• DocumentCode
    483927
  • Title

    A Study on Geophysical Model Function Modeling with Water Surface Temperature as One of the Input Parameters

  • Author

    Xie, Xuetong ; Chen, Kehai ; Yu, Wenxian ; Hu, Weidong ; Zeng, Qiming ; Fang, Yu

  • Author_Institution
    P.R. China; Inst. of Remote Sensing & Geographic Inf. Syst., Nat. Univ. of Defense Technol., Beijing
  • Volume
    1
  • fYear
    2008
  • fDate
    7-11 July 2008
  • Abstract
    Geophysical model function is the basis for the wind vector retrieval with scatterometer and a number of models have been developed to operationally retrieve the ocean surface wind in the past three decades. However, none of the operational models ever took the water surface temperature into account in its modeling, which is considered to have some effect on the ocean backscattering, and in turn on the model accuracy. Taking Sea Winds as an example, this paper attempts to develop new geophysical model functions with surface temperature to be taken into account by using its level 2A data and corresponding buoy data. For contrast, two independent models are established for the ocean water and fresh water respectively. The modeling results and analysis indicate that some effect of the surface temperature on backscatter were found for both types of water, but with a larger extent of the temperature effect for fresh water.
  • Keywords
    backscatter; geophysics computing; hydrology; neural nets; ocean temperature; remote sensing; wind; SeaWinds; fresh water temperature; geophysical model function modeling; neural network; ocean backscattering effect; ocean surface wind; scatterometer; water surface temperature; water types; wind vector retrieval; Azimuth; Backscatter; Neural networks; Ocean temperature; Polarization; Radar measurements; Sea surface; Surface resistance; Temperature sensors; Wind speed; Geophysical model function; backscattering coefficient; neural network; temperature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4244-2807-6
  • Electronic_ISBN
    978-1-4244-2808-3
  • Type

    conf

  • DOI
    10.1109/IGARSS.2008.4778878
  • Filename
    4778878