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Hurricane Imaging Radiometer (HIRAD) tropical rainfall retrievals
- Date Issued:
- 2019
- Abstract/Description:
- The Hurricane Imaging Radiometer (HIRAD) is an airborne passive microwave remote sensor, developed to measure wind speed and rain rate in hurricanes. This dissertation concerns the development of a signal processing algorithm to infer tropical rainfall from HIRAD radiance (brightness temperature, Tb) measurements.The basis of the rain rate retrieval algorithm is an improved forward microwave radiative transfer model (RTM) that incorporates the HIRAD multi-antenna-beam geometry, and uses semi-empirical coefficients derived from an airborne experiment that occurred in the Gulf of Mexico off Tampa Bay in 2013. During this flight, HIRAD observed a squall line of thunderstorms simultaneously with an airborne meteorological radar (High Altitude Wind and Rain Profiler, HIWRAP), located on the same airplane. Also, ground based NEXRAD radars from the National Weather Service (located at Tampa and Tallahassee) provided high resolution simultaneous rain rate measurements.Using NEXRAD rainfall as the surface truth input to the HIRAD RTM, empirical rain microwave absorption coefficients were tuned to match the measured brightness temperatures. Also, the collocated HIWRAP radar reflectivity (dBZ) measurements were cross correlated with NEXRAD to derive the empirical HIWRAP radar reflectivity to rain rate relationship. Finally, the HIRAD measured Tbs were input to the HIRAD rain retrieval algorithm to derive estimates of rain rate, which were validated using the independent HIWRAP measurements of rain rate.
Title: | Hurricane Imaging Radiometer (HIRAD) tropical rainfall retrievals. |
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Name(s): |
Alasgah, Abdusalam, Author Jones, W Linwood, Committee Chair Wahid, Parveen, Committee Member Mikhael, Wasfy, Committee Member Gong, Xun, Committee Member Zec, Josko, Committee Member University of Central Florida, Degree Grantor |
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Type of Resource: | text | |
Date Issued: | 2019 | |
Publisher: | University of Central Florida | |
Language(s): | English | |
Abstract/Description: | The Hurricane Imaging Radiometer (HIRAD) is an airborne passive microwave remote sensor, developed to measure wind speed and rain rate in hurricanes. This dissertation concerns the development of a signal processing algorithm to infer tropical rainfall from HIRAD radiance (brightness temperature, Tb) measurements.The basis of the rain rate retrieval algorithm is an improved forward microwave radiative transfer model (RTM) that incorporates the HIRAD multi-antenna-beam geometry, and uses semi-empirical coefficients derived from an airborne experiment that occurred in the Gulf of Mexico off Tampa Bay in 2013. During this flight, HIRAD observed a squall line of thunderstorms simultaneously with an airborne meteorological radar (High Altitude Wind and Rain Profiler, HIWRAP), located on the same airplane. Also, ground based NEXRAD radars from the National Weather Service (located at Tampa and Tallahassee) provided high resolution simultaneous rain rate measurements.Using NEXRAD rainfall as the surface truth input to the HIRAD RTM, empirical rain microwave absorption coefficients were tuned to match the measured brightness temperatures. Also, the collocated HIWRAP radar reflectivity (dBZ) measurements were cross correlated with NEXRAD to derive the empirical HIWRAP radar reflectivity to rain rate relationship. Finally, the HIRAD measured Tbs were input to the HIRAD rain retrieval algorithm to derive estimates of rain rate, which were validated using the independent HIWRAP measurements of rain rate. | |
Identifier: | CFE0007775 (IID), ucf:52379 (fedora) | |
Note(s): |
2019-12-01 Ph.D. Engineering and Computer Science, Electrical and Computer Engineering Doctoral This record was generated from author submitted information. |
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Subject(s): |
HIRAD -- HIWRAP NEXRAD brightness temperature RTM rain rate microwave radiometer |
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Persistent Link to This Record: | http://purl.flvc.org/ucf/fd/CFE0007775 | |
Restrictions on Access: | public 2019-12-15 | |
Host Institution: | UCF |