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","Master of Science (M.S.)","College of Engineering and Computer Science","Electrical Engineering and Computer Science","Electrical Engineering"]},{"key":"dc:description.abstract","label":"Abstract","values":["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"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Hurricane Wind Retrieval Algorithm Development For An Airborne Conical Scanning Scatterometer"]}]}],"canonical_facts":{"dc:contributor":["Jones, W. Linwood"],"dc:creator":["Vasudevan, Santhosh"],"dc:description":["If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
","Master of Science (M.S.)","College of Engineering and Computer Science","Electrical Engineering and Computer Science","Electrical Engineering"],"dc:description.abstract":["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"],"dc:format":["application/pdf"],"dc:identifier":["CFE0001477"],"dc:identifier.uri":["https://stars.library.ucf.edu/etd/986"],"dc:language":["English"],"dc:subject":["remote sensing","scatterometer","wind retrieval","radar","hurricane","MLE","IWRAP","Electrical and Computer Engineering","Electrical and Electronics","Engineering"],"dc:title":["Hurricane Wind Retrieval Algorithm Development For An Airborne Conical Scanning Scatterometer"],"dc:type":["Masters Thesis (Open Access)"]},"updated_at":"2026-07-24T05:09:34Z"}