Coverart for item
The Resource A wind and rain backscatter model derived from AMSR and SeaWinds data, by Seth N. Nielsen

A wind and rain backscatter model derived from AMSR and SeaWinds data, by Seth N. Nielsen

Label
A wind and rain backscatter model derived from AMSR and SeaWinds data
Title
A wind and rain backscatter model derived from AMSR and SeaWinds data
Statement of responsibility
by Seth N. Nielsen
Creator
Subject
Genre
Language
eng
Summary
The SeaWinds scatterometers aboard the QuikSCAT and ADEOS II satellites were originally designed to measure wind vectors over the ocean by exploiting the relationship between wind-induced surface roughening and the normalized radar backscatter cross-section. Recently, an algorithm for simultaneously retrieving wind and rain (SWR) from scatterometer measurements was developed that enables SeaWinds to correct rain-corrupted wind measurements and retrieve rain rate data. This algorithm is based on co-locating Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) and SeaWinds on QuikSCAT data. In this thesis, a new wind and rain radar backscatter model is developed for the SWR algorithm using a global co-located data set with rain data from the Advanced Microwave Scanning Radiometer (AMSR) and backscatter data from the SeaWinds scatterometer aboard the Advanced Earth Observing Satellite 2 (ADEOS II). The model includes the effects of phenomena such as backscatter due to wind stress, atmospheric rain attenuation, and effective rain backscatter. Rain effect parameters of the model vary with integrated rain rate, which is defined as the product of rain height and rain rate. This study accounts for rain height in the model in order to calculate surface rain rate from the integrated rain rate. A simple model for the mean rain height versus latitude and longitude is proposed based on AMSR data and methods of incorporating this model into the SWR retrieval process are developed. The performance of the new SWR algorithm is measured by comparison of wind vectors and rain rates to the previous SWR algorithm, AMSR rain rates, and NCEP numerical weather prediction winds. The new SWR algorithm produces accurate rain estimates and detects rain with a low false alarm rate. The wind correction capabilities of the SWR algorithm are effective at correcting rain-induced inaccuracies. A qualitative comparison of the wind and rain retrieval for Hurricane Isabel demonstrates these capabilities
Cataloging source
UPB
Degree
M.S.
Dissertation year
2007
Granting institution
Brigham Young University. Dept. of Electrical and Computer Engineering
Illustrations
illustrations
Index
no index present
Literary form
non fiction
Nature of contents
  • bibliography
  • theses
Label
A wind and rain backscatter model derived from AMSR and SeaWinds data, by Seth N. Nielsen
Link
http://hdl.lib.byu.edu/1877/etd1979
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. 53-55)
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Dimensions
cm.
Extent
xx, 59 p.
Media category
unmediated
Media MARC source
rdamedia
Other physical details
ill. (some col.)
System control number
  • UtOrBLW
  • (OCoLC)ocn378696032
Label
A wind and rain backscatter model derived from AMSR and SeaWinds data, by Seth N. Nielsen
Link
http://hdl.lib.byu.edu/1877/etd1979
Publication
Bibliography note
Includes bibliographical references (p. 53-55)
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Dimensions
cm.
Extent
xx, 59 p.
Media category
unmediated
Media MARC source
rdamedia
Other physical details
ill. (some col.)
System control number
  • UtOrBLW
  • (OCoLC)ocn378696032

Library Locations

Processing Feedback ...