In mountains the snow cover is heterogeneously distributed in space and time. The spatial and temporal variability of the Alpine snow cover has a major influence on avalanche danger, snow hydrology, mountain ecology and winter tourism. In winter, already deposited snow is redistributed by saltation/suspension or precipitation is deposited preferentially in leeward slopes. The driving mechanism is wind and precipitation interacting with the snow cover surface. Although the mountain snow cover gets patchy in spring, the snow depth patterns typically remain during the ablation period. The patchiness of mountain snow covers is, therefore, mainly caused by end of winter snow depth distribution and the spatially variable energy balance. The local energy balance is driven by net radiation and the turbulent exchange of sensible and latent heat. Once the snow cover is patchy, the heterogeneous temperature field causes the development of thermal internal boundary layers and the advection of warm air from adjacent bare ground to snow covered areas. The main purpose of this work is to enhance the understanding of processes driving the small scale variability of mountain snow covers. The relative importance of the main snow cover processes contributing to observed snow deposition patterns after individual snow storms and during the ablation season are investigated. The different processes are identified and quantified by modelling, measuring and statistically analysing the snowpack, its interaction with the atmosphere and its spatial distribution. Several state of the art techniques of measurements, models and statistical analysis are applied to explore wind induced snow transport processes and the local energy balance. Four studies were conducted at three small Alpine catchments: The Gaudergrat, the Wannengrat and the SLF flat field research site Versuchsfeld. From these three study sites, the Wannengrat features the most complex topography and offers most facilities for high density measurements of snow depths and meteorological variables. All studies are based on atmospheric and snow transport modelling. The meteorological model Advanced Regional Prediction System (ARPS) was used to calculate mean flow fields. The flow fields were then used to drive the snow transport module of Alpine3D, which is a model to calculate snow cover processes. Within the snow transport module, saltation, suspension and preferential deposition of precipitation are calculated. Modelled flow fields were validated against measurements from high density network of permanent and mobile weather stations and indirect estimates from snow surface structures. Modelled snow deposition patterns were validated against snow depth measurements obtained from Terrestrial Laser Scans after ten major storms. In order to explore the spatial characteristics of measured and modelled distribution of snow depths and mean flow fields semivariogram analysis and 2-D autocorrelation functions were applied.
Michael Lehning, Dylan Stewart Reynolds, Michael Haugeneder