Abstract. Mountain snow-cover is normally heterogeneously distributed due to wind and precipitation interacting with the snow cover on various scales. The aim of this study was to investigate snow deposition and wind-induced snow-transport processes on different scales and to analyze some major drift events caused by north-west storms during two consecutive accumulation periods. In particular, we distinguish between the individual processes that cause specific drifts using a physically based model approach. Very high resolution wind fields (5 m) were computed with the atmospheric model Advanced Regional Prediction System (ARPS) and used as input for a model of snow-surface processes (Alpine3D) to calculate saltation, suspension and preferential deposition of precipitation. Several flow features during north-west storms were identified with input from a high-density network of permanent and mobile weather stations and indirect estimations of wind directions from snowsurface structures, such as snow dunes and sastrugis. We also used Terrestrial and Airborne Laser Scanning measurements to investigate snow-deposition patterns and to validate the model. The model results suggest that the in-slope deposition patterns, particularly two huge cross-slope cornicelike drifts, developed only when the prevailing wind direction was northwesterly and were formed mainly due to snow redistribution processes (saltation-driven). In contrast, more homogeneous deposition patterns on a ridge scale were formed during the same periods mainly due to preferential deposition of precipitation. The numerical analysis showed that snow-transport processes were sensitive to the changing topography due to the smoothing effect of the snow cover.

Abstract:The snow cover in the Alps is heavily affected by climate change. Recent data show that at altitudes below 1200 m a.s.l. a time-continuous winter snow cover is becoming an exception rather than the rule. This would also change the timing and characteristics of river discharge in Alpine catchments. We present an assessment of future snow and runoff in two Alpine catchments, the larger Inn catchment (1945 km 2 ) and the smaller Dischma catchment (43 km 2 ), based on two common climate change scenario (IPCC A2 and B2 (IPCC, 2007)). [etc]. The changes in snow cover and discharge are predicted using Alpine3D, a model for the high-resolution simulation of Alpine surface processes, in particular snow, soil and vegetation processes. The predicted changes in snow and discharge are extreme. While the current climate still supports permanent snow and ice on the highest peaks at altitudes above 3000 m a.s.l., this zone would disappear under the future climate scenarios. The changes in snow cover could be summarized by approximately shifting the elevation zones down by 900 m. The corresponding changes in discharge are also severe: while the current climate scenario shows a significant contribution from snow melt until middle to late summer, the future climate scenarios would feature a much narrower snow melt discharge peak in spring. A further observation is that heavy precipitation events in the fall would change from mainly snow to mainly rain and would have a higher probability of producing flooding. Future work is needed to quantify the effect of model uncertainties on such predictions.

Abstract.Using numerical models which require large meteorological data sets is sometimes difficult and problems can often be traced back to the Input/Output functionality. Complex models are usually developed by the environmental sciences community with a focus on the core modelling issues. As a consequence, the I/O routines that are costly to properly implement are often error-prone, lacking flexibility and robustness. With the increasing use of such models in operational applications, this situation ceases to be simply uncomfortable and becomes a major issue.The MeteoIO library has been designed for the specific needs of numerical models that require meteorological data. The whole task of data preprocessing has been delegated to this library, namely retrieving, filtering and resampling the data if necessary as well as providing spatial interpolations and parameterizations. The focus has been to design an Application Programming Interface (API) that (i) provides a uniform interface to meteorological data in the models, (ii) hides the complexity of the processing taking place, and (iii) guarantees a robust behaviour in the case of format errors, erroneous or missing data. Moreover, in an operational context, this error handling should avoid unnecessary interruptions in the simulation process.A strong emphasis has been put on simplicity and modularity in order to make it extremely easy to support new data formats or protocols and to allow contributors with diverse backgrounds to participate. This library is also regularly evaluated for computing performance and further optimized where necessary. Finally, it is released under an Open Source license and is available at http://models.slf.ch/p/meteoio. This paper gives an overview of the MeteoIO library from the point of view of conceptual design, architecture, features and computational performance. A scientific evaluation of the produced results is not given here since the scientific algorithms that are used have already been published elsewhere.

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Abstract. This study focuses on an assessment of the future snow depth for two larger Alpine catchments. Automatic weather station data from two diverse regions in the Swiss Alps have been used as input for the Alpine3D surface process model to compute the snow cover at a 200 m horizontal resolution for the reference period (1999–2012). Future temperature and precipitation changes have been computed from 20 downscaled GCM-RCM chains for three different emission scenarios, including one intervention scenario (2 °C target) and for three future time periods (2020–2049, 2045–2074, 2070–2099). By applying simple daily change values to measured time series of temperature and precipitation, small-scale climate scenarios have been calculated for the median estimate and extreme changes. The projections reveal a decrease in snow depth for all elevations, time periods and emission scenarios. The non-intervention scenarios demonstrate a decrease of about 50 % even for elevations above 3000 m. The most affected elevation zone for climate change is located below 1200 m, where the simulations show almost no snow towards the end of the century. Depending on the emission scenario and elevation zone the winter season starts half a month to 1 month later and ends 1 to 3 months earlier in this last scenario period. The resulting snow cover changes may be roughly equivalent to an elevation shift of 500–800 or 700–1000 m for the two non-intervention emission scenarios. At the end of the century the number of snow days may be more than halved at an elevation of around 1500 m and only 0–2 snow days are predicted in the lowlands. The results for the intervention scenario reveal no differences for the first scenario period but clearly demonstrate a stabilization thereafter, comprising much lower snow cover reductions towards the end of the century (ca. 30 % instead of 70 %).