The statistical relationship between the leading climate patterns of mid-tropospheric flow and atmospheric blocking over the Euro-Atlantic region during winter is investigated using three new two-dimensional blocking indicators. The focus is on the leading climate pattern of the 500-hPa geopotential variability, i.e. the North Atlantic Oscillation (NAO). The results indicate that the blocking-NAO relation is not restricted to the North Atlantic region, where blocking and the NAO are known to be out of phase. All three indicators show that the positive NAO phase is characterised by an enhanced occurrence of blocking-type high-pressure systems over the European mainland. The sign change of the NAO-blocking relation from west to east is well detectable with the two-dimensional blocking indicators and it is found further south than at the traditionally studied blocking latitudes near 60°N. The analysis of blocking events by seasonal NAO indices leads to similar (albeit less significant) results as with a daily NAO index stratification. This indicates that the relation between the NAO and blocking is fairly insensitive to the chosen time resolution.The investigation is extended from the second to fourth pattern of the mid-tropospheric flow variability using empirical orthogonal function (EOF) patterns. It reveals that one phase of each of the major Euro-Atlantic climate patterns is collocated with the region of maximum blocking frequency. The clearest separation between positive (negative) EOF phases and blocking (no blocking) situations is found for EOF × 2 and 3 and is associated with changes from zonal to ridge-like flow, similar to the so-called northern European 'blocking signature'. This is an indication that the purely statistically defined EOF patterns are related to the physical blocking phenomenon.

[1] Swiss Alpine snow cover is varying substantially on interannual to decadal time scales. In the late 20th century decreases in snow days (SD) have been observed for stations below 1300 m asl. A regression model is used in this work to quantify the importance of mean temperature and precipitation as well as large-scale climate variability in order to explain the observed trends. Both, local-and largescale models account for a modest fraction of the observed seasonal variability. Results suggest that the recent decrease in low altitude snow cover can mainly be attributed to an increase in temperature. Differences are found for northern and southern Switzerland concerning the influence of large-scale climate patterns. In contrast to southern Alpine regions, northern Alpine interannual SD variability is almost unaffected by the North Atlantic Oscillation (NAO). Decadal trends, however, can be explained via temperature only by a model that includes the explanatory variable NAO.

Abstract:A decision scheme has been developed to indicate the likely dominant runoff forming on temperate grassland hill slopes. The decision scheme was developed from data collected from sprinkler experiments on 60 m 2 plots at a number of grassland sites in Switzerland. The scheme requires input of hydrological properties of the surface and each major horizon of the soil. Worked examples of the application of the decision scheme to determine the dominant hydrological processes and runoff types are given for three actual grassland hill slopes.

Temperature is a key variable for monitoring global climate change. Here we perform a trend analysis of Swiss temperatures from 1959 to 2008, using a new 2 × 2 km gridded data-set based on carefully homogenised ground observations from MeteoSwiss. The aim of this study is twofold: first, to discuss the spatial and altitudinal temperature trend characteristics in detail, and second, to quantify the contribution of changes in atmospheric circulation and local effects to these trends.The seasonal trends are all positive and mostly significant with an annual average warming rate of 0.35°C/decade (∼1.6 times the northern hemispheric warming rate), ranging from 0.17 in autumn to 0.48°C/decade in summer. Altitudedependent trends are found in autumn and early winter where the trends are stronger at low altitudes (<800 m asl), and in spring where slightly stronger trends are found at altitudes close to the snow line.Part of the trends can be explained by changes in atmospheric circulation, but with substantial differences from season to season. In winter, circulation effects account for more than half the trends, while this contribution is much smaller in other seasons. After removing the effect of circulation, the trends still show seasonal variations with higher values in spring and summer. The circulation-corrected trends are closer to the values simulated by a set of ENSEMBLES regional climate models, with the models still tending towards a trend underestimation in spring and summer.Our results suggest that both circulation changes and more local effects are important to explain part of recent warming in spring, summer, and autumn. Snow-albedo feedback effects could be responsible for the stronger spring trends at altitudes close to the snow line, but the overall effect is small. In autumn, the observed decrease in fog frequency might be a key process in explaining the stronger temperature trends at low altitudes.

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.