a category three as it approached the Gulf Coast. Ivan damaged not only properties and businesses along the coast but inland as well. Heavy rains caused rivers and lakes to overflow their banks and tornadoes spawned by the storm struck Tennessee, Kentucky, Louisiana, and Georgia.The purpose of this research is to examine if hurricane insurance or separate endorsements adequately protects and reimburses owners for their losses and to access public and private responses to natural hazards and disaster mitigation using Gulf Shores, Alabama as a case study. Since fall 2004, many homeowners and business owners have been negotiating with their insurance companies. Owners received some help from the organizations like FEMA and the American Red Cross but these efforts were not enough to recuperate all the damages and losses. This study seeks to place the issues of insurance costs, claims and coverage in Gulf Shores, Alabama within the overall context of natural hazards research using archival sources, observation, questionnaires, and formal and informal interviews as data sources. In light of continuing migration to hurricane prone coastal areas, ever-increasing property values and insurance premiums, and the added risk of increasing hurricane frequency, this research contributes to a better understanding of the role of insurance on natural hazard mitigation and preparedness. / Department of Geography

Thesis: Ph. D., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Civil and Environmental Engineering; and the Woods Hole Oceanographic Institution), 2017 / Cataloged from PDF version of thesis. / Includes bibliographical references. / Waves, currents, and bathymetric change observed along 11 km of the southern shoreline of Martha's Vineyard include storm events, strong tidal flows (> 2 m/s), and an inlet migrating 2.5 km in ~7 years. A field-verified Delft3D numerical model developed for this system is used to examine the hydrodynamics in the nearshore and their effect on the migrating inlet. An initial numerical experiment showed that the observed 700 tidal modulation of wave direction in the nearshore was owing to interactions with tidal currents, and not to depth-induced refraction as waves propagated over complex shallow bathymetry. A second set of simulations focused on the separation of tidal currents from the southeast corner of Martha's Vineyard, showing the positive correlation between flow separation and sediment transport around a curved shoreline. Observations of waves, currents, and bathymetric change during hurricanes were reproduced in a third numerical experiment examining the competition between storm waves, which enhance inlet migration, and strong tidal currents, which scour the inlet and reduce migration rates. The combined field observations and simulations examined here demonstrate the importance of wave and tidal current forcings on morphological evolution at timescales of days to months. / by Julia A. Hopkins. / Ph. D. / Ph.D. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Civil and Environmental Engineering; and the Woods Hole Oceanographic Institution)

This work addresses hurricane preparedness in Escambia County, Florida. It explores preparing for hurricanes as an informal learning process occurring within personal networks and embedded in beliefs, values, and attitudes. Findings reveal that participants learned to prepare from their parents in childhood and improved upon that knowledge through direct experience in adulthood. Later, they passed this knowledge on to their children as well as co-workers. These preparations are embedded in beliefs of self-determination and attitudes of endurance. However, this body of knowledge and their respective practices are not equally accessible to all. Recommendations are provided so local organizations can incorporate local knowledge and practices with preparedness improvement efforts and foster social cohesion as well.

Hurricane hazards result from the combined processes of wind, waves, storm surge, and overwash (Lennon et al., 1996). Predicting the severity of these hazards requires immense effort to quantify the processes and then predict how different coastal regions respond to them. A somewhat simpler, but no less daunting task is to begin to predict the hazards due to potential erosion of barrier islands. A four-part scale has been developed by Sallenger (2000) to provide a framework for understanding how barrier islands might respond during extreme storm events. These four regimes describe how beach and dune elevations interact with surge and wave runup. This study will produce estimates of potential hazards through combining lidar surveys of dune elevation with modeled elevations of storm water levels. Direct measurements of maximum wave heights during hurricanes are rare. We evaluated three simple equations proposed by Kjerfve (1986), Young (1988), and Hsu (1998) to forecast the maximum wave height (Hmax) generated by three 1999 hurricanes. Model results were compared to wave data recorded by the National Oceanic and Atmospheric Administration (NOAA) wave rider buoys. The radius of maximum winds, wind speed, forward velocity, distance from buoy to the storm's eye-wall (r), and buoy's position relative to the quadrant of the storm (Q) were found to have significant and direct roles in evaluating recorded hurricane induced wave heights (H) and thus, were individually examined for each comparison. The implications of the r and Q on H were assessed when determining the overall effectiveness of the modelers' equations. Linear regression analyses tested the accuracy of each modeled prediction of the Hmax, comparing it to the observed wave heights. Three statistical criteria were used to quantify model performance. Hsu's model was the most reliable and useful forecasting technique. Despite the predictive skill of Hsu's model, direct observations of the maximum wave conditions, when available and appropriate, are preferred as inputs for SWAN, a 3rd generation shoaling wave model. Outputs from SWAN are used to calculate the empirical relationships for wave runup. For our test case, pre and post-storm topographies were surveyed as part of a joint USGS-NASA program using lidar technology. These data sets were used to calculate changes in the elevation and location of the dune crest (Dhigh) and dune base (Dlow) for the North Carolina Outer Banks. We hindcast potential coastal hazards (erosional hot spots) using the pre-storm morphology and modeled wave runup and compare those estimates to the measured results from the post-storm survey. Links among the existing topography and spatial variations in wave runup were found to be 95% correlated for the north-south and east-west facing barrier islands. Application of Sallenger's (2000) four-part Storm Impact Scale to the pre-storm Dhigh elevation survey and wave runup extremes (Rhigh and Rlow) were found to accurately predict zones of overwash and showed potential to forecast the inundation regime.

This dissertation investigates the financial health of municipalities in the United States, their margins of response to fiscal shocks, and their exposure and response to climate risk stemming from hurricanes. In Chapter 1, we construct a novel data set on the fiscal position of municipalities in the United States and document a secular decline in their financial health. Our data combines financial data from the Annual Comprehensive Financial Reports (ACFRs) of municipalities along with Census data of their revenue and expenditure cash flows. We find that a large share of municipalities operate with a negative net position---akin to a negative book equity position in the corporate context. We find that most of the decline originates from the accumulation of legacy obligations, i.e., pensions and other post-employment benefits (OPEBs); this is recognized by municipal bond markets through higher credit spreads. While accounting values from the ACFRs are informative, they are based on book valuations which potentially convey limited information about the economic value of assets and liabilities. Thus, we turn to the market valuation of local governments' equity by estimating an SDF that matches the valuation of a wide range of assets in the economy to prices future tax and expenditure claims. Using market prices for tax and expenditure claims, and market valuations of liability positions we find that the market values of equity are highly correlated with the book values. The negative equity position---in terms of book and market values---for some local governments suggests the presence of implicit insurance by the state and federal governments. The deteriorating fiscal position of municipalities across the United States raises questions about fiscal adjustment mechanisms municipalities have at their disposal and the general equilibrium effects of any adjustment taken. In Chapter 2, we utilize quasi-experimental variation in the year of property tax assessments in the state of Connecticut to provide causal evidence of the fiscal adjustment following a large decline in property values after the Great Financial Crisis. We find that local governments adjust tax rates to maintain stable tax revenues; there is no change in public employment levels and limited adjustments of public services. Our micro data on people's location further allows us to causally estimate the migration elasticity to a change in property tax rates. We find evidence of inter-state migration in response to an increase in property tax rates; and no statistically significant response of intra-state migration. Detailed property and location choice data reveal the elasticity of migration with regard to the property tax bill. An increase in the property tax bill by ten percent leads to an average increase in the migration propensity by about 1.5%. Finally, in Chapter 3, I investigate the investment component of local economic growth in municipalities after hurricanes. Using hand collected and web-scraped statutory property tax rate data in the U.S., I find that municipalities respond to hurricane impact by raising tax rates. I find the hike in tax rates is persistent for 3-4 years after hurricane impact. The response is four times larger for major hurricanes compared to minor hurricanes. However, the increase in tax rates is not expected to be large enough to cause significant out-migration after the average hurricane. I supplement these findings with a novel data set of firm facility-level hurricane impact. I find that firms initially decrease investment in the quarter following hurricane impact and increase it in the final quarters of the second year after impact. Taken together, this chapter presents a novel set of stylized facts on government and firm mitigation investment response to hurricane disasters. In particular, the precarious fiscal health of municipalities coupled with increasing costs of mitigating and managing climate risk poses serious questions about optimal policy in assisting local governments vulnerable to climate change.

This dissertation will specifically address the issue of improving the quality of satellite scatterometer retrieved ocean surface vector winds (OVW), especially in the presence of strong rain associated with tropical cyclones. A novel active/passive OVW retrieval algorithm is developed that corrects Ku-band scatterometer measurements for rain effects and then uses them to retrieve accurate OVW. The rain correction procedure makes use of independent information available from collocated multi-frequency passive microwave observations provided by a companion sensor and also from simultaneous C-band scatterometer measurements. The synergy of these active and passive measurements enables improved correction for rain effects, which enhances the utility of Ku-band scatterometer measurements in extreme wind events. The OVW retrieval algorithm is based on the next generation instrument conceptual design for future US scatterometers, i.e. the Dual Frequency Scatterometer (DFS) developed by NASA’s Jet Propulsion Laboratory. Under this dissertation research, an end-to-end computer simulation was developed to evaluate the performance of this active/passive technique for retrieving hurricane force winds in the presence of intense rain. High-resolution hurricane wind and precipitation fields were simulated for several scenes of Hurricane Isabel in 2003 using the Weather Research and Forecasting (WRF) Model. Using these numerical weather model environmental fields, active/passive measurements were simulated for instruments proposed for the Global Change Observation Mission- Water Cycle (GCOM-W2) satellite series planned by the Japanese Aerospace Exploration Agency. Further, the quality of the simulation was evaluated using actual hurricane measurements from the Advanced Microwave Scanning Radiometer and iv SeaWinds scatterometer onboard the Advanced Earth Observing Satellite-II (ADEOS-II). The analysis of these satellite data provided confidence in the capability of the simulation to generate realistic active/passive measurements at the top of the atmosphere. Results are very encouraging, and they show that the new algorithm can retrieve accurate ocean surface wind speeds in realistic hurricane conditions using the rain corrected Ku-band scatterometer measurements. They demonstrate the potential to improve wind measurements in extreme wind events for future wind scatterometry missions such as the proposed GCOM-W2.

Major disasters such as wildfire, tornado, hurricane, tropical storm, flooding cause disruptions in infrastructure systems such as power outage, disruption to water supply system, wastewater management, telecommunication failures, and transportation facilities. Disruptions in electricity infrastructures have negative impacts on sectors throughout a region, including education, medical services, financial, and recreation sectors. In this study, we introduce a novel approach to investigate the factors which can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and utilizing a comprehensive set of county-level data, we have estimated a Generalized Accelerated Failure Time (GAFT) model that accounts for spatial dependence among observations for time to event data. The model fit improved by 12% after considering the effects of spatial correlation in time to event data. Using GAFT model and Hurricane Irma's impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates among different types of power companies: investor-owned power companies, rural and municipal cooperatives; (2) the relationship between the duration of power outage and power system variables; (3) the relationship between the duration of power outage and socioeconomic attributes. The findings of this study indicate that counties with a higher percentage of customers served by investor-owned electric companies and lower median household income, faced power outage for a longer time. This paper identifies the key factors to predict restoration time of hurricane-induced power outages, allowing disaster management agencies to adopt strategies required for restoration process.

No description available.

Long-term omni-directional ambient noise was collected at several sites in the Gulf of Mexico during 2004 and 2005. The Naval Oceanographic Office deployed bottom moored Environmental Acoustic Recording System (EARS) buoys approximately 159 nautical miles south of Panama City, Florida, in water depths of 3200 meters. The hydrophone of each buoy was 265 meters above the bottom. The data duration ranged from 10-14 months. The buoys were located near a major shipping lane, with an estimated 1.5 to 4.5 ships per day passing nearby. The data were sampled at 2500 Hz and have a bandwidth of 10-1000 Hz. Data are processed in eight 1/3-octave frequency bands, centered from 25 to 950 Hz, and monthly values of the following statistical quantities are computed from the resulting eight time series of noise spectral level: mean, median, standard deviation, skewness, kurtosis and coherence time. Four hurricanes were recorded during the summer of 2004 and they have a major impact on all of the noise statistics. Noise levels at higher frequencies (400-950 Hz) peak during extremely windy months (summer hurricanes and winter storms). Standard deviation is least in the region 100-200 Hz but increases at higher frequencies, especially during periods of high wind variability (summer hurricanes). Skewness is positive from 25-400 Hz and negative from 630-950 Hz. Skewness and kurtosis are greatest near 100 Hz. Coherence time is low in shipping bands and high in weather bands, and it peaks during hurricanes. The noise coherence is also analyzed. The 14-month time series in each 1/3- octave band is highly correlated with other 1/3-octave band time series ranging from 2 octaves below to 2 octaves above the band's center frequency. Spatial coherence between hydrophones is also analyzed for hydrophone separations of 2.29, 2.56 and 4.84 km over a 10-month period. The noise field is highly coherent out to the maximum distance studied, 4.84 km. Additionally, fluctuations of each time series are analyzed to determine time scales of greatest variability. The 14-month data show clearly that variability occurs primarily over three time scales: 7-22 hours (shipping-related), 56-282 hours (2-12 days, weather-related) and over an 8-12 month period.

This study examines ten major storms that have affected Louisiana in the last fifty years, beginning with Hurricane Betsy in 1965. The goal is to determine if the nine coastal parishes are prepared adequately for another major hurricane impact. It examines storms that have affected the state physically, in terms of property and ecological damages. It also considers storms that provided non-physical influences, by way of mitigation policy changes and social, economical, ecological, and political policy alterations. The main focus is on the transformations, if any, of social vulnerability in light of emergency preparedness in the areas impacted, particularly along the Louisiana coast. I argue that, while the State has come a long way, Louisiana is not currently prepared adequately to handle another major storm by 2015. Furthermore, I offer recommendations for improvement in preparedness measures for the future.