Modeling Snow Depth for Improved Simulation of Snow–Vegetation–Atmosphere Interactions

John E. Strack Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Glen E. Liston Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Roger A. Pielke Sr. Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

The presence of snow and its relationship to surrounding vegetation significantly impacts the surface energy balance. For accurate atmospheric model simulations, the degree to which a snowpack can cover vegetation must be realistically represented. Both vegetation height and snow depth must be reasonably known to determine the amount of masking.

The Regional Atmospheric Modeling System/Land Ecosystem–Atmosphere Feedback, version two (RAMS/ LEAF-2) snow model was modified to simulate snow depth in addition to snow water equivalent and was driven offline with observed atmospheric forcing data. The model was run for five of the Boreal Ecosystem–Atmosphere Study (BOREAS) surface mesonet stations over the 1995/96 winter. The time evolution of simulated snow depth was compared with the observed snow depth. Averaged over the winter, the modeled snow depth at the four low-wind stations was within 0.09 m of the observations, and the average percent error was 27%, while the one wind-blown station was considerably worse. The average depth error at all five stations was ±0.08 m. This is shown to be sufficient to reasonably account for the surface energy balance effects of vegetation protruding through the snow.

Corresponding author address: John E. Strack, Department of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523-1371. Email: jstrack@atmos.colostate.edu

Abstract

The presence of snow and its relationship to surrounding vegetation significantly impacts the surface energy balance. For accurate atmospheric model simulations, the degree to which a snowpack can cover vegetation must be realistically represented. Both vegetation height and snow depth must be reasonably known to determine the amount of masking.

The Regional Atmospheric Modeling System/Land Ecosystem–Atmosphere Feedback, version two (RAMS/ LEAF-2) snow model was modified to simulate snow depth in addition to snow water equivalent and was driven offline with observed atmospheric forcing data. The model was run for five of the Boreal Ecosystem–Atmosphere Study (BOREAS) surface mesonet stations over the 1995/96 winter. The time evolution of simulated snow depth was compared with the observed snow depth. Averaged over the winter, the modeled snow depth at the four low-wind stations was within 0.09 m of the observations, and the average percent error was 27%, while the one wind-blown station was considerably worse. The average depth error at all five stations was ±0.08 m. This is shown to be sufficient to reasonably account for the surface energy balance effects of vegetation protruding through the snow.

Corresponding author address: John E. Strack, Department of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523-1371. Email: jstrack@atmos.colostate.edu

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