There are many calamitous events such as earthquakes, hurricanes, tsunamis etc. that occur suddenly and cause great loss of life, damage, or hardship. Hurricanes cause significant damage to power distribution systems, resulting in prolonged customer outages and excessive delays in the reconstruction efforts. Accordingly, predicting the effects of power outages on the performance of power distribution systems is of major importance to government agencies, utilities, and customers. Unfortunately, the current tools to predict the performance of power distribution systems during catastrophic events are limited in both the performance measures considered, as well as in their ability to model real systems. The main goal of this research is to develop a methodology for simulating hurricanes of different intensity on power distribution systems of small and medium size cities. Our study includes a detailed comparison between the engineering-based and connectivity-based models of power distribution systems, as well as the impact of power re-routing algorithms on the system reliability. Our approach is based on fragility curves that capture the ability of the system to withstand a range of wind speeds. In addition, we develop a multiscale approach that facilitates efficient computation of fragility curves for large cities. With this approach, hurricanes are simulated over small zones of a city and fragility curves are obtained. These are used to estimate the damage for identical zones throughout the city. To validate our techniques, two testbeds, Micropolis and Mesopolis, were used. Micropolis is synthetic model for a small city and Mesopolis for a big city. Obtained results have validated our approach and have shown that they can be used to effectively predict hurricane damage.

The tropical cyclone is a majestic, yet violent atmospheric weather system occurring over tropical waters. Their majesty evolves from the significant range of spatial scales they operate over: from the mesoscale, to the larger synoptic-scale. Their associated violent winds and seas, however, are often the cause of damage and destruction for settlements in their path. Between 10/11/07 and 16/11/07, tropical cyclone Sidr formed and intensified into a category 5 hurricane over the southeast tropical waters of the northern Indian Ocean. Sidr tracked west, then north, during the course of its life, and eventually made landfall on 15/11/07, as a category 4 cyclone near the settlement of Barguna, Bangladesh. The storm affected approximately 2.7 million people in Bangladesh, and of that number 4234 were killed. In this study, the dynamics of tropical cyclone Sidr are simulated using version 2.2.1 of Advanced Weather Research and Forecasting — a non-hydrostatic, two-way interactive, triply-nested-grid mesoscale model. Three experiments were developed examining model sensitivity to ocean-atmosphere interaction; initialisation time; and choice of convective parameterisation scheme. All experiments were verified against analysed synoptic data. The ocean-atmosphere experiment involved one simulation of a cold sea surface temperature, fixed at 10 °C; and simulated using a 15 km grid resolution. The initialisation experiment involved three simulations of different model start time: 108-, 72-, and 48-hours before landfall respectively. These were simulated using a 15 km grid resolution. The convective experiment consisted of four simulations, with three of these using a different implicit convective scheme. The three schemes used were, the Kain-Fritsch, Betts-Miller-Janjic, and Grell-Devenyi ensemble. The fourth case simulated convection explicitly. A nested domain of 5km grid spacing was used in the convective experiment, for high resolution modelling. In all experiments, the Eta-Ferrier microphysics scheme, and the Mellor-Yamada-Janjic planetary boundary layer scheme were used. As verified against available observations, the model showed considerable sensitivity in each of the experiments. The model was found to be well suited for combining ocean-atmosphere interactions: a cool sea surface caused cyclone Sidr to dissipate within 24 hours. The initialisation simulations indicated moderate model sensitivity to initialisation time: variations were found for both cyclone track and intensity. Of the three simulations, an initialisation time 108 hours prior to landfall, was found to most accurately represent cyclone Sidr’s track and intensity. Finally, the convective simulations showed that considerable differences were found in cyclone track, intensity, and structure, when using different convective schemes. The Kain-Fritsch scheme produced the most accurate cyclone track and structure, but the rainfall rate was spurious on the sub-grid-scale. The Betts-Miller-Janjic scheme resolved realistic rainfall on both domains, but cyclone intensity was poor. Of particular significance, was that explicit convection produced a similar result to the Grell-Devenyi ensemble for both model domain resolutions. Overall, the results suggest that the modelled cyclone is highly sensitive to changes in initial conditions. In particular, in the context of other studies, it appears that the combination of convective scheme, microphysics scheme, and boundary layer scheme, are most significant for accurate track and intensity prediction.

Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. James O'Brien, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Jan. 13, 2005). Includes bibliographical references.

Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. Paul Ruscher, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Jan 18, 2005). Includes bibliographical references.

Thesis (M.S.)--University of North Carolina at Wilmington, 2004. / Includes bibliographical references (leaves : 60-61).

Thesis (M.S.)--University of Alabama at Birmingham, 2009. / Title from PDF t.p. (viewed July 21, 2010). Includes bibliographical references (p. 90-93).

Thesis (Ph. D.)--Ohio State University, 2005. / Title from first page of PDF file. Includes bibliographical references (p. 152-162).

Thesis (M.S.)--Florida State University, 2006. / Advisor: Xiaolei Zou, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed June 13, 2006). Document formatted into pages; containsxi, 65 pages. Includes bibliographical references.

Thesis (M.A.)--Baylor University, 2009. / Includes bibliographical references (p. 50-51).

Hurricanes can cause considerable damage along the coastlines of the United States. There are very little data relating hurricanes and sea turtle nesting. Hurricane season (June- November) and sea turtle nesting season, for the study period, (March- September) overlap in Broward County, Florida. This paper examines the relationship between the Hurricane Impact Index (HII) and hatching success of loggerhead sea turtles (Caretta caretta) and HII and washout rate. For ten of the eleven storms studied, there was no significant relationship between HII and hatching success (percent). Tropical Storm Ophelia (2005) showed a significantly higher (p=0.0206) hatching success after the storm’s passing than before the storm’s passing. There was a significant relationship between washout rate and HII (p=0.026).