Article ID Journal Published Year Pages File Type
4675953 Cold Regions Science and Technology 2012 7 Pages PDF
Abstract

Buried surface hoar is a well-known weak snowpack layer, often associated with snow avalanches. Knowledge about the spatial distribution of surface hoar is therefore of great importance for avalanche forecasting. We investigate if spatial variations of surface hoar in mountainous terrain can be modeled based on terrain characteristics. Using a detailed radiation balance model, distributed radiation over an ensemble of 1800 simulated topographies, covering a wide range of terrain characteristics, was computed. Light winds and increased relative humidity were assumed to be favorable for surface hoar formation. To describe surface hoar formation, we derived a sky view factor threshold associated with the minimum snow surface cooling necessary for surface hoar formation based on laboratory measurements. To describe surface hoar destruction, as a first approach, we assumed that surface hoar only survives on shaded slopes. Applying two simple thresholds to our spatial radiation modelings, our results show that the spatial distribution of surface hoar is greatly affected by large-scale terrain roughness and sun elevation angle. Spatial correlation ranges for surface hoar, on the order of several hundred meters, were closely related to the typical spacing between mountains. Furthermore, correlation ranges of surface hoar decreased with increasing sun elevation angle. Overall, the modeled spatial patterns of surface hoar were in line with previously published spatial field observations, suggesting that simple terrain parameters can very well be used to describe the predominant surface hoar layer patterns in complex topography.

► Spatial variations of surface hoar in mountainous terrain are modeled. ► Simple thresholds for surface hoar formation and destruction are used. ► A sky view factor threshold was obtained from laboratory measurements. ► Modeled patterns were in line with previously published spatial field observations. ► Spatial correlation lengths mainly depend on typical mountain spacing.

Related Topics
Physical Sciences and Engineering Earth and Planetary Sciences Earth and Planetary Sciences (General)
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