• Title of article

    Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments

  • Author/Authors

    Zak?ek، نويسنده , , Klemen and Schroedter-Homscheidt، نويسنده , , Marion، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    8
  • From page
    414
  • To page
    421
  • Abstract
    Some applications, e.g. from traffic or energy management, require air temperature data in high spatial and temporal resolution at two metres height above the ground ( T 2 m ), sometimes in near-real-time. Thus, a parameterization based on boundary layer physical principles was developed that determines the air temperature from remote sensing data (SEVIRI data aboard the MSG and MODIS data aboard Terra and Aqua satellites). The method consists of two parts. First, a downscaling procedure from the SEVIRI pixel resolution of several kilometres to a one kilometre spatial resolution is performed using a regression analysis between the land surface temperature (LST) and the normalized differential vegetation index (NDVI) acquired by the MODIS instrument. Second, the lapse rate between the LST and T 2 m is removed using an empirical parameterization that requires albedo, down-welling surface short-wave flux, relief characteristics and NDVI data. The method was successfully tested for Slovenia, the French region Franche-Comté and southern Germany for the period from May to December 2005, indicating that the parameterization is valid for Central Europe. This parameterization results in a root mean square deviation RMSD of 2.0 K during the daytime with a bias of −0.01 K and a correlation coefficient of 0.95. This is promising, especially considering the high temporal (30 min) and spatial resolution (1000 m) of the results.
  • Keywords
    Air temperature , Land surface temperature , SEVIRI , MODIS
  • Journal title
    ISPRS Journal of Photogrammetry and Remote Sensing
  • Serial Year
    2009
  • Journal title
    ISPRS Journal of Photogrammetry and Remote Sensing
  • Record number

    2228695