Volume 43 Issue 6
Dec.  2023
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Article Navigation >  Chinese Journal of Space Science  > 2023  >  43(6): 1135-1149 Open Access
CHEN Jinyan, ZHAO Long, YANG Kun, TIAN Jiaxin, PAN Jinmei, ZHANG Ke. Toward Optimization of Key Parameters in Noah-MP Surface Albedo Using Satellite Remote Sensing Products (in Chinese). Chinese Journal of Space Science, 2023, 43(6): 1135-1149 doi: 10.11728/cjss2023.06.2023-0086
Citation: CHEN Jinyan, ZHAO Long, YANG Kun, TIAN Jiaxin, PAN Jinmei, ZHANG Ke. Toward Optimization of Key Parameters in Noah-MP Surface Albedo Using Satellite Remote Sensing Products (in Chinese). Chinese Journal of Space Science, 2023, 43(6): 1135-1149 doi: 10.11728/cjss2023.06.2023-0086
shu

Toward Optimization of Key Parameters in Noah-MP Surface Albedo Using Satellite Remote Sensing Products

doi: 10.11728/cjss2023.06.2023-0086 cstr: 32142.14.cjss2023.06.2023-0086
  • 1.

    Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715

  • 2.

    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715

  • 3.

    Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084

  • 4.

    State Key Laboratory Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101

  • Received Date: 2023-08-16
  • Rev Recd Date: 2023-11-09
    • Available Online: 2023-12-07
    Abstract
  • Surface albedo is a key factor affecting land-air interactions. The accurate estimate of surface albedo is of great value for improving land model’s capability in hydrothermal simulation. In the Noah-MP (the Noah land surface model with multiple parameterizations) land surface model, estimation of soil albedo mainly relies on a look-up table-based method that characterize the albedo of different soil types with the so-called soil color. However, the soil color has not yet been calibrated at the regional or global scale, which greatly hinders the regional albedo simulation. In addition, the calculation of bare soil albedo is highly sensitive to surface soil moisture. To this end, this study first produces an ensemble of albedo time series with regard to different soil types with data assimilation generated soil moisture as input. Then, the optimal 0.25° soil color for the Tibetan Plateau region were screened by referring MODIS albedo and excluding the impacts from dense vegetation and snow cover. The evaluation results show that the spatial distribution of optimized soil color can reasonably reflect the relationship between soil texture and albedo, and improved Noah-MP albedo estimation in over 70% of the grid cells in the study area.

     

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