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Solar radiation in the visible spectrum can penetrate through snowpack to a considerable depth, which is named as the euphotic depth in snow. If the snow depth is no greater than the euphotic depth, the surface albedo is greatly affected by the underlying surface. This study defines the euphotic depth as the depth where the residual solar radiation in snow began to be less than 1.0 W m−2 and provides a convenient approach to estimate it. A two-stream, multilayer radiation penetration model (SNow, ICe, and Aerosol Radiation) was applied to predict the vertical profiles of solar radiation based on regular measurements of snow pits and downward solar radiation at Col de Porte (CDP), France from 1993 to 2011. The euphotic depth in snow at CDP exhibits clear seasonal variations, with median values in winter months of 6.8, 8.8, and 10.5 cm, and those in spring remaining nearly on the same level (24.4 and 24.2 cm). The maximum euphotic depth at CDP reached as deep as 78 cm. Further analyses demonstrated that the euphotic depth in snow is related to not only the external initial solar irradiance but also the interior snow extinction coefficient. Stronger illumination and smaller snow extinction coefficients may correspond to greater euphotic depths in snowpack.

The presence of light-absorbing aerosols (LAA) in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consideration. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow–Atmosphere–Soil Transfer (SAST) model, which includes the impacts of LAA on snow. Specifically, the Snow, Ice and Aerosol Radiation (SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot (SASP), Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m−2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and “snow all gone” day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.

On the basis of a simple snow-atmosphere-soil transfer (SAST) model previously developed, this paper presents an improved snow-atmosphere-soil transfer (ISAST) model that has a new numerical scheme and an improved method of layering the snowpack. The new model takes the snow cover temperature and ice content in the snow cover as prognostic variables. This approach, which effectively solves the snow cover temperature distribution when the snow cover is melting or freezing, lessens the iteration time and computation time, which is important for GCM simulation. In this model, the snow cover is divided into three layers (ISAST3) or seven layers (ISAST7). The simulation results obtained using the ISAST7 model agree well with observations in terms of snow depth, snow equivalent water and snow cover lifetime at five Russian sites. The new ISAST model has better simulation capacity for snow cover than the previous SAST model. When the snow cover is deep, the simulation of the ISAST7 model is better than that of the ISAST3 model. Testing shows that our ISAST model is approximately 20% faster than the SAST model.

A vertical one-dimensional numerical model for heat transferring within the near-surface snow layer of the Antarctic Ice Sheet was developed based on simplified parameterizations of associated physical processes for the atmosphere, radiation, and snow/ice systems. Using the meteorological data of an automatic weather station (AWS) at Dome A (80°22′S, 70°22′E), we applied the model to simulate the seasonal temperature variation within a depth of 20 m. Comparison of modeled results with observed snow temperatures at 4 measurement depths (0.1, 1, 3, 10 m) shows good agreement and consistent seasonal variations. The model results reveal the vertical temperature structure within the near-surface snow layer and its seasonal variance with more details than those by limited measurements. Analyses on the model outputs of the surface energy fluxes show that: 1) the surface energy balance at Dome A is characterized by the compensation between negative net radiation and the positive sensible fluxes, and 2) the sensible heat is on average transported from the atmosphere to the snow, and has an evident increase in spring. The results are considered well representative for the highest interior Antarctic Plateau.

Snow albedo is an important factor influencing the snow surface energy budget and snow melting, yet uncertainties remain in the calculation of spectrally resolved snow surface albedo because the spectral composition (visible versus near infrared) of the incident solar radiation is seldom available. The influence of the spectral composition of the incoming solar radiation on the snow surface albedo, snow surface energy budget, and final snow ablation is investigated through sensitivity experiments of four snow seasons at two open sites in the Alps by using a multi-layer Snow-Atmosphere-Soil-Transfer scheme (SAST). Since the snow albedo in the near infrared (NIR) spectral band is significantly lower than that in the visible (VIS) band, and almost the entire NIR part of the solar radiation is absorbed in the top layer of the snow pack, given a fixed amount of incoming solar radiation, a lower VIS/NIR ratio implies that more NIR radiation is reaching the ground surface and more is absorbed by the top layer of the snow pack, therefore, speeding up the snow melting and increasing the surface runoff, although a lesser part of the solar radiation in the visible band is transmitted into and trapped by the sub-layer of the snow pack. The above VIS/NIR ratio effect of the incoming solar radiation can result in a couple of days difference in the timing of snow ablation and it becomes more significant in late spring when the total solar radiation is intensified with seasonal evolution. Snow aging also slightly intensifies this VIS/NIR ratio effect.

We developed and evaluated a three-layer snow model for application in general circulation models. This one-dimensional snow model has many features of the detailed physically based model SNTHERM, yet is computationally much simpler. We have also extended the point model to vegetated areas using the parameter-ization concepts of the Biosphere-Atmosphere Transfer Scheme (BATS). Results of model applications for two types of vegetated fields - a short grassland in the French Alps and an old aspen forest in the southern study area of BOREAS - were presented. The results, on one hand, indicate the suitability of the model structure and parameter setting; on the other hand, the results explore the limitation of using 'point' field observations to evaluate an area model.

This paper presents a simple snow model for climate studies. There are three prognostic variables in the model: specific enthalpy, snow water equivalent, and snow depth. This model is developed on the basis of up-to-date comprehensive and complex snow schemes but with substantial simplification and improvement. The effects of vapor on snow processes have been analyzed in the paper. On the basis of the analysis, vapor's contribution in the mass equation is eliminated, and an effective conductivity coefficient, which includes a simple parameterization for vapor diffusion effect, is used to describe its contribution in the energy equation to simplify the computation. Specific enthalpy is used in the energy balance equation. Using enthalpy rather than temperature greatly simplifies the computational procedure for the phase change calculation in the snow process. This approach, along with a one-step test scheme that avoids iterations, saves computational time, which is important for general circulation model (GCM) simulations. The layering scheme is a critical part in the model. After many tests, it is found that three layers with an appropriate layering scheme are adequate for most cases. Preliminary testing using Russian and French snow data shows that the three-layer model is able to produce reasonable and consistent results.