Articles | Volume 19, issue 7
https://doi.org/10.5194/tc-19-2407-2025
© Author(s) 2025. 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-19-2407-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Jul 2025
Research article |
| 04 Jul 2025
| 04 Jul 2025
Trends in the annual snow melt-out day over the French Alps and Pyrenees from 38 years of high-resolution satellite data (1986–2023)
Zacharie Barrou Dumont
CORRESPONDING AUTHOR
Centre d'Etudes Spatiales de la Biosphère, CESBIO, CNES/CNRS/IRD/UT3 Paul Sabatier, Toulouse, France
Magellium, Ramonville, France
Simon Gascoin
CORRESPONDING AUTHOR
Centre d'Etudes Spatiales de la Biosphère, CESBIO, CNES/CNRS/IRD/UT3 Paul Sabatier, Toulouse, France
Jordi Inglada
Centre d'Etudes Spatiales de la Biosphère, CESBIO, CNES/CNRS/IRD/UT3 Paul Sabatier, Toulouse, France
Andreas Dietz
German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Muenchener Strasse 20, 82234 Wessling, Germany
Jonas Köhler
German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Muenchener Strasse 20, 82234 Wessling, Germany
Matthieu Lafaysse
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etude de la Neige, Grenoble, France
Diego Monteiro
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etude de la Neige, Grenoble, France
Carlo Carmagnola
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etude de la Neige, Grenoble, France
Arthur Bayle
Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, Laboratoire d'Ecologie Alpine (LECA), 38000 Grenoble, France
Jean-Pierre Dedieu
Institute of Environmental Geosciences (IGE), Université Grenoble Alpes/CNRS/Grenoble INP/INRAE/IRD, Grenoble, France
Olivier Hagolle
Centre d'Etudes Spatiales de la Biosphère, CESBIO, CNES/CNRS/IRD/UT3 Paul Sabatier, Toulouse, France
Philippe Choler
Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, Laboratoire d'Ecologie Alpine (LECA), 38000 Grenoble, France
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Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
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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César Deschamps-Berger, Simon Gascoin, David Shean, Hannah Besso, Ambroise Guiot, and Juan Ignacio López-Moreno
The Cryosphere, 17, 2779–2792, https://doi.org/10.5194/tc-17-2779-2023, https://doi.org/10.5194/tc-17-2779-2023, 2023
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The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.
Arthur Bayle, Bradley Z. Carlson, Anaïs Zimmer, Sophie Vallée, Antoine Rabatel, Edoardo Cremonese, Gianluca Filippa, Cédric Dentant, Christophe Randin, Andrea Mainetti, Erwan Roussel, Simon Gascoin, Dov Corenblit, and Philippe Choler
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Oscar Dick, Léo Viallon-Galinier, François Tuzet, Pascal Hagenmuller, Mathieu Fructus, Benjamin Reuter, Matthieu Lafaysse, and Marie Dumont
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Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327, https://doi.org/10.5194/nhess-22-3309-2022, https://doi.org/10.5194/nhess-22-3309-2022, 2022
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Georg Lackner, Florent Domine, Daniel F. Nadeau, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 3357–3373, https://doi.org/10.5194/tc-16-3357-2022, https://doi.org/10.5194/tc-16-3357-2022, 2022
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We compared the snowpack at two sites separated by less than 1 km, one in shrub tundra and the other one within the boreal forest. Even though the snowpack was twice as thick at the forested site, we found evidence that the vertical transport of water vapor from the bottom of the snowpack to its surface was important at both sites. The snow model Crocus simulates no water vapor fluxes and consequently failed to correctly simulate the observed density profiles.
Joëlle Voglimacci-Stephanopoli, Anna Wendleder, Hugues Lantuit, Alexandre Langlois, Samuel Stettner, Andreas Schmitt, Jean-Pierre Dedieu, Achim Roth, and Alain Royer
The Cryosphere, 16, 2163–2181, https://doi.org/10.5194/tc-16-2163-2022, https://doi.org/10.5194/tc-16-2163-2022, 2022
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Changes in the state of the snowpack in the context of observed global warming must be considered to improve our understanding of the processes within the cryosphere. This study aims to characterize an arctic snowpack using the TerraSAR-X satellite. Using a high-spatial-resolution vegetation classification, we were able to quantify the variability in snow depth, as well as the topographic soil wetness index, which provided a better understanding of the electromagnetic wave–ground interaction.
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.
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.
Georg Lackner, Florent Domine, Daniel F. Nadeau, Annie-Claude Parent, François Anctil, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 127–142, https://doi.org/10.5194/tc-16-127-2022, https://doi.org/10.5194/tc-16-127-2022, 2022
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The surface energy budget is the sum of all incoming and outgoing energy fluxes at the Earth's surface and has a key role in the climate. We measured all these fluxes for an Arctic snowpack and found that most incoming energy from radiation is counterbalanced by thermal radiation and heat convection while sublimation was negligible. Overall, the snow model Crocus was able to simulate the observed energy fluxes well.
Mariel C. Dirscherl, Andreas J. Dietz, and Claudia Kuenzer
The Cryosphere, 15, 5205–5226, https://doi.org/10.5194/tc-15-5205-2021, https://doi.org/10.5194/tc-15-5205-2021, 2021
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We provide novel insight into the temporal evolution of supraglacial lakes across six major Antarctic ice shelves in 2015–2021. For Antarctic Peninsula ice shelves, we observe extensive meltwater ponding during the 2019–2020 and 2020–2021 summers. Over East Antarctica, lakes were widespread during 2016–2019 and at a minimum in 2020–2021. We investigate environmental controls, revealing lake ponding to be coupled to atmospheric modes, the near-surface climate and the local glaciological setting.
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.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
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The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Guillaume Evin, Matthieu Lafaysse, Maxime Taillardat, and Michaël Zamo
Nonlin. Processes Geophys., 28, 467–480, https://doi.org/10.5194/npg-28-467-2021, https://doi.org/10.5194/npg-28-467-2021, 2021
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Forecasting the height of new snow is essential for avalanche hazard surveys, road and ski resort management, tourism attractiveness, etc. Météo-France operates a probabilistic forecasting system using a numerical weather prediction system and a snowpack model. It provides better forecasts than direct diagnostics but exhibits significant biases. Post-processing methods can be applied to provide automatic forecasting products from this system.
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.
Esteban Alonso-González, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, and Simon Gascoin
Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, https://doi.org/10.5194/hess-25-4455-2021, 2021
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Snow water resources represent a key hydrological resource for the Mediterranean regions, where most of the precipitation falls during the winter months. This is the case for Lebanon, where snowpack represents 31 % of the spring flow. We have used models to generate snow information corrected by means of remote sensing snow cover retrievals. Our results highlight the high temporal variability in the snowpack in Lebanon and its sensitivity to further warming caused by its hypsography.
Celia A. Baumhoer, Andreas J. Dietz, Christof Kneisel, Heiko Paeth, and Claudia Kuenzer
The Cryosphere, 15, 2357–2381, https://doi.org/10.5194/tc-15-2357-2021, https://doi.org/10.5194/tc-15-2357-2021, 2021
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We present a record of circum-Antarctic glacier and ice shelf front change over the last two decades in combination with potential environmental variables forcing frontal retreat. Along the Antarctic coastline, glacier and ice shelf front retreat dominated between 1997–2008 and advance between 2009–2018. Decreasing sea ice days, intense snowmelt, weakening easterly winds, and relative changes in sea surface temperature were identified as enabling factors for glacier and ice shelf front retreat.
Andreas Kääb, Mylène Jacquemart, Adrien Gilbert, Silvan Leinss, Luc Girod, Christian Huggel, Daniel Falaschi, Felipe Ugalde, Dmitry Petrakov, Sergey Chernomorets, Mikhail Dokukin, Frank Paul, Simon Gascoin, Etienne Berthier, and Jeffrey S. Kargel
The Cryosphere, 15, 1751–1785, https://doi.org/10.5194/tc-15-1751-2021, https://doi.org/10.5194/tc-15-1751-2021, 2021
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Hardly recognized so far, giant catastrophic detachments of glaciers are a rare but great potential for loss of lives and massive damage in mountain regions. Several of the events compiled in our study involve volumes (up to 100 million m3 and more), avalanche speeds (up to 300 km/h), and reaches (tens of kilometres) that are hard to imagine. We show that current climate change is able to enhance associated hazards. For the first time, we elaborate a set of factors that could cause these events.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev., 14, 1595–1614, https://doi.org/10.5194/gmd-14-1595-2021, https://doi.org/10.5194/gmd-14-1595-2021, 2021
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In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
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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.
Vincent Vionnet, Christopher B. Marsh, Brian Menounos, Simon Gascoin, Nicholas E. Wayand, Joseph Shea, Kriti Mukherjee, and John W. Pomeroy
The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, https://doi.org/10.5194/tc-15-743-2021, 2021
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Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
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.
El Mahdi El Khalki, Yves Tramblay, Christian Massari, Luca Brocca, Vincent Simonneaux, Simon Gascoin, and Mohamed El Mehdi Saidi
Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, https://doi.org/10.5194/nhess-20-2591-2020, 2020
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In North Africa, the vulnerability to floods is high, and there is a need to improve the flood-forecasting systems. Remote-sensing and reanalysis data can palliate the lack of in situ measurements, in particular for soil moisture, which is a crucial parameter to consider when modeling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modeling in Morocco.
César Deschamps-Berger, Simon Gascoin, Etienne Berthier, Jeffrey Deems, Ethan Gutmann, Amaury Dehecq, David Shean, and Marie Dumont
The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, https://doi.org/10.5194/tc-14-2925-2020, 2020
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We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it with accurate airborne laser-scanning measurements in the Sierra Nevada, USA. We find that satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountains.
Patrick Le Moigne, François Besson, Eric Martin, Julien Boé, Aaron Boone, Bertrand Decharme, Pierre Etchevers, Stéphanie Faroux, Florence Habets, Matthieu Lafaysse, Delphine Leroux, and Fabienne Rousset-Regimbeau
Geosci. Model Dev., 13, 3925–3946, https://doi.org/10.5194/gmd-13-3925-2020, https://doi.org/10.5194/gmd-13-3925-2020, 2020
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The study describes how a hydrometeorological model, operational at Météo-France, has been improved. Particular emphasis is placed on the impact of climatic data, surface, and soil parametrizations on the model results. Model simulations and evaluations carried out on a variety of measurements of river flows and snow depths are presented. All improvements in climate, surface data, and model physics have a positive impact on system performance.
C. Abou Chakra, J. Somma, S. Gascoin, P. Fanise, and L. Drapeau
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 119–125, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-119-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-119-2020, 2020
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
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The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Abbas Fayad and Simon Gascoin
Hydrol. Earth Syst. Sci., 24, 1527–1542, https://doi.org/10.5194/hess-24-1527-2020, https://doi.org/10.5194/hess-24-1527-2020, 2020
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Seasonal snowpack is an essential water resource in Mediterranean mountains. Here, we look at the role of water percolation in simulating snow mass (SWE), for the first time, in Mount Lebanon. We use SnowModel, a distributed snow model, forced by station data. The main sources of uncertainty were attributed to rain–snow partitioning, transient winter snowmelt, and the subpixel snow cover. Yet, we show that a process-based model is suitable to simulate wet snowpack in Mediterranean mountains.
Marion Réveillet, Shelley MacDonell, Simon Gascoin, Christophe Kinnard, Stef Lhermitte, and Nicole Schaffer
The Cryosphere, 14, 147–163, https://doi.org/10.5194/tc-14-147-2020, https://doi.org/10.5194/tc-14-147-2020, 2020
Jari-Pekka Nousu, Matthieu Lafaysse, Matthieu Vernay, Joseph Bellier, Guillaume Evin, and Bruno Joly
Nonlin. Processes Geophys., 26, 339–357, https://doi.org/10.5194/npg-26-339-2019, https://doi.org/10.5194/npg-26-339-2019, 2019
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Forecasting the height of new snow is crucial for avalanche hazard, road viability, ski resorts and tourism. The numerical models suffer from systematic and significant errors which are misleading for the final users. Here, we applied for the first time a state-of-the-art statistical method to correct ensemble numerical forecasts of the height of new snow from their statistical link with measurements in French Alps and Pyrenees. Thus the realism of automatic forecasts can be quickly improved.
S. Ferrant, A. Selles, M. Le Page, A. AlBitar, S. Mermoz, S. Gascoin, A. Bouvet, S. Ahmed, and Y. Kerr
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W6, 285–292, https://doi.org/10.5194/isprs-archives-XLII-3-W6-285-2019, https://doi.org/10.5194/isprs-archives-XLII-3-W6-285-2019, 2019
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.
Simon Gascoin, Manuel Grizonnet, Marine Bouchet, Germain Salgues, and Olivier Hagolle
Earth Syst. Sci. Data, 11, 493–514, https://doi.org/10.5194/essd-11-493-2019, https://doi.org/10.5194/essd-11-493-2019, 2019
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The Sentinel-2 satellite mission allows the observation of the land surface at unprecedented resolutions (20 m every 5 days). The frequency of observations can be further increased with Landsat-8. Here we describe a new collection of snow maps made from Sentinel-2 and Landsat-8 and evaluate their accuracy. The data are routinely produced over several mountain areas and freely distributed via http://theia.cnes.fr. These new data could unlock advances in our understanding of mountain ecosystems.
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.
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.
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.
Adrien Gilbert, Silvan Leinss, Jeffrey Kargel, Andreas Kääb, Simon Gascoin, Gregory Leonard, Etienne Berthier, Alina Karki, and Tandong Yao
The Cryosphere, 12, 2883–2900, https://doi.org/10.5194/tc-12-2883-2018, https://doi.org/10.5194/tc-12-2883-2018, 2018
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In Tibet, two glaciers suddenly collapsed in summer 2016 and produced two gigantic ice avalanches, killing nine people. This kind of phenomenon is extremely rare. By combining a detailed modelling study and high-resolution satellite observations, we show that the event was triggered by an increasing meltwater supply in the fine-grained material underneath the two glaciers. Contrary to what is often thought, this event is not linked to a change in the thermal condition at the glacier base.
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.
Esteban Alonso-González, J. Ignacio López-Moreno, Simon Gascoin, Matilde García-Valdecasas Ojeda, Alba Sanmiguel-Vallelado, Francisco Navarro-Serrano, Jesús Revuelto, Antonio Ceballos, María Jesús Esteban-Parra, and Richard Essery
Earth Syst. Sci. Data, 10, 303–315, https://doi.org/10.5194/essd-10-303-2018, https://doi.org/10.5194/essd-10-303-2018, 2018
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We present a new daily gridded snow depth and snow water equivalent database over the Iberian Peninsula from 1980 to 2014 structured in common elevation bands. The data have proved their consistency with in situ observations and remote sensing data (MODIS). The presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism and risk management.
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.
Jordi Etchanchu, Vincent Rivalland, Simon Gascoin, Jérôme Cros, Tiphaine Tallec, Aurore Brut, and Gilles Boulet
Hydrol. Earth Syst. Sci., 21, 5693–5708, https://doi.org/10.5194/hess-21-5693-2017, https://doi.org/10.5194/hess-21-5693-2017, 2017
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This study assesses the contribution of vegetation dynamics and land use products from high-resolution remote sensing data in the soil–vegetation–atmosphere Transfer ISBA model. We used a field-scale approach (each field is a computation cell) to take advantage of the resolution. The simulations done over an agricultural area in southwestern France showed that integrating such products leads to an improvement of the hydrometeorological fluxes like evapotranspiration or drainage.
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.
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.
Abbas Fayad, Simon Gascoin, Ghaleb Faour, Pascal Fanise, Laurent Drapeau, Janine Somma, Ali Fadel, Ahmad Al Bitar, and Richard Escadafal
Earth Syst. Sci. Data, 9, 573–587, https://doi.org/10.5194/essd-9-573-2017, https://doi.org/10.5194/essd-9-573-2017, 2017
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Snowmelt plays a key role in the replenishment of the karst groundwater in Lebanon. The proper estimation of the water contained in the snowpack is one of Lebanon's most challenging questions. In this paper, we present continuous meteorological and snow course observations for the first time in the snow-dominated regions of Mount Lebanon. This new dataset can be used to feed an advanced snowpack model and is the first step towards a better evaluation of the snowmelt in Lebanon.
Louise Steffensen Schmidt, Guðfinna Aðalgeirsdóttir, Sverrir Guðmundsson, Peter L. Langen, Finnur Pálsson, Ruth Mottram, Simon Gascoin, and Helgi Björnsson
The Cryosphere, 11, 1665–1684, https://doi.org/10.5194/tc-11-1665-2017, https://doi.org/10.5194/tc-11-1665-2017, 2017
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The regional climate model HIRHAM5 is evaluated over Vatnajökull, Iceland, using automatic weather stations and mass balance observations from 1995 to 2014. From this we asses whether the model can be used to reconstruct the mass balance of the glacier. We find that the simulated energy balance is underestimated overall, but it has been improved by using a new albedo scheme. The specific mass balance is reconstructed back to 1980, thus expanding on the observational records of the mass balance.
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.
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
Paul Hublart, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache
Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, https://doi.org/10.5194/hess-20-3691-2016, 2016
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Our paper explores the reliability of conceptual catchment models in the dry Andes. First, we show that explicitly accounting for irrigation water use improves streamflow predictions during dry years. Second, we show that sublimation losses can be easily incorporated into temperature-based melt models without increasing model complexity too much. Our work also highlights areas requiring additional research, including the need for a better conceptualization of runoff generation processes.
Louis Quéno, Vincent Vionnet, Ingrid Dombrowski-Etchevers, Matthieu Lafaysse, Marie Dumont, and Fatima Karbou
The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, https://doi.org/10.5194/tc-10-1571-2016, 2016
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Simulations are carried out in the Pyrenees with the snowpack model Crocus, driven by meteorological forecasts from the model AROME at kilometer resolution. The evaluation is done with ground-based measurements, satellite data and reference simulations. Studying daily snow depth variations allows to separate different physical processes affecting the snowpack. We show the benefits of AROME kilometric resolution and dynamical behavior in terms of snowpack spatial variability in a mountain range.
R. Marti, S. Gascoin, E. Berthier, M. de Pinel, T. Houet, and D. Laffly
The Cryosphere, 10, 1361–1380, https://doi.org/10.5194/tc-10-1361-2016, https://doi.org/10.5194/tc-10-1361-2016, 2016
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To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. We used very-high-resolution stereo satellites imagery (Pléiades) to generate a map of snow depth in a small Pyrenean catchment. The validation results are promising and open the possibility to retrieve the snow depth at a metric horizontal resolution in remote mountainous areas, even when no field data are available.
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.
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.
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.
P. Choler
Biogeosciences, 12, 3885–3897, https://doi.org/10.5194/bg-12-3885-2015, https://doi.org/10.5194/bg-12-3885-2015, 2015
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It is shown that inter-annual variations in the primary productivity of mountain grasslands are primarily governed by variations in the length of the snow-free period and to a much lesser extent by temperature and precipitation during the growing season. Meteorological variables controlling snow cover dynamics are thus of paramount importance to understand and model the amount and timing of biomass production in mountain pastures.
S. Gascoin, O. Hagolle, M. Huc, L. Jarlan, J.-F. Dejoux, C. Szczypta, R. Marti, and R. Sánchez
Hydrol. Earth Syst. Sci., 19, 2337–2351, https://doi.org/10.5194/hess-19-2337-2015, https://doi.org/10.5194/hess-19-2337-2015, 2015
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There is a good agreement between the MODIS snow products and observations from automatic stations and Landsat snow maps in the Pyrenees. The optimal thresholds for which a MODIS pixel is marked as snow-covered are 40mm in water equivalent and 150mm in snow depth.
We generate a gap-filled snow cover climatology for the Pyrenees. We compute the mean snow cover duration by elevation and aspect classes. We show anomalous snow patterns in 2012 and consequences on hydropower production.
S. Ferrant, S. Gascoin, A. Veloso, J. Salmon-Monviola, M. Claverie, V. Rivalland, G. Dedieu, V. Demarez, E. Ceschia, J.-L. Probst, P. Durand, and V. Bustillo
Hydrol. Earth Syst. Sci., 18, 5219–5237, https://doi.org/10.5194/hess-18-5219-2014, https://doi.org/10.5194/hess-18-5219-2014, 2014
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A set of high spatial and temporal satellite images have been used to spatially calibrate crop growth within an agro-hydrological model dedicated to nitrogen contamination of stream water. This type of spatial calibration greatly improved the simulation of nitrogen plant uptake and better constrained nutrient fluxes in the river. This is an example of the benefit of the forthcoming Sentinel-2 high resolution optical image series that will be acquired every 4/5 days over continental surfaces.
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
F. Domine, S. Morin, E. Brun, M. Lafaysse, and C. M. Carmagnola
The Cryosphere, 7, 1915–1929, https://doi.org/10.5194/tc-7-1915-2013, https://doi.org/10.5194/tc-7-1915-2013, 2013
A. Rabatel, A. Letréguilly, J.-P. Dedieu, and N. Eckert
The Cryosphere, 7, 1455–1471, https://doi.org/10.5194/tc-7-1455-2013, https://doi.org/10.5194/tc-7-1455-2013, 2013
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
Related subject area
Discipline: Snow | Subject: Seasonal Snow
Sublimation measurements of tundra and taiga snowpack in Alaska
Insights into microphysical and optical properties of typical mineral dust within industrial-polluted snowpack via wet/dry deposition in Changchun, Northeastern China
An examination of changes in autumn Eurasian snow cover and its relationship with the winter Arctic Oscillation using 20th Century Reanalysis version 3
Historical snow measurements in the central and southern Apennine Mountains: climatology, variability, and trend
Influence of Snow Spatial Variability on Cosmic Ray Neutron SWE
Benchmarking of snow water equivalent (SWE) products based on outcomes of the SnowPEx+ Intercomparison Project
A random forest derived 35-year snow phenology record reveals climate trends in the Yukon River Basin
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
Leveraging Citizen Science, LiDAR, and Machine Learning for Snow Depth Estimation in Complex Terrain Environments
Dynamic identification of snow phenology in the Northern Hemisphere
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?
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
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
Observed snow depth trends in the European Alps: 1971 to 2019
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
Kelsey A. Stockert, Eugénie S. Euskirchen, and Svetlana L. Stuefer
The Cryosphere, 19, 1739–1755, https://doi.org/10.5194/tc-19-1739-2025, https://doi.org/10.5194/tc-19-1739-2025, 2025
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Sublimation is the hidden portion of the water cycle where snow changes phase directly to water vapor, skipping the liquid state. Though sublimation is difficult to measure, especially in remote regions such as Arctic and subarctic Alaska where this study took place, our measurements confirm that sublimation is a substantial component of the annual water cycle. Results from this research contribute to knowledge of how site conditions affect sublimation rates and the winter hydrologic cycle.
Tenglong Shi, Jiayao Wang, Daizhou Zhang, Jiecan Cui, Zihang Wang, Yue Zhou, Wei Pu, Yang Bai, Zhigang Han, Meng Liu, Yanbiao Liu, Hongbin Xie, Minghui Yang, Ying Li, Meng Gao, and Xin Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-124, https://doi.org/10.5194/egusphere-2025-124, 2025
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This study examines the properties of dust in snow in Changchun, China, using advanced technology to analyze its size, shape, and light absorption. We found that dust composition affects how much heat is absorbed by snow, with certain minerals, like hematite, making snow melt faster. Our research highlights the importance of creating clear standards for classifying dust, which could improve climate models and field observations. This work helps better understand dust's role in climate change.
Gareth J. Marshall
The Cryosphere, 19, 663–683, https://doi.org/10.5194/tc-19-663-2025, https://doi.org/10.5194/tc-19-663-2025, 2025
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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. Using data back to 1836, we show that there have been significant decreases in October and November SC. For the first time, we describe a robust relationship between September SC in northeastern Eurasia and the AO. In addition, the longer dataset reveals the temporal variability in previously identified SC–AO relationships.
Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon
The Cryosphere, 19, 565–595, https://doi.org/10.5194/tc-19-565-2025, https://doi.org/10.5194/tc-19-565-2025, 2025
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This “journey through time” discovers historical information about snow precipitation in the Italian Apennines. In this area, in the second half of the 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 above sea level. The old data rescued in this study strongly enhance our knowledge about past snowfall variability and climate in the Mediterranean area.
Haejo Kim, Eric Sproles, and Samuel E. Tuttle
EGUsphere, https://doi.org/10.5194/egusphere-2025-31, https://doi.org/10.5194/egusphere-2025-31, 2025
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Monitoring of a shallow and highly variable snowpack’s water content has been shown to be reliable with Cosmic Ray Neutron Sensing (CRNS). After hundreds of simulations, we show a CRNS instrument is best placed near areas of low snow that are nearby regions of high for an accurate estimate of the prairie snowpack’s water content. The snow water equivalent from a CRNS was 2 to 5 times more likely to be representative of the prairie snow, compared to traditional snow monitoring methods.
Lawrence Mudryk, Colleen Mortimer, Chris Derksen, Aleksandra Elias Chereque, and Paul Kushner
The Cryosphere, 19, 201–218, https://doi.org/10.5194/tc-19-201-2025, https://doi.org/10.5194/tc-19-201-2025, 2025
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We evaluate and rank 23 different datasets on their ability to accurately estimate historical snow amounts. The evaluation uses new a set of surface snow measurements with improved spatial coverage, enabling evaluation across both mountainous and nonmountainous regions. Performance measures vary tremendously across the products: while most perform reasonably in nonmountainous regions, accurate representation of snow amounts in mountainous regions and of historical trends is much more variable.
Caleb G. Pan, Kristofer Lasko, John S. Kimball, Jinyang Du, Tate G. Meehan, Peter B. Kirchner, and Sean P. Griffin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3608, https://doi.org/10.5194/egusphere-2024-3608, 2025
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This study examines 35 years of snow cover changes in Alaska’s Yukon River Basin using machine learning to track snowmelt timing and disappearance. Results show snow is melting earlier and disappearing faster due to rising temperatures, highlighting the effects of climate change on water resources, ecosystems, and communities. The findings improve understanding of snow dynamics and provide critical insights for addressing climate-driven challenges in the region.
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.
Dane Liljestrand, Ryan Johnson, Bethany Neilson, Patrick Strong, and Elizabeth Cotter
EGUsphere, https://doi.org/10.5194/egusphere-2024-3545, https://doi.org/10.5194/egusphere-2024-3545, 2024
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This work introduces a model specifically designed for high-resolution snow depth estimation, leveraging citizen-science snow observations and snow-off LiDAR terrain features to provide an accessible and cost-effective method for snowpack modeling in regions lacking high-quality data products or collection networks. This work demonstrates that reliable basin-scale snow depth estimates can be achieved in difficult environments with very few observations and low institutional costs.
Le Wang, Xin Miao, Xinyun Hu, Yizhuo Li, Bo Qiu, Jun Ge, and Weidong Guo
EGUsphere, https://doi.org/10.5194/egusphere-2024-3431, https://doi.org/10.5194/egusphere-2024-3431, 2024
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Snow phenology is a crucial indicator for assessing seasonal changes in snow. In this work, we find that snow phenology is significantly impacted by datasets and methods used, and current methods often overlook the spatial and temporal variability in snow across the Northern Hemisphere. To address this, we develop a dynamic threshold method, which contributes to better representing the seasonal changes of snow cover across the Northern Hemisphere, especially on the Tibetan Plateau.
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.
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.
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.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
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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.
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.
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Short summary
We generated annual maps of snow melt-out days at 20 m resolution over a period of 38 years from 10 different satellites. This study fills a knowledge gap regarding the evolution of mountain snow in Europe by covering a much longer period and characterizing trends at much higher resolutions than previous studies. We found a trend for earlier melt-out with average reductions of 5.51 d per decade over the French Alps and 4.04 d per decade over the Pyrenees for the period 1986–2023.
We generated annual maps of snow melt-out days at 20 m resolution over a period of 38 years from...
