Articles | Volume 15, issue 3
https://doi.org/10.5194/tc-15-1343-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-1343-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
18 Mar 2021
Research article | Highlight paper |
| 18 Mar 2021
| 18 Mar 2021
Observed snow depth trends in the European Alps: 1971 to 2019
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
Alice Crespi
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
Giacomo Bertoldi
Institute for Alpine Environment, Eurac Research, Bolzano, 39100, Italy
Carlo Maria Carmagnola
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, Grenoble, 38000, France
Christoph Marty
WSL Institute for Snow and Avalanche Research SLF, Davos, 7260, Switzerland
Samuel Morin
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, Grenoble, 38000, France
Wolfgang Schöner
Department of Geography and Regional Sciences, University of Graz, Graz, 8010, Austria
Daniele Cat Berro
Società Meteorologica Italiana, Moncalieri, 10024, Italy
Gabriele Chiogna
Chair of Hydrology and River Basin Management, Technical University Munich, Munich, 80333, Germany
Department of Geography, University of Innsbruck, Innsbruck, 6020, Austria
Ludovica De Gregorio
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
Sven Kotlarski
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich-Airport, 8058, Switzerland
Bruno Majone
Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, 38123, Italy
Gernot Resch
Department of Geography and Regional Sciences, University of Graz, Graz, 8010, Austria
Silvia Terzago
Institute of Atmospheric Sciences and Climate, National Research Council, (CNR-ISAC), Turin, 10133, Italy
Mauro Valt
Centro Valanghe di Arabba, Arabba, 32020, Italy
Walter Beozzo
Meteotrentino, Provincia Autonoma di Trento, Trento, 38122, Italy
Paola Cianfarra
Dipartimento di Scienze della Terra, dell'Ambiente e della Vita – DISTAV, Università degli Studi di Genova, Genova, 16132, Italy
Isabelle Gouttevin
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, Grenoble, 38000, France
Giorgia Marcolini
Chair of Hydrology and River Basin Management, Technical University Munich, Munich, 80333, Germany
Claudia Notarnicola
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
Marcello Petitta
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
SSPT-MET-CLIM, ENEA, Rome, 00123, Italy
Simon C. Scherrer
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich-Airport, 8058, Switzerland
Ulrich Strasser
Department of Geography, University of Innsbruck, Innsbruck, 6020, Austria
Michael Winkler
ZAMG, Innsbruck, 6020, Austria
Marc Zebisch
Institute for Earth Observation, Eurac Research, Bolzano, 39100, Italy
Andrea Cicogna
ARPA Friuli Venezia Giulia, Palmanova, 33057, Italy
Roberto Cremonini
ARPA Piemonte, Torino, 10135, Italy
Andrea Debernardi
Assetto idrogeologico dei bacini montani, Region Valle d'Aosta, Aosta, 11100, Italy
Fondazione Montagna sicura, Courmayeur, 11013, Italy
Mattia Faletto
ARPA Piemonte, Torino, 10135, Italy
Mauro Gaddo
Meteotrentino, Provincia Autonoma di Trento, Trento, 38122, Italy
Lorenzo Giovannini
Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, 38123, Italy
Luca Mercalli
Società Meteorologica Italiana, Moncalieri, 10024, Italy
Jean-Michel Soubeyroux
Météo-France, Direction de la Climatologie et des Services Climatiques, Toulouse, 31057, France
Andrea Sušnik
Meteorology Office, Slovenian Environment Agency, Ljubljana, 1000, Slovenia
Alberto Trenti
Meteotrentino, Provincia Autonoma di Trento, Trento, 38122, Italy
Stefano Urbani
Centro Nivometeorologico, ARPA Lombardia, Bormio, 23032, Italy
Viktor Weilguni
Abteilung I/3 – Wasserhaushalt (HZB), BMLRT, Vienna, 1010, Austria
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Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
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Erwan Le Roux, Guillaume Evin, Raphaëlle Samacoïts, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
The Cryosphere, 17, 4691–4704, https://doi.org/10.5194/tc-17-4691-2023, https://doi.org/10.5194/tc-17-4691-2023, 2023
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Sonika Shahi, Jakob Abermann, Tiago Silva, Kirsty Langley, Signe Hillerup Larsen, Mikhail Mastepanov, and Wolfgang Schöner
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Diego Monteiro and Samuel Morin
The Cryosphere, 17, 3617–3660, https://doi.org/10.5194/tc-17-3617-2023, https://doi.org/10.5194/tc-17-3617-2023, 2023
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Klaus Haslinger, Wolfgang Schöner, Jakob Abermann, Gregor Laaha, Konrad Andre, Marc Olefs, and Roland Koch
Nat. Hazards Earth Syst. Sci., 23, 2749–2768, https://doi.org/10.5194/nhess-23-2749-2023, https://doi.org/10.5194/nhess-23-2749-2023, 2023
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Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
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Valentina Premier, Carlo Marin, Giacomo Bertoldi, Riccardo Barella, Claudia Notarnicola, and Lorenzo Bruzzone
The Cryosphere, 17, 2387–2407, https://doi.org/10.5194/tc-17-2387-2023, https://doi.org/10.5194/tc-17-2387-2023, 2023
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Roberto Cremonini, Tanel Voormansik, Piia Post, and Dmitri Moisseev
Atmos. Meas. Tech., 16, 2943–2956, https://doi.org/10.5194/amt-16-2943-2023, https://doi.org/10.5194/amt-16-2943-2023, 2023
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Extreme rainfall for a specific location is commonly evaluated when designing stormwater management systems. This study investigates the use of quantitative precipitation estimations (QPEs) based on polarimetric weather radar data, without rain gauge corrections, to estimate 1 h rainfall total maxima in Italy and Estonia. We show that dual-polarization weather radar provides reliable QPEs and effective estimations of return periods for extreme rainfall in climatologically homogeneous regions.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
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The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
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We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Robert Vautard, Geert Jan van Oldenborgh, Rémy Bonnet, Sihan Li, Yoann Robin, Sarah Kew, Sjoukje Philip, Jean-Michel Soubeyroux, Brigitte Dubuisson, Nicolas Viovy, Markus Reichstein, Friederike Otto, and Iñaki Garcia de Cortazar-Atauri
Nat. Hazards Earth Syst. Sci., 23, 1045–1058, https://doi.org/10.5194/nhess-23-1045-2023, https://doi.org/10.5194/nhess-23-1045-2023, 2023
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A deep frost occurred in early April 2021, inducing severe damages in grapevine and fruit trees in France. We found that such extreme frosts occurring after the start of the growing season such as those of April 2021 are currently about 2°C colder [0.5 °C to 3.3 °C] in observations than in preindustrial climate. This observed intensification of growing-period frosts is attributable, at least in part, to human-caused climate change, making the 2021 event 50 % more likely [10 %–110 %].
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
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Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Silvia Terzago, Giulio Bongiovanni, and Jost von Hardenberg
Hydrol. Earth Syst. Sci., 27, 519–542, https://doi.org/10.5194/hess-27-519-2023, https://doi.org/10.5194/hess-27-519-2023, 2023
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Reliable seasonal forecasts of the abundance of mountain snowpack over the winter/spring ahead provide valuable information for water management, hydropower production and ski tourism. We present a climate service prototype to generate multi-model ensemble seasonal forecasts of mountain snow depth, based on Copernicus seasonal forecast system meteorological data used to force the SNOWPACK model. The prototype shows skill at predicting snow depth below and above normal and extremely dry seasons.
Ruth Stephan, Stefano Terzi, Mathilde Erfurt, Silvia Cocuccioni, Kerstin Stahl, and Marc Zebisch
Nat. Hazards Earth Syst. Sci., 23, 45–64, https://doi.org/10.5194/nhess-23-45-2023, https://doi.org/10.5194/nhess-23-45-2023, 2023
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This study maps agriculture's vulnerability to drought in the European pre-Alpine regions of Thurgau (CH) and Podravska (SI). We combine region-specific knowledge with quantitative data mapping; experts of the study regions, far apart, identified a few common but more region-specific factors that we integrated in two vulnerability scenarios. We highlight the benefits of the participatory approach in improving the quantitative results and closing the gap between science and practitioners.
Tiago Silva, Jakob Abermann, Brice Noël, Sonika Shahi, Willem Jan van de Berg, and Wolfgang Schöner
The Cryosphere, 16, 3375–3391, https://doi.org/10.5194/tc-16-3375-2022, https://doi.org/10.5194/tc-16-3375-2022, 2022
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To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.
Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie
Geosci. Model Dev., 15, 6115–6142, https://doi.org/10.5194/gmd-15-6115-2022, https://doi.org/10.5194/gmd-15-6115-2022, 2022
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CSTools (short for Climate Service Tools) is an R package that contains process-based methods for climate forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. In addition to describing the structure and methods in the package, we also present three use cases to illustrate the seasonal climate forecast post-processing for specific purposes.
Thomas Goelles, Tobias Hammer, Stefan Muckenhuber, Birgit Schlager, Jakob Abermann, Christian Bauer, Víctor J. Expósito Jiménez, Wolfgang Schöner, Markus Schratter, Benjamin Schrei, and Kim Senger
Geosci. Instrum. Method. Data Syst., 11, 247–261, https://doi.org/10.5194/gi-11-247-2022, https://doi.org/10.5194/gi-11-247-2022, 2022
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We propose a newly developed modular MObile LIdar SENsor System (MOLISENS) to enable new applications for small industrial light detection and ranging (lidar) sensors. MOLISENS supports both monitoring of dynamic processes and mobile mapping applications. The mobile mapping application of MOLISENS has been tested under various conditions, and results are shown from two surveys in the Lurgrotte cave system in Austria and a glacier cave in Longyearbreen on Svalbard.
Bruno Majone, Diego Avesani, Patrick Zulian, Aldo Fiori, and Alberto Bellin
Hydrol. Earth Syst. Sci., 26, 3863–3883, https://doi.org/10.5194/hess-26-3863-2022, https://doi.org/10.5194/hess-26-3863-2022, 2022
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In this work, we introduce a methodology for devising reliable future high streamflow scenarios from climate change simulations. The calibration of a hydrological model is carried out to maximize the probability that the modeled and observed high flow extremes belong to the same statistical population. Application to the Adige River catchment (southeastern Alps, Italy) showed that this procedure produces reliable quantiles of the annual maximum streamflow for use in assessment studies.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
Earth Syst. Dynam., 13, 1059–1075, https://doi.org/10.5194/esd-13-1059-2022, https://doi.org/10.5194/esd-13-1059-2022, 2022
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Anticipating risks related to climate extremes is critical for societal adaptation to climate change. In this study, we propose a statistical method in order to estimate future climate extremes from past observations and an ensemble of climate change simulations. We apply this approach to snow load data available in the French Alps at 1500 m elevation and find that extreme snow load is projected to decrease by −2.9 kN m−2 (−50 %) between 1986–2005 and 2080–2099 for a high-emission scenario.
Michael Matiu and Florian Hanzer
Hydrol. Earth Syst. Sci., 26, 3037–3054, https://doi.org/10.5194/hess-26-3037-2022, https://doi.org/10.5194/hess-26-3037-2022, 2022
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Regional climate models not only provide projections on temperature and precipitation, but also on snow. Here, we employed statistical post-processing using satellite observations to reduce bias and uncertainty from model projections of future snow-covered area and duration under different greenhouse gas concentration scenarios for the European Alps. Snow cover area/duration decreased overall in the future, three times more strongly with 4–5° global warming as compared to 1.5–2°.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
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Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
Yves Bühler, Peter Bebi, Marc Christen, Stefan Margreth, Lukas Stoffel, Andreas Stoffel, Christoph Marty, Gregor Schmucki, Andrin Caviezel, Roderick Kühne, Stephan Wohlwend, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 22, 1825–1843, https://doi.org/10.5194/nhess-22-1825-2022, https://doi.org/10.5194/nhess-22-1825-2022, 2022
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To calculate and visualize the potential avalanche hazard, we develop a method that automatically and efficiently pinpoints avalanche starting zones and simulate their runout for the entire canton of Grisons. The maps produced in this way highlight areas that could be endangered by avalanches and are extremely useful in multiple applications for the cantonal authorities, including the planning of new infrastructure, making alpine regions more safe.
Matthieu Vernay, Matthieu Lafaysse, Diego Monteiro, Pascal Hagenmuller, Rafife Nheili, Raphaëlle Samacoïts, Deborah Verfaillie, and Samuel Morin
Earth Syst. Sci. Data, 14, 1707–1733, https://doi.org/10.5194/essd-14-1707-2022, https://doi.org/10.5194/essd-14-1707-2022, 2022
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This paper introduces the latest version of the freely available S2M dataset which provides estimates of both meteorological and snow cover variables, as well as various avalanche hazard diagnostics at different elevations, slopes and aspects for the three main French high-elevation mountainous regions. A complete description of the system and the dataset is provided, as well as an overview of the possible uses of this dataset and an objective assessment of its limitations.
Linh N. Luu, Robert Vautard, Pascal Yiou, and Jean-Michel Soubeyroux
Earth Syst. Dynam., 13, 687–702, https://doi.org/10.5194/esd-13-687-2022, https://doi.org/10.5194/esd-13-687-2022, 2022
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This study downscales climate information from EURO-CORDEX (approx. 12 km) output to a higher horizontal resolution (approx. 3 km) for the south of France. We also propose a matrix of different indices to evaluate the high-resolution precipitation output. We find that a higher resolution reproduces more realistic extreme precipitation events at both daily and sub-daily timescales. Our results and approach are promising to apply to other Mediterranean regions and climate impact studies.
Lucas Berard-Chenu, Hugues François, Emmanuelle George, and Samuel Morin
The Cryosphere, 16, 863–881, https://doi.org/10.5194/tc-16-863-2022, https://doi.org/10.5194/tc-16-863-2022, 2022
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This study investigates the past snow reliability (1961–2019) of 16 ski resorts in the French Alps using state-of-the-art snowpack modelling. We used snowmaking investment figures to infer the evolution of snowmaking coverage at the individual ski resort level. Snowmaking improved snow reliability for the core of the winter season for the highest-elevation ski resorts. However it did not counterbalance the decreasing trend in snow cover reliability for lower-elevation ski resorts and in spring.
Achille Capelli, Franziska Koch, Patrick Henkel, Markus Lamm, Florian Appel, Christoph Marty, and Jürg Schweizer
The Cryosphere, 16, 505–531, https://doi.org/10.5194/tc-16-505-2022, https://doi.org/10.5194/tc-16-505-2022, 2022
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Snow occurrence, snow amount, snow density and liquid water content (LWC) can vary considerably with climatic conditions and elevation. We show that low-cost Global Navigation Satellite System (GNSS) sensors as GPS can be used for reliably measuring the amount of water stored in the snowpack or snow water equivalent (SWE), snow depth and the LWC under a broad range of climatic conditions met at different elevations in the Swiss Alps.
Johannes Aschauer and Christoph Marty
Geosci. Instrum. Method. Data Syst., 10, 297–312, https://doi.org/10.5194/gi-10-297-2021, https://doi.org/10.5194/gi-10-297-2021, 2021
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Methods for reconstruction of winter long data gaps in snow depth time series are compared. The methods use snow depth data from neighboring stations or calculate snow depth from temperature and precipitation data. All methods except one are able to reproduce the average snow depth and maximum snow depth in a winter reasonably well. For reconstructing the number of snow days with snow depth ≥ 1 cm, results suggest using a snow model instead of relying on data from neighboring stations.
Zacharie Barrou Dumont, Simon Gascoin, Olivier Hagolle, Michaël Ablain, Rémi Jugier, Germain Salgues, Florence Marti, Aurore Dupuis, Marie Dumont, and Samuel Morin
The Cryosphere, 15, 4975–4980, https://doi.org/10.5194/tc-15-4975-2021, https://doi.org/10.5194/tc-15-4975-2021, 2021
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Since 2020, the Copernicus High Resolution Snow & Ice Monitoring Service has distributed snow cover maps at 20 m resolution over Europe in near-real time. These products are derived from the Sentinel-2 Earth observation mission, with a revisit time of 5 d or less (cloud-permitting). Here we show the good accuracy of the snow detection over a wide range of regions in Europe, except in dense forest regions where the snow cover is hidden by the trees.
Moritz Buchmann, Michael Begert, Stefan Brönnimann, and Christoph Marty
The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, https://doi.org/10.5194/tc-15-4625-2021, 2021
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We investigated the impacts of local-scale variations by analysing snow climate indicators derived from parallel snow measurements. We found the largest relative inter-pair differences for all indicators in spring and the smallest in winter. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and provide, in combination with break-detection methods, the groundwork in view of any homogenization efforts regarding snow time series.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
The Cryosphere, 15, 4335–4356, https://doi.org/10.5194/tc-15-4335-2021, https://doi.org/10.5194/tc-15-4335-2021, 2021
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Extreme snowfall can cause major natural hazards (avalanches, winter storms) that can generate casualties and economic damage. In the French Alps, we show that between 1959 and 2019 extreme snowfall mainly decreased below 2000 m of elevation and increased above 2000 m. At 2500 m, we find a contrasting pattern: extreme snowfall decreased in the north, while it increased in the south. This pattern might be related to increasing trends in extreme snowfall observed near the Mediterranean Sea.
Pirmin Philipp Ebner, Franziska Koch, Valentina Premier, Carlo Marin, Florian Hanzer, Carlo Maria Carmagnola, Hugues François, Daniel Günther, Fabiano Monti, Olivier Hargoaa, Ulrich Strasser, Samuel Morin, and Michael Lehning
The Cryosphere, 15, 3949–3973, https://doi.org/10.5194/tc-15-3949-2021, https://doi.org/10.5194/tc-15-3949-2021, 2021
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A service to enable real-time optimization of grooming and snow-making at ski resorts was developed and evaluated using both GNSS-measured snow depth and spaceborne snow maps derived from Copernicus Sentinel-2. The correlation to the ground observation data was high. Potential sources for the overestimation of the snow depth by the simulations are mainly the impact of snow redistribution by skiers, compensation of uneven terrain, or spontaneous local adaptions of the snow management.
Harald Schellander, Michael Winkler, and Tobias Hell
Adv. Sci. Res., 18, 135–144, https://doi.org/10.5194/asr-18-135-2021, https://doi.org/10.5194/asr-18-135-2021, 2021
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Each building has to withstand a certain mass of snow. In the Alps, snow load standards are coarse, and inconsistencies at national borders are common. A new methodology to derive a snow load map for Austria is presented. It consists of modeling and spatially interpolating snow loads with modern extreme value statistics. The new approach is much more accurate than the currently used Austrian snow load map and provides a reproducible base for other countries.
Alice Crespi, Michael Matiu, Giacomo Bertoldi, Marcello Petitta, and Marc Zebisch
Earth Syst. Sci. Data, 13, 2801–2818, https://doi.org/10.5194/essd-13-2801-2021, https://doi.org/10.5194/essd-13-2801-2021, 2021
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A 250 m gridded dataset of 1980–2018 daily mean temperature and precipitation records for Trentino–South Tyrol (north-eastern Italian Alps) was derived from a quality-controlled and homogenized archive of station observations. The errors associated with the final interpolated fields were assessed and thoroughly discussed. The product will be regularly updated and is meant to support regional climate studies and local monitoring and applications in integration with other fine-resolution data.
Michael Warscher, Thomas Marke, and Ulrich Strasser
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-68, https://doi.org/10.5194/essd-2021-68, 2021
Revised manuscript not accepted
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Continuous observations of snow and climate in high altitudes are still sparse. We present data from automatic weather and snow stations in the Ötztal Alps (Austria) that include continuous recordings of snow cover properties (snow depth, water equivalent, density, solid and liquid water content, snow temperature profiles, surface temperature, snow drift). The data can be used in different scientific fields, as well as in operational applications, i.e., avalanche warning and flood forecasting.
Michael Winkler, Harald Schellander, and Stefanie Gruber
Hydrol. Earth Syst. Sci., 25, 1165–1187, https://doi.org/10.5194/hess-25-1165-2021, https://doi.org/10.5194/hess-25-1165-2021, 2021
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A new method to calculate the mass of snow is provided. It is quite simple but gives surprisingly good results. The new approach only requires regular snow depth observations to simulate respective water mass that is stored in the snow. It is called
ΔSNOW model, its code is freely available, and it can be applied in various climates. The method is especially interesting for studies on extremes (e.g., snow loads or flooding) and climate (e.g., precipitation trends).
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, https://doi.org/10.5194/hess-24-5355-2020, 2020
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The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
Nat. Hazards Earth Syst. Sci., 20, 2961–2977, https://doi.org/10.5194/nhess-20-2961-2020, https://doi.org/10.5194/nhess-20-2961-2020, 2020
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To minimize the risk of structure collapse due to extreme snow loads, structure standards rely on 50-year return levels of ground snow load (GSL), i.e. levels exceeded once every 50 years on average, that do not account for climate change. We study GSL data in the French Alps massifs from 1959 and 2019 and find that these 50-year return levels are decreasing with time between 900 and 4800 m of altitude, but they still exceed return levels of structure standards for half of the massifs at 1800 m.
Fabian Willibald, Sven Kotlarski, Adrienne Grêt-Regamey, and Ralf Ludwig
The Cryosphere, 14, 2909–2924, https://doi.org/10.5194/tc-14-2909-2020, https://doi.org/10.5194/tc-14-2909-2020, 2020
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Climate change will significantly reduce snow cover, but the extent remains disputed. We use regional climate model data as a driver for a snow model to investigate the impacts of climate change and climate variability on snow. We show that natural climate variability is a dominant source of uncertainty in future snow trends. We show that anthropogenic climate change will change the interannual variability of snow. Those factors will increase the vulnerabilities of snow-dependent economies.
Jordi Bolibar, Antoine Rabatel, Isabelle Gouttevin, and Clovis Galiez
Earth Syst. Sci. Data, 12, 1973–1983, https://doi.org/10.5194/essd-12-1973-2020, https://doi.org/10.5194/essd-12-1973-2020, 2020
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We present a dataset of annual glacier mass changes for all the 661 glaciers in the French Alps for the 1967–2015 period, reconstructed using deep learning (i.e. artificial intelligence). We estimate an average annual mass loss of –0.69 ± 0.21 m w.e., the highest being in the Chablais, Ubaye and Champsaur massifs and the lowest in the Mont Blanc, Oisans and Haute Tarentaise ranges. This dataset can be of interest to hydrology and ecology studies on glacierized catchments in the French Alps.
Silvia Terzago, Valentina Andreoli, Gabriele Arduini, Gianpaolo Balsamo, Lorenzo Campo, Claudio Cassardo, Edoardo Cremonese, Daniele Dolia, Simone Gabellani, Jost von Hardenberg, Umberto Morra di Cella, Elisa Palazzi, Gaia Piazzi, Paolo Pogliotti, and Antonello Provenzale
Hydrol. Earth Syst. Sci., 24, 4061–4090, https://doi.org/10.5194/hess-24-4061-2020, https://doi.org/10.5194/hess-24-4061-2020, 2020
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In mountain areas high-quality meteorological data to drive snow models are rarely available, so coarse-resolution data from spatial interpolation of the available in situ measurements or reanalyses are typically employed. We perform 12 experiments using six snow models with different degrees of complexity to show the impact of the accuracy of the forcing on snow depth and snow water equivalent simulations at the Alpine site of Torgnon, discussing the results in relation to the model complexity.
Thomas Mölg, Douglas R. Hardy, Emily Collier, Elena Kropač, Christina Schmid, Nicolas J. Cullen, Georg Kaser, Rainer Prinz, and Michael Winkler
Earth Syst. Dynam., 11, 653–672, https://doi.org/10.5194/esd-11-653-2020, https://doi.org/10.5194/esd-11-653-2020, 2020
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The glaciers on Kilimanjaro summit are like sample spots of the climate in the tropical mid-troposphere. Measurements of air temperature, air humidity, and precipitation with automated weather stations show that the differences in these meteorological elements between two altitudes (~ 5600 and ~ 5900 m) vary significantly over the day and the seasons, in concert with airflow dynamics around the mountain. Knowledge of these variations will improve atmosphere and cryosphere models.
Carlo Marin, Giacomo Bertoldi, Valentina Premier, Mattia Callegari, Christian Brida, Kerstin Hürkamp, Jochen Tschiersch, Marc Zebisch, and Claudia Notarnicola
The Cryosphere, 14, 935–956, https://doi.org/10.5194/tc-14-935-2020, https://doi.org/10.5194/tc-14-935-2020, 2020
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In this paper, we use for the first time the synthetic aperture radar (SAR) time series acquired by Sentinel-1 to monitor snowmelt dynamics in alpine regions. We found that the multitemporal SAR allows the identification of the three phases that characterize the melting process, i.e., moistening, ripening and runoff, in a spatial distributed way. We believe that the presented investigation could have relevant applications for monitoring and predicting the snowmelt progress over large regions.
Jordi Bolibar, Antoine Rabatel, Isabelle Gouttevin, Clovis Galiez, Thomas Condom, and Eric Sauquet
The Cryosphere, 14, 565–584, https://doi.org/10.5194/tc-14-565-2020, https://doi.org/10.5194/tc-14-565-2020, 2020
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We introduce a novel approach for simulating glacier mass balances using a deep artificial neural network (i.e. deep learning) from climate and topographical data. This has been added as a component of a new open-source parameterized glacier evolution model. Deep learning is found to outperform linear machine learning methods, mainly due to its nonlinearity. Potential applications range from regional mass balance reconstructions from observations to simulations for past and future climates.
Marco Falocchi, Werner Tirler, Lorenzo Giovannini, Elena Tomasi, Gianluca Antonacci, and Dino Zardi
Earth Syst. Sci. Data, 12, 277–291, https://doi.org/10.5194/essd-12-277-2020, https://doi.org/10.5194/essd-12-277-2020, 2020
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This paper describes a dataset of tracer concentrations and meteorological measurements collected during the Bolzano Tracer EXperiment (BTEX) to evaluate the pollutant dispersion from a waste incinerator close to Bolzano (Italian Alps).
BTEX represents one of the few experiments available in the literature performed over complex mountainous terrain to evaluate dispersion processes by means of controlled tracer releases. This dataset represents a useful benchmark for testing dispersion models.
Christian G. Andresen, David M. Lawrence, Cathy J. Wilson, A. David McGuire, Charles Koven, Kevin Schaefer, Elchin Jafarov, Shushi Peng, Xiaodong Chen, Isabelle Gouttevin, Eleanor Burke, Sarah Chadburn, Duoying Ji, Guangsheng Chen, Daniel Hayes, and Wenxin Zhang
The Cryosphere, 14, 445–459, https://doi.org/10.5194/tc-14-445-2020, https://doi.org/10.5194/tc-14-445-2020, 2020
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Widely-used land models project near-surface drying of the terrestrial Arctic despite increases in the net water balance driven by climate change. Drying was generally associated with increases of active-layer depth and permafrost thaw in a warming climate. However, models lack important mechanisms such as thermokarst and soil subsidence that will change the hydrological regime and add to the large uncertainty in the future Arctic hydrological state and the associated permafrost carbon feedback.
Ana Casanueva, Sven Kotlarski, Sixto Herrera, Andreas M. Fischer, Tord Kjellstrom, and Cornelia Schwierz
Geosci. Model Dev., 12, 3419–3438, https://doi.org/10.5194/gmd-12-3419-2019, https://doi.org/10.5194/gmd-12-3419-2019, 2019
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Given the large number of available data sets and products currently produced for climate impact studies, it is challenging to distil the most accurate and useful information for climate services. This work presents a comparison of methods widely used to generate climate projections, from different sources and at different spatial resolutions, in order to assess the role of downscaling and statistical post-processing (bias correction).
Robert Vautard, Geert Jan van Oldenborgh, Friederike E. L. Otto, Pascal Yiou, Hylke de Vries, Erik van Meijgaard, Andrew Stepek, Jean-Michel Soubeyroux, Sjoukje Philip, Sarah F. Kew, Cecilia Costella, Roop Singh, and Claudia Tebaldi
Earth Syst. Dynam., 10, 271–286, https://doi.org/10.5194/esd-10-271-2019, https://doi.org/10.5194/esd-10-271-2019, 2019
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The effect of human activities on the probability of winter wind storms like the ones that occurred in Western Europe in January 2018 is analysed using multiple model ensembles. Despite a significant probability decline in observations, we find no significant change in probabilities due to human influence on climate so far. However, such extreme events are likely to be slightly more frequent in the future. The observed decrease in storminess is likely to be due to increasing roughness.
Michael Engel, Daniele Penna, Giacomo Bertoldi, Gianluca Vignoli, Werner Tirler, and Francesco Comiti
Hydrol. Earth Syst. Sci., 23, 2041–2063, https://doi.org/10.5194/hess-23-2041-2019, https://doi.org/10.5194/hess-23-2041-2019, 2019
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Hydrometric and geochemical dynamics are controlled by interplay of meteorological conditions, topography and geological heterogeneity. Nivo-meteorological indicators (such as global solar radiation, temperature and decreasing snow depth) explain monthly conductivity and isotopic dynamics best. These insights are important for better understanding hydrochemical responses of glacierized catchments under a changing cryosphere.
Pierre Spandre, Hugues François, Deborah Verfaillie, Marc Pons, Matthieu Vernay, Matthieu Lafaysse, Emmanuelle George, and Samuel Morin
The Cryosphere, 13, 1325–1347, https://doi.org/10.5194/tc-13-1325-2019, https://doi.org/10.5194/tc-13-1325-2019, 2019
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This study investigates the snow reliability of 175 ski resorts in the Pyrenees (France, Spain and Andorra) and the French Alps under past and future conditions (1950–2100) using state-of-the-art climate projections and snowpack modelling accounting for snow management, i.e. grooming and snowmaking. The snow reliability of ski resorts shows strong elevation and regional differences, and our study quantifies changes in snow reliability induced by snowmaking under various climate scenarios.
Biagio Di Mauro, Roberto Garzonio, Micol Rossini, Gianluca Filippa, Paolo Pogliotti, Marta Galvagno, Umberto Morra di Cella, Mirco Migliavacca, Giovanni Baccolo, Massimiliano Clemenza, Barbara Delmonte, Valter Maggi, Marie Dumont, François Tuzet, Matthieu Lafaysse, Samuel Morin, Edoardo Cremonese, and Roberto Colombo
The Cryosphere, 13, 1147–1165, https://doi.org/10.5194/tc-13-1147-2019, https://doi.org/10.5194/tc-13-1147-2019, 2019
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The snow albedo reduction due to dust from arid regions alters the melting dynamics of the snowpack, resulting in earlier snowmelt. We estimate up to 38 days of anticipated snow disappearance for a season that was characterized by a strong dust deposition event. This process has a series of further impacts. For example, earlier snowmelts may alter the hydrological cycle in the Alps, induce higher sensitivity to late summer drought, and finally impact vegetation and animal phenology.
Kristyna Falatkova, Miroslav Šobr, Anton Neureiter, Wolfgang Schöner, Bohumír Janský, Hermann Häusler, Zbyněk Engel, and Vojtěch Beneš
Earth Surf. Dynam., 7, 301–320, https://doi.org/10.5194/esurf-7-301-2019, https://doi.org/10.5194/esurf-7-301-2019, 2019
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In the last 50 years the Adygine glacier has been subject to relatively fast recession comparable to other glaciers in Tien Shan. As a consequence, a three-level cascade of glacial lakes formed, two of which were categorised as having medium outburst susceptibility. By 2050, the glacier is expected to have shrunk to 56–73 % of its 2012 extent. Further development of the site will result in formation of new lakes and probably also increase of outburst susceptibility due to permafrost degradation.
Laurie Caillouet, Jean-Philippe Vidal, Eric Sauquet, Benjamin Graff, and Jean-Michel Soubeyroux
Earth Syst. Sci. Data, 11, 241–260, https://doi.org/10.5194/essd-11-241-2019, https://doi.org/10.5194/essd-11-241-2019, 2019
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SCOPE Climate is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature, and Penman–Monteith reference evapotranspiration over France. It is the first century-long gridded high-resolution homogeneous dataset available over France. It thus paves the way for studying local historical meteorological events and for assessing the local climate variability from the end of the 19th century.
Yves Lejeune, Marie Dumont, Jean-Michel Panel, Matthieu Lafaysse, Philippe Lapalus, Erwan Le Gac, Bernard Lesaffre, and Samuel Morin
Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, https://doi.org/10.5194/essd-11-71-2019, 2019
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This paper introduces and provides access to a daily (1960–2017) and an hourly (1993–2017) dataset of snow and meteorological data measured at the Col de Porte site, 1325 m a.s.l, Charteuse, France. The daily dataset can be used to quantify the effect of climate change at this site, with a reduction of the mean snow depth of 39 cm from 1960–1990 to 1990–2017. The daily and hourly datasets are useful and appropriate for driving and evaluating a snowpack model over such a long period.
Rafael Pimentel, Carlo Marín, Ludovica De Gregorio, Mattia Callegari, María J. Pérez-Palazón, Claudia Notarnicola, and María J. Polo
Proc. IAHS, 380, 67–72, https://doi.org/10.5194/piahs-380-67-2018, https://doi.org/10.5194/piahs-380-67-2018, 2018
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In Mediterranean regions, the spatiotemporal evolution of the snow cover can experiment quick changes and high frequency sensors are required to adequately monitor such shifts. This work presents a methodological approach to validate the improved MODIS daily snow cover maps, in a Sierra Nevada (southern Spain), from a reference data set obtained by Landsat TM data. The results show a significantly high correlation between the two snow map products at differents spatial scale.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Isabelle Gouttevin, Moritz Langer, Henning Löwe, Julia Boike, Martin Proksch, and Martin Schneebeli
The Cryosphere, 12, 3693–3717, https://doi.org/10.5194/tc-12-3693-2018, https://doi.org/10.5194/tc-12-3693-2018, 2018
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Snow insulates the ground from the cold air in the Arctic winter, majorly affecting permafrost. This insulation depends on snow characteristics and is poorly quantified. Here, we characterize it at a carbon-rich permafrost site, using a recent technique that retrieves the 3-D structure of snow and its thermal properties. We adapt a snowpack model enabling the simulation of this insulation over a whole winter. We estimate that local snow variations induce up to a 6 °C spread in soil temperatures.
Silvia Terzago, Elisa Palazzi, and Jost von Hardenberg
Nat. Hazards Earth Syst. Sci., 18, 2825–2840, https://doi.org/10.5194/nhess-18-2825-2018, https://doi.org/10.5194/nhess-18-2825-2018, 2018
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This study proposes a modification to a stochastic downscaling method for precipitation, RainFARM, to improve the representation of the statistics of the daily precipitation at fine scales (1 km) in mountain areas. This method has been demonstrated in the Alps and it has been found to reconstruct small-scale precipitation distribution. It can be employed in a number of applications, including the analysis of extreme events and their statistics and hydrometeorological hazards.
Frank Techel, Christoph Mitterer, Elisabetta Ceaglio, Cécile Coléou, Samuel Morin, Francesca Rastelli, and Ross S. Purves
Nat. Hazards Earth Syst. Sci., 18, 2697–2716, https://doi.org/10.5194/nhess-18-2697-2018, https://doi.org/10.5194/nhess-18-2697-2018, 2018
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In 1993, the European Avalanche Warning Services agreed upon a common danger scale to describe the regional avalanche hazard: the European Avalanche Danger Scale. Using published avalanche forecasts, we explored whether forecasters use the scale consistently. We noted differences in the use of the danger levels, some of which could be linked to the size of the regions a regional danger level is issued for. We recommend further harmonizing the avalanche forecast products in the Alps.
Alexandra Touzeau, Amaëlle Landais, Samuel Morin, Laurent Arnaud, and Ghislain Picard
Geosci. Model Dev., 11, 2393–2418, https://doi.org/10.5194/gmd-11-2393-2018, https://doi.org/10.5194/gmd-11-2393-2018, 2018
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We introduced a new module of water vapor diffusion into the snowpack model Crocus. Vapor transport locally modifies the density of snow layers, possibly influencing compaction. It also affects the original isotopic signature of snow layers. We also introduced water isotopes (𝛿18O) in the model. Over 10 years, the modeled attenuation of isotopic variations due to vapor diffusion is 7–18 % lower than the observations. Thus, other processes are required to explain the total attenuation.
Graziella Devoli, Davide Tiranti, Roberto Cremonini, Monica Sund, and Søren Boje
Nat. Hazards Earth Syst. Sci., 18, 1351–1372, https://doi.org/10.5194/nhess-18-1351-2018, https://doi.org/10.5194/nhess-18-1351-2018, 2018
Kay Helfricht, Lea Hartl, Roland Koch, Christoph Marty, and Marc Olefs
Hydrol. Earth Syst. Sci., 22, 2655–2668, https://doi.org/10.5194/hess-22-2655-2018, https://doi.org/10.5194/hess-22-2655-2018, 2018
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We calculated hourly new snow densities from automated measurements. This time interval reduces the influence of settling of the freshly deposited snow. We found an average new snow density of 68 kg m−3. The observed variability could not be described using different parameterizations, but a relationship to temperature is partly visible at hourly intervals. Wind speed is a crucial parameter for the inter-station variability. Our findings are relevant for snow models working on hourly timescales.
Marion Réveillet, Delphine Six, Christian Vincent, Antoine Rabatel, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Vincent Vionnet, and Maxime Litt
The Cryosphere, 12, 1367–1386, https://doi.org/10.5194/tc-12-1367-2018, https://doi.org/10.5194/tc-12-1367-2018, 2018
Deborah Verfaillie, Matthieu Lafaysse, Michel Déqué, Nicolas Eckert, Yves Lejeune, and Samuel Morin
The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, https://doi.org/10.5194/tc-12-1249-2018, 2018
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This article addresses local changes of seasonal snow and its meteorological drivers, at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps, for the period 1960–2100. We use an ensemble of adjusted RCM outputs consistent with IPCC AR5 GCM outputs (RCPs 2.6, 4.5 and 8.5) and the snowpack model Crocus. Beyond scenario-based approach, global temperature levels on the order of 1.5 °C and 2 °C above preindustrial levels correspond to 25 and 32% reduction of mean snow depth.
Julia Boike, Inge Juszak, Stephan Lange, Sarah Chadburn, Eleanor Burke, Pier Paul Overduin, Kurt Roth, Olaf Ippisch, Niko Bornemann, Lielle Stern, Isabelle Gouttevin, Ernst Hauber, and Sebastian Westermann
Earth Syst. Sci. Data, 10, 355–390, https://doi.org/10.5194/essd-10-355-2018, https://doi.org/10.5194/essd-10-355-2018, 2018
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A 20-year data record from the Bayelva site at Ny-Ålesund, Svalbard, is presented on meteorology, energy balance components, surface and subsurface observations. This paper presents the data set, instrumentation, calibration, processing and data quality control. The data show that mean annual, summer and winter soil temperature data from shallow to deeper depths have been warming over the period of record, indicating the degradation and loss of permafrost at this site.
Martin Beniston, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, Florie Giacona, Christian Hauck, Matthias Huss, Hendrik Huwald, Michael Lehning, Juan-Ignacio López-Moreno, Jan Magnusson, Christoph Marty, Enrique Morán-Tejéda, Samuel Morin, Mohamed Naaim, Antonello Provenzale, Antoine Rabatel, Delphine Six, Johann Stötter, Ulrich Strasser, Silvia Terzago, and Christian Vincent
The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, https://doi.org/10.5194/tc-12-759-2018, 2018
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This paper makes a rather exhaustive overview of current knowledge of past, current, and future aspects of cryospheric issues in continental Europe and makes a number of reflections of areas of uncertainty requiring more attention in both scientific and policy terms. The review paper is completed by a bibliography containing 350 recent references that will certainly be of value to scholars engaged in the fields of glacier, snow, and permafrost research.
Florian Hanzer, Kristian Förster, Johanna Nemec, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 22, 1593–1614, https://doi.org/10.5194/hess-22-1593-2018, https://doi.org/10.5194/hess-22-1593-2018, 2018
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Climate change effects on snow, glaciers, and hydrology are investigated for the Ötztal Alps region (Austria) using a hydroclimatological model driven by climate projections for the RCP2.6, RCP4.5, and RCP8.5 scenarios. The results show declining snow amounts and strongly retreating glaciers with moderate effects on catchment runoff until the mid-21st century, whereas annual runoff volumes decrease strongly towards the end of the century.
Kristian Förster, Florian Hanzer, Elena Stoll, Adam A. Scaife, Craig MacLachlan, Johannes Schöber, Matthias Huttenlau, Stefan Achleitner, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 22, 1157–1173, https://doi.org/10.5194/hess-22-1157-2018, https://doi.org/10.5194/hess-22-1157-2018, 2018
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This article presents predictability analyses of snow accumulation for the upcoming winter season. The results achieved using two coupled atmosphere–ocean general circulation models and a water balance model show that the tendency of snow water equivalent anomalies (i.e. the sign of anomalies) is correctly predicted in up to 11 of 13 years. The results suggest that some seasonal predictions may be capable of predicting tendencies of hydrological model storages in parts of Europe.
Ulrich Strasser, Thomas Marke, Ludwig Braun, Heidi Escher-Vetter, Irmgard Juen, Michael Kuhn, Fabien Maussion, Christoph Mayer, Lindsey Nicholson, Klaus Niedertscheider, Rudolf Sailer, Johann Stötter, Markus Weber, and Georg Kaser
Earth Syst. Sci. Data, 10, 151–171, https://doi.org/10.5194/essd-10-151-2018, https://doi.org/10.5194/essd-10-151-2018, 2018
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A hydrometeorological and glaciological data set is presented with recordings from several research sites in the Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria). The data sets are spanning 150 years and represent a unique pool of high mountain observations, enabling combined research of atmospheric, cryospheric and hydrological processes in complex terrain, and the development of state-of-the-art hydroclimatological and glacier mass balance models.
Prisco Frei, Sven Kotlarski, Mark A. Liniger, and Christoph Schär
The Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, https://doi.org/10.5194/tc-12-1-2018, 2018
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Snowfall is central to Alpine environments, and its future changes will be associated with pronounced impacts. We here assess future snowfall changes in the European Alps based on an ensemble of state-of-the-art regional climate model experiments and on two different greenhouse gas emission scenarios. The results reveal pronounced changes in the Alpine snowfall climate with considerable snowfall reductions at low and mid-elevations but also snowfall increases at high elevations in midwinter.
Deborah Verfaillie, Michel Déqué, Samuel Morin, and Matthieu Lafaysse
Geosci. Model Dev., 10, 4257–4283, https://doi.org/10.5194/gmd-10-4257-2017, https://doi.org/10.5194/gmd-10-4257-2017, 2017
Francois Tuzet, Marie Dumont, Matthieu Lafaysse, Ghislain Picard, Laurent Arnaud, Didier Voisin, Yves Lejeune, Luc Charrois, Pierre Nabat, and Samuel Morin
The Cryosphere, 11, 2633–2653, https://doi.org/10.5194/tc-11-2633-2017, https://doi.org/10.5194/tc-11-2633-2017, 2017
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Light-absorbing impurities deposited on snow, such as soot or dust, strongly modify its evolution. We implemented impurity deposition and evolution in a detailed snowpack model, thereby expanding the reach of such models into addressing the subtle interplays between snow physics and impurities' optical properties. Model results were evaluated based on innovative field observations at an Alpine site. This allows future investigations in the fields of climate, hydrology and avalanche prediction.
Jesús Revuelto, Grégoire Lecourt, Matthieu Lafaysse, Isabella Zin, Luc Charrois, Vincent Vionnet, Marie Dumont, Antoine Rabatel, Delphine Six, Thomas Condom, Samuel Morin, Alessandra Viani, and Pascal Sirguey
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-184, https://doi.org/10.5194/tc-2017-184, 2017
Revised manuscript not accepted
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We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope.
Christopher J. L. D'Amboise, Karsten Müller, Laurent Oxarango, Samuel Morin, and Thomas V. Schuler
Geosci. Model Dev., 10, 3547–3566, https://doi.org/10.5194/gmd-10-3547-2017, https://doi.org/10.5194/gmd-10-3547-2017, 2017
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We present a new water percolation routine added to the Crocus model. The new routine is physically based, describing motion of water through a layered snowpack considering capillary-driven and gravity flow. We tested the routine on two data sets. Wet-snow layers were able to reach higher saturations than the empirical routine. Meaningful applicability is limited until new and better parameterizations of water retention are developed, and feedbacks are adjusted to handle higher saturations.
Mathieu Barrere, Florent Domine, Bertrand Decharme, Samuel Morin, Vincent Vionnet, and Matthieu Lafaysse
Geosci. Model Dev., 10, 3461–3479, https://doi.org/10.5194/gmd-10-3461-2017, https://doi.org/10.5194/gmd-10-3461-2017, 2017
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Global warming projections still suffer from a limited representation of the permafrost–carbon feedback. This study assesses the capacity of snow-soil coupled models to simulate the permafrost thermal regime at Bylot Island, a high Arctic site. Significant flaws are found in the description of Arctic snow properties, resulting in erroneous heat transfers between the soil and the snow in simulations. Improved snow schemes are needed to accurately predict the future of permafrost.
Silvia Terzago, Jost von Hardenberg, Elisa Palazzi, and Antonello Provenzale
The Cryosphere, 11, 1625–1645, https://doi.org/10.5194/tc-11-1625-2017, https://doi.org/10.5194/tc-11-1625-2017, 2017
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The estimate of the current and future conditions of snow resources in mountain areas depends on the availability of reliable fine-resolution data sets and of climate models capable of properly representing snow processes and snow–climate interactions. This work considers the snow water equivalent data sets from remote sensing, reanalyses, regional and global climate models available for the Alps and explores their ability to provide a coherent view of the snowpack features and its changes.
Matthieu Lafaysse, Bertrand Cluzet, Marie Dumont, Yves Lejeune, Vincent Vionnet, and Samuel Morin
The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, https://doi.org/10.5194/tc-11-1173-2017, 2017
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Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC by implementing new representations of different physical processes in a coupled multilayer ground/snowpack model. This system is a promising tool to integrate snow modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack modelling applications.
Marie Dumont, Laurent Arnaud, Ghislain Picard, Quentin Libois, Yves Lejeune, Pierre Nabat, Didier Voisin, and Samuel Morin
The Cryosphere, 11, 1091–1110, https://doi.org/10.5194/tc-11-1091-2017, https://doi.org/10.5194/tc-11-1091-2017, 2017
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Snow spectral albedo in the visible/near-infrared range has been continuously measured during a winter season at Col de Porte alpine site (French Alps; 45.30° N, 5.77°E; 1325 m a.s.l.). This study highlights that the variations of spectral albedo can be successfully explained by variations of the following snow surface variables: snow-specific surface area, effective light-absorbing impurities content, presence of liquid water and slope.
Pierre Spandre, Hugues François, Emmanuel Thibert, Samuel Morin, and Emmanuelle George-Marcelpoil
The Cryosphere, 11, 891–909, https://doi.org/10.5194/tc-11-891-2017, https://doi.org/10.5194/tc-11-891-2017, 2017
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The production of machine-made snow is generalized in ski resorts and represents the most common adaptation method to mitigate effects of climate variability and its projected changes. However, the actual snow mass that can be recovered from a given water mass used for snowmaking remains poorly known. All results were consistent with 60 % (±10 %) of the water mass found as snow within the edge of the ski slope, with most of the lost fraction of water being due to site-dependent characteristics.
Christoph Marty, Sebastian Schlögl, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 517–529, https://doi.org/10.5194/tc-11-517-2017, https://doi.org/10.5194/tc-11-517-2017, 2017
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We simulate the future snow cover in the Alps with the help of a snow model, which is fed by projected temperature and precipitation changes from a large set of climate models. The results demonstrate that snow below 1000 m is probably a rare guest at the end of the century. Moreover, even above 3000 m the simulations show a drastic decrease in snow depth. However, the results reveal that the projected snow cover reduction can be mitigated by 50 % if we manage to keep global warming below 2°.
Daniele Penna, Michael Engel, Giacomo Bertoldi, and Francesco Comiti
Hydrol. Earth Syst. Sci., 21, 23–41, https://doi.org/10.5194/hess-21-23-2017, https://doi.org/10.5194/hess-21-23-2017, 2017
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In this research we used environmental tracers in the Saldur River catchment, Italian Alps to obtain new insight into the hydrology of glacierized catchments. We analysed the spatio-temporal variability of the tracer signature within the catchment, distinguished the contribution of groundwater, glacier melt and snowmelt to stream discharge, identified the sources of uncertainty in the estimation of streamflow components and presented a paradigm of hydrological function of glacierized catchments.
Jan Schmieder, Florian Hanzer, Thomas Marke, Jakob Garvelmann, Michael Warscher, Harald Kunstmann, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 20, 5015–5033, https://doi.org/10.5194/hess-20-5015-2016, https://doi.org/10.5194/hess-20-5015-2016, 2016
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We present novel research on the spatiotemporal variability of snowmelt isotopic content in a high-elevation catchment with complex terrain
to improve the isotope-based hydrograph separation method. A modelling approach was used to weight the plot-scale snowmelt isotopic content
with melt rates for the north- and south-facing slope. The investigations showed that it is important to sample at least north- and south-facing slopes,
because of distinct isotopic differences between both slopes.
Florent Domine, Mathieu Barrere, and Samuel Morin
Biogeosciences, 13, 6471–6486, https://doi.org/10.5194/bg-13-6471-2016, https://doi.org/10.5194/bg-13-6471-2016, 2016
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Warming-induced shrub growth in the Arctic traps snow and modifies snow properties, hence the permafrost thermal regime. In the Canadian high Arctic, we measured snow physical properties in the presence and absence of willow shrubs (Salix richardsonii). Shrubs dramatically reduce snow density and thermal conductivity, seriously limiting soil winter cooling. Simulations taking into account only winter changes show that shrub growth leads to a ground winter warming of up to 13 °C.
Antoine Marmy, Jan Rajczak, Reynald Delaloye, Christin Hilbich, Martin Hoelzle, Sven Kotlarski, Christophe Lambiel, Jeannette Noetzli, Marcia Phillips, Nadine Salzmann, Benno Staub, and Christian Hauck
The Cryosphere, 10, 2693–2719, https://doi.org/10.5194/tc-10-2693-2016, https://doi.org/10.5194/tc-10-2693-2016, 2016
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This paper presents a new semi-automated method to calibrate the 1-D soil model COUP. It is the first time (as far as we know) that this approach is developed for mountain permafrost. It is applied at six test sites in the Swiss Alps. In a second step, the calibrated model is used for RCM-based simulations with specific downscaling of RCM data to the borehole scale. We show projections of the permafrost evolution at the six sites until the end of the century and according to the A1B scenario.
Mattia Vaccarono, Renzo Bechini, Chandra V. Chandrasekar, Roberto Cremonini, and Claudio Cassardo
Atmos. Meas. Tech., 9, 5367–5383, https://doi.org/10.5194/amt-9-5367-2016, https://doi.org/10.5194/amt-9-5367-2016, 2016
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The data quality of radars must be ensured and continuously monitored. The aim of this paper is to provide an integrated approach able to monitor the calibration of operational dual-polarization radars. The set of methods considered appears suitable to establish an online tool to monitor the stability of the radar calibration with an accuracy of about 2 dB. This is considered adequate to automatically detect any unexpected change in the radar system requiring further investigations.
Kristian Förster, Felix Oesterle, Florian Hanzer, Johannes Schöber, Matthias Huttenlau, and Ulrich Strasser
Proc. IAHS, 374, 143–150, https://doi.org/10.5194/piahs-374-143-2016, https://doi.org/10.5194/piahs-374-143-2016, 2016
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We present first results of a coupled seasonal prediction modelling system that runs at monthly time steps for a small catchment in the Austrian Alps. Meteorological forecasts are obtained from the CFSv2 model which are downscaled to the Alpine Water balance And Runoff Estimation model AWARE. Initial conditions are obtained using the physically based, hydro-climatological snow model AMUNDSEN. In this way, ensemble simulations of the coupled model are compared to observations.
Deborah Verfaillie, Michel Déqué, Samuel Morin, and Matthieu Lafaysse
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-168, https://doi.org/10.5194/gmd-2016-168, 2016
Revised manuscript not accepted
Gregor Laaha, Juraj Parajka, Alberto Viglione, Daniel Koffler, Klaus Haslinger, Wolfgang Schöner, Judith Zehetgruber, and Günter Blöschl
Hydrol. Earth Syst. Sci., 20, 3967–3985, https://doi.org/10.5194/hess-20-3967-2016, https://doi.org/10.5194/hess-20-3967-2016, 2016
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We present a framework for assessing climate impacts on future low flows that combines different sources of information termed pillars. To illustrate the framework, three pillars are chosen: low-flow observation, climate observations and climate projections. By combining different sources of information we aim at more robust projections than obtained from each pillar alone. The viability of the framework is illustrated for four example catchments from Austria.
Florian Hanzer, Kay Helfricht, Thomas Marke, and Ulrich Strasser
The Cryosphere, 10, 1859–1881, https://doi.org/10.5194/tc-10-1859-2016, https://doi.org/10.5194/tc-10-1859-2016, 2016
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The hydroclimatological model AMUNDSEN is set up to simulate snow and ice accumulation, ablation, and runoff for a study region in the Ötztal Alps (Austria) in the period 1997–2013. A new validation concept is introduced and demonstrated by evaluating the model performance using several independent data sets, e.g. snow depth measurements, satellite-derived snow maps, lidar data, glacier mass balances, and runoff measurements.
Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
The Cryosphere, 10, 1721–1737, https://doi.org/10.5194/tc-10-1721-2016, https://doi.org/10.5194/tc-10-1721-2016, 2016
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The winter snow insulation is a key process for air–soil temperature coupling and is relevant for permafrost simulations. Differences in simulated air–soil temperature relationships and their modulation by climate conditions are found to be related to the snow model physics. Generally, models with better performance apply multilayer snow schemes.
Ghislain Picard, Laurent Arnaud, Jean-Michel Panel, and Samuel Morin
The Cryosphere, 10, 1495–1511, https://doi.org/10.5194/tc-10-1495-2016, https://doi.org/10.5194/tc-10-1495-2016, 2016
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A cost-effective automatic laser scan has been built to measure snow depth spatio-temporal variations. Deployed in the Alps and in Dome C (Antarctica), two devices acquired daily scans covering a surface area of 100–150 m2. The precision and long-term stability of the measurements are about 1 cm and the accuracy is better than 5 cm. These high performances are particularly suited at Dome C, where it was possible to reveal that most of the accumulation in the year 2015 stems from a single event.
Kristian Förster, Florian Hanzer, Benjamin Winter, Thomas Marke, and Ulrich Strasser
Geosci. Model Dev., 9, 2315–2333, https://doi.org/10.5194/gmd-9-2315-2016, https://doi.org/10.5194/gmd-9-2315-2016, 2016
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For many applications in geoscientific modelling hourly meteorological time series are required, which generally cover shorter periods of time compared to daily time series. We present an open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST) capable of disaggregating temperature, precipitation, humidity, wind speed, and shortwave radiation (i.e. making 24 out of 1 value). Results indicate a good reconstruction of diurnal features at five sites in different climates.
Juraj Parajka, Alfred Paul Blaschke, Günter Blöschl, Klaus Haslinger, Gerold Hepp, Gregor Laaha, Wolfgang Schöner, Helene Trautvetter, Alberto Viglione, and Matthias Zessner
Hydrol. Earth Syst. Sci., 20, 2085–2101, https://doi.org/10.5194/hess-20-2085-2016, https://doi.org/10.5194/hess-20-2085-2016, 2016
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Streamflow estimation during low-flow conditions is important for estimation of environmental flows, effluent water quality, hydropower operations, etc. However, it is not clear how the uncertainties in assumptions used in the projections translate into uncertainty of estimated future low flows. The objective of the study is to explore the relative role of hydrologic model calibration and climate scenarios in the uncertainty of low-flow projections in Austria.
Sebastiano Piccolroaz, Michele Di Lazzaro, Antonio Zarlenga, Bruno Majone, Alberto Bellin, and Aldo Fiori
Hydrol. Earth Syst. Sci., 20, 2047–2061, https://doi.org/10.5194/hess-20-2047-2016, https://doi.org/10.5194/hess-20-2047-2016, 2016
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We present HYPERstream, an innovative, parsimonious, and computationally efficient streamflow routing scheme based on the width function instantaneous unit hydrograph theory. HYPERstream is designed to be easily coupled with climate models and to preserve the geomorphological dispersion of the river network, irrespective of the model grid size. This makes HYPERstream well suited for multi-scale applications (from catchment up to continental scale) and to investigate extreme events (e.g. floods).
Luc Charrois, Emmanuel Cosme, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Quentin Libois, and Ghislain Picard
The Cryosphere, 10, 1021–1038, https://doi.org/10.5194/tc-10-1021-2016, https://doi.org/10.5194/tc-10-1021-2016, 2016
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This study investigates the assimilation of optical reflectances, snowdepth data and both combined into a multilayer snowpack model. Data assimilation is performed with an ensemble-based method, the Sequential Importance Resampling Particle filter. Experiments assimilating only synthetic data are conducted at one point in the French Alps, the Col du Lautaret, over five hydrological years. Results of the assimilation experiments show improvements of the snowpack bulk variables estimates.
Bertrand Decharme, Eric Brun, Aaron Boone, Christine Delire, Patrick Le Moigne, and Samuel Morin
The Cryosphere, 10, 853–877, https://doi.org/10.5194/tc-10-853-2016, https://doi.org/10.5194/tc-10-853-2016, 2016
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We analyze how snowpack processes and soil properties impact the soil temperature profiles over northern Eurasian regions using a land surface model. A correct representation of snow compaction is critical in winter while snow albedo is dominant in spring. In summer, soil temperature is more affected by soil organic carbon content, which strongly influences the maximum thaw depth in permafrost regions. This work was done to improve the representation of boreal region processes in climate models.
Christian Viel, Anne-Lise Beaulant, Jean-Michel Soubeyroux, and Jean-Pierre Céron
Adv. Sci. Res., 13, 51–55, https://doi.org/10.5194/asr-13-51-2016, https://doi.org/10.5194/asr-13-51-2016, 2016
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The use of seasonal forecast, combined with an impact model, could have a tangible positive effect on long-term decisions. This paper presents such an example for the management of a dam in France, studied in the framework of the FP7 project EUPORIAS. It details the assessment process, lead in collaboration with the stakeholder, especially the evaluation of the decision itself. It demonstrates that the introduction of relevant climate products could significantly improve existing practice.
Ursula Weiser, Marc Olefs, Wolfgang Schöner, Gernot Weyss, and Bernhard Hynek
The Cryosphere, 10, 775–790, https://doi.org/10.5194/tc-10-775-2016, https://doi.org/10.5194/tc-10-775-2016, 2016
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Geometric effects induced by tilt errors lead to erroneous measurement of snow albedo. These errors are corrected where tilts of sensors and slopes are unknown. Atmospheric parameters are taken from a nearby reference measurement or a radiation model. The developed model is fitted to the measured data to determine tilts and directions which vary daily due to changing atmospheric conditions and snow cover. The results show an obvious under- or overestimation of albedo depending on the slope direction.
Marc Olefs, Dietmar J. Baumgartner, Friedrich Obleitner, Christoph Bichler, Ulrich Foelsche, Helga Pietsch, Harald E. Rieder, Philipp Weihs, Florian Geyer, Thomas Haiden, and Wolfgang Schöner
Atmos. Meas. Tech., 9, 1513–1531, https://doi.org/10.5194/amt-9-1513-2016, https://doi.org/10.5194/amt-9-1513-2016, 2016
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We present the Austrian RADiation monitoring network (ARAD) that has been established to advance national climate monitoring and to support satellite retrieval, atmospheric modeling and solar energy techniques' development. Measurements cover the downwelling solar and thermal infrared radiation using instruments according to Baseline Surface Radiation Network (BSRN) standards. The paper outlines the aims and scopes of ARAD, its measurement and calibration standards, methods and strategies.
T. Marke, E. Mair, K. Förster, F. Hanzer, J. Garvelmann, S. Pohl, M. Warscher, and U. Strasser
Geosci. Model Dev., 9, 633–646, https://doi.org/10.5194/gmd-9-633-2016, https://doi.org/10.5194/gmd-9-633-2016, 2016
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This article describes the extension of the ESCIMO.spread spreadsheet-based point energy balance snow model by (i) an advanced approach for precipitation phase detection, (ii) a concept for cold and liquid water storage consideration and (iii) a canopy sub-model that allows one to quantify the effect of a forest canopy on the meteorological conditions inside the forest as well as the simulation of snow accumulation and ablation inside a forest stand.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
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Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
Q. Libois, G. Picard, L. Arnaud, M. Dumont, M. Lafaysse, S. Morin, and E. Lefebvre
The Cryosphere, 9, 2383–2398, https://doi.org/10.5194/tc-9-2383-2015, https://doi.org/10.5194/tc-9-2383-2015, 2015
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The albedo and surface energy budget of the Antarctic Plateau are largely determined by snow specific surface area. The latter experiences substantial daily-to-seasonal variations in response to meteorological conditions. In particular, it decreases by a factor three in summer, causing a drop in albedo. These variations are monitored from in situ and remote sensing observations at Dome C. For the first time, they are also simulated with a snowpack evolution model adapted to Antarctic conditions.
J. Erbland, J. Savarino, S. Morin, J. L. France, M. M. Frey, and M. D. King
Atmos. Chem. Phys., 15, 12079–12113, https://doi.org/10.5194/acp-15-12079-2015, https://doi.org/10.5194/acp-15-12079-2015, 2015
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In this paper, we describe the development of a numerical model which aims at representing nitrate recycling at the air-snow interface on the East Antarctic Plateau. Stable isotopes are used as diagnostic and evaluation tools by comparing the model's results to recent field measurements of nitrate and key atmospheric species at Dome C, Antarctica. From sensitivity tests conducted with the model, we propose a framework for the interpretation of the nitrate isotope record in deep ice cores.
R. Marti, S. Gascoin, T. Houet, O. Ribière, D. Laffly, T. Condom, S. Monnier, M. Schmutz, C. Camerlynck, J. P. Tihay, J. M. Soubeyroux, and P. René
The Cryosphere, 9, 1773–1795, https://doi.org/10.5194/tc-9-1773-2015, https://doi.org/10.5194/tc-9-1773-2015, 2015
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Pyrenean glaciers are currently the southernmost glaciers in Europe. Using an exceptional archive of historical data sets and recent accurate observations, we propose the reconstruction of the length, area, elevation, and mass balance of Ossoue Glacier (French Pyrenees) since the Little Ice Age. We show that its evolution is in good agreement with climatic data. Assuming that the current ablation rate stays constant, Ossoue Glacier will disappear midway through the 21st century.
Y. Brugnara, R. Auchmann, S. Brönnimann, R. J. Allan, I. Auer, M. Barriendos, H. Bergström, J. Bhend, R. Brázdil, G. P. Compo, R. C. Cornes, F. Dominguez-Castro, A. F. V. van Engelen, J. Filipiak, J. Holopainen, S. Jourdain, M. Kunz, J. Luterbacher, M. Maugeri, L. Mercalli, A. Moberg, C. J. Mock, G. Pichard, L. Řezníčková, G. van der Schrier, V. Slonosky, Z. Ustrnul, M. A. Valente, A. Wypych, and X. Yin
Clim. Past, 11, 1027–1047, https://doi.org/10.5194/cp-11-1027-2015, https://doi.org/10.5194/cp-11-1027-2015, 2015
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A data set of instrumental pressure and temperature observations for the early instrumental period (before ca. 1850) is described. This is the result of a digitisation effort involving the period immediately after the eruption of Mount Tambora in 1815, combined with the collection of already available sub-daily time series. The highest data availability is therefore for the years 1815 to 1817. An analysis of pressure variability and of case studies in Europe is performed for that period.
F. Besson, E. Bazile, C. Soci, J.-M. Soubeyroux, G. Ouzeau, and M. Perrin
Adv. Sci. Res., 12, 137–140, https://doi.org/10.5194/asr-12-137-2015, https://doi.org/10.5194/asr-12-137-2015, 2015
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Due to the evolution of the observation network, hourly 2m temperature analysis performed by reanalysis systems shows temporal inhomogeneities. In this study, the diurnal temperature cycle has been reconstructed for stations which only record extreme temperatures to produce new “pseudo” hourly temperature observations. Then they are provided to analysis systems; the results have shown that it enables reducing the bias in temperature analysis.
F. Domine, M. Barrere, D. Sarrazin, S. Morin, and L. Arnaud
The Cryosphere, 9, 1265–1276, https://doi.org/10.5194/tc-9-1265-2015, https://doi.org/10.5194/tc-9-1265-2015, 2015
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The thermal conductivity of Arctic snow strongly impacts ground temperature, nutrient recycling and vegetation growth. We have monitored the thermal conductivity of snow in low-Arctic shrub tundra for two consecutive winters using heated needle probes. We observe very different thermal conductivity evolutions in both winters studied, with more extensive melting in the second winter. Results illustrate the effect of vegetation on snow properties and the need to include it in snow physics models.
D. Penna, M. Engel, L. Mao, A. Dell'Agnese, G. Bertoldi, and F. Comiti
Hydrol. Earth Syst. Sci., 18, 5271–5288, https://doi.org/10.5194/hess-18-5271-2014, https://doi.org/10.5194/hess-18-5271-2014, 2014
K. Förster, G. Meon, T. Marke, and U. Strasser
Hydrol. Earth Syst. Sci., 18, 4703–4720, https://doi.org/10.5194/hess-18-4703-2014, https://doi.org/10.5194/hess-18-4703-2014, 2014
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Four snow models of different complexity (temperature-index vs. energy balance models) are compared using observed and dynamically downscaled atmospheric analysis data as input. Biases in simulated precipitation lead to lower model performance. However, simulated meteorological conditions are proven to be a valuable meteorological data source as they provide model input in regions with limited availability of observations and allow the application of energy balance approaches.
X. V. Phan, L. Ferro-Famil, M. Gay, Y. Durand, M. Dumont, S. Morin, S. Allain, G. D'Urso, and A. Girard
The Cryosphere, 8, 1975–1987, https://doi.org/10.5194/tc-8-1975-2014, https://doi.org/10.5194/tc-8-1975-2014, 2014
S. Hasson, V. Lucarini, M. R. Khan, M. Petitta, T. Bolch, and G. Gioli
Hydrol. Earth Syst. Sci., 18, 4077–4100, https://doi.org/10.5194/hess-18-4077-2014, https://doi.org/10.5194/hess-18-4077-2014, 2014
L. Laiti, D. Zardi, M. de Franceschi, G. Rampanelli, and L. Giovannini
Atmos. Chem. Phys., 14, 9771–9786, https://doi.org/10.5194/acp-14-9771-2014, https://doi.org/10.5194/acp-14-9771-2014, 2014
L. Ferrero, M. Castelli, B. S. Ferrini, M. Moscatelli, M. G. Perrone, G. Sangiorgi, L. D'Angelo, G. Rovelli, B. Moroni, F. Scardazza, G. Močnik, E. Bolzacchini, M. Petitta, and D. Cappelletti
Atmos. Chem. Phys., 14, 9641–9664, https://doi.org/10.5194/acp-14-9641-2014, https://doi.org/10.5194/acp-14-9641-2014, 2014
H. Castebrunet, N. Eckert, G. Giraud, Y. Durand, and S. Morin
The Cryosphere, 8, 1673–1697, https://doi.org/10.5194/tc-8-1673-2014, https://doi.org/10.5194/tc-8-1673-2014, 2014
P. Nicolle, R. Pushpalatha, C. Perrin, D. François, D. Thiéry, T. Mathevet, M. Le Lay, F. Besson, J.-M. Soubeyroux, C. Viel, F. Regimbeau, V. Andréassian, P. Maugis, B. Augeard, and E. Morice
Hydrol. Earth Syst. Sci., 18, 2829–2857, https://doi.org/10.5194/hess-18-2829-2014, https://doi.org/10.5194/hess-18-2829-2014, 2014
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
M. Dietzel, A. Leis, R. Abdalla, J. Savarino, S. Morin, M. E. Böttcher, and S. Köhler
Biogeosciences, 11, 3149–3161, https://doi.org/10.5194/bg-11-3149-2014, https://doi.org/10.5194/bg-11-3149-2014, 2014
C. M. Carmagnola, S. Morin, M. Lafaysse, F. Domine, B. Lesaffre, Y. Lejeune, G. Picard, and L. Arnaud
The Cryosphere, 8, 417–437, https://doi.org/10.5194/tc-8-417-2014, https://doi.org/10.5194/tc-8-417-2014, 2014
L. Carturan, R. Filippi, R. Seppi, P. Gabrielli, C. Notarnicola, L. Bertoldi, F. Paul, P. Rastner, F. Cazorzi, R. Dinale, and G. Dalla Fontana
The Cryosphere, 7, 1339–1359, https://doi.org/10.5194/tc-7-1339-2013, https://doi.org/10.5194/tc-7-1339-2013, 2013
J. Erbland, W. C. Vicars, J. Savarino, S. Morin, M. M. Frey, D. Frosini, E. Vince, and J. M. F. Martins
Atmos. Chem. Phys., 13, 6403–6419, https://doi.org/10.5194/acp-13-6403-2013, https://doi.org/10.5194/acp-13-6403-2013, 2013
E. Mair, G. Bertoldi, G. Leitinger, S. Della Chiesa, G. Niedrist, and U. Tappeiner
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-8683-2013, https://doi.org/10.5194/hessd-10-8683-2013, 2013
Preprint withdrawn
Related subject area
Discipline: Snow | Subject: Seasonal Snow
Snow depth sensitivity to mean temperature, precipitation, and elevation in the Austrian and Swiss Alps
Use of multiple reference data sources to cross-validate gridded snow water equivalent products over North America
Characterization of non-Gaussianity in the snow distributions of various landscapes
A simple snow temperature index model exposes discrepancies between reanalysis snow water equivalent products
Which global reanalysis dataset has better representativeness in snow cover on the Tibetan Plateau?
Spatial and temporal changes in autumn Eurasian snow cover and its relationship with the Arctic Oscillation
Historical snowfall measurements in the Central and Southern Apennine Mountains: climatology, variability and trend
Snow depth in high-resolution regional climate model simulations over southern Germany – suitable for extremes and impact-related research?
Snow water equivalent retrieval over Idaho – Part 2: Using L-band UAVSAR repeat-pass interferometry
Benchmarking of SWE products based on outcomes of the SnowPEx+ Intercomparison Project
Spatiotemporal snow water storage uncertainty in the midlatitude American Cordillera
Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982–2018
Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets
Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas
Change in the potential snowfall phenology: past, present, and future in the Chinese Tianshan mountainous region, Central Asia
The benefits of homogenising snow depth series – Impacts on decadal trends and extremes for Switzerland
Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain
Impact of measured and simulated tundra snowpack properties on heat transfer
Homogeneity assessment of Swiss snow depth series: comparison of break detection capabilities of (semi-)automatic homogenization methods
Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network
Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982–2014
Multilayer observation and estimation of the snowpack cold content in a humid boreal coniferous forest of eastern Canada
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset
Local-scale variability of seasonal mean and extreme values of in situ snow depth and snowfall measurements
Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
Quantification of the radiative impact of light-absorbing particles during two contrasted snow seasons at Col du Lautaret (2058 m a.s.l., French Alps)
Snow depth estimation and historical data reconstruction over China based on a random forest machine learning approach
Evaluation of long-term Northern Hemisphere snow water equivalent products
Towards a webcam-based snow cover monitoring network: methodology and evaluation
Simulated single-layer forest canopies delay Northern Hemisphere snowmelt
Converting snow depth to snow water equivalent using climatological variables
Avalanches and micrometeorology driving mass and energy balance of the lowest perennial ice field of the Alps: a case study
The optical characteristics and sources of chromophoric dissolved organic matter (CDOM) in seasonal snow of northwestern China
Brief Communication: Early season snowpack loss and implications for oversnow vehicle recreation travel planning
Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps
Matthew Switanek, Gernot Resch, Andreas Gobiet, Daniel Günther, Christoph Marty, and Wolfgang Schöner
The Cryosphere, 18, 6005–6026, https://doi.org/10.5194/tc-18-6005-2024, https://doi.org/10.5194/tc-18-6005-2024, 2024
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Snow depth plays an important role in water resources, mountain tourism, and hazard management across the European Alps. Our study uses station-based historical observations to quantify how changes in temperature and precipitation affect average seasonal snow depth. We find that the relationship between these variables has been surprisingly robust over the last 120 years. This allows us to more accurately estimate how future climate will affect seasonal snow depth in different elevation zones.
Colleen Mortimer, Lawrence Mudryk, Eunsang Cho, Chris Derksen, Mike Brady, and Carrie Vuyovich
The Cryosphere, 18, 5619–5639, https://doi.org/10.5194/tc-18-5619-2024, https://doi.org/10.5194/tc-18-5619-2024, 2024
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Ground measurements of snow water equivalent (SWE) are vital for understanding the accuracy of large-scale estimates from satellites and climate models. We compare two types of measurements – snow courses and airborne gamma SWE estimates – and analyze how measurement type impacts the accuracy assessment of gridded SWE products. We use this analysis to produce a combined reference SWE dataset for North America, applicable for future gridded SWE product evaluations and other applications.
Noriaki Ohara, Andrew D. Parsekian, Benjamin M. Jones, Rodrigo C. Rangel, Kenneth M. Hinkel, and Rui A. P. Perdigão
The Cryosphere, 18, 5139–5152, https://doi.org/10.5194/tc-18-5139-2024, https://doi.org/10.5194/tc-18-5139-2024, 2024
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Snow distribution characterization is essential for accurate snow water estimation for water resource prediction from existing in situ observations and remote-sensing data at a finite spatial resolution. Four different observed snow distribution datasets were analyzed for Gaussianity. We found that non-Gaussianity of snow distribution is a signature of the wind redistribution effect. Generally, seasonal snowpack can be approximated well by a Gaussian distribution for a fully snow-covered area.
Aleksandra Elias Chereque, Paul J. Kushner, Lawrence Mudryk, Chris Derksen, and Colleen Mortimer
The Cryosphere, 18, 4955–4969, https://doi.org/10.5194/tc-18-4955-2024, https://doi.org/10.5194/tc-18-4955-2024, 2024
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We look at three commonly used snow depth datasets that are produced through a combination of snow modelling and historical measurements (reanalysis). When compared with each other, these datasets have differences that arise for various reasons. We show that a simple snow model can be used to examine these inconsistencies and highlight issues. This method indicates that one of the complex datasets should be excluded from further studies.
Shirui Yan, Yang Chen, Yaliang Hou, Kexin Liu, Xuejing Li, Yuxuan Xing, Dongyou Wu, Jiecan Cui, Yue Zhou, Wei Pu, and Xin Wang
The Cryosphere, 18, 4089–4109, https://doi.org/10.5194/tc-18-4089-2024, https://doi.org/10.5194/tc-18-4089-2024, 2024
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The snow cover over the Tibetan Plateau (TP) plays a role in climate and hydrological systems, yet there are uncertainties in snow cover fraction (SCF) estimations within reanalysis datasets. This study utilized the Snow Property Inversion from Remote Sensing (SPIReS) SCF data to assess the accuracy of eight widely used reanalysis SCF datasets over the TP. Factors contributing to uncertainties were analyzed, and a combined averaging method was employed to provide optimized SCF simulations.
Gareth J. Marshall
EGUsphere, https://doi.org/10.5194/egusphere-2024-1892, https://doi.org/10.5194/egusphere-2024-1892, 2024
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Eurasian autumn snow cover (SC) can influence Northern Hemisphere weather in the following winter by affecting the Arctic Oscillation (AO) mode of atmospheric variability. We find that the relationship between the rate of October snow advance and the AO is predominantly of opposite sign between east and west Eurasia. Periods when the SC advance is strongly related to the AO, and thus might be used for weather prediction, occur when the sign of the relationship is reversed in one of the regions.
Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon
EGUsphere, https://doi.org/10.5194/egusphere-2024-1056, https://doi.org/10.5194/egusphere-2024-1056, 2024
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This study offers a “journey through time” to discover historical information about snow precipitation in the Italian Apennines. In this area, in the second half of past century, a gradual decline in snow persistence on the ground as well as in the frequency of occurrence of snowfall events has been observed, especially in sites located above 1000 m a.s.l.. The old data rescued in this study strongly enhances our knowledge about past snowfall variability and climate in the Mediterranean area.
Benjamin Poschlod and Anne Sophie Daloz
The Cryosphere, 18, 1959–1981, https://doi.org/10.5194/tc-18-1959-2024, https://doi.org/10.5194/tc-18-1959-2024, 2024
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Information about snow depth is important within climate research but also many other sectors, such as tourism, mobility, civil engineering, and ecology. Climate models often feature a spatial resolution which is too coarse to investigate snow depth. Here, we analyse high-resolution simulations and identify added value compared to a coarser-resolution state-of-the-art product. Also, daily snow depth extremes are well reproduced by two models.
Zachary Hoppinen, Shadi Oveisgharan, Hans-Peter Marshall, Ross Mower, Kelly Elder, and Carrie Vuyovich
The Cryosphere, 18, 575–592, https://doi.org/10.5194/tc-18-575-2024, https://doi.org/10.5194/tc-18-575-2024, 2024
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We used changes in radar echo travel time from multiple airborne flights to estimate changes in snow depths across Idaho for two winters. We compared our radar-derived retrievals to snow pits, weather stations, and a 100 m resolution numerical snow model. We had a strong Pearson correlation and root mean squared error of 10 cm relative to in situ measurements. Our retrievals also correlated well with our model, especially in regions of dry snow and low tree coverage.
Lawrence Mudryk, Colleen Mortimer, Chris Derksen, Aleksandra Elias Chereque, and Paul Kushner
EGUsphere, https://doi.org/10.5194/egusphere-2023-3014, https://doi.org/10.5194/egusphere-2023-3014, 2024
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We evaluate and rank 23 products that estimate historical snow amounts. The evaluation uses new a set of ground measurements with improved spatial coverage enabling evaluation across both mountain and non-mountain regions. Performance measures vary tremendously across the products: while most perform reasonably in non-mountain regions, accurate representation of snow amounts in mountain regions and of historical trends is much more variable.
Yiwen Fang, Yufei Liu, Dongyue Li, Haorui Sun, and Steven A. Margulis
The Cryosphere, 17, 5175–5195, https://doi.org/10.5194/tc-17-5175-2023, https://doi.org/10.5194/tc-17-5175-2023, 2023
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Using newly developed snow reanalysis datasets as references, snow water storage is at high uncertainty among commonly used global products in the Andes and low-resolution products in the western United States, where snow is the key element of water resources. In addition to precipitation, elevation differences and model mechanism variances drive snow uncertainty. This work provides insights for research applying these products and generating future products in areas with limited in situ data.
Kerttu Kouki, Kari Luojus, and Aku Riihelä
The Cryosphere, 17, 5007–5026, https://doi.org/10.5194/tc-17-5007-2023, https://doi.org/10.5194/tc-17-5007-2023, 2023
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We evaluated snow cover properties in state-of-the-art reanalyses (ERA5 and ERA5-Land) with satellite-based datasets. Both ERA5 and ERA5-Land overestimate snow mass, whereas albedo estimates are more consistent between the datasets. Snow cover extent (SCE) is accurately described in ERA5-Land, while ERA5 shows larger SCE than the satellite-based datasets. The trends in snow mass, SCE, and albedo are mostly negative in 1982–2018, and the negative trends become more apparent when spring advances.
Diego Monteiro and Samuel Morin
The Cryosphere, 17, 3617–3660, https://doi.org/10.5194/tc-17-3617-2023, https://doi.org/10.5194/tc-17-3617-2023, 2023
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Beyond directly using in situ observations, often sparsely available in mountain regions, climate model simulations and so-called reanalyses are increasingly used for climate change impact studies. Here we evaluate such datasets in the European Alps from 1950 to 2020, with a focus on snow cover information and its main drivers: air temperature and precipitation. In terms of variability and trends, we identify several limitations and provide recommendations for future use of these datasets.
Leon J. Bührle, Mauro Marty, Lucie A. Eberhard, Andreas Stoffel, Elisabeth D. Hafner, and Yves Bühler
The Cryosphere, 17, 3383–3408, https://doi.org/10.5194/tc-17-3383-2023, https://doi.org/10.5194/tc-17-3383-2023, 2023
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Information on the snow depth distribution is crucial for numerous applications in high-mountain regions. However, only specific measurements can accurately map the present variability of snow depths within complex terrain. In this study, we show the reliable processing of images from aeroplane to large (> 100 km2) detailed and accurate snow depth maps around Davos (CH). We use these maps to describe the existing snow depth distribution, other special features and potential applications.
Xuemei Li, Xinyu Liu, Kaixin Zhao, Xu Zhang, and Lanhai Li
The Cryosphere, 17, 2437–2453, https://doi.org/10.5194/tc-17-2437-2023, https://doi.org/10.5194/tc-17-2437-2023, 2023
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Quantifying change in the potential snowfall phenology (PSP) is an important area of research for understanding regional climate change past, present, and future. However, few studies have focused on the PSP and its change in alpine mountainous regions. We proposed three innovative indicators to characterize the PSP and its spatial–temporal variation. Our study provides a novel approach to understanding PSP in alpine mountainous regions and can be easily extended to other snow-dominated regions.
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
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Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Zachary S. Miller, Erich H. Peitzsch, Eric A. Sproles, Karl W. Birkeland, and Ross T. Palomaki
The Cryosphere, 16, 4907–4930, https://doi.org/10.5194/tc-16-4907-2022, https://doi.org/10.5194/tc-16-4907-2022, 2022
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Snow depth varies across steep, complex mountain landscapes due to interactions between dynamic natural processes. Our study of a winter time series of high-resolution snow depth maps found that spatial resolutions greater than 0.5 m do not capture the complete patterns of snow depth spatial variability at a couloir study site in the Bridger Range of Montana, USA. The results of this research have the potential to reduce uncertainty associated with snowpack and snow water resource analysis.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, and Julia Boike
The Cryosphere, 16, 4201–4222, https://doi.org/10.5194/tc-16-4201-2022, https://doi.org/10.5194/tc-16-4201-2022, 2022
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Measurements of the properties of the snow and soil were compared to simulations of the Community Land Model to see how well the model represents snow insulation. Simulations underestimated snow thermal conductivity and wintertime soil temperatures. We test two approaches to reduce the transfer of heat through the snowpack and bring simulated soil temperatures closer to measurements, with an alternative parameterisation of snow thermal conductivity being more appropriate.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
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Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont
The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022, https://doi.org/10.5194/tc-16-1281-2022, 2022
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The mountainous snow cover is highly variable at all temporal and spatial scales. Snow cover models suffer from large errors, while snowpack observations are sparse. Data assimilation combines them into a better estimate of the snow cover. A major challenge is to propagate information from observed into unobserved areas. This paper presents a spatialized version of the particle filter, in which information from in situ snow depth observations is successfully used to constrain nearby simulations.
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022, https://doi.org/10.5194/tc-16-1007-2022, 2022
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We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.
Achut Parajuli, Daniel F. Nadeau, François Anctil, and Marco Alves
The Cryosphere, 15, 5371–5386, https://doi.org/10.5194/tc-15-5371-2021, https://doi.org/10.5194/tc-15-5371-2021, 2021
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Cold content is the energy required to attain an isothermal (0 °C) state and resulting in the snow surface melt. This study focuses on determining the multi-layer cold content (30 min time steps) relying on field measurements, snow temperature profile, and empirical formulation in four distinct forest sites of Montmorency Forest, eastern Canada. We present novel research where the effect of forest structure, local topography, and meteorological conditions on cold content variability is explored.
Yufei Liu, Yiwen Fang, and Steven A. Margulis
The Cryosphere, 15, 5261–5280, https://doi.org/10.5194/tc-15-5261-2021, https://doi.org/10.5194/tc-15-5261-2021, 2021
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We examined the spatiotemporal distribution of stored water in the seasonal snowpack over High Mountain Asia, based on a new snow reanalysis dataset. The dataset was derived utilizing satellite-observed snow information, which spans across 18 water years, at a high spatial (~ 500 m) and temporal (daily) resolution. Snow mass and snow storage distribution over space and time are analyzed in this paper, which brings new insights into understanding the snowpack variability over this region.
Moritz Buchmann, Michael Begert, Stefan Brönnimann, and Christoph Marty
The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, https://doi.org/10.5194/tc-15-4625-2021, 2021
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We investigated the impacts of local-scale variations by analysing snow climate indicators derived from parallel snow measurements. We found the largest relative inter-pair differences for all indicators in spring and the smallest in winter. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and provide, in combination with break-detection methods, the groundwork in view of any homogenization efforts regarding snow time series.
Rhae Sung Kim, Sujay Kumar, Carrie Vuyovich, Paul Houser, Jessica Lundquist, Lawrence Mudryk, Michael Durand, Ana Barros, Edward J. Kim, Barton A. Forman, Ethan D. Gutmann, Melissa L. Wrzesien, Camille Garnaud, Melody Sandells, Hans-Peter Marshall, Nicoleta Cristea, Justin M. Pflug, Jeremy Johnston, Yueqian Cao, David Mocko, and Shugong Wang
The Cryosphere, 15, 771–791, https://doi.org/10.5194/tc-15-771-2021, https://doi.org/10.5194/tc-15-771-2021, 2021
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High SWE uncertainty is observed in mountainous and forested regions, highlighting the need for high-resolution snow observations in these regions. Substantial uncertainty in snow water storage in Tundra regions and the dominance of water storage in these regions points to the need for high-accuracy snow estimation. Finally, snow measurements during the melt season are most needed at high latitudes, whereas observations at near peak snow accumulations are most beneficial over the midlatitudes.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
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This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
Jianwei Yang, Lingmei Jiang, Kari Luojus, Jinmei Pan, Juha Lemmetyinen, Matias Takala, and Shengli Wu
The Cryosphere, 14, 1763–1778, https://doi.org/10.5194/tc-14-1763-2020, https://doi.org/10.5194/tc-14-1763-2020, 2020
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There are many challenges for accurate snow depth estimation using passive microwave data. Machine learning (ML) techniques are deemed to be powerful tools for establishing nonlinear relations between independent variables and a given target variable. In this study, we investigate the potential capability of the random forest (RF) model on snow depth estimation at temporal and spatial scales. The result indicates that the fitted RF algorithms perform better on temporal than spatial scales.
Colleen Mortimer, Lawrence Mudryk, Chris Derksen, Kari Luojus, Ross Brown, Richard Kelly, and Marco Tedesco
The Cryosphere, 14, 1579–1594, https://doi.org/10.5194/tc-14-1579-2020, https://doi.org/10.5194/tc-14-1579-2020, 2020
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Existing stand-alone passive microwave SWE products have markedly different climatological SWE patterns compared to reanalysis-based datasets. The AMSR-E SWE has low spatial and temporal correlations with the four reanalysis-based products evaluated and GlobSnow and perform poorly in comparisons with snow transect data from Finland, Russia, and Canada. There is better agreement with in situ data when multiple SWE products, excluding the stand-alone passive microwave SWE products, are combined.
Céline Portenier, Fabia Hüsler, Stefan Härer, and Stefan Wunderle
The Cryosphere, 14, 1409–1423, https://doi.org/10.5194/tc-14-1409-2020, https://doi.org/10.5194/tc-14-1409-2020, 2020
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We present a method to derive snow cover maps from freely available webcam images in the Swiss Alps. With marginal manual user input, we can transform a webcam image into a georeferenced map and therewith perform snow cover analyses with a high spatiotemporal resolution over a large area. Our evaluation has shown that webcams could not only serve as a reference for improved validation of satellite-based approaches, but also complement satellite-based snow cover retrieval.
Markus Todt, Nick Rutter, Christopher G. Fletcher, and Leanne M. Wake
The Cryosphere, 13, 3077–3091, https://doi.org/10.5194/tc-13-3077-2019, https://doi.org/10.5194/tc-13-3077-2019, 2019
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Vegetation is often represented by a single layer in global land models. Studies have found deficient simulation of thermal radiation beneath forest canopies when represented by single-layer vegetation. This study corrects thermal radiation in forests for a global land model using single-layer vegetation in order to assess the effect of deficient thermal radiation on snow cover and snowmelt. Results indicate that single-layer vegetation causes snow in forests to be too cold and melt too late.
David F. Hill, Elizabeth A. Burakowski, Ryan L. Crumley, Julia Keon, J. Michelle Hu, Anthony A. Arendt, Katreen Wikstrom Jones, and Gabriel J. Wolken
The Cryosphere, 13, 1767–1784, https://doi.org/10.5194/tc-13-1767-2019, https://doi.org/10.5194/tc-13-1767-2019, 2019
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We present a new statistical model for converting snow depths to water equivalent. The only variables required are snow depth, day of year, and location. We use the location to look up climatological parameters such as mean winter precipitation and mean temperature difference (difference between hottest month and coldest month). The model is simple by design so that it can be applied to depth measurements anywhere, anytime. The model is shown to perform better than other widely used approaches.
Rebecca Mott, Andreas Wolf, Maximilian Kehl, Harald Kunstmann, Michael Warscher, and Thomas Grünewald
The Cryosphere, 13, 1247–1265, https://doi.org/10.5194/tc-13-1247-2019, https://doi.org/10.5194/tc-13-1247-2019, 2019
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The mass balance of very small glaciers is often governed by anomalous snow accumulation, winter precipitation being multiplied by snow redistribution processes, or by suppressed snow ablation driven by micrometeorological effects lowering net radiation and turbulent heat exchange. In this study we discuss the relative contribution of snow accumulation (avalanches) versus micrometeorology (katabatic flow) on the mass balance of the lowest perennial ice field of the Alps, the Ice Chapel.
Yue Zhou, Hui Wen, Jun Liu, Wei Pu, Qingcai Chen, and Xin Wang
The Cryosphere, 13, 157–175, https://doi.org/10.5194/tc-13-157-2019, https://doi.org/10.5194/tc-13-157-2019, 2019
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We first investigated the optical characteristics and potential sources of chromophoric dissolved organic matter (CDOM) in seasonal snow over northwestern China. The abundance of CDOM showed regional variation. At some sites strongly influenced by local soil, the absorption of CDOM cannot be neglected compared to black carbon. We found two humic-like and one protein-like fluorophores in snow. The major sources of snow CDOM were soil, biomass burning, and anthropogenic pollution.
Benjamin J. Hatchett and Hilary G. Eisen
The Cryosphere, 13, 21–28, https://doi.org/10.5194/tc-13-21-2019, https://doi.org/10.5194/tc-13-21-2019, 2019
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We examine the timing of early season snowpack relevant to oversnow vehicle (OSV) recreation over the past 3 decades in the Lake Tahoe region (USA). Data from two independent data sources suggest that the timing of achieving sufficient snowpack has shifted later by 2 weeks. Increasing rainfall and more dry days play a role in the later onset. Adaptation strategies are provided for winter travel management planning to address negative impacts of loss of early season snowpack for OSV usage.
Deborah Verfaillie, Matthieu Lafaysse, Michel Déqué, Nicolas Eckert, Yves Lejeune, and Samuel Morin
The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, https://doi.org/10.5194/tc-12-1249-2018, 2018
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This article addresses local changes of seasonal snow and its meteorological drivers, at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps, for the period 1960–2100. We use an ensemble of adjusted RCM outputs consistent with IPCC AR5 GCM outputs (RCPs 2.6, 4.5 and 8.5) and the snowpack model Crocus. Beyond scenario-based approach, global temperature levels on the order of 1.5 °C and 2 °C above preindustrial levels correspond to 25 and 32% reduction of mean snow depth.
Cited articles
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A new instrumental precipitation dataset for the greater alpine region for the period 1800–2002,
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Auer, I., Böhm, R., Jurkovic, A., Lipa, W., Orlik, A., Potzmann, R., Schöner, W., Ungersböck, M., Matulla, C., Briffa, K., Jones, P., Efthymiadis, D., Brunetti, M., Nanni, T., Maugeri, M., Mercalli, L., Mestre, O., Moisselin, J.-M., Begert, M., Müller-Westermeier, G., Kveton, V., Bochnicek, O., Stastny, P., Lapin, M., Szalai, S., Szentimrey, T., Cegnar, T., Dolinar, M., Gajic-Capka, M., Zaninovic, K., Majstorovic, Z., and Nieplova, E.: HISTALP—historical instrumental climatological surface time series of the Greater Alpine Region,
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Short summary
The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
The first Alpine-wide assessment of station snow depth has been enabled by a collaborative...
