661 resultados para Hurricane Wilma


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General note: Title and date provided by Bettye Lane.

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HURDAT is the main historical archive of all tropical storms and hurricanes in the North Atlantic Basin, which includes the Caribbean Sea and Gulf of Mexico, from 1851 to the present. HURDAT is maintained and updated annually by the National Hurricane Center at Miami, Florida. Today, HURDAT is widely used by research scientists, operational hurricane forecasters, insurance companies, emergency managers and others. HURDAT contains both systematic biases and random errors. Thus, the reanalysis of HURDAT is vital. For this thesis, HURDAT is reanalyzed for the period of 1954-1963. The track and intensity of each existing tropical cyclone in HURDAT is assessed in the light of 21st century understanding and previously unrecognized tropical cyclones are detected and analyzed. The resulting changes will be recommended to the National Hurricane Center Best Track Change Committee for inclusion in HURDAT.

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The main focus of this thesis was to gain a better understanding about the dynamics of risk perception and its influence on people’s evacuation behavior. Another major focus was to improve our knowledge regarding geo-spatial and temporal variations of risk perception and hurricane evacuation behavior. A longitudinal dataset of more than eight hundred households were collected following two major hurricane events, Ivan and Katrina. The longitudinal survey data was geocoded and a geo-spatial database was integrated to it. The geospatial database was composed of distance, elevation and hazard parameters with respect to the respondent’s household location. A set of Bivariate Probit (BP) model suggests that geospatial variables have had significant influences in explaining hurricane risk perception and evacuation behavior during both hurricanes. The findings also indicated that people made their evacuation decision in coherence with their risk perception. In addition, people updated their hurricane evacuation decision in a subsequent similar event.

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Tropical Cyclones are a continuing threat to life and property. Willoughby (2012) found that a Pareto (power-law) cumulative distribution fitted to the most damaging 10% of US hurricane seasons fit their impacts well. Here, we find that damage follows a Pareto distribution because the assets at hazard follow a Zipf distribution, which can be thought of as a Pareto distribution with exponent 1. The Z-CAT model is an idealized hurricane catastrophe model that represents a coastline where populated places with Zipf- distributed assets are randomly scattered and damaged by virtual hurricanes with sizes and intensities generated through a Monte-Carlo process. Results produce realistic Pareto exponents. The ability of the Z-CAT model to simulate different climate scenarios allowed testing of sensitivities to Maximum Potential Intensity, landfall rates and building structure vulnerability. The Z-CAT model results demonstrate that a statistical significant difference in damage is found when only changes in the parameters create a doubling of damage.

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Hurricane Sandy was the largest storm on historical record in the Atlantic Ocean basin with extensive coastal damage caused by large waves and high storm surge. The primary objectives of this thesis are to compare and evaluate three different spatially-varying surface wind fields of Hurricane Sandy to investigate the impact of the differences between the complex wind fields on predictions of the sea surface evolution, and to evaluate the impact of the storm on the hydrodynamics in Great South Bay (GSB) and the discharge of ocean water into the back-barrier bay from overwash over Fire Island. Three different spatially-varying surface wind fields were evaluated and compared to wind observations, including the parametric Holland (1980) model (H80), the parametric Generalized Asymmetric Holland Model (GAHM), and results from the WeatherFlow Regional Atmospheric Modelling System (WRAMS). The winds were used to drive the coupled Delft3D-SWAN hydrodynamic and ocean wave models on a regional grid. The results indicate that the WRAMS wind field produces wave model predictions in the best agreement with significant wave height observations, followed by the GAHM and H80 wind fields and that a regional atmospheric wind model is best for hindcasting hurricane waves and water levels when detailed observations are available, while a parametric vortex model is best for forecasting hurricane sea surface conditions. Using a series of four connected Delft3D-SWAN grids to achieve finer resolution over Fire Island and GSB, a higher resolution WRAMS was used to predict waves and storm surge. The results indicate that strong local winds have the largest influence on water level fluctuations in GSB. Three numerical solutions were conducted with varying extents of barrier island overwash. The simulations allowing for minor and major overwash indicated good agreement with observations in the east end of GSB and suggest that island overwash provided a significant contribution of ocean water to GSB during the storm. Limiting the overwash in the numerical model directly impacts the total discharge into GSB from the ocean through existing inlets. The results of this study indicate that barrier island overwash had a significant impact on the water levels in eastern GSB.