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HURRICANE WIND RETRIEVAL ALGORITHM DEVELOPMENT FOR AN AIRBORNE CONICAL SCANNING SCATTEROMETER
Title
HURRICANE WIND RETRIEVAL ALGORITHM DEVELOPMENT FOR AN AIRBORNE CONICAL SCANNING SCATTEROMETER.
Creator
Vasudevan, Santhosh, Jones, Linwood, University of Central Florida
Abstract / Description
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...
Show moreReliable 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
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Date Issued
2006
Identifier
CFE0001477, ucf:47093
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001477
HURRICANE WIND SPEED AND RAIN RATE RETRIEVAL ALGORITHM FOR THE STEPPED FREQUENCY MICROWAVE RADIOMETER
Title
HURRICANE WIND SPEED AND RAIN RATE RETRIEVAL ALGORITHM FOR THE STEPPED FREQUENCY MICROWAVE RADIOMETER.
Creator
Amarin, Ruba, Jones, Linwood, University of Central Florida
Abstract / Description
This thesis presents the development and validation of the Hurricane Imaging Retrieval Algorithm (HIRA) for the measurement of oceanic surface wind speed and rain rate in hurricanes. The HIRA is designed to process airborne microwave brightness temperatures from the NOAA, Stepped Frequency Microwave Radiometer (SFMR), which routinely collects data during NOAA hurricane hunter aircraft flights. SFMR measures wind speeds and rain rates at nadir only, but HIRA will soon be integrated with an...
Show moreThis thesis presents the development and validation of the Hurricane Imaging Retrieval Algorithm (HIRA) for the measurement of oceanic surface wind speed and rain rate in hurricanes. The HIRA is designed to process airborne microwave brightness temperatures from the NOAA, Stepped Frequency Microwave Radiometer (SFMR), which routinely collects data during NOAA hurricane hunter aircraft flights. SFMR measures wind speeds and rain rates at nadir only, but HIRA will soon be integrated with an improved surface wind speed model for expanded utilization with next generation microwave hurricane imagers, such as the Hurricane Imaging Radiometer (HIRad). HIRad will expand the nadir only measurements of SFMR to allow the measurement of hurricane surface winds and rain over a wide swath Results for the validation of HIRA retrievals are presented using SFMR brightness temperature data for 22 aircraft flights in 5 hurricanes during 2003-2005. Direct comparisons with the standard NOAA SFMR empirical algorithm provided excellent results for wind speeds up to 70 m/s. and rain rates up to 50 mm/hr.
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Date Issued
2006
Identifier
CFE0001313, ucf:47024
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001313
AN IMPROVED HURRICANE WIND VECTOR RETRIEVAL ALGORITHM USING SEAWINDS SCATTEROMETER
Title
AN IMPROVED HURRICANE WIND VECTOR RETRIEVAL ALGORITHM USING SEAWINDS SCATTEROMETER.
Creator
Laupattarakasem, Peth, Jones, Linwood, University of Central Florida
Abstract / Description
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...
Show moreOver 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).
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Date Issued
2009
Identifier
CFE0002654, ucf:48242
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002654