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Volume 21 Issue 4

Jul.  2004

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2004 >  21(4): 529-535

An Empirical Formula to Compute Snow Cover Fraction in GCMs

  • 1.

    State Key Laboratory of Numerical Modeling for Atmospherics Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Laboratory for Climate Study, National Climate Center, Beijing 100081,State Key Laboratory of Numerical Modeling for Atmospherics Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029


doi: 10.1007/BF02915720

  • There exists great uncertainty in parameterizing snow cover fraction in most general circulation models (GCMs) using various empirical formulae, which has great influence on the performance of GCMs.This work reviews the commonly used relationships between region-averaged snow depth (or snow water equivalent) and snow cover extent (or fraction) and suggests a new empirical formula to compute snow cover fraction, which only depends on the domain-averaged snow depth, for GCMs with different horizontal resolution. The new empirical formula is deduced based on the 10-yr (1978-1987) 0.5°× 0.5° weekly snow depth data of the scanning multichannel microwave radiometer (SMMR) driven from the Nimbus-7Satellite. Its validation to estimate snow cover for various GCM resolutions was tested using the climatology of NOAA satellite-observed snow cover.
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    [2] Donglin GUO, Huijun WANG, 2016: Comparison of a Very-fine-resolution GCM with RCM Dynamical Downscaling in Simulating Climate in China, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 559-570.  doi: 10.1007/s00376-015-5147-y
    [3] CHEN Hua, GUO Jing, XIONG Wei, GUO Shenglian, Chong-Yu XU, 2010: Downscaling GCMs Using the Smooth Support Vector Machine Method to Predict Daily Precipitation in the Hanjiang Basin, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 274-284.  doi: 10.1007/s00376-009-8071-1
    [4] Akio KITOH, Masahiro HOSAKA, Yukimasa ADACHI, Kenji KAMIGUCHI, 2005: Future Projections of Precipitation Characteristics in East Asia Simulated by the MRI CGCM2, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 467-478.  doi: 10.1007/BF02918481
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    [6] XIA Kun, WANG Bin, LI Lijuan, SHEN Si, HUANG Wenyu, XU Shiming, DONG Li, LIU Li, 2014: Evaluation of Snow Depth and Snow Cover Fraction Simulated by Two Versions of the Flexible Global Ocean-Atmosphere-Land System Model, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 407-420.  doi: 10.1007/s00376-013-3026-y
    [7] Efang ZHONG, Qian LI, Shufen SUN, Wen CHEN, Shangfeng CHEN, Debashis NATH, 2017: Improvement of a Snow Albedo Parameterization in the Snow-Atmosphere-Soil Transfer Model: Evaluation of Impacts of Aerosol on Seasonal Snow Cover, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 1333-1345.  doi: 10.1007/s00376-017-7019-0
    [8] Shengzhe CHEN, Jiping LIU, Yifan DING, Yuanyuan ZHANG, Xiao CHENG, Yongyun HU, 2021: Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 168-186.  doi: 10.1007/s00376-020-0213-5
    [9] ZENG Heqing, JIA Gensuo, 2013: Impacts of Snow Cover on Vegetation Phenology in the Arctic from Satellite Data, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1421-1432.  doi: 10.1007/s00376-012-2173-x
    [10] Sun Shufen, Li Jingyang, 2001: A Sensitivity Study on Parameterization Scheme of Snow Internal and Interfacial Processes in Snow Model, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 910-928.
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    [12] WANG Aihui, ZENG Xubin, 2009: Improving the Treatment of the Vertical Snow Burial Fraction over Short Vegetation in the NCAR CLM3, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 877-886.  doi: 10.1007/s00376-009-8098-3
    [13] WEN Lijuan, Nidhi NAGABHATLA, Lü Shihua, Shih-Yu WANG, 2013: Impact of Rain Snow Threshold Temperature on Snow Depth Simulation in Land Surface and Regional Atmospheric Models, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1449-1460.  doi: 10.1007/s00376-012-2192-7
    [14] Li Guo ping, Lu Jinghua, Jin Bingling, Bu Nima, 2001: The Effects of Anomalous Snow Cover of the Tibetan Plateau on the Surface Heating, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 1207-1214.  doi: 10.1007/s00376-001-0034-0
    [15] Kunhui YE, Renguang WU, 2017: Autumn Snow Cover Variability over Northern Eurasia and Roles of Atmospheric Circulation, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 847-858.  doi: 10.1007/s00376-017-6287-z
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    • Manuscript History

    Manuscript received: 10 July 2004
    Manuscript revised: 10 July 2004
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    An Empirical Formula to Compute Snow Cover Fraction in GCMs

    • 1. State Key Laboratory of Numerical Modeling for Atmospherics Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Laboratory for Climate Study, National Climate Center, Beijing 100081,State Key Laboratory of Numerical Modeling for Atmospherics Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
    • Manuscript received: 2004-07-10
    • Manuscript revised: 2004-07-10

    Abstract: There exists great uncertainty in parameterizing snow cover fraction in most general circulation models (GCMs) using various empirical formulae, which has great influence on the performance of GCMs.This work reviews the commonly used relationships between region-averaged snow depth (or snow water equivalent) and snow cover extent (or fraction) and suggests a new empirical formula to compute snow cover fraction, which only depends on the domain-averaged snow depth, for GCMs with different horizontal resolution. The new empirical formula is deduced based on the 10-yr (1978-1987) 0.5°× 0.5° weekly snow depth data of the scanning multichannel microwave radiometer (SMMR) driven from the Nimbus-7Satellite. Its validation to estimate snow cover for various GCM resolutions was tested using the climatology of NOAA satellite-observed snow cover.

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