Reliable ocean wind vector measurements can be obtained using active microwave remote sensing (scatterometry) techniques. With the increase in the number of severe hurricanes making landfall in the United States, there is increased emphasis on operational monitoring of hurricane winds from aircraft. This thesis presents a data processing algorithm to provide real-time hurricane wind vector retrievals (wind speed and direction) from conically scanning airborne microwave scatterometer measurements of ocean surface backscatter. The algorithm is developed to best suit the specifications for the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division's airborne scatterometer – Integrated Wind and Rain Airborne Profiler (IWRAP). Based on previous scatterometer wind retrieval methodologies, the main focus of the work is to achieve rapid data processing to provide real-time measurements to the NOAA Hurricane Center. A detailed description is presented of special techniques used. Because IWRAP flight data were not available at the time of this development, the wind retrieval performance was evaluated using a Monte Carlo simulation, whereby radar backscatter measurements were simulated with instrument and geophysical noise and then used to infer the surface wind conditions in a simulated (numerical weather model) hurricane wind field

This thesis presents the development and validation of the Hurricane Imaging Retrieval Algorithm (HIRA) for the measurement of oceanic surface wind speed and rain rate in hurricanes. The HIRA is designed to process airborne microwave brightness temperatures from the NOAA, Stepped Frequency Microwave Radiometer (SFMR), which routinely collects data during NOAA hurricane hunter aircraft flights. SFMR measures wind speeds and rain rates at nadir only, but HIRA will soon be integrated with an improved surface wind speed model for expanded utilization with next generation microwave hurricane imagers, such as the Hurricane Imaging Radiometer (HIRad). HIRad will expand the nadir only measurements of SFMR to allow the measurement of hurricane surface winds and rain over a wide swath Results for the validation of HIRA retrievals are presented using SFMR brightness temperature data for 22 aircraft flights in 5 hurricanes during 2003-2005. Direct comparisons with the standard NOAA SFMR empirical algorithm provided excellent results for wind speeds up to 70 m/s. and rain rates up to 50 mm/hr.

This dissertation presents the development of a two-dimensional St. Johns River model and the coupling of hydrodynamic and wave models for the simulation of storm tides. The hydrodynamic model employed for calculating tides and surges is ADCIRC-2DDI (ADvanced CIRCulation Model for Shelves, Coasts and Estuaries, Two-Dimensional Depth Integrated) developed by Luettich et al. (1992). The finite element based model solves the fully nonlinear shallow water equations in the generalized wave continuity form. Hydrodynamic applications are operated with the following forcings: 1) astronomical tides, 2) inflows from tributaries, 3) meteorological effects (winds and pressure), and 4) waves (wind-induced waves). The wave model applied for wind-induced wave simulation is the third-generation SWAN (Simulating WAves Nearshore), applicable to the estimation of wave parameters in coastal areas and estuaries. The SWAN model is governed by the wave action balance equation driven by wind, sea surface elevations and current conditions (Holthuijsen et al. 2004). The overall work is comprised of three major phases: 1) To develop a model domain that incorporates the entire East Coast of the United States, Gulf of Mexico and Caribbean Sea, while honing in on the St. Johns River area; 2) To employ output from the SWAN model with the ADCIRC model and produce a uni-directional coupling of the two models in order to investigate the effects of the wave radiation stresses; 3) To couple the ADCIRC model with the SWAN model to describe the complete interactions of the two physical processes. Model calibration and comparisons are accomplished in three steps. First, astronomical tide simulation results are calibrated with historical NOS (National Ocean Service) tide data. Second, overland and riverine flows and meteorological effects are included, and computed river levels are compared with the historical NOS water level data. Finally, the storm tides generated by Hurricane Floyd are simulated and compared with historical data. This research results in a prototype for real-time simulation of tides and waves for flash flood and river-stage forecasting efforts of the NWS Forecasting Centers that border coastal areas. The following two main conclusions are reported: 1) regardless of whether one uses uni-coupling or coupling, wind-induced waves result in an approximately 10 – 15 % higher peak storm tide level than without any coupling; and 2) the wave-current interaction described by the coupling model results in decreasing peaks and increasing troughs in the storm tide hydrograph. Two main corollary conclusions are also drawn from a 122-day hindcast for the period spanning June 1 – October 1, 2005. First, wind forcing for the St. Johns River is equal to or greater than that of astronomic tides and generally supersedes the impact of inflows, while pressure variations have a minimal impact. Secondly, water levels inside the St. Johns River depend on the wind forcings in the deep ocean; however, if one applies an elevation hydrograph boundary condition from a large-scale domain model to a local-scale domain model the results are highly accurate.

Over the last three decades, microwave remote sensing has played a significant role in ocean surface wind measurement, and several scatterometer missions have flown in space since early 1990's. Although they have been extremely successful for measuring ocean surface winds with high accuracy for the vast majority of marine weather conditions, unfortunately, the conventional scatterometer cannot measure extreme winds condition such as hurricane. The SeaWinds scatterometer, onboard the QuikSCAT satellite is NASA's only operating scatterometer at present. Like its predecessors, it measures global ocean vector winds; however, for a number of reasons, the quality of the measurements in hurricanes are significantly degraded. The most pressing issues are associated with the presence of precipitation and Ku-band saturation effects, especially in extreme wind speed regime such as tropical cyclones (hurricanes and typhoons). Under this dissertation, an improved hurricane ocean vector wind retrieval approach, named as Q-Winds, was developed using existing SeaWinds scatterometer data. This unique data processing algorithm uses combined SeaWinds active and passive measurements to extend the use of SeaWinds for tropical cyclones up to approximately 50 m/s (Hurricane Category-3). Results show that Q-Winds wind speeds are consistently superior to the standard SeaWinds Project Level 2B wind speeds for hurricane wind speed measurement, and also Q-Winds provides more reliable rain flagging algorithm for quality assurance purposes. By comparing to H*Wind, Q-Winds achieves ~9% of error, while L2B-12.5km exhibits wind speed saturation at ~30 m/s with error of ~31% for high wind speed ( > 40 m/s).

An electromagnetic model is developed for predicting the microwave blackbody emission from the ocean surface over a wide range of frequencies, incidence angles, and wind vector (speed and direction) for both horizontal and vertical polarizations. This ocean surface emissivity model is intended to be incorporated into an oceanic radiative transfer model to be used for microwave radiometric applications including geophysical retrievals over oceans. The model development is based on a collection of published ocean emissivity measurements obtained from satellites, aircraft, field experiments, and laboratory measurements. This dissertation presents the details of methods used in the ocean surface emissivity model development and comparisons with current emissivity models and aircraft radiometric measurements in hurricanes. Especially, this empirically derived ocean emissivity model relates changes in vertical and horizontal polarized ocean microwave brightness temperature measurements over a wide range of observation frequencies and incidence angles to physical roughness changes in the ocean surface, which are the result of the air/sea interaction with surface winds. Of primary importance are the Stepped Frequency Microwave Radiometer (SFMR) brightness temperature measurements from hurricane flights and independent measurements of surface wind speed that are used to define empirical relationships between C-band (4 - 7 GHz) microwave brightness temperature and surface wind speed. By employing statistical regression techniques, we develop a physical-based ocean emissivity model with empirical coefficients that depends on geophysical parameters, such as wind speed, wind direction, sea surface temperature, and observational parameters, such as electromagnetic frequency, electromagnetic polarization, and incidence angle.

This dissertation presents results for an end-to-end computer simulation of a new airborne microwave remote sensor, the Hurricane Imaging Radiometer, HIRAD, which will provide improved hurricane surveillance. The emphasis of this research is the retrieval of hurricane-force wind speeds in the presence of intense rain and over long atmospheric slant path lengths that are encountered across its wide swath. Brightness temperature (Tb) simulations are performed using a forward microwave radiative transfer model (RTM) that includes an ocean surface emissivity model at high wind speeds developed especially for HIRAD high incidence angle measurements and a rain model for the hurricane environment. Also included are realistic sources of errors (e.g., instrument NEDT, antenna pattern convolution of scene Tb, etc.), which are expected in airborne hurricane observations. Case studies are performed using 3D environmental parameters produced by numerical hurricane models for actual hurricanes. These provide realistic 'nature runs' of rain, water vapor, clouds and surface winds from which simulated HIRAD Tb's are derived for various flight tracks from a high altitude aircraft. Using these simulated HIRAD measurements, Monte Carlo retrievals of wind speed and rain rate are performed using available databases of sea surface temperatures and climatological hurricane atmospheric parameters (excluding rain) as a priori information. Examples of retrieved hurricane wind speed and rain rate images are presented, and comparisons of the retrieved parameters with the numerical model data are made. Statistical results are presented over a broad range of wind and rain conditions and as a function of path length over the full swath.

The magnitude of damage caused to the United States (US) coast due to hurricanes has increased significantly in the last decade. During the period 2004-2005, the US experienced seven of the costliest hurricanes in the country's history (NWS TPC-5, 2007) leading to an estimated loss of ~ $158 billion. The present method for predicting hurricane losses, HAZUS (HAZard US), is solely based on hurricane hazard and damage caused to building envelopes only and not to structural systems (Vickery et al., 2006). This method does not take into account an intermediate step that allows for better damage estimates, which is structural response to the hazards that in turn can be mapped to the damage. The focus of this study was to quantify the uncertainty in response of structures to the hurricane hazards associated with hurricanes from performance based engineering perspective. The study enumerates hazards associated with hurricanes events. The hazards considered can be quantified using a variety of measures, such as wind speed intensities, wave and surge heights. These hazards are quantified in terms of structural loads and are then applied to a structural system. Following that, structural analysis was performed to estimate the response from the structural system for given loads. All the possible responses are measured and they are fitted with suitable probability distribution to estimate the probability of a response. The response measured then can be used to understand the performance of a given structure under the various hurricane loads. Dynamic vs. static analysis was performed and results were compared. This will answer a few questions like, if there is any need to do both static and dynamic analysis and how hurricane loads affect the structural material models. This being an exploratory study, available resources, research, and models were used. For generation of annual or extreme values of hazard, various available wind speed, storm surge, and wave height models were studied and evaluated. The wind field model by Batts et al. (1980) was selected for generation of annual wind speed data. For calculation of maximum storm surge height, the Sea, Lake Overland Surges from Hurricane (SLOSH, Jelesnianski et al., 1992) program was used. Wave data was acquired from a National Oceanic and Atmospheric Administration (NOAA) database. The (extreme or annual) wind speed, surge height, and wave height generated were then fitted by suitable probability distributions to find the realizations of hazards and their probabilities. The distribution properties were calculated, correlations between the data were established, and a joint probability distribution function (PDF) of the parameters (wind speed, wave height, and storm surge) was generated. Once the joint distribution of extreme loads was established, the next step was to measure the dynamic response of the structural system to these hazards. To measure the structural response, a finite element model of three-story concrete frame were constructed. Time histories of wind load were generated from wind net pressure coefficients recorded in a wind tunnel test (Main and Fritz, 2006). Wave load time histories were generated using laboratory basin test (Hawke's et al., 1993) wave height time history data and were converted into wave loads using Bernoulli's equation. Surge height was treated as a hydrostatic load in this analysis. These load time histories were then applied to the finite element model and response was measured. Response of the structural system was measured in terms of the mean and maximum displacements recorded at specific nodes of model. Response was calculated for loads having constant mean wind speed and surge/wave and different time histories. The dominant frequency in the wind load time histories was closer to the natural frequency of the structural model used than the dominant frequency in the wave height time histories. Trends in the response for various combinations of mean wind speed, wave height, and surge heights were analyzed. It was observed that responses are amplified with increase in the mean wind speed. Less response was measured for change in mean surge/wave height as the tributary area for wave forces was less compared to wind force. No increase in dynamic amplification factor was observed for increase in force time histories case.

The intent of this thesis is to analyze the racial attitudes of residents in the Orlando MSA towards Puerto Rican migrants that have moved as a result of Hurricane Maria and analyze the effects these attitudes may have on racial residential segregation in Central Florida. As the state with the third largest population of Latinos, Florida's residential landscape continues to be uniquely formed by a diverse, and markedly Latino, population. Florida's location in relation to South American and Caribbean countries has made it an opportune destination for immigrants and refugees. Therefore, it came as no surprise that when Hurricane Maria hit Puerto Rico in late 2017, thousands of Puerto Ricans sought refuge in Florida. This thesis examines racial attitudes towards this group of Puerto Rican migrants and the ways in which they could potentially affect neighborhood demographics. The study proceeds by collecting survey responses from participants living in the Orlando areas being analyzed. The survey asks participants about their general views of Puerto Rican migrants, it tests their knowledge of racial residential patterns in Orlando, and it analyzes their neighborhood preferences using a show card method.

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