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The effective thermal conductivity of snow, keff, is a critical variable which determines the temperature gradient in the snowpack and heat exchanges between the ground and the atmosphere through the snow. Its accurate knowledge is therefore required to simulate snow metamorphism, the ground thermal regime, permafrost stability, nutrient recycling and vegetation growth. Yet, few data are available on the seasonal evolution of snow thermal conductivity in the Arctic. We have deployed heated needle probes on low-Arctic shrub tundra near Umiujaq, Quebec, (N56°34'; W76°29') and monitored automatically the evolution of keff for two consecutive winters, 2012-2013 and 2013-2014, at four heights in the snowpack. Shrubs are 20 cm high dwarf birch. Here, we develop an algorithm for the automatic determination of keff from the heating curves and obtain 404 keff values. We evaluate possible errors and biases associated with the use of the heated needles. The time evolution of keff is very different for both winters. This is explained by comparing the meteorological conditions in both winters, which induced different conditions for snow metamorphism. In particular, important melting events in the second year increased snow hardness, impeding subsequent densification and increase in thermal conductivity.We conclude that shrubs have very important impacts on snow physical evolution: (1) shrubs absorb light and facilitate snow melt under intense radiation; (2) the dense twig network of dwarf birch prevent snow compaction, and therefore keff increase; (3) the low density depth hoar that forms within shrubs collapsed in late winter, leaving a void that was not filled by snow. [ABSTRACT FROM AUTHOR]

The permeability (K) of snow to air flow affects the transfer of energy, water vapor and chemical species between the snow and the atmosphere. Yet today little is known about the temporal evolution of snow permeability as a function of metamorphic regime. Furthermore, our ability to simulate snow permeability over the seasonal evolution of a snowpack has not been tested. Here we have measured the evolution of snow permeability in a subarctic snowpack subject to high temperature-gradient (TG) metamorphism. We have also measured the evolution of the same snowpack deposited over tables so that it evolved in the equi-temperature (ET) regime. Permeability varies in the range 31 × 10−10 (ET regime) to 650 × 10−10 m2 (TG regime). Permeability increases over time in TG conditions and decreases under ET conditions. Using measurements of density ρ and of specific surface area (SSA), from which the equivalent sphere radius r is determined, we show that the equation linking SSA, density ρ and permeability, K = 3.0 r2 e(−0.013 ρ) (with K in m2, r in m and ρ in kg m−3) obtained in a previous study adequately predicts permeability values. The detailed snowpack model Crocus is used to simulate the physical properties of the TG and ET snowpacks. For the most part, all variables are well reproduced. Simulated permeabilities are up to a factor of two greater than measurements for depth hoar layers, which we attribute to snow microstructure and its aerodynamic properties. Finally, the large difference in permeabilities between ET and TG metamorphic regimes will impact atmosphere-snow energy and mass exchanges. These effects deserve consideration in predicting the effect of climate change on snow properties and snow–atmosphere interactions. [ABSTRACT FROM AUTHOR]

This study compares different methods to retrieve the specific surface area (SSA) of snow from satellite radiance measurements in mountainous terrain. It aims at addressing the effect on the retrieval of topographic corrections of reflectance, namely slope and aspect of terrain, multiple reflections on neighbouring slopes and accounting (or not) for the anisotropy of snow reflectance. Using MODerate resolution Imaging Spectrometer (MODIS) data for six different clear sky scenes spanning a wide range of snow conditions during the winter season 2008-2009 over a domain of 46×50 km in the French Alps, we compared SSA retrievals with and without topographic correction, with a spherical or non-spherical snow reflectance model and, in spherical case, with or without anisotropy corrections. The retrieved SSA values were compared to field measurements and to the results of the detailed snowpack model Crocus, fed by driving data from the SAFRAN meteorological analysis. It was found that the difference in terms of surface SSA between retrieved values and SAFRAN-Crocus output was minimal when the topographic correction was taken into account, when using a retrieval method assuming disconnected spherical snow grains. In this case, the root mean square deviation was 9.4m² kg-1 and the mean difference was 0.1m² kg-1, based on 3170 pairs of observation and simulated values. The added-value of the anisotropy correction was not significant in our case, which may be explained by the presence of mixed pixels and surface roughness. MODIS retrieved data show SSA variations with elevation and aspect which are physically consistent and in good agreement with SAFRAN-Crocus outputs. The variability of the MODIS retrieved SSA within the topographic classes of the model was found to be relatively small (3.9m² kg-1). This indicates that semi-distributed snowpack simulations in mountainous terrain with a sufficiently large number of classes provides a representation of the snowpack variability consistent with the scale of MODIS 500m pixels. [ABSTRACT FROM AUTHOR]

The article presents a study on the three-dimensional (3-D)-based numerical computations of snow permeability and microstructure. It says that the study was spanning range of seasonal snow types and detected anisotropy of permeability. Results reveal that regression curve is the best relationship linking the average value of intrinsic permeability (K) to snow density and surface area.