Abstract. The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

Time series of snow depth bear relevant information for environmental studies in Alpine areas. In addition, due to its sensitivity to air temperature, snow depth dynamic is a robust indicator of climate change effects in mountainous areas. Unfortunately, collecting accurate snow depth data is a difficult task and often time series are obtained by merging data from different sources. Especially in the past, observations were not standardized, such that changes in the operator and in the equipment were sources of inhomogeneities in the time series. To overcome this problem and make the most efficient use of the available information, homogenization techniques may be used. However, a standardized approach for homogenizing snow depth data is currently lacking, despite its importance in climatic and hydrological studies. We evaluate the performance of the Standard Normal Homogeneity Test (SNHT) to homogenize mean seasonal snow depth data collected in the Province of Trento, Northeastern Italy. The proposed algorithm showed good performance in both detecting breakpoints and identifying homogeneous time series. Breakpoints have been detected in about 20% of the analysed time series. A homogeneity analysis on mean seasonal snow depth datasets is hence recommended before performing climatological studies.

<p>The European Alps stretch over a range of climate zones, which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses, which complicates comparisons between regions and makes Alpine wide conclusions questionable. Here, we present an Alpine wide analysis of snow depth from six Alpine countries: Austria, France, Germany, Italy, Slovenia, and Switzerland; including altogether more than 2000 stations, of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions, which match the climatic forcing zones: north & high Alpine, northeast, northwest, southeast, and south & high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations for November to May. The average trend among all stations for seasonal (November to May) mean snow depth was -8.4 % per decade, for seasonal maximum snow depth -5.6 % per decade, and for seasonal snow cover duration -5.6 % per decade. However, regional trends differed substantially after accounting for elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.</p>