• DocumentCode
    2698283
  • Title

    Estimation of Surface Net Radiation from Solar Shortwave Radiation Measurements

  • Author

    Wang, Kaicun ; Liang, Shunlin

  • Author_Institution
    Dept. of Geogr., Univ. of Maryland, College Park, MD
  • Volume
    5
  • fYear
    2008
  • fDate
    7-11 July 2008
  • Abstract
    This study develops a method to estimate surface daytime net radiation (Rn) from solar shortwave radiation measurements with help of the conventional meteorological observations and vegetation indices from satellite. Data collected at twenty-two sites in the U.S. and two sites on the Tibetan Plateau (China) from 2000 to 2006 are used to develop and validate the method. The land cover types of the sites vary among desert, semi-desert, croplands, grasslands and forest. The elevations of the sites range from 98 m to 4700 m. The results show that our method estimates Rn accurately. The bias varies from -7.8 W m-2 to 9.7 W m-2 (plusmn3% in relative value) for different sites, while the root mean square error ranges from 12.8 W m-2 to 21 W m-2 (from +5% to +9% in relative value) for different sites with an average of 16.9 W m-2 (+6% relative) for all sites. For all sites the correlation coefficient is about 0.99. The correlation coefficient between the measured and predicted annual abnormal (year-average subtract multi-year average) in daytime Rn is as high as 0.91, indicating that the method can be used to accurately estimate long-term variation in Rn.
  • Keywords
    atmospheric boundary layer; solar radiation; vegetation; AD 2000 to 2006; China; Tibetan Plateau; US; altitude 98 m to 4700 m; meteorological observations; solar shortwave radiation; surface net radiation estimation; vegetation indices; Clouds; Geography; Meteorology; Ocean temperature; Satellites; Sea measurements; Sea surface; Solar radiation; Temperature sensors; Vegetation; Climate; Net radiation; Solar radiation;
  • 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.2008.4780134
  • Filename
    4780134