Advances in Earth Science ›› 2014, Vol. 29 ›› Issue (1): 56-67. doi: 1001-8166(2014)01-0056-12

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Remote Sensing Estimates of Key Land Surface Vegetation Variables Used in Climate Model: A Review

Chen Hongping 1, Jia Gensuo 1, Feng Jinming 1, Dong Yansheng 3   

  1. 1. Key Laboratory of Regional Climate-Environment Research for Temperate East Asia (RCE-TEA), Chinese Academy of Sciences, Beijing 100029, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China; 3. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
  • Received:2013-06-18 Online:2014-01-10 Published:2014-01-10

Chen Hongping,Jia Gensuo,Feng Jinming,Dong Yansheng. Remote Sensing Estimates of Key Land Surface Vegetation Variables Used in Climate Model: A Review[J]. Advances in Earth Science, 2014, 29(1): 56-67.

Satellite remote sensing data play an important role in the improvement of climate models forcing field, relevant physical parameters and simulation accuracy. At present, there are many years of satellite remote sensing data and a variety of products about land surface attributes. However, the application of satellite remote sensing data to climate models is still very limited. Fully using satellite remote sensing data is important to improving the simulation ability. In the paper, remote sensing estimates methods of three key land surface parameters including Fractional Vegetation Coverage(FVC), Leaf Area Index(LAI)and surface albedo(Albedo)is reviewed and upor downscaling land surface variables in validation process is analyzed. Secondly, taking WRF(Weather Research and Forecasting)model as an example, three parameters in climate model are described. Finally, the key problems of using remote sensing data in climate models are discussed, which comprise the uncertainties and scales of remote sensing estimation parameters and the future direction is prospected.
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