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A hurricane's destructive nature must be evaluated on as small a scale as possible to reveal the various types of mesoscale circulations that are embedded within the storm's overall wind field. This research develops a technique to estimate small scale surface wind speeds in hurricanes crossing Florida, and thereby identify areas of anomalous winds. Level II Doppler radar data are analyzed onto a high resolution (1 degree radial, 0.5 km gate) grid. An algorithm is developed to estimate the total wind speed from a combination of radial velocity and quality controlled reflectivity. These variables are utilized by identifying the location of the eye and then using radial velocities and an assumed symmetric wind field about the eye to estimate the total wind field over the entire radar scan area. Once the total wind field is computed along a scan, reduction factors are used to transpose the winds at the varying beam altitudes down to the surface using similarity theory. Case studies of Hurricanes Jeanne (2004), Frances (2004), Wilma (2005), Irene (1999), Ivan (2004) and Charlie (2004) are investigated. The success of the algorithm depends greatly on the ability of the Weather Surveillance Radar 88 Doppler (WSR-88D) to sample the velocity data and the ability to properly unfold it. Hurricane Wilma is an example of dry air being entrained into the cyclone, which produces an inadequate concentration of targets to provide a velocity profile, thereby resulting in poor results. Computed wind speeds are compared with National Weather Service (NWS) ASOS observations and independent wind observations supplied by the University of Florida. The estimated winds and those from the two datasets exhibit reasonable agreement; however, additional validation is needed to determine the actual skill of the algorithm. The observed data indicate that gust factors are not optimally estimated by applying a uniform percentage of the total wind speed. Further investigation is needed to determine the proper procedure for estimating wind gusts. Results also show that the algorithm can be used with some confidence to diagnose the damage potential for embedded tornadic cells located within the land-falling hurricane.
A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
Includes bibliographical references.
Henry E. Fuelberg, Professor Directing Dissertation; Anthony Stallins, University Representative; Robert E. Hart, Committee Member; Guosheng Liu, Committee Member; Mark Bourassa, Committee Member.
Florida State University
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