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AN IMPROVED HURRICANE WIND VECTOR RETRIEVAL ALGORITHM USING SEAWINDS SCATTEROMETER
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| Title | AN IMPROVED HURRICANE WIND VECTOR RETRIEVAL ALGORITHM USING SEAWINDS SCATTEROMETER |
| Author | Laupattarakasem, Peth
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| Keywords | Remote sensing
wind vector retrieval
hurricane
QuikSCAT
SeaWinds
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| Abstract | 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). |
| Adviser | Jones, W. Linwood
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| Publisher | University of Central Florida |
| Degree | Ph.D.
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| Degree Discipline | School of Electrical Engineering and Computer Science
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| Degree Grantor | Engineering and Computer Science
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| Degree Program | Electrical Engineering PhD
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| Graduation Date | 2009-01-01 |
| Type | Doctoral dissertation
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| Access Level | Public - Allow Worldwide Access
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| Release Date | 2009-05-21 |
| Repository | University Archives
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| Repository Collection | Electronic Theses and Dissertations
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| Identifier | CFE0002654 |
| Access Link | http://purl.fcla.edu/fcla/etd/CFE0002654 |
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