• DocumentCode
    2200260
  • Title

    Ocean surface wind retrieval from stationary and moving platform marine radar data

  • Author

    Lund, Björn ; Graber, Hans C. ; Horstmann, Jochen ; Terrill, Eric

  • Author_Institution
    RSMAS, Univ. of Miami, Miami, FL, USA
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    2790
  • Lastpage
    2793
  • Abstract
    In this paper we evaluate different methods to retrieve wind information from marine radar data. In contrast to traditional in-situ sensors, marine radar wind data cover a large area and therefore are much less susceptible to air flow distortion by the platform. Unlike previous studies that have been limited to fixed-platform data, this study includes data from a quasi-stationary and moving platform. Images collected with a standard marine HH-polarized X-band radar operating at grazing incidence angle exhibit a single intensity peak in the upwind direction. Marine radar images that are averaged over about 1 min may also show wind streaks, which are usually well-aligned with the mean surface wind direction. Here, we use both phenomena to retrieve wind directional information and compare results to determine the best approach under the given conditions. To retrieve wind speeds, an empirical model function which relates average backscatter intensity to wind speed is developed.
  • Keywords
    atmospheric boundary layer; atmospheric techniques; oceanography; remote sensing by radar; velocity measurement; wind; empirical model function; grazing incidence angle operation; marine HH-polarized X-band radar; marine radar images; mean surface wind direction; moving platform marine radar data; ocean surface wind retrieval; quasistationary platform marine radar data; wind speed retrieval; Backscatter; Radar antennas; Radar imaging; Sea measurements; Standards; Wind speed; Marine radar; sea surface; signal analysis; wind;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6350853
  • Filename
    6350853