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.

The major patterns of interannual Swiss Alpine snow pack variability were determined and their relation to local and large-scale climate variability and recent trends was investigated. The snow variables considered were the seasonally averaged new snow sum, snow depth and snow days for winter (DJF) in the period 1958-1999. Three major patterns of large-scale snow variability were identified. The first pattern explains ~50% of total variance and extends over the entire area except the southernmost parts. The second pattern explains ~15% of total variance and has a dipole structure with a maximum on the northern and a strong minimum on the southern slope of the Alps. The third pattern (~10% of total variance) is height dependent with a strong maximum at lowland stations and a minimum at high stations. In contrast to the first and second pattern, the third pattern's time component shows a distinct trend. It is well correlated with the 0°C isotherm which increased from 600 m a.s.l. in the 1960s to ~900 m a.s.l. in the late 1990s and could be related to climate change. Variability in the first new snow sum pattern was primarily related to total precipitation anomalies. In contrast, variability in the first snow day pattern was primarily related to temperature anomalies. The dominance of precipitation for new snow sums and the dominance of temperature for snow days is physically consistent with the former being controlled by accumulation only and the latter by accumulation and ablation. The surface pressure anomaly pattern linked to the first new snow sum pattern is centred over southeastern Europe, resembling the Euro-Atlantic blocking pattern. For snow days the corresponding pressure anomaly is shifted further southeastward. The second snow pattern is mainly influenced by an East Atlantic like pattern, whereas only the third (height and temperature dependent) pattern is strongly linked to the North Atlantic Oscillation index.

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.

Changes in intensity and frequency of daily heavy precipitation and hot temperature extremes are analyzed in Swiss observations for the years 1901-2014/2015. A spatial pooling of temperature and precipitation stations is applied to analyze the emergence of trends. Over 90% of the series show increases in heavy precipitation intensity, expressed as annual maximum daily precipitation (mean change: +10.4% 100 years À1 ; 31% significant, p < 0.05) and in heavy precipitation frequency, expressed as the number of events greater than the 99th percentile of daily precipitation (mean change: +26.5% 100 years À1 ; 35% significant, p < 0.05). The intensity of heavy precipitation increases on average by 7.7% K À1 smoothed Swiss annual mean temperature, a value close to the Clausius-Clapeyron scaling. The hottest day and week of the year have warmed by 1.6 K to 2.3 K depending on the region, while the Swiss annual mean temperature increased by 1.9 K. The frequency of very hot days exceeding the 99th percentile of daily maximum temperature has more than tripled. Despite considerable local internal variability, increasing trends in heavy precipitation and hot temperature extremes are now found at most Swiss stations. The identified trends are unlikely to be random and are consistent with climate model projections, with theoretical understanding of a human-induced change in the energy budget and water cycle and with detection and attribution studies of extremes on larger scales.

Abstract. Rainfall-runoff models that adequately represent the real hydrological processes and that do not have to be calibrated, are needed in hydrology. Such a model would require information about the runoff processes occurring in a catchment and their spatial distribution. Therefore, the aim of this article is (1) to develop a methodology that allows the delineation of dominant runoff processes (DRP) in the field and with a GIS, and (2) to illustrate how such a map can be used in rainfall-runoff modelling.Soil properties were assessed of 44 soil profiles in two Swiss catchments. On some profiles, sprinkling experiments were performed and soil-water levels measured. With these data, the dominant runoff processes (DRP) were determined using the Scherrer and Naef (2003) process decision scheme. At the same time, a simplified method was developed to make it possible to determine the DRP only on the basis of maps of the soil, topography and geology. In 67% of the soil profiles, the two methods indicated the same processes; in 24% with minor deviations.By transforming the simplified method into a set of rules that could be introduced into a GIS, the distributions of the different DRPs in two catchments could be delineated automatically so that maps of the dominant runoff processes could be produced. These maps agreed well with manually derived maps and field observations. Flood-runoff volumes could be quite accurately predicted on the basis of the rainfall measured and information on the water retention capacity contained in the DRP map. This illustrates the potential of the DRP maps for defining the infiltration parameters used in rainfall-runoff models.Correspondence to: P. Schmocker-Fackel