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.

The Adige Valley is one of the major corridors connecting the Po Plain with the inner Alps. A series of permanent weather stations and one wind profiler provide regular monitoring of air temperature, atmospheric pressure, global solar radiation, wind speed and direction over the 140 km valley length and in the adjacent plain. Data from these stations are analyzed for a subset of days on which weather conditions favoured full development of diurnal valley winds in the period 2012–2014. The analysis highlights typical features in the alternating patterns of diurnal up‐valley winds and nocturnal down‐valley winds. In particular, the wind intensity depends linearly on the along‐valley pressure gradient, supporting the concept of a quasi‐steady balance between the pressure gradient and surface friction. Also, in agreement with previous investigations, the amplitude of the surface pressure cycle increases in the up‐valley direction, causing the reversal of the horizontal pressure gradient twice per day. In contrast, no appreciable along‐valley variation in the diurnal temperature range is found. The analysis of surface temperature and pressure measurements suggests that the larger pressure perturbations found far into the valley are caused by the increased depth of the atmospheric layer subject to heating and cooling. Local inhomogeneities in the valley cross‐section, in particular in the vicinity of a large basin, cause temperature and pressure perturbations that are strong enough to alter the typical cycle of down‐ and up‐valley winds. Similarly, local wind convergence over the major cities during the night is explained in terms of the urban heat island effect.

High-resolution simulations are performed with the Weather Research and Forecasting (WRF) model, coupled with an advanced urban parameterization scheme, to evaluate the modifications induced by the urban area of Trento on boundary-layer processes in the Alpine Adige Valley in a typical summer sunny day. Specific gridded datasets of urban morphology parameters and anthropogenic heat releases were created to provide high-resolution input information for the urban scheme. Comparison of model results against measurements from surface weather stations shows that the model simulates reasonably well the development of valley winds, as well as the complex interaction occurring north of Trento between the up-valley wind of the Adige Valley and a lake breeze flowing from a tributary valley. The urban heat island of the city is also well captured by the model, with stronger intensities at night and lower values during daytime. Comparisons with an idealized simulation, where all the urban land use grid points are replaced by cropland, suggest that the city inhibits the development of the ground-based thermal inversion at night and also affects valley winds, modifying both the typical down-valley wind, and the interaction between the up-valley wind of the Adige Valley and the lake breeze. Further sensitivity tests are performed to evaluate the impacts of the gridded datasets of urban morphology and anthropogenic heat releases, and to assess what are the benefits of using the advanced urban scheme against a simple bulk parameterization. Results highlight that even the moderate anthropogenic heat releases present in Trento appreciably affect nocturnal temperatures in the city, while gridded information on urban parameters is not essential in the present case, because urban morphology does not display a high spatial variability. However, it is shown that the choice of the urban scheme may have significant impacts on both temperature and wind fields.

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The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.

The temperature contrasts typically marking urban heat island (UHI) effects in the city of Trento, Italy, located in an Alpine valley and inhabited in its inner urban area by a population of about 56 000, are investigated. Time series of air temperature data, collected at an urban weather station, in the city center, and at five extraurban stations are compared. The latter are representative of rural and suburban areas, both on the valley floor and on the valley sidewalls. It is found that the extraurban weather stations, being affected by different local-scale climatic conditions, display different temperature contrasts with the urban site. However, the diurnal cycle of the UHI is characterized by similar patterns of behavior at all of the extraurban weather stations: the UHI intensity is stronger at night, whereas during the central hours of the day an ''urban cool island'' is likely to occur. The diurnal maximum UHI intensity turns out to be typically of order 38C, but under particularly favorable conditions it may be higher than 68C. An urban cool island effect is also detected, which is probably caused by the compactness of the inner urban area, and displays typical diurnal maximum intensities of order 1.58C. As to the seasonal dependence, at the extraurban weather stations on the valley floor the UHI intensity tends to be slightly stronger during dry months, whereas on the valley sidewalls it is mainly influenced by the seasonal lapse-rate changes. Further weather factors, such as wind speed and cloud cover, also affect urbanization effects, making them weaker with stronger winds and cloudier skies.

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