Thermal Regime of Snow Cover in Winter in The High-Mountainous Part of Elbrus According To Observational Data and Modeling Results

Abstract

Based on the analysis of the results of two measurement episodes in February 2021/22 and calculations using the LSM SPONSOR model, we obtained estimates of the variability of the snow surface thermal balance components and the thermal regime of the snowpack in the ablation zone of the Garabashi glacier on the southern slope of Mount Elbrus at 3850 m above sea level. A quantitative assessment of the sensitivity of the heat balance components to variations in key physical parameters has been performed. It is shown that the optimal value of the emissivity coefficient of snow cover in mountainous areas is 0.98: the absolute error in calculating the radiation temperature of the snow surface at this value does not exceed 1°С, in addition, the model adequately reproduces the thermal regime of deep layers of snow cover. It is also shown that a change in snow density by ±100 kg/m3 can lead to deviations in the temperature of the snow mass by several degrees. This indicates an urgent need to solve the methodological problem of measurements with thermocouples, in which the integrity of the snow mass is inevitably violated. A good agreement between the results of calculations of turbulent sensible heat fluxes in the SPONSOR model with direct measurements (correlation coefficient 0.9) is demonstrated. Based on the measurement data, the fact of a fairly high frequency of high values of turbulent fluxes under conditions of intense radiative heating in combination with high wind speeds was revealed, which apparently turns out to be typical for high-mountain regions in winter (unlike the plains). For cases of strongly stable stratification in the surface layer, the model systematically overestimates the absolute values of heat fluxes. This may be due to the well-known problem of implementing the calculation scheme based on the Monin-Obukhov theory under conditions of temperature inversions. The inaccuracy in determining the snow surface roughness parameter, which in high mountain conditions is characterized by significant temporal variability, can contribute to the error.