### Influence of water vapor diffusion on heat transfer in snow cover

#### A.V. SosnovskiY, N.I. Osokin

Institute of Geography, Russian Academy of Sciences, 119017, Moscow, Staromonetnyi per., 29, Russia, alexandr_sosnovskiy@mail.ru, osokinn@mail.ru
An assessment is made of the influence of water vapor diffusion on heat transfer in snow cover in terms of the mathematical model of heat transfer and taking into account the diffusion of water vapor and sublimation/condensation. It is established that a consideration of the water vapor diffusion increases the penetration depth of the cold front with a temperature of –1 °С by 20–30 and 33–43 % in the snow mass with a density of 250 and 180 kg/m3, respectively. A characteristic of the influence of temperature and snow density on heat transfer due to the water vapor diffusion is provided. When the temperature increases from –25 to –1 °C, the proportion of the heat transfer in snow cover due to the water vapor diffusion increases from 9 to 45 % in the snow with 150 kg/m3, and from 3 to 21 % in the snow with density 400 kg/m3. It was found that the snow density largely determines the value of the coefficient of effective thermal conductivity, whereas meanwhile the penetration depth of the temperature front into the snow weakly depends on snow density. This is due to a slight change of the thermal diffusivity coefficient of the snow with a change in density. Generalized dependencies of the coefficient of thermal conductivity of the snow are presented, and a comparison of them with other formulas is made. The dependence obtained for the highest values of the thermal conductivity coefficient corresponds to the values of thermal conductivity at the snow temperature of –1 °C; the snow temperature lies between –10 and –12 °C for mean values. Calculations from the dependence for the smallest values of the thermal conductivity coefficient largely coincide with estimations based on M. Sturm’s formula of M. Sturm for granular snow.

Keywords: thermal conductivity coefficient, density, snow cover, temperature, mathematical modeling.
DOI: 10.21782/GiPR0206-1619-2019-1(187-193)