WSL Institute for Snow and Avalanche Research SLF Davos Switzerland

Switzerland

WSL Institute for Snow and Avalanche Research SLF Davos Switzerland

Switzerland

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Proksch M.,University of Innsbruck | Lowe H.,WSL Institute for Snow and Avalanche Research SLF Davos Switzerland | Schneebeli M.,WSL Institute for Snow and Avalanche Research SLF Davos Switzerland
Journal of Geophysical Research F: Earth Surface | Year: 2015

Precise measurements of snow structural parameters are crucial to understand the formation of snowpacks by deposition and metamorphism and to characterize the stratigraphy for many applications and remote sensing in particular. The area-wide acquisition of structural parameters at high spatial resolution from state-of-the-art methods is, however, still cumbersome, since the time required for a single profile is a serious practical limitation. As a remedy we have developed a statistical model to extract three major snow structural parameters: density, correlation length, and specific surface area (SSA) solely from the SnowMicroPen (SMP), a high-resolution penetrometer, which allows a meter profile to be measured with millimeter resolution in less than 1 min. The model was calibrated by combining SMP data with 3-D microstructural data from microcomputed tomography which was used to reconstruct full-depth snow profiles from different snow climates (Alpine, Arctic, and Antarctic). Density, correlation length, and SSA were derived from the SMP with a mean relative error of 10.6%, 16.4%, and 23.1%, respectively. For validation, we compared the density and SSA derived from the SMP to traditional measurements and near-infrared profiles. We demonstrate the potential of our method by the retrieval of a two-dimensional stratigraphy at Kohnen Station, Antarctica, from a 46 m long SMP transect. The result clearly reveals past depositional and metamorphic events, and our findings show that the SMP can be used as an objective, high-resolution tool to retrieve essential snow structural parameters efficiently in the field. ©2015. American Geophysical Union.


Crouzy B.,Group AHEAD | Forclaz R.,Group AHEAD | Sovilla B.,WSL Institute for Snow and Avalanche Research SLF Davos Switzerland | Corripio J.,meteoexploration.com Innsbruck Austria | Perona P.,Group AHEAD
Journal of Geophysical Research F: Earth Surface | Year: 2015

We quantify the synchronization between snowfall and natural avalanches in relation to terrain properties at the detachment zone. We analyze field statistics of 549 avalanche events in terms of slope, aspect, timing, coordinate, and release area, identified by a georeferencing procedure applied on terrestrial photography. The information from the digital pictures, together with associated meteorological data, provides us with the input needed for model calibration, namely, the magnitude of snowfall, the snow compaction rate, and the timing of precipitation and of avalanche events. Synchronization between snowfall and avalanches is established for different slope categories. We obtain an average probability of release after a snow event of 30% and 16% for the high- and low-slope categories (average slope 44° and 36°, respectively). Using the notion of information entropy, we quantify the uncertainty in predicting avalanche occurrence from a snow event. The steeper slopes correspond to a larger entropy in avalanche prediction. Further, the presented method allows us to establish the return period of avalanches without requiring a long series of data. When considering events regardless of their release depth, the avalanches had a return period of 48 days (higher slopes) and 88 days (lower slopes). Finally, we determine the average daily detachment rate as a function of snow depth and the return period of avalanches as a function of the release depth. ©2015. American Geophysical Union.


Paterna E.,WSL Institute for Snow and Avalanche Research SLF Davos Switzerland | Crivelli P.,WSL Institute for Snow and Avalanche Research SLF Davos Switzerland | Lehning M.,Ecole Polytechnique Federale de Lausanne
Geophysical Research Letters | Year: 2016

The wind-driven redistribution of snow has a significant impact on the climate and mass balance of polar and mountainous regions. Locally, it shapes the snow surface, producing dunes and sastrugi. Sediment transport has been mainly represented as a function of the wind strength, and the two processes assumed to be stationary and in equilibrium. The wind flow in the atmospheric boundary layer is unsteady and turbulent, and drifting snow may never reach equilibrium. Our question is therefore: what role do turbulent eddies play in initiating and maintaining drifting snow? To investigate the interaction between drifting snow and turbulence experimentally, we conducted several wind tunnel measurements of drifting snow over naturally deposited snow covers. We observed a coupling between snow transport and turbulent flow only in a weak saltation regime. In stronger regimes it self-organizes developing its own length scales and efficiently decoupling from the wind forcing. © 2016. American Geophysical Union. All Rights Reserved.

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