• DocumentCode
    1345075
  • Title

    Validating a scatterometer wind algorithm for ERS-1 SAR

  • Author

    Fetterer, Florence ; Gineris, Denise ; Wackerman, Christopher C.

  • Author_Institution
    Naval Res. Lab., Stennis Space Center, MS, USA
  • Volume
    36
  • Issue
    2
  • fYear
    1998
  • fDate
    3/1/1998 12:00:00 AM
  • Firstpage
    479
  • Lastpage
    492
  • Abstract
    The ocean surface wind field is observed from space operationally using scatterometry. The European Space Agency´s (ESAs) ERS-1 satellite scatterometer routinely produces a wind product that is assimilated into forecast models. Scatterometry cannot give accurate wind estimates close to land, however, because the field of view of a spaceborne scatterometer is on the order of 50 km. Side lobe contamination, due to the large contrast in backscatter between land and water, compounds the problem. Synthetic aperture radar (SAR) can provide wind speed and direction estimates on a finer scale, so that high-resolution wind fields can be constructed near shore. An algorithm has been developed that uses the spectral expression of wind in SAR imagery to estimate wind direction and calibrated backscatter to estimate wind strength. Three versions, based on C-band scatterometer algorithms, are evaluated for accuracy in potential operational use. Algorithm estimates are compared with wind measurements from buoys in the Gulf of Alaska, Bering Strait, and off the Pacific Northwest coast by using a data set of 61 near-coincident buoy and ERS-1 SAR observations. Representative figures for the accuracy of the algorithm are ±2 m/s for wind speed and ±37° for wind direction at a 25-km spatial resolution
  • Keywords
    atmospheric techniques; radar imaging; remote sensing by radar; spaceborne radar; synthetic aperture radar; wind; ERS-1; SAR; direction; marine atmosphere; measurement technique; meteorology; radar remote sensing; radar scatterometry; satellite remote sensing; spaceborne radar; surface wind; synthetic aperture radar; validation algorithm; wind; wind speed; Backscatter; Brain modeling; Oceans; Predictive models; Radar measurements; Satellites; Sea surface; Spaceborne radar; Wind forecasting; Wind speed;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.662731
  • Filename
    662731