Abstract
Abstract. Snow transport is one of the most dominant processes influencing the snow cover accumulation and ablation in high mountain environments. Hence, the spatial and temporal variability of the snow cover is significantly modified with respective consequences on the total amount of water in the snow pack, on the temporal dynamics of the runoff and on the energy balance of the surface. For the present study we used the snow transport model SnowModel in combination with MM5 (Penn State University – National Center for Atmospheric Research MM5 model) generated wind fields. In a first step the MM5 wind fields were downscaled by using a semi-empirical approach which accounts for the elevation difference of model and real topography, and vegetation. The target resolution of 30 m corresponds to the resolution of the best available DEM and land cover map of the test site Berchtesgaden National Park. For the numerical modelling, data of six automatic meteorological stations were used, comprising the winter season (September–August) of 2003/04 and 2004/05. In addition we had automatic snow depth measurements and periodic manual measurements of snow courses available for the validation of the results. It could be shown that the model performance of SnowModel could be improved by using downscaled MM5 wind fields for the test site. Furthermore, it was shown that an estimation of snow transport from surrounding areas to glaciers becomes possible by using downscaled MM5 wind fields.
Highlights
In alpine terrain wind induced snow transport may lead to a significant redistribution of the existing snow cover (Doesken and Judson, 1996; Pomeroy et al, 1998; Balk and Elder, 2000; Doorschot, 2002; Bowling et al, 2004; Bernhardt et al, 2009)
The maximum modelled sublimation rates are slightly higher than those of the 200 m MM5 runs (920 mm to 860 mm) but the total amount of sublimation for the whole area is significantly smaller (0.5 mm to 12 mm per 30 m grid cell in average). This is due to the fact that areas of high sublimation rates are again limited to the crest regions having a smaller spatial extent in the high resolution digital elevation model (DEM)
The downscaling procedure described in 4 was able to improve the convergence between meteorological station and model results in a significant way
Summary
In alpine terrain wind induced snow transport may lead to a significant redistribution of the existing snow cover (Doesken and Judson, 1996; Pomeroy et al, 1998; Balk and Elder, 2000; Doorschot, 2002; Bowling et al, 2004; Bernhardt et al, 2009). Bernhardt et al.: High resolution modelling of snow transport et al (2009) utilized a library of pre-generated MM5 wind fields for providing physically derived wind fields as input for SnowModel (Liston and Elder, 2006) and have demonstrated the general functionality of this approach at a gridscale of 200 m They could show that simulated snow transport was significantly increased when using MM5 wind fields due to elevation and convergence “speed up” effects at the crest regions. In order to further improve SnowModel predictions, a procedure for generating downscaled 30 m grid MM5 wind fields is introduced to drive fine resolution (30 m) SnowModel runs These results are evaluated against remotely sensed snow cover maps for the winter season 2003/04 and winter field campaign data of 2004/05. The predictive power of the coupled SnowModel-MM5 model is demonstrated for the snow water equivalent (SWE) dynamics of a small kar glaciers (Blaueis, Fig. 1)
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