Impact of the snow cover scheme on snow distribution and energy budget modeling over the Tibetan Plateau

  • Zhipeng Xie
  • Zeyong Hu
  • Zhenghui Xie
  • Binghao Jia
  • Genhou Sun
  • Yizhen Du
  • Haiqing Song
Original Paper

Abstract

This paper presents the impact of two snow cover schemes (NY07 and SL12) in the Community Land Model version 4.5 (CLM4.5) on the snow distribution and surface energy budget over the Tibetan Plateau. The simulated snow cover fraction (SCF), snow depth, and snow cover days were evaluated against in situ snow depth observations and a satellite-based snow cover product and snow depth dataset. The results show that the SL12 scheme, which considers snow accumulation and snowmelt processes separately, has a higher overall accuracy (81.8%) than the NY07 (75.8%). The newer scheme performs better in the prediction of overall accuracy compared with the NY07; however, SL12 yields a 15.1% underestimation rate while NY07 overestimated the SCF with a 15.2% overestimation rate. Both two schemes capture the distribution of the maximum snow depth well but show large positive biases in the average value through all periods (3.37, 3.15, and 1.48 cm for NY07; 3.91, 3.52, and 1.17 cm for SL12) and overestimate snow cover days compared with the satellite-based product and in situ observations. Higher altitudes show larger root-mean-square errors (RMSEs) in the simulations of snow depth and snow cover days during the snow-free period. Moreover, the surface energy flux estimations from the SL12 scheme are generally superior to the simulation from NY07 when evaluated against ground-based observations, in particular for net radiation and sensible heat flux. This study has great implications for further improvement of the subgrid-scale snow variations over the Tibetan Plateau.

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Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  • Zhipeng Xie
    • 1
    • 2
  • Zeyong Hu
    • 1
    • 3
  • Zhenghui Xie
    • 4
  • Binghao Jia
    • 4
  • Genhou Sun
    • 1
    • 2
  • Yizhen Du
    • 2
    • 5
  • Haiqing Song
    • 6
  1. 1.Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhouChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.CAS Center for Excellence in Tibetan Plateau Earth SciencesBeijingChina
  4. 4.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  5. 5.State Key Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhouChina
  6. 6.Ecological and Agriculture Meteorology Center of Inner Mongolia Autonomous RegionHuhehaoteChina

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