Validation of the Snow Submodel of the Biosphere–Atmosphere Transfer Scheme with Russian Snow Cover and Meteorological Observational Data

Abstract

Snow cover is one of the most important variables affecting agriculture, hydrology, and climate, but detailed measurements are not widely available. Therefore, the effectiveness and validity of snow schemes in general circulation models have been difficult to assess. Using long-term snow cover data from the former Soviet Union, this paper focuses on the validation of the snow submodel in the Biosphere?Atmosphere Transfer Scheme (BATS) using 6 years of data (1978?83) at six stations. Fundamental uncertainties in the datasets limit the accuracy of our assessment of the model?s performance. In the absence of a wind correction for the gauge-measured precipitation and with the standard rain?snow transition criterion (2.2°C), the model gives reasonable simulations of snow water equivalent and surface temperature for all of the six stations and the six winters examined. In particular, the time of accumulation and the end of ablation and the alteration due to aging are well captured. With some simple modifications of the code, the model can also reproduce snow depth, snow cover fraction, and surface albedo. In view of the scheme?s simplicity and efficiency, these results are encouraging. However, if a wind correction is applied to the gauge-measured precipitation, the model shows increased root-mean-square errors in snow water equivalent for all six stations except Tulun. Perhaps, the better agreement without wind correction means that the snow has blown beyond the area of snow measurement, as might be accounted for only by a detailed regional snow?wind distribution model. This study underlines four aspects that warrant special attention: (i) estimation of the downward longwave radiation, (ii) separation of the aging processes for snowpack density and snow surface albedo, (iii) parameterization of snow cover fraction, and (iv) choice of critical temperature for rain?snow transition.