2021
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Observed snow depth trends in the European Alps: 1971 to 2019
Michael Matiu,
Alice Crespi,
Giacomo Bertoldi,
Carlo Maria Carmagnola,
Christoph Marty,
Samuel Morin,
Wolfgang Schöner,
Daniele Cat Berro,
Gabriele Chiogna,
Ludovica De Gregorio,
Sven Kotlarski,
Bruno Majone,
Gernot Resch,
Silvia Terzago,
Mauro Valt,
Walter Beozzo,
Paola Cianfarra,
Isabelle Gouttevin,
Giorgia Marcolini,
Claudia Notarnicola,
Marcello Petitta,
Simon C. Scherrer,
Ulrich Strasser,
Michael Winkler,
Marc Zebisch,
A. Cicogna,
Roberto Cremonini,
Andrea Debernardi,
Mattia Faletto,
Mauro Gaddo,
Lorenzo Giovannini,
Luca Mercalli,
Jean Michel Soubeyroux,
Andrea Sušnik,
Alberto Trenti,
Stefano Urbani,
Viktor Weilguni
The Cryosphere, Volume 15, Issue 3
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.
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Evaluating a prediction system for snow management
Pirmin Philipp Ebner,
Franziska Koch,
Valentina Premier,
Carlo Marín,
Florian Hanzer,
Carlo Maria Carmagnola,
Hugues François,
Daniel Günther,
Fabiano Monti,
Olivier Hargoaa,
Ulrich Strasser,
Samuel Morin,
Michael Lehning
The Cryosphere, Volume 15, Issue 8
Abstract. The evaluation of snowpack models capable of accounting for snow management in ski resorts is a major step towards acceptance of such models in supporting the daily decision-making process of snow production managers. In the framework of the EU Horizon 2020 (H2020) project PROSNOW, a service to enable real-time optimization of grooming and snow-making in ski resorts was developed. We applied snow management strategies integrated in the snowpack simulations of AMUNDSEN, Crocus, and SNOWPACK–Alpine3D for nine PROSNOW ski resorts located in the European Alps. We assessed the performance of the snow simulations for five winter seasons (2015–2020) using both ground-based data (GNSS-measured snow depth) and spaceborne snow maps (Copernicus Sentinel-2). Particular attention has been devoted to characterizing the spatial performance of the simulated piste snow management at a resolution of 10 m. The simulated results showed a high overall accuracy of more than 80 % for snow-covered areas compared to the Sentinel-2 data. Moreover, the correlation to the ground observation data was high. Potential sources for local differences in the snow depth between the simulations and the measurements are mainly the impact of snow redistribution by skiers; compensation of uneven terrain when grooming; or spontaneous local adaptions of the snow management, which were not reflected in the simulations. Subdividing each individual ski resort into differently sized ski resort reference units (SRUs) based on topography showed a slight decrease in mean deviation. Although this work shows plausible and robust results on the ski slope scale by all three snowpack models, the accuracy of the results is mainly dependent on the detailed representation of the real-world snow management practices in the models. As snow management assessment and prediction systems get integrated into the workflow of resort managers, the formulation of snow management can be refined in the future.
2020
DOI
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Observed snow depth trends in the European Alps 1971 to 2019
Michael Matiu,
Alice Crespi,
Giacomo Bertoldi,
Carlo Maria Carmagnola,
Christoph Marty,
Samuel Morin,
Wolfgang Schöner,
Daniele Cat Berro,
Gabriele Chiogna,
Ludovica De Gregorio,
Sven Kotlarski,
Bruno Majone,
Gernot Resch,
Silvia Terzago,
Mauro Valt,
Walter Beozzo,
Paola Cianfarra,
Isabelle Gouttevin,
Giorgia Marcolini,
Claudia Notarnicola,
Marcello Petitta,
Simon C. Scherrer,
Ulrich Strasser,
Michael Winkler,
Marc Zebisch,
A. Cicogna,
Roberto Cremonini,
Andrea Debernardi,
Mattia Faletto,
Mauro Gaddo,
Lorenzo Giovannini,
Luca Mercalli,
Jean‐Michel Soubeyroux,
Andrea Sušnik,
Alberto Trenti,
Stefano Urbani,
Viktor Weilguni
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. 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, northeast, northwest, southeast and southwest. Linear trends of mean monthly snow depth between 1971 to 2019 showed decreases in snow depth for 87 % of the stations. December to February trends were on average −1.1 cm decade−1 (min, max: −10.8, 4.4; elevation range 0–1000 m), −2.5 (−25.1, 4.4; 1000–2000 m) and −0.1 (−23.3, 9.9; 2000–3000 m), with stronger trends in March to May: −0.6 (−10.9, 1.0; 0–1000 m), −4.6 (−28.1, 4.1; 1000–2000 m) and −7.6 (−28.3, 10.5; 2000–3000 m). However, regional trends differed substantially, which challenges the notion of generalizing results from one Alpine 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.
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Long‐term trends (1958–2017) in snow cover duration and depth in the Pyrenees
J. I. López‐Moreno,
Jean Michel Soubeyroux,
Simon Gascoin,
Esteban Alonso‐González,
Nuria Durán-Gómez,
Matthieu Lafaysse,
Matthieu Vernay,
Carlo Maria Carmagnola,
Samuel Morin
International Journal of Climatology, Volume 40, Issue 14
This study investigated the temporal variability and changes in snow cover duration and the average snow depth from December to April in the Pyrenees at 1,500 and 2,100 m a.s.l. for the period 1958–2017. This is the first such analysis for the entire mountain range using SAFRAN‐Crocus simulations run for this specific purpose. The SAFRAN‐Crocus simulations were evaluated for the period 1980–2016 using 28 in situ snow depth data time series, and for the period 2000–2017 using MODIS observations of the snow cover duration. Following confirmation that the simulated snow series satisfactorily reproduced the observed evolution of the snowpack, the Mann–Kendall test showed that snow cover duration and average depth decreased during the full study period, but this was only statistically significant at 2,100 m a.s.l. The temporal evolution in the snow series indicated marked differences among massifs, elevations, and snow variables. In general, the most western massifs of the French Pyrenees underwent a greater decrease in the snowpack, while in some eastern massifs the snowpack did not decrease, and in some cases increased at 1,500 m a.s.l. The results suggest that the trends were consistent over time, as they were little affected by the start and end year of the study period, except if trends are computed only starting after 1980, when no significant trends were apparent. Most of the observed negative trends were not correlated with changes in the atmospheric circulation patterns during the snow season. This suggests that the continuous warming in the Pyrenees since the beginning of the industrial period, and particularly the sharp increase since 1955, is a major driver explaining the snow cover decline in the Pyrenees.