Abstract
Abstract. A snowpack has a profound effect on the hydrology and surface energy conditions of an area through its effects on surface albedo and roughness and its insulating properties. The modeling of a snowpack, soil water dynamics, and the coupling of the snowpack and underlying soil layer has been widely reported. However, the coupled liquid–vapor–air flow mechanisms considering the snowpack effect have not been investigated in detail. In this study, we incorporated the snowpack effect (Utah energy balance snowpack model, UEB) into a common modeling framework (Simultaneous Transfer of Energy, Mass, and Momentum in Unsaturated Soils with Freeze-Thaw, STEMMUS-FT), i.e., STEMMUS-UEB. It considers soil water and energy transfer physics with three complexity levels (basic coupled, advanced coupled water and heat transfer, and finally explicit consideration of airflow, termed BCD, ACD, and ACD-air, respectively). We then utilized in situ observations and numerical experiments to investigate the effect of snowpack on soil moisture and heat transfer with the abovementioned model complexities. Results indicated that the proposed model with snowpack can reproduce the abrupt increase of surface albedo after precipitation events while this was not the case for the model without snowpack. The BCD model tended to overestimate the land surface latent heat flux (LE). Such overestimations were largely reduced by ACD and ACD-air models. Compared with the simulations considering snowpack, there is less LE from no-snow simulations due to the neglect of snow sublimation. The enhancement of LE was found after winter precipitation events, which is sourced from the surface ice sublimation, snow sublimation, and increased surface soil moisture. The relative role of the mentioned three sources depends on the timing and magnitude of precipitation and the pre-precipitation soil hydrothermal regimes. The simple BCD model cannot provide a realistic partition of mass transfer flux. The ACD model, with its physical consideration of vapor flow, thermal effect on water flow, and snowpack, can identify the relative contributions of different components (e.g., thermal or isothermal liquid and vapor flow) to the total mass transfer fluxes. With the ACD-air model, the relative contribution of each component (mainly the isothermal liquid and vapor flows) to the mass transfer was significantly altered during the soil thawing period. It was found that the snowpack affects not only the soil surface moisture conditions (surface ice and soil water content in the liquid phase) and energy-related states (albedo, LE) but also the transfer patterns of subsurface soil liquid and vapor flow.
Highlights
In cold regions, the snowpack has a profound effect on hydrology and surface energy through its change of surface albedo, roughness, and insulating properties (Boone and Etchevers, 2001; Zhang, 2005)
The Yakou case is for demonstrating the validity of the developed STEMMUSUEB model in reproducing the snowpack dynamics
On the basis of the aforementioned STEMMUS-Utah energy balance snowpack model (UEB) coupling framework, the various complexities of vadose zone physics were further implemented as three alternative model versions
Summary
The snowpack has a profound effect on hydrology and surface energy through its change of surface albedo, roughness, and insulating properties (Boone and Etchevers, 2001; Zhang, 2005). In current soil–snow modeling research, soil water and heat transfer are usually not fully coupled, and the vapor flow and airflow are absent (Koren et al, 1999; Niu et al, 2011; Swenson et al, 2012) This may lead to the unrealistic interpretation of the underlying soil physical processes and the snowpack energy budgets (Su et al, 2013; Wang et al, 2017). The abbreviations used in the table are as follows: HT_cond, heat conduction; Advc, advection; LH_phas, latent heat due to phase change; HT_Convect, convective heat due to liquid; SHP, soil physical process; Albedo_SNW_1A, snow albedo 1A, a function of snow age; Albedo_SNW_1B, snow albedo 1B, empirical function considering dry and wet states; Albedo_SNW_1C, snow albedo 1C, a function of extinction coefficient, grain size, and solar zenith angle; Albedo_SNW_2, snow albedo 2, a two-stream radiative transfer solution considering snow aging, solar zenith angle, optical parameters, and impurity; Albedo_SNW_3A, snow albedo 3A, prognostic snow albedo considering aging effect; Albedo_SNW_3B, snow albedo 3B, prognostic snow albedo considering aging effect and vegetation type dependent; Albedo_SNW_3C, snow albedo 3C, prognostic snow albedo considering aging and optical diameter; Albedo_SNW_3D, snow albedo 3D, prognostic snow albedo considering age and microstructure; Albedo_SNW_3E, snow albedo 3E, prognostic snow albedo considering aging effect and dry and wet states; Albedo_SNW_3F, snow albedo 3F, prognostic snow albedo considering aging effect and solar zenith angle; Albedo_SNW_4, snow albedo 4, diagnostic snow albedo considering snow aging, sleet and snowfall fraction, grain diameter, cloud fraction, and solar elevation effect; Density_SNW_1, snow density 1 relying on in situ measurements; Density_SNW_2A, snow density 2A, a function of air temperature; Density_SNW_2B, snow density 2B, a function of extinction coefficient and grain-size; Density_SNW_2C, snow density 2C, a function of old (densification), newly fallen (air temperature) snow pack density, and snow depth; Density_SNW_3, snow density 3, diagnostic density considering wet-bulb temperature; Density_SNW_4A, snow density 4A, prognostic density considering temperature, wind effect, snow compaction, and water and ice states; Density_SNW_4B, snow density 4B, prognostic density considering overburden and thermal metamorphisms; Density_SNW_4C, snow density 4C, prognostic snow density considering snow compaction and settling; Density_SNW_4D, snow density 4D, prognostic snow density considering snow compaction and wind-induced densification; Density_SNW_4E, snow density 4E, prognostic snow density considering snow compaction, settling, and vapor transfer; Density_SNW_4F, snow density 4F, prognostic density, a function of wind speed and air temperature; Density_SNW_4G, Snow density 4G, prognostic density, a function of stress state and microstructure; Density_SNW_4H, Snow density 4H, prognostic density considering snow temperature
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