[1] In mountain regions wind is known to cause snow redistribution. While physically based models of snow redistribution have been developed for flat to gently rolling terrain, extension of these findings to steep terrain has been limited by the complexity of wind fields in such areas. In this study, we applied a nonhydrostatic and compressible atmospheric prediction model to steep alpine topography and compared the results to a fully distributed data set of snow depth estimations. The results show reduced horizontal wind velocity as well as an increasing downward vertical wind velocity over areas with the largest winter accumulation, which are mostly glacierized. We show that the wind velocity normal to the local surface, which should be zero in a nondivergent flow field and is a direct measure of increased or decreased local deposition, is a function of small-scale features of local topography. The correlation between wind fields, snow accumulation, and glacierization suggests that accurate modeling of wind fields over glacierized areas in complex terrain is a key factor for understanding the mass balance distribution of glaciers.Citation: Dadic, R., R. Mott, M. Lehning, and P. Burlando (2010), Wind influence on snow depth distribution and accumulation over glaciers,

Abstract. The spatial distribution of alpine snow covers is characterised by large variability. Taking this variability into account is important for many tasks including hydrology, glaciology, ecology or natural hazards. Statistical modelling is frequently applied to assess the spatial variability of the snow cover. For this study, we assembled seven data sets of high-resolution snow-depth measurements from different mountain regions around the world. All data were obtained from airborne laser scanning near the time of maximum seasonal snow accumulation. Topographic parameters were used to model the snow depth distribution on the catchment-scale by applying multiple linear regressions. We found that by averaging out the substantial spatial heterogeneity at the metre scales, i.e. individual drifts and aggregating snow accumulation at the landscape or hydrological response unit scale (cell size 400 m), that 30 to 91 % of the snow depth variability can be explained by models that are calibrated to local conditions at the single study areas. As all sites were sparsely vegetated, only a few topographic variables were included as explanatory variables, including elevation, slope, the deviation of the aspect from north (northing), and a wind sheltering parameter. In most cases, elevation, slope and northing are very good predictors of snow distribution. A comparison of the models showed that importance of parameters and their coefficients differed among the catchments. A "global" model, combining all the data from all areas investigated, could only explain 23 % of the variability. It appears that local statistical models cannot be transferred to different regions. However, models developed on one peak snow season are good predictors for other peak snow seasons.

Spectral albedo was measured along a 6 km transect near the Allan Hills in East Antarctica. The transect traversed the sequence from new snow through old snow, firn, and white ice, to blue ice, showing a systematic progression of decreasing albedo at all wavelengths, as well as decreasing specific surface area (SSA) and increasing density. Broadband albedos under clear‐sky range from 0.80 for snow to 0.57 for blue ice, and from 0.87 to 0.65 under cloud. Both air bubbles and cracks scatter sunlight; their contributions to SSA were determined by microcomputed tomography on core samples of the ice. Although albedo is governed primarily by the SSA (and secondarily by the shape) of bubbles or snow grains, albedo also correlates highly with porosity, which, as a proxy variable, would be easier for ice sheet models to predict than bubble sizes. Albedo parameterizations are therefore developed as a function of density for three broad wavelength bands commonly used in general circulation models: visible, near‐infrared, and total solar. Relevance to Snowball Earth events derives from the likelihood that sublimation of equatorward‐flowing sea glaciers during those events progressively exposed the same sequence of surface materials that we measured at Allan Hills, with our short 6 km transect representing a transect across many degrees of latitude on the Snowball ocean. At the equator of Snowball Earth, climate models predict thick ice, or thin ice, or open water, depending largely on their albedo parameterizations; our measured albedos appear to be within the range that favors ice hundreds of meters thick.