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The Predictability of Winter Snow Cover over the Western United States

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  • A set of model runs was made with the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3 (CCM3) to investigate and help assess the relative roles of snow cover anomalies and initial atmospheric states on the subsequent accumulation and ablation seasons. In order to elucidate the physical mechanisms responsible for the large impact in one case but small impact in the other, two experiments with CCM3 were made that imposed an exaggerated initial snow cover [1-m snow water equivalent (SWE)] over the western U.S. domain. One run was started on 1 December, the other on 1 February. These runs made it clear that the high albedo of snow was the dominant physical process. An additional set of runs with realistic yearly snow anomalies was also made. Results suggest that for runs starting in February (late winter), the initial prescription of snow cover is more important than the initial atmospheric state in determining the subsequent evolution of snow cover. For runs starting in December (early winter), the results are less clear, with neither the initial snow cover nor the initial state of the atmosphere appearing to be the dominant factor. In February, when the sun is relatively high in the sky and days are longer, the albedo effect is a dominant factor; while in December the sun was too low in the sky and days too short for the albedo effect to be important. As the winter season progressed, the subsequent accumulation of snow eliminated the effects of the initial December anomalies.
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  • Marshall, Susan, Robert J. Oglesby, Anne W. Nolin, 2003: The Predictability of Winter Snow Cover over the Western United States. Journal of Climate, 16, 1062–1073.
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  • 16
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  • 7
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  • This work was supported by grants from the National Science Foundation, the NASA Land Surface Hydrology Program and by the NOAA Office of Global Programs. In particular, SM was supported by NSF Grant ATM-9901357, NOAA Grant NA66GPO268, and NASA Grant NAG8-1514 for this study. RJO was supported in this study by NOAA Grant NA66GPO278 and NASA Grant NAG8-1515. AWN was supported by NSF Grant ATM-9900687. Computational resources were provided by the Scientific Computing Division of NCAR under project 35851000. NCAR is supported by the National Science Foundation.
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