DocumentCode
2675928
Title
A novel method for estimating offshore wind fields using synthetic aperture radar and meteorological model data
Author
Cameron, Iain D. ; Woodhouse, Iain H. ; Walker, Nick
Author_Institution
Univ. of Edinburgh Edinburgh, Edinburgh
fYear
2007
fDate
23-28 July 2007
Firstpage
3273
Lastpage
3276
Abstract
Synthetic aperture radar (SAR) provides a promising method for offshore wind field estimation, particularly in the context of important for offshore wind farm development. This paper introduces an iterative maximum aposteriori probability (MAP) method for combining meteorological model output with synthetic aperture radar for offshore wind field estimation. The MAP approach is demonstrated for 40 ENVISAT ASAR scenes collected for 2004-2006 over the UK Irish Sea. Both the CMOD4 and CMOD5 geophysical model functions are implemented and retrievals using MAP and a simpler direction based windspeed algorithm are validated against insitu mast observations. The CMOD5 MAP algorithm in particular shows promising results with an estimates on average within 2 observations.
Keywords
atmospheric techniques; data assimilation; iterative methods; maximum likelihood estimation; remote sensing by radar; synthetic aperture radar; wind; wind power; AD 2004 to 2006; CMOD4 geophysical model function; CMOD5 geophysical model function; ENVISAT ASAR data; UK Irish sea; iterative MAP method; maximum aposteriori probability; meteorological model data; offshore wind farm development; offshore wind field estimation; synthetic aperture radar; Backscatter; Information retrieval; Iterative methods; Layout; Meteorology; Radar scattering; Sea surface; Synthetic aperture radar; Wind farms; Wind speed; Maximum Aposteriori Probability; Offshore wind; SAR;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location
Barcelona
Print_ISBN
978-1-4244-1211-2
Electronic_ISBN
978-1-4244-1212-9
Type
conf
DOI
10.1109/IGARSS.2007.4423543
Filename
4423543
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