Simulation of Snow Mass and Extent in Global Climate Models
Zong-Liang Yang1, Robert E. Dickinson1, M. Shaikh1, Xiaogang Gao2,
Roger C. Bales2, Soroosh Sorooshian2, and Jiming Jin3
An evaluation of the Biosphere-Atmosphere Transfer Scheme (BATS) snow sub-model was done,
both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Com-
munity Climate Model (CCM). We have evaluated, in the stand-alone mode, the performance of
BATS parameterizations at local scales using ground-based observations from the former Soviet
Union and from Mammoth Mountain, California. The BATS snow scheme reproduces the seasonal
evolution of snow water equivalent in both sites, and the results compare well with those from a
more complex, physically based model (SNTHERM). In the coupled mode, we have evaluated the
modeled precipitation, temperature, and snow cover extent from BATS as linked to the NCAR CCM
using available observations. The coupled models capture the broad pattern of seasonal and geo-
graphical distribution of snow cover, with better performance in the Eurasian than in the North
American continent. The poor simulations of snow variables coincide with poor simulations of sur-
face air temperature and precipitation, primarily due to lack of realism in the model topography.
Because of the importance of snow for correct climate simulations, it is necessary to determine what
level of complexity of snow models is adequate for general circulation models (GCMs) and what
snow properties need to be simulated. Several features of process-level snowmelt models could be
used to help capture sub-grid scale variability and improve snowmelt simulations.
1 Institute of Atmospheric Physics, University of Arizona, Tucson, Arizona 85721, USA
2 Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721,
USA
23 Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080, China
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