In silico assessment of light penetration into snow: implications to the prediction of slab failures leading to avalanches

Snow avalanches are a natural hazard that incur great cost to both property and to human welfare. In some countries they are known to cause more fatalities than both earthquakes and landslides. They also pose a threat to transportation corridors such as year-round highways and railroads that must pass through mountainous regions. There are two categories of avalanche formation that must be recognized when considering slope failure: loose and slab. The former occurs when there is little cohesion in the snowpack and a localized failure progresses downslope. This takes place when the slope angle is steeper than the angle of repose, making failure circumstances comparatively easy to predict. In contrast, slab avalanches occur when a cohesive slab of snow is released over an extended plane of weakness. This happens when a stress, such as the loading of fresh or windblown snow, or the weight of a person, is introduced to a slab layer which has formed on top of a weak layer. The formation of the weak layer that governs slab releases is much more difficult to predict, making this category of avalanche more hazardous. The plane of the weak layer may be comprised of different types of crystals (e.g., hoar and faceted). These are formed either at the surface or at a subsurface depth through morphological processes involving the transport of heat and vapour pressure gradients through the snowpack. These formations are weak since they exhibit poor intergranular bonding and lack shear strength. Even though it has been recognized as a factor in a significant fraction of failure events, the formation of near-surface faceted crystal layers has not been studied extensively. Elucidating the formation of subsurface faceted crystals will advance the current understanding about the formation of snow slabs, which in turn, could be used in the prediction of slope failure. The formation process of subsurface faceted crystals is tied to the penetration of solar radiation into the snowpack. More specifically, absorbed radiation provides the energy that gives rise to the morphological processes governing crystal growth. Consequently, the quantification of light penetration through snow is of interest for studies on the formation of the weak layers associated with snow failure. Despite its importance, investigations of light penetration through snow are still scarce in the literature, and the datasets obtained from field work are affected by experimental limitations. To overcome these limitations and to advance the understanding of light penetration into near-surface layers of snow, we employed a predictive in silico experimental setup. Our findings demonstrate that snow grain size and sample density must be carefully accounted for when estimating the quantity of solar radiation contributing to the subsurface morphological processes that form faceted crystals. In addition, our in silico experiments provide a detailed assessment of the hyperspectral transmission profiles at different depths. To the best of our knowledge, such an assessment has not been reported in the related literature to date.

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