Abstract
A comparative study of three snow models with different complexities was carried out to assess how a physically detailed snow model can improve snow modeling within general circulation models. The three models were (a) the U.S. Army Cold Regions Research and Engineering Laboratory Model (SNTHERM), which uses the mixture theory to simulate multiphase water and energy transfer processes in snow layers; (b) a simplified three-layer model, Snow‐Atmosphere‐Soil Transfer (SAST), which includes only the ice and liquid-water phases; and (c) the snow submodel of the Biosphere‐Atmosphere Transfer Scheme (BATS), which calculates snowmelt from the energy budget and snow temperature by the force‐restore method. Given the same initial conditions and forcing of atmosphere and radiation, these three models simulated time series of snow water equivalent, surface temperature, and fluxes very well, with SNTHERM giving the best match with observations and SAST simulation being close. BATS captured the major processes in the upper portion of a snowpack where solar radiation provides the main energy source and gave satisfying results for seasonal periods. Some biases occurred in BATS surface temperature and energy exchange due to its neglecting of liquid water and underestimating snow density. Ice heat conduction, meltwater heat transport, and the melt‐freeze process of snow exhibit strong diurnal variations and large gradients at the uppermost layers of snowpacks. Using two layers in the upper 20 cm and one deeper layer at the bottom to simulate the multiphase snowmelt processes, SAST closely approximated the performance of SNTHERM with computational requirements comparable to those of BATS.
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