Christoph Marty

Sensitivity of Alpine3D modeled snow cover to modifications in DEM resolution, station coverage and meteorological input quantities

This study presents a comprehensive sensitivity and uncertainty assessment of important input parameters on the Alpine3D modeled snow water equivalent (SWE) for two different alpine catchments. Horizontal resolution of the DEM grid, station coverage and several meteorological input quantities were modified. Decreasing the horizontal resolution from 25źm to 1000źm leads to a 10% higher SWE. Modifications in the spatial coverage of meteorological stations influences the SWE up to 20%. Modifications of meteorological input quantities within some plausible ranges lead to changes in SWE up to 30%. The results demonstrate that Alpine3D input uncertainties are in general in the same range as the typical measurement uncertainty of SWE and the uncertainty of the typical scenario spread of GCM-RCM ensemble runs. Modifications of meteorological input quantities lead to changes in SWE up to 30%.Alpine3D input uncertainties are in general in the same range as the typical measurement uncertainty of SWE.

European In-Situ Snow Measurements: Practices and Purposes

In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and Technology (COST) Action ES1404, called “A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical weather prediction”. Here we present the results of this survey, which was answered by 125 participants from 99 operational and research institutions, belonging to 38 European countries. The typologies of environments where the snow measurements are performed range from mountain to low elevated plains, including forests, bogs, tundra, urban areas, glaciers, lake ice, and sea ice. Of the respondents, 93% measure snow macrophysical parameters, such as snow presence, snow depth (HS), snow water equivalent (SWE), and snow density. These describe the bulk characteristics of the whole snowpack or of a snow layer, and they are the primary snow properties that are needed for most operational applications (such as hydrological monitoring, avalanche forecast, and weather forecast). In most cases, these measurements are done with manual methods, although for snow presence, HS, and SWE, automatized methods are also applied by some respondents. Parameters characterizing precipitating and suspended snow (such as the height of new snow, precipitation intensity, flux of drifting/blowing snow, and particle size distribution), some of which are crucial for the operational services, are measured by 74% of the respondents. Parameters characterizing the snow microstructural properties (such as the snow grain size and shape, and specific surface area), the snow electromagnetic properties (such as albedo, brightness temperature, and backscatter), and the snow composition (such as impurities and isotopes) are measured by 41%, 26%, and 13% of the respondents, respectively, mostly for research applications. The results of this survey are discussed from the perspective of the need of enhancing the efficiency and coverage of the in-situ observational network applying automatic and cheap measurement methods. Moreover, recommendations for the enhancement and harmonization of the observational network and measurement practices are provided.