Articles | Volume 19, issue 13
https://doi.org/10.5194/gmd-19-6273-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-19-6273-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
14 Jul 2026
Model description paper |
| 14 Jul 2026
| 14 Jul 2026
Version 3.0.2 of the Crocus snowpack model
Matthieu Lafaysse
CORRESPONDING AUTHOR
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Marie Dumont
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Basile De Fleurian
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Mathieu Fructus
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Rafife Nheili
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Léo Viallon-Galinier
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Matthieu Baron
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Aaron Boone
Météo-France, CNRS, Univ. Toulouse, CNRM, Toulouse, France
Axel Bouchet
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Julien Brondex
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
now at: Institut des Géosciences de l'Environnement (IGE), CNRS, INRAE, IRD, Grenoble INP, Univ. Grenoble Alpes, Grenoble, France
Carlo Carmagnola
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Bertrand Cluzet
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Kévin Fourteau
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Ange Haddjeri
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
now at: Institut des Géosciences de l'Environnement (IGE), CNRS, INRAE, IRD, Grenoble INP, Univ. Grenoble Alpes, Grenoble, France
Pascal Hagenmuller
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Giulia Mazzotti
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
now at: Institut des Géosciences de l'Environnement (IGE), CNRS, INRAE, IRD, Grenoble INP, Univ. Grenoble Alpes, Grenoble, France
Marie Minvielle
Météo-France, CNRS, Univ. Toulouse, CNRM, Toulouse, France
Samuel Morin
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Louis Quéno
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
now at: WSL Institute for Snow and Avalanche Research (SLF), Davos, Switzerland
Léon Roussel
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Pierre Spandre
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
François Tuzet
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Vincent Vionnet
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d'Éudes de la Neige, Grenoble, France
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada
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Paul Fournier, Antoine Blanc, Juliette Blanchet, and Matthieu Lafaysse
EGUsphere, https://doi.org/10.5194/egusphere-2026-2497, https://doi.org/10.5194/egusphere-2026-2497, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
When rain falls on snow, the combined effect of rainfall and snowmelt can generate flooding. Using hourly weather data across the French Alps over 1958–2024, we identified and characterized such rain-on-snow events and linked them to documented natural hazard events. While these events have become less frequent overall due to shorter snow seasons, the most intense ones have shifted toward lower, more populated elevations, meaning they are increasingly likely to impact communities.
Syam Chintala, Lionel Jarlan, Vincent Rivalland, Aaron Boone, Oluwakemi Dare-Idowu, Valerie Le Dantec, Gilles Boulet, BVN P. Kambhammettu, and Aurore Brut
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This preprint is open for discussion and under review for Biogeosciences (BG).
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We studied how maize crops use water and absorb carbon under contrasting climates using a land surface model coupled with a photosynthesis scheme. The model successfully reproduced ecosystem-scale crop productivity, water loss, and water use efficiency, a key indicator linking carbon uptake and water use. Our results show that the model can reliably capture crop responses to climate and irrigation practices, helping improve predictions of agricultural water use and crop productivity.
Moritz Oberrauch, Bertrand Cluzet, Jan Magnusson, Giulia Mazzotti, Rebecca Mott, Louis Quéno, Clare Webster, Tobias Zolles, and Tobias Jonas
The Cryosphere, 20, 3387–3403, https://doi.org/10.5194/tc-20-3387-2026, https://doi.org/10.5194/tc-20-3387-2026, 2026
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We present a snow dataset that provides daily information on snow depth, snow amount, and meltwater for Switzerland from 2016 to 2025. It combines weather data, computer simulations, and ground observations to give the most complete picture of how snow changes over time. Because mountain snow strongly affects avalanches, floods, water resources, and ecosystems, this freely available dataset supports better understanding and decision-making in these areas.
Louis Védrine, Marius Brun, Mathis Bozon, Benoît Laurent, and Pascal Hagenmuller
EGUsphere, https://doi.org/10.5194/egusphere-2026-2612, https://doi.org/10.5194/egusphere-2026-2612, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Snow slowly compacts under its own weight, and this process depends strongly on temperature, but past estimates vary widely. We developed a device to precisely control temperature and tested the same snow sample under different conditions. We found two distinct temperature regimes and a stronger sensitivity than assumed in existing snowpack models, improving how snow compaction is represented.
Giulia Mazzotti, Félix Vaccaro, Antoine Courteaud, Mathieu Fructus, Jan Magnusson, Isabelle Gouttevin, Jari-Pekka Nousu, and Matthieu Lafaysse
EGUsphere, https://doi.org/10.5194/egusphere-2026-1464, https://doi.org/10.5194/egusphere-2026-1464, 2026
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This study evaluates spatial simulations with the new snow model MEB-Crocus over mountainous, forested terrain. In lack of forest snow observations over large areas, simulations are assessed against simulations with the state-of-the art model FSM2oshd. Results show that the data characterizing the vegetation is as important for model performance as the mathematical description of physical processes. These insights inform future improvements of MEB-Crocus for its application to alpine regions.
Nicolas R. Leroux, Vincent Vionnet, Courtney Bayer, Julien Meloche, Arlan Dirkson, Franck Lespinas, Mark Buehner, Marco Carrera, Benoit Montpetit, Bernard Bilodeau, Maria Abrahamowicz, and Chris Derksen
The Cryosphere, 20, 2773–2792, https://doi.org/10.5194/tc-20-2773-2026, https://doi.org/10.5194/tc-20-2773-2026, 2026
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This study evaluates the assimilation of Ku-band radar backscatter into a multilayer snowpack model to support the upcoming Terrestrial Snow Mass Mission. Synthetic experiments were conducted at Arctic, continental, and alpine sites over three winters using a particle filter. Results show that assimilating backscatter improves estimates of snow water equivalent, depth, and vertical snow properties, laying the groundwork for future satellite missions focused on radar-based snow monitoring.
Audrey Goutard, Marion Réveillet, Fanny Brun, Delphine Six, Kevin Fourteau, Charles Amory, Xavier Fettweis, Mathieu Fructus, Arbindra Khadka, and Matthieu Lafaysse
The Cryosphere, 20, 2393–2416, https://doi.org/10.5194/tc-20-2393-2026, https://doi.org/10.5194/tc-20-2393-2026, 2026
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Short summary
A new scheme has been developed in a snowpack model (SURFEX/ISBA-Crocus), to consider the impact of liquid water dynamics on bare ice, including albedo feedback and refreezing. When applied to the Mera Glacier in Nepal, the model reveals strong seasonal effects on the energy and mass balance, with increased melting in dry seasons and significant refreezing during the monsoon. This development improves mass balance modeling under increasing rainfall and bare ice exposure due to climate warming.
Kévin Fourteau, Julien Brondex, Clément Cancès, and Marie Dumont
Geosci. Model Dev., 19, 3193–3212, https://doi.org/10.5194/gmd-19-3193-2026, https://doi.org/10.5194/gmd-19-3193-2026, 2026
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The percolation of liquid water down snowpacks is a complex phenomenon, and its representation can sometimes be complicated for snowpack models. The goal of this article is to transpose some state-of-the-art strategies used for modeling liquid percolation in other media (such as rocks or soil) into snowpack models. With this, snowpack models can be made more efficient, requiring less time and power to perform their computation.
Oscar Dick, Neige Calonne, Benoît Laurent, and Pascal Hagenmuller
Earth Syst. Sci. Data, 18, 2875–2889, https://doi.org/10.5194/essd-18-2875-2026, https://doi.org/10.5194/essd-18-2875-2026, 2026
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Snow microstructure undergoes constant shape transformations known as snow metamorphism. Observing first-hand snow metamorphism is key to improving the modelling of these transformations. In this work, we monitor snow microstructure evolution during metamorphism by X-ray tomography. We provide a data set at high spatial and temporal resolution of 3D images of snow microstructure evolving through a wide range of experimental conditions, along with videos showing these transformations.
Mickaël Lalande, Alexandre Roy, Libo Wang, Diana Verseghy, Vincent Vionnet, Florent Dominé, and Christophe Kinnard
EGUsphere, https://doi.org/10.5194/egusphere-2026-492, https://doi.org/10.5194/egusphere-2026-492, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This study enhances a snow model for Arctic environments by improving the heat exchanges within the snowpack and at its interfaces, revising the compaction scheme, and adding consideration of blowing snow sublimation losses. Simulations at ten Arctic, mid-latitude, and Alpine sites show significant reductions in simulated soil and snow temperature biases and improved simulated snow depth and density, which are key features to improve simulated energy, water, and carbon budgets in the Arctic.
Oscar M. Baez-Villanueva, Alfredo Crespo-Otero, Sara Modanesi, Pierre Laluet, Sergio Vicente-Serrano, Jaap Schellekens, Jacopo Dari, Hylke E. Beck, Wouter Dorigo, Christian Massari, Chiara Corbari, Joppe Massant, Kwint Delbare, Olivier Bonte, Aaron Boone, Diego Fernández-Prieto, and Diego G. Miralles
EGUsphere, https://doi.org/10.5194/egusphere-2026-1856, https://doi.org/10.5194/egusphere-2026-1856, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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We developed a new method to estimate daily land evaporation at high resolution across the Iberian Peninsula, explicitly accounting for irrigation. By combining satellite and meteorological data, we show that irrigation can strongly increase evaporation in agricultural areas. The results better match ground observations and improve understanding of water use. This approach can support farming decisions and water management at the regional scale, and will be extended to global applications.
Vincent Haagmans, Giulia Mazzotti, Clare Webster, and Tobias Jonas
Hydrol. Earth Syst. Sci., 30, 1691–1717, https://doi.org/10.5194/hess-30-1691-2026, https://doi.org/10.5194/hess-30-1691-2026, 2026
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In the Central European Alps, forests store about 20–30 % of midwinter snow. The effect of forests on snow cover varies greatly with topography, forest structure, weather, and regions. Forests usually decrease snow accumulation and decelerate melt, often leading to a later snow disappearance, especially on sunny slopes. But annual variations are considerable and can even reverse such effects. Environmental shifts will further complicate snow cover dynamics in these mountain forests.
Konstantin Gregor, Benjamin F. Meyer, Tillmann Gaida, Victor Justo Vasquez, Karina Bett-Williams, Matthew Forrest, João P. Darela-Filho, Sam Rabin, Marcos Longo, Joe R. Melton, Johan Nord, Peter Anthoni, Vladislav Bastrikov, Thomas Colligan, Christine Delire, Michael C. Dietze, George Hurtt, Akihiko Ito, Lasse T. Keetz, Jürgen Knauer, Johannes Köster, Tzu-Shun Lin, Lei Ma, Marie Minvielle, Stefan Olin, Sebastian Ostberg, Hao Shi, Reiner Schnur, Qing Sun, Peter E. Thornton, and Anja Rammig
Geosci. Model Dev., 19, 2407–2436, https://doi.org/10.5194/gmd-19-2407-2026, https://doi.org/10.5194/gmd-19-2407-2026, 2026
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Geoscientific models are crucial for understanding Earth’s processes. However, they sometimes do not adhere to highest software quality standards, and scientific results are often hard to reproduce due to the complexity of the workflows. Here we gather the expertise of 20 modeling groups and software engineers to define best practices for making geoscientific models maintainable, usable, and reproducible. We conclude with an open-source example serving as a reference for modeling communities.
Julien Brondex, Olivier Gagliardini, Adrien Gilbert, and Emmanuel Thibert
The Cryosphere, 20, 1655–1677, https://doi.org/10.5194/tc-20-1655-2026, https://doi.org/10.5194/tc-20-1655-2026, 2026
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We investigate crevasse initiation by analyzing the artificial drainage of a water-filled cavity at Tête Rousse Glacier (Mont Blanc, France). Using a numerical model, we compute stress fields in response to water level variations in the cavity and compare them to observed crevasse patterns. Results show that a non-linear viscous rheology and a maximum principal stress criterion (with a stress threshold of 100–130 kPa) best predict crevasse occurrence.
Benjamin Bouchard, Vincent Vionnet, Étienne Gaborit, and Vincent Fortin
EGUsphere, https://doi.org/10.5194/egusphere-2026-928, https://doi.org/10.5194/egusphere-2026-928, 2026
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We show that representing macropores based on soil liquid water significantly improves streamflow simulation in the SVS land surface model under frozen soil conditions. Tested at over 580 stations in the Great-Lakes and Saint-Lawrence region for five years, this simple method can be easily transferred to other land surface models. Our results show that frozen soil infiltration is key for realistic streamflow simulations in cold climates, which is critical for operational hydrological prediction.
Marin Kneib, Patrick Wagnon, Laurent Arnaud, Louise Balmas, Olivier Laarman, Bruno Jourdain, Amaury Dehecq, Emmanuel Lemeur, Fanny Brun, Andrea Kneib-Walter, Ilaria Santin, Laurane Charrier, Thierry Faug, Giulia Mazzotti, Antoine Rabatel, Delphine Six, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2026-786, https://doi.org/10.5194/egusphere-2026-786, 2026
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Avalanches are vital for glacier survival, yet their impact is difficult to quantify. We used low-cost cameras and drones to monitor an avalanche cone in the French Alps for two years. By accounting for ice flow, we found that avalanches can deposit 30 meters of snow annually – 50 times more than normal snowfall. This high-frequency data reveals that these cones fill until reaching a specific steepness, after which new snow slides further down to the base.
Nicola Imperatore, Simon Gascoin, Matthieu Lafaysse, Marie Dumont, Adrien Mauss, Stéphane Guével, and Jean-Baptiste Hernandez
EGUsphere, https://doi.org/10.5194/egusphere-2026-1122, https://doi.org/10.5194/egusphere-2026-1122, 2026
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Daily satellite snow cover observations are beneficial for water management in mountain regions, but it's crucial to understand their uncertainties. We evaluate the next-generation NASA constellation in mountainous terrain using higher-resolution satellite imagery as reference. We find an overall consistent performance across the platforms and combine their data to reduce cloud cover. These results support a confident transition and open new opportunities in snowpack modeling.
Belén Martí, Jannis Groh, Guylaine Canut, and Aaron Boone
Geosci. Model Dev., 19, 1991–2021, https://doi.org/10.5194/gmd-19-1991-2026, https://doi.org/10.5194/gmd-19-1991-2026, 2026
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The characterization of vegetation at two sites proved insufficient to adequately simulate the evapotranspiration. A dry surface layer was implemented in the land surface model SURFEX-ISBA (Externalized Surface-Interactions Soil-Biosphere-Atmosphere) v9.0. It is compared to simulations without a soil resistance. The application to an alfalfa site and a natural grass site in semiarid conditions results in an improvement in the estimation of the latent heat flux. The surface energy budget and the soil and vegetation characteristics are explored in detail.
Bertrand Decharme, Diane Tzanos, Lucas Hardouin, Aaron Boone, Marie Minvielle, Patrick Le Moigne, and Rémi Gaillard
EGUsphere, https://doi.org/10.5194/egusphere-2026-860, https://doi.org/10.5194/egusphere-2026-860, 2026
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We developed a new method to represent how organic matter in soils, together with a mineral soil compaction adjustment, influences the movement of water and heat in land models. We implemented this approach in a global model and performed long-term simulations driven by weather data and global soil maps. Compared with an older empirical method, it produces more consistent soil moisture, runoff, evaporation, and ground temperature and shows closer agreement with observations.
Simon Filhol, Clément Misset, Noélie Bontemps, Diego Cusicanqui, Emmanuel Paquet, Marie Dumont, Olivier Gagliardini, Pascal Lacroix, Simon Gascoin, Guillaume Thirel, Julien Brondex, Pascal Hagenmuller, Eric Larose, Philipp Schoeneich, Denis Roy, Emmanuel Thibert, Nicolas Eckert, Félix de Montety, Robin Mainieri, Alexandre Hauet, Frédéric Gottardi, Johan Berthet, Alexandre Baratier, Frédéric Liébault, Małgorzata Chmiel, Guillaume Piton, Guillaume Chambon, Guillaume James, Philippe Frey, Philip Deline, Laurent Astrade, Christian Vincent, Dominique Laigle, Alain Recking, Fatima Karbou, Adrien Mauss, Mylène Bonnefoy-Demongeot, Firmin Fontaine, Mickael Langlais, Etienne Berthier, and Antoine Blanc
EGUsphere, https://doi.org/10.5194/egusphere-2026-971, https://doi.org/10.5194/egusphere-2026-971, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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On June 21 2024, the village of La Bérarde, in the French Alps, was devastated by a flood destroying centuries old buildings. This study is an interdisciplinary work to decipher the causes and chronology of the event. The flood started with decadal rain falling on a thick snowpack. A lake observed on top of a glacier few days prior, had drained post event. With climate change, should we expect more similar compound events for alpine communities?
Diego Monteiro, Léo Viallon-Galinier, Kévin Fourteau, Oscar Dick, and Pascal Hagenmuller
EGUsphere, https://doi.org/10.5194/egusphere-2026-733, https://doi.org/10.5194/egusphere-2026-733, 2026
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This research aims to improve dry-snow slab avalanche forecasts, particularly the propagation of cracks in weak layers, as current models rely on uncertain and difficult-to-measure parameters. We combined snowpack simulations with field measurements to link fracture energy to measurable and modelable snow properties. This new approach better reproduces observed crack lengths and allows weak layers to be tracked throughout the season, thereby improving operational avalanche risk assessment.
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Julien Meloche, Benoit Montpetit, Nicolas R. Leroux, Richard Essery, Gabriel Hould Gosselin, and Philip Marsh
The Cryosphere, 20, 1315–1338, https://doi.org/10.5194/tc-20-1315-2026, https://doi.org/10.5194/tc-20-1315-2026, 2026
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The impact of uncertainties in the simulation of density and specific surface area (SSA) by the snow model Crocus (embedded in the Soil, Vegetation and Snow v2 land surface model) on the simulation of snow backscatter (13.5 GHz) using the Snow Microwave Radiative Transfer model were quantified. The simulation of SSA was found to be a key model uncertainty. Underestimated SSA values lead to high errors in the simulation of backscatter, reduced by implementing a minimum SSA value (8.7 m2 kg−1).
Louis Védrine and Pascal Hagenmuller
The Cryosphere, 20, 1257–1277, https://doi.org/10.5194/tc-20-1257-2026, https://doi.org/10.5194/tc-20-1257-2026, 2026
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This study investigates how snow settles under its own weight. Using three-dimensional simulations of real snow microstructures and more than 178 past experiments, we show that settlement follows a power law depending on stress and density. This unifies previously conflicting approaches, reconciles contradictory results, and provides a solid basis for improving the representation of snowpack.
Kevin Fourteau, Kaoane Jondeau, Clément Cancès, and Marie Dumont
EGUsphere, https://doi.org/10.5194/egusphere-2026-510, https://doi.org/10.5194/egusphere-2026-510, 2026
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In physics, entropy and the second principle of thermodynamics are related to the notion of stability. In applied mathematics, the same idea of entropy can be transposed to computer models, to ensure that they do not spontaneously oscillate or diverge. The goal of this work is to apply this type of methods to snowpack modelling. We show that entropy-consistent, and thus more robust models, can be designed following a few general criteria.
François Doussot, Léo Viallon-Galinier, Nicolas Eckert, and Pascal Hagenmuller
EGUsphere, https://doi.org/10.5194/egusphere-2026-336, https://doi.org/10.5194/egusphere-2026-336, 2026
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Avalanches are sensitive to climate warming, but long and reliable records are rare. We combined avalanche observations with weather and snow simulations in the Haute-Maurienne valley (French Alps). This allowed us to reconstruct past avalanche activity and explore future changes. The results show a strong long-term decline in avalanche occurrence, especially in spring, while extreme events decrease more slowly. This study provides quantitative insights to support mountain risk management.
Elisa Kamir, Samuel Morin, Guillaume Evin, Penelope Gehring, Bodo Wichura, and Ali Nadir Arslan
Earth Syst. Sci. Data, 18, 17–32, https://doi.org/10.5194/essd-18-17-2026, https://doi.org/10.5194/essd-18-17-2026, 2026
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This article describes a dataset of annual snow depth maximum across Europe, from 1961 to 2015, based on a regional reanalysis. It evaluates the performance of the dataset, against in-situ snow depth observations. This dataset is found to perform well in most environments, with challenges at high elevation and some coastal areas. Assessing the quality of this dataset is necessary in order to use it as a baseline to infer future changes of extreme snow loads under climate change.
Vincent Vionnet, Nicolas R. Leroux, Vincent Fortin, Maria Abrahamowicz, Georgina Woolley, Giulia Mazzotti, Manon Gaillard, Matthieu Lafaysse, Alain Royer, Florent Domine, Nathalie Gauthier, Nick Rutter, Chris Derksen, and Stéphane Bélair
Geosci. Model Dev., 18, 9119–9147, https://doi.org/10.5194/gmd-18-9119-2025, https://doi.org/10.5194/gmd-18-9119-2025, 2025
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Snow microstructure controls snowpack properties, but most land surface models overlook this factor. To support future satellite missions, we created a new land surface model based on the Crocus scheme that simulates snow microstructure. Key improvements include better snow albedo representation, enhanced Arctic snow modeling, and improved forest module to capture Canada's diverse snow conditions. Results demonstrate improved simulations of snow density and melt across large regions of Canada.
Benoit Montpetit, Julien Meloche, Vincent Vionnet, Chris Derksen, Georgina Woolley, Nicolas R. Leroux, Paul Siqueira, J. Max Adam, and Mike Brady
The Cryosphere, 19, 5465–5484, https://doi.org/10.5194/tc-19-5465-2025, https://doi.org/10.5194/tc-19-5465-2025, 2025
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This paper presents the workflow to retrieve snow water equivalent from radar measurements for the future Canadian radar satellite mission, Terrestrial Snow Mass Mission. The workflow is validated by using airborne radar data collected at Trail Valley Creek, Canada, during winter 2018–2019. We detail important considerations to have in the context of a satellite mission over a vast region such as Canada. Results show that it is possible to achieve the desired accuracy over an Arctic environment.
Léon Roussel, Marie Dumont, Marion Réveillet, Delphine Six, Marin Kneib, Pierre Nabat, Kévin Fourteau, Diego Monteiro, Simon Gascoin, Emmanuel Thibert, Antoine Rabatel, Jean-Emmanuel Sicart, Mylène Bonnefoy, Luc Piard, Olivier Laarman, Bruno Jourdain, Mathieu Fructus, Matthieu Vernay, and Matthieu Lafaysse
The Cryosphere, 19, 5201–5230, https://doi.org/10.5194/tc-19-5201-2025, https://doi.org/10.5194/tc-19-5201-2025, 2025
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Saharan dust deposits frequently turn alpine glaciers orange. Mineral dust reduces snow albedo and increases snow and glaciers melt rate. Using physical modeling, we quantified the impact of dust on the Argentière Glacier over the period 2019–2022. We found that the contribution of mineral dust to the melt represents between 8 % and 16 % of Argentière Glacier summer melt. At specific locations, the impact of dust over one year can rise to an equivalent of 1.2 m of melted ice.
Cyrille Mosbeux, Peter Råback, Adrien Gilbert, Julien Brondex, Fabien Gillet-Chaulet, Nicolas C. Jourdain, Mondher Chekki, Olivier Gagliardini, and Gaël Durand
EGUsphere, https://doi.org/10.5194/egusphere-2025-3039, https://doi.org/10.5194/egusphere-2025-3039, 2025
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Transport processes like rocks carried by ice flow and damage evolution – a proxy for crevasses – are key in ice sheet modeling and should occur without diffusion. Yet, standard numerical methods often blur these features. We explore a particle-based Semi-Lagrangian approach, comparing it to a Discontinuous Galerkin method, and show it can accurately simulate such transport when run at high enough resolution.
Julien Meloche, Nicolas R. Leroux, Benoit Montpetit, Vincent Vionnet, and Chris Derksen
The Cryosphere, 19, 2949–2962, https://doi.org/10.5194/tc-19-2949-2025, https://doi.org/10.5194/tc-19-2949-2025, 2025
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Measuring snow mass from radar measurements is possible with information on snow and a radar model to link the measurements to snow. A key variable in a retrieval is the number of snow layers, with more layers yielding richer information but at increased computational cost. Here, we show the capabilities of a new method for simplifying a complex snowpack while preserving the scattering behavior of the snowpack and conserving its mass.
Colleen Mortimer and Vincent Vionnet
Earth Syst. Sci. Data, 17, 3619–3640, https://doi.org/10.5194/essd-17-3619-2025, https://doi.org/10.5194/essd-17-3619-2025, 2025
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In situ observations of snow water equivalent (SWE) are critical for climate applications and resource management. NorSWE is a dataset of in situ SWE observations covering North America, Norway, Finland, Switzerland, Russia, and Nepal over the period 1979–2021. It includes more than 11.5 million observations from more than 10 000 different locations compiled from nine different sources. Snow depth and derived bulk snow density are included when available.
Zacharie Barrou Dumont, Simon Gascoin, Jordi Inglada, Andreas Dietz, Jonas Köhler, Matthieu Lafaysse, Diego Monteiro, Carlo Carmagnola, Arthur Bayle, Jean-Pierre Dedieu, Olivier Hagolle, and Philippe Choler
The Cryosphere, 19, 2407–2429, https://doi.org/10.5194/tc-19-2407-2025, https://doi.org/10.5194/tc-19-2407-2025, 2025
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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.
Richard Essery, Giulia Mazzotti, Sarah Barr, Tobias Jonas, Tristan Quaife, and Nick Rutter
Geosci. Model Dev., 18, 3583–3605, https://doi.org/10.5194/gmd-18-3583-2025, https://doi.org/10.5194/gmd-18-3583-2025, 2025
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How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.
Alireza Amani, Marie-Amélie Boucher, Alexandre R. Cabral, Vincent Vionnet, and Étienne Gaborit
Hydrol. Earth Syst. Sci., 29, 2445–2465, https://doi.org/10.5194/hess-29-2445-2025, https://doi.org/10.5194/hess-29-2445-2025, 2025
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Accurately estimating groundwater recharge using numerical models is particularly difficult in cold regions with snow and soil freezing. This study evaluated a physics-based model against high-resolution field measurements. Our findings highlight a need for a better representation of soil-freezing processes, offering a roadmap for future model development. This leads to more accurate models to aid in water resource management decisions in cold climates.
Sophie Barthelemy, Bertrand Bonan, Miquel Tomas-Burguera, Gilles Grandjean, Séverine Bernardie, Jean-Philippe Naulin, Patrick Le Moigne, Aaron Boone, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 29, 2321–2337, https://doi.org/10.5194/hess-29-2321-2025, https://doi.org/10.5194/hess-29-2321-2025, 2025
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A drought index is developed that quantifies drought on an annual scale, making it applicable to monitoring clay shrinkage damage to buildings. A comparison with the number of insurance claims for subsidence shows that the presence of trees near individual houses must be taken into account. Significant soil moisture droughts occurred in France in 2003, 2018, 2019, 2020, and 2022. Particularly high index values are observed in 2022. It is found that droughts will become more severe in the future.
Matthieu Vernay, Matthieu Lafaysse, and Clotilde Augros
Atmos. Meas. Tech., 18, 1731–1755, https://doi.org/10.5194/amt-18-1731-2025, https://doi.org/10.5194/amt-18-1731-2025, 2025
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This paper provides a comprehensive evaluation of the quality of radar-based precipitation estimation in mountainous areas and presents a method to mitigate the main shortcomings identified. It then compares three different ensemble analysis methods that combine radar-based precipitation estimates with forecasts from an ensemble numerical weather prediction model.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data, 17, 703–717, https://doi.org/10.5194/essd-17-703-2025, https://doi.org/10.5194/essd-17-703-2025, 2025
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In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
Manon Gaillard, Vincent Vionnet, Matthieu Lafaysse, Marie Dumont, and Paul Ginoux
The Cryosphere, 19, 769–792, https://doi.org/10.5194/tc-19-769-2025, https://doi.org/10.5194/tc-19-769-2025, 2025
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This study presents an efficient method to improve large-scale snow albedo simulations by considering the spatial variability in light-absorbing particles (LAPs) like black carbon and dust. A global climatology of LAP deposition was created and used to optimize a parameter in the Crocus snow model. Testing at 10 global sites improved albedo predictions by 10 % on average and over 25 % in the Arctic. This method can enhance other snow models' predictions without complex simulations.
Tanguy Ronan Lunel, Belen Marti, Aaron Boone, and Patrick Le Moigne
EGUsphere, https://doi.org/10.5194/egusphere-2024-3562, https://doi.org/10.5194/egusphere-2024-3562, 2025
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Modelling evapotranspiration is essential for understanding the water cycle. While irrigation is known to increase evapotranspiration, it is less known that it also modifies local weather, which can in turn partially reduce evapotranspiration. This latter phenomenon is overlooked in some land surface model configurations. This study investigates and quantifies the impact of this oversight, showing that land surface models overestimate evapotranspiration by about 25% for crops in irrigated areas.
Xavier Faïn, Sophie Szopa, Vaishali Naïk, Patricia Martinerie, David M. Etheridge, Rachael H. Rhodes, Cathy M. Trudinger, Vasilii V. Petrenko, Kévin Fourteau, and Philip Place
Atmos. Chem. Phys., 25, 1105–1119, https://doi.org/10.5194/acp-25-1105-2025, https://doi.org/10.5194/acp-25-1105-2025, 2025
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Carbon monoxide (CO) plays a crucial role in the atmosphere's oxidizing capacity. In this study, we analyse how historical (1850–2014) [CO] outputs from state-of-the-art global chemistry–climate models over Greenland and Antarctica are able to capture both absolute values and trends recorded in multi-site ice archives. A disparity in [CO] growth rates emerges in the Northern Hemisphere between models and observations from 1920–1975 CE, possibly linked to uncertainties in CO emission factors.
Bertrand Cluzet, Jan Magnusson, Louis Quéno, Giulia Mazzotti, Rebecca Mott, and Tobias Jonas
The Cryosphere, 18, 5753–5767, https://doi.org/10.5194/tc-18-5753-2024, https://doi.org/10.5194/tc-18-5753-2024, 2024
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We use novel wet-snow maps from Sentinel-1 to evaluate simulations of a snow-hydrological model over Switzerland. These data are complementary to available in situ snow depth observations as they capture a broad diversity of topographic conditions. Wet-snow maps allow us to detect a delayed melt onset in the model, which we resolve thanks to an improved parametrization. This paves the way to further evaluation, calibration, and data assimilation using wet-snow maps.
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024, https://doi.org/10.5194/tc-18-5685-2024, 2024
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Parameterisations of Arctic snow processes were implemented into the multi-physics ensemble version of the snow model Crocus (embedded within the Soil, Vegetation, and Snow version 2 land surface model) and evaluated at an Arctic tundra site. Optimal combinations of parameterisations that improved the simulation of density and specific surface area featured modifications that raise wind speeds to increase compaction in surface layers, prevent snowdrift, and increase viscosity in basal layers.
Diego Monteiro, Cécile Caillaud, Matthieu Lafaysse, Adrien Napoly, Mathieu Fructus, Antoinette Alias, and Samuel Morin
Geosci. Model Dev., 17, 7645–7677, https://doi.org/10.5194/gmd-17-7645-2024, https://doi.org/10.5194/gmd-17-7645-2024, 2024
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Modeling snow cover in climate and weather forecasting models is a challenge even for high-resolution models. Recent simulations with CNRM-AROME have shown difficulties when representing snow in the European Alps. Using remote sensing data and in situ observations, we evaluate modifications of the land surface configuration in order to improve it. We propose a new surface configuration, enabling a more realistic simulation of snow cover, relevant for climate and weather forecasting applications.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024, https://doi.org/10.5194/tc-18-4671-2024, 2024
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Computer models, like those used in climate change studies, are written by modellers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modelling as an example, we examine the process behind the decisions to understand what motivates or limits modellers in their decision-making. We find that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency in our research practice.
Giulia Mazzotti, Jari-Pekka Nousu, Vincent Vionnet, Tobias Jonas, Rafife Nheili, and Matthieu Lafaysse
The Cryosphere, 18, 4607–4632, https://doi.org/10.5194/tc-18-4607-2024, https://doi.org/10.5194/tc-18-4607-2024, 2024
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As many boreal and alpine forests have seasonal snow, models are needed to predict forest snow under future environmental conditions. We have created a new forest snow model by combining existing, very detailed model components for the canopy and the snowpack. We applied it to forests in Switzerland and Finland and showed how complex forest cover leads to a snowpack layering that is very variable in space and time because different processes prevail at different locations in the forest.
Julien Westhoff, Johannes Freitag, Anaïs Orsi, Patricia Martinerie, Ilka Weikusat, Michael Dyonisius, Xavier Faïn, Kevin Fourteau, and Thomas Blunier
The Cryosphere, 18, 4379–4397, https://doi.org/10.5194/tc-18-4379-2024, https://doi.org/10.5194/tc-18-4379-2024, 2024
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We study the EastGRIP area, Greenland, in detail with traditional and novel techniques. Due to the compaction of the ice, at a certain depth, atmospheric gases can no longer exchange, and the atmosphere is trapped in air bubbles in the ice. We find this depth by pumping air from a borehole, modeling, and using a new technique based on the optical appearance of the ice. Our results suggest that the close-off depth lies at around 58–61 m depth and more precisely at 58.3 m depth.
Dylan Reynolds, Louis Quéno, Michael Lehning, Mahdi Jafari, Justine Berg, Tobias Jonas, Michael Haugeneder, and Rebecca Mott
The Cryosphere, 18, 4315–4333, https://doi.org/10.5194/tc-18-4315-2024, https://doi.org/10.5194/tc-18-4315-2024, 2024
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Information about atmospheric variables is needed to produce simulations of mountain snowpacks. We present a model that can represent processes that shape mountain snowpack, focusing on the accumulation of snow. Simulations show that this model can simulate the complex path that a snowflake takes towards the ground and that this leads to differences in the distribution of snow by the end of winter. Overall, this model shows promise with regard to improving forecasts of snow in mountains.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Benoit Montpetit, Joshua King, Julien Meloche, Chris Derksen, Paul Siqueira, J. Max Adam, Peter Toose, Mike Brady, Anna Wendleder, Vincent Vionnet, and Nicolas R. Leroux
The Cryosphere, 18, 3857–3874, https://doi.org/10.5194/tc-18-3857-2024, https://doi.org/10.5194/tc-18-3857-2024, 2024
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This paper validates the use of free open-source models to link distributed snow measurements to radar measurements in the Canadian Arctic. Using multiple radar sensors, we can decouple the soil from the snow contribution. We then retrieve the "microwave snow grain size" to characterize the interaction between the snow mass and the radar signal. This work supports future satellite mission development to retrieve snow mass information such as the future Canadian Terrestrial Snow Mass Mission.
Clémence Herny, Pascal Hagenmuller, Guillaume Chambon, Isabel Peinke, and Jacques Roulle
The Cryosphere, 18, 3787–3805, https://doi.org/10.5194/tc-18-3787-2024, https://doi.org/10.5194/tc-18-3787-2024, 2024
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This paper presents the evaluation of a numerical discrete element method (DEM) by simulating cone penetration tests in different snow samples. The DEM model demonstrated a good ability to reproduce the measured mechanical behaviour of the snow, namely the force evolution on the cone and the grain displacement field. Systematic sensitivity tests showed that the mechanical response depends not only on the microstructure of the sample but also on the mechanical parameters of grain contacts.
Romilly Harris Stuart, Amaëlle Landais, Laurent Arnaud, Christo Buizert, Emilie Capron, Marie Dumont, Quentin Libois, Robert Mulvaney, Anaïs Orsi, Ghislain Picard, Frédéric Prié, Jeffrey Severinghaus, Barbara Stenni, and Patricia Martinerie
The Cryosphere, 18, 3741–3763, https://doi.org/10.5194/tc-18-3741-2024, https://doi.org/10.5194/tc-18-3741-2024, 2024
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Ice core δO2/N2 records are useful dating tools due to their local insolation pacing. A precise understanding of the physical mechanism driving this relationship, however, remain ambiguous. By compiling data from 15 polar sites, we find a strong dependence of mean δO2/N2 on accumulation rate and temperature in addition to the well-documented insolation dependence. Snowpack modelling is used to investigate which physical properties drive the mechanistic dependence on these local parameters.
Johanna Teresa Malle, Giulia Mazzotti, Dirk Nikolaus Karger, and Tobias Jonas
Earth Syst. Dynam., 15, 1073–1115, https://doi.org/10.5194/esd-15-1073-2024, https://doi.org/10.5194/esd-15-1073-2024, 2024
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Land surface processes are crucial for the exchange of carbon, nitrogen, and energy in the Earth system. Using meteorological and land use data, we found that higher resolution improved not only the model representation of snow cover but also plant productivity and that water returned to the atmosphere. Only by combining high-resolution models with high-quality input data can we accurately represent complex spatially heterogeneous processes and improve our understanding of the Earth system.
Louis Quéno, Rebecca Mott, Paul Morin, Bertrand Cluzet, Giulia Mazzotti, and Tobias Jonas
The Cryosphere, 18, 3533–3557, https://doi.org/10.5194/tc-18-3533-2024, https://doi.org/10.5194/tc-18-3533-2024, 2024
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Snow redistribution by wind and avalanches strongly influences snow hydrology in mountains. This study presents a novel modelling approach to best represent these processes in an operational context. The evaluation of the simulations against airborne snow depth measurements showed remarkable improvement in the snow distribution in mountains of the eastern Swiss Alps, with a representation of snow accumulation and erosion areas, suggesting promising benefits for operational snow melt forecasts.
Tanguy Lunel, Maria Antonia Jimenez, Joan Cuxart, Daniel Martinez-Villagrasa, Aaron Boone, and Patrick Le Moigne
Atmos. Chem. Phys., 24, 7637–7666, https://doi.org/10.5194/acp-24-7637-2024, https://doi.org/10.5194/acp-24-7637-2024, 2024
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During the summer in Catalonia, a cool wind, the marinada, blows into the eastern Ebro basin in the afternoon. This study investigates its previously unclear dynamics using observations and a meteorological model. It is found to be driven by a cool marine air mass that flows over the mountains into the basin. The study shows how the sea breeze, upslope winds, larger weather patterns and irrigation play a prominent role in the formation and characteristics of the marinada.
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamps-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
The Cryosphere, 18, 3081–3116, https://doi.org/10.5194/tc-18-3081-2024, https://doi.org/10.5194/tc-18-3081-2024, 2024
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Our study addresses the complex challenge of evaluating distributed alpine snow simulations with snow transport against snow depths from Pléiades stereo imagery and snow melt-out dates from Sentinel-2 and Landsat-8 satellites. Additionally, we disentangle error contributions between blowing snow, precipitation heterogeneity, and unresolved subgrid variability. Snow transport enhances the snow simulations at high elevations, while precipitation biases are the main error source in other areas.
Kévin Fourteau, Johannes Freitag, Mika Malinen, and Henning Löwe
The Cryosphere, 18, 2831–2846, https://doi.org/10.5194/tc-18-2831-2024, https://doi.org/10.5194/tc-18-2831-2024, 2024
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Understanding the settling of snow under its own weight has applications from avalanche forecasts to ice core interpretations. We study how this settling can be modeled using 3D images of the internal structure of snow and ice deformation mechanics. We found that classical ice mechanics, as used, for instance, in glacier flow, explain the compaction of dense polar snow but not that of lighter seasonal snow. How, exactly, the ice deforms during light snow compaction thus remains an open question.
Anna Braun, Kévin Fourteau, and Henning Löwe
The Cryosphere, 18, 1653–1668, https://doi.org/10.5194/tc-18-1653-2024, https://doi.org/10.5194/tc-18-1653-2024, 2024
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The specific surface of snow dictates key physical properties and continuously evolves in natural snowpacks. This is referred to as metamorphism. This work develops a rigorous physical model for this evolution, which is able to reproduce X-ray tomography measurements without using unphysical tuning parameters. Our results emphasize that snow crystal growth at the micrometer scale ultimately controls the pace of metamorphism.
Kavitha Sundu, Johannes Freitag, Kévin Fourteau, and Henning Löwe
The Cryosphere, 18, 1579–1596, https://doi.org/10.5194/tc-18-1579-2024, https://doi.org/10.5194/tc-18-1579-2024, 2024
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Ice crystals often show a rod-like, vertical orientation in snow and firn; they are said to be anisotropic. The stiffness in the vertical direction therefore differs from the horizontal, which, for example, impacts the propagation of seismic waves. To quantify this anisotropy, we conducted finite-element simulations of 391 snow, firn, and ice core microstructures obtained from X-ray tomography. We then derived a parameterization that may be employed for advanced seismic studies in polar regions.
Kévin Fourteau, Julien Brondex, Fanny Brun, and Marie Dumont
Geosci. Model Dev., 17, 1903–1929, https://doi.org/10.5194/gmd-17-1903-2024, https://doi.org/10.5194/gmd-17-1903-2024, 2024
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In this paper, we provide a novel numerical implementation for solving the energy exchanges at the surface of snow and ice. By combining the strong points of previous models, our solution leads to more accurate and robust simulations of the energy exchanges, surface temperature, and melt while preserving a reasonable computation time.
Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis Le Toumelin, Vincent Vionnet, and Mathieu Fructus
Geosci. Model Dev., 17, 1297–1326, https://doi.org/10.5194/gmd-17-1297-2024, https://doi.org/10.5194/gmd-17-1297-2024, 2024
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Increasing the spatial resolution of numerical systems simulating snowpack evolution in mountain areas requires representing small-scale processes such as wind-induced snow transport. We present SnowPappus, a simple scheme coupled with the Crocus snow model to compute blowing-snow fluxes and redistribute snow among grid points at 250 m resolution. In terms of numerical cost, it is suitable for large-scale applications. We present point-scale evaluations of fluxes and snow transport occurrence.
Jari-Pekka Nousu, Matthieu Lafaysse, Giulia Mazzotti, Pertti Ala-aho, Hannu Marttila, Bertrand Cluzet, Mika Aurela, Annalea Lohila, Pasi Kolari, Aaron Boone, Mathieu Fructus, and Samuli Launiainen
The Cryosphere, 18, 231–263, https://doi.org/10.5194/tc-18-231-2024, https://doi.org/10.5194/tc-18-231-2024, 2024
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The snowpack has a major impact on the land surface energy budget. Accurate simulation of the snowpack energy budget is difficult, and studies that evaluate models against energy budget observations are rare. We compared predictions from well-known models with observations of energy budgets, snow depths and soil temperatures in Finland. Our study identified contrasting strengths and limitations for the models. These results can be used for choosing the right models depending on the use cases.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
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The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023, https://doi.org/10.5194/gmd-16-7075-2023, 2023
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Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.
Samuel Morin, Hugues François, Marion Réveillet, Eric Sauquet, Louise Crochemore, Flora Branger, Étienne Leblois, and Marie Dumont
Hydrol. Earth Syst. Sci., 27, 4257–4277, https://doi.org/10.5194/hess-27-4257-2023, https://doi.org/10.5194/hess-27-4257-2023, 2023
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Ski resorts are a key socio-economic asset of several mountain areas. Grooming and snowmaking are routinely used to manage the snow cover on ski pistes, but despite vivid debate, little is known about their impact on water resources downstream. This study quantifies, for the pilot ski resort La Plagne in the French Alps, the impact of grooming and snowmaking on downstream river flow. Hydrological impacts are mostly apparent at the seasonal scale and rather neutral on the annual scale.
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
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Xavier Faïn, David M. Etheridge, Kévin Fourteau, Patricia Martinerie, Cathy M. Trudinger, Rachael H. Rhodes, Nathan J. Chellman, Ray L. Langenfelds, Joseph R. McConnell, Mark A. J. Curran, Edward J. Brook, Thomas Blunier, Grégory Teste, Roberto Grilli, Anthony Lemoine, William T. Sturges, Boris Vannière, Johannes Freitag, and Jérôme Chappellaz
Clim. Past, 19, 2287–2311, https://doi.org/10.5194/cp-19-2287-2023, https://doi.org/10.5194/cp-19-2287-2023, 2023
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We report on a 3000-year record of carbon monoxide (CO) levels in the Southern Hemisphere's high latitudes by combining ice core and firn air measurements with modern direct atmospheric samples. Antarctica [CO] remained stable (–835 to 1500 CE), decreased during the Little Ice Age, and peaked around 1985 CE. Such evolution reflects stable biomass burning CO emissions before industrialization, followed by growth from CO anthropogenic sources, which decline after 1985 due to improved combustion.
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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We assess projected changes in snowfall extremes in the French Alps as a function of elevation and global warming level for a high-emission scenario. On average, heavy snowfall is projected to decrease below 3000 m and increase above 3600 m, while extreme snowfall is projected to decrease below 2400 m and increase above 3300 m. At elevations in between, an increase is projected until +3 °C of global warming and then a decrease. These results have implications for the management of risks.
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.
Fanny Brun, Owen King, Marion Réveillet, Charles Amory, Anton Planchot, Etienne Berthier, Amaury Dehecq, Tobias Bolch, Kévin Fourteau, Julien Brondex, Marie Dumont, Christoph Mayer, Silvan Leinss, Romain Hugonnet, and Patrick Wagnon
The Cryosphere, 17, 3251–3268, https://doi.org/10.5194/tc-17-3251-2023, https://doi.org/10.5194/tc-17-3251-2023, 2023
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The South Col Glacier is a small body of ice and snow located on the southern ridge of Mt. Everest. A recent study proposed that South Col Glacier is rapidly losing mass. In this study, we examined the glacier thickness change for the period 1984–2017 and found no thickness change. To reconcile these results, we investigate wind erosion and surface energy and mass balance and find that melt is unlikely a dominant process, contrary to previous findings.
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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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
Léo Viallon-Galinier, Pascal Hagenmuller, and Nicolas Eckert
The Cryosphere, 17, 2245–2260, https://doi.org/10.5194/tc-17-2245-2023, https://doi.org/10.5194/tc-17-2245-2023, 2023
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Avalanches are a significant issue in mountain areas where they threaten recreationists and human infrastructure. Assessments of avalanche hazards and the related risks are therefore an important challenge for local authorities. Meteorological and snow cover simulations are thus important to support operational forecasting. In this study we combine it with mechanical analysis of snow profiles and find that observed avalanche data improve avalanche activity prediction through statistical methods.
Giulia Mazzotti, Clare Webster, Louis Quéno, Bertrand Cluzet, and Tobias Jonas
Hydrol. Earth Syst. Sci., 27, 2099–2121, https://doi.org/10.5194/hess-27-2099-2023, https://doi.org/10.5194/hess-27-2099-2023, 2023
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This study analyses snow cover evolution in mountainous forested terrain based on 2 m resolution simulations from a process-based model. We show that snow accumulation patterns are controlled by canopy structure, but topographic shading modulates the timing of melt onset, and variability in weather can cause snow accumulation and melt patterns to vary between years. These findings advance our ability to predict how snow regimes will react to rising temperatures and forest disturbances.
Oscar Dick, Léo Viallon-Galinier, François Tuzet, Pascal Hagenmuller, Mathieu Fructus, Benjamin Reuter, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 17, 1755–1773, https://doi.org/10.5194/tc-17-1755-2023, https://doi.org/10.5194/tc-17-1755-2023, 2023
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Saharan dust deposition can drastically change the snow color, turning mountain landscapes into sepia scenes. Dust increases the absorption of solar energy by the snow cover and thus modifies the snow evolution and potentially the avalanche risk. Here we show that dust can lead to increased or decreased snowpack stability depending on the snow and meteorological conditions after the deposition event. We also show that wet-snow avalanches happen earlier in the season due to the presence of dust.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Pyei Phyo Lin, Isabel Peinke, Pascal Hagenmuller, Matthias Wächter, M. Reza Rahimi Tabar, and Joachim Peinke
The Cryosphere, 16, 4811–4822, https://doi.org/10.5194/tc-16-4811-2022, https://doi.org/10.5194/tc-16-4811-2022, 2022
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Characterization of layers of snowpack with highly resolved micro-cone penetration tests leads to detailed fluctuating signals. We used advanced stochastic analysis to differentiate snow types by interpreting the signals as a mixture of continuous and discontinuous random fluctuations. These two types of fluctuation seem to correspond to different mechanisms of drag force generation during the experiments. The proposed methodology provides new insights into the characterization of snow layers.
Jaime Gaona, Pere Quintana-Seguí, María José Escorihuela, Aaron Boone, and María Carmen Llasat
Nat. Hazards Earth Syst. Sci., 22, 3461–3485, https://doi.org/10.5194/nhess-22-3461-2022, https://doi.org/10.5194/nhess-22-3461-2022, 2022
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Droughts represent a particularly complex natural hazard and require explorations of their multiple causes. Part of the complexity has roots in the interaction between the continuous changes in and deviation from normal conditions of the atmosphere and the land surface. The exchange between the atmospheric and surface conditions defines feedback towards dry or wet conditions. In semi-arid environments, energy seems to exceed water in its impact over the evolution of conditions, favoring drought.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
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.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
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Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
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.
Basile de Fleurian, Richard Davy, and Petra M. Langebroek
The Cryosphere, 16, 2265–2283, https://doi.org/10.5194/tc-16-2265-2022, https://doi.org/10.5194/tc-16-2265-2022, 2022
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As temperature increases, more snow and ice melt at the surface of ice sheets. Here we use an ice dynamics and subglacial hydrology model with simplified geometry and climate forcing to study the impact of variations in meltwater on ice dynamics. We focus on the variations in length and intensity of the melt season. Our results show that a longer melt season leads to faster glaciers, but a more intense melt season reduces glaciers' seasonal velocities, albeit leading to higher peak velocities.
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.
Xavier Faïn, Rachael H. Rhodes, Philip Place, Vasilii V. Petrenko, Kévin Fourteau, Nathan Chellman, Edward Crosier, Joseph R. McConnell, Edward J. Brook, Thomas Blunier, Michel Legrand, and Jérôme Chappellaz
Clim. Past, 18, 631–647, https://doi.org/10.5194/cp-18-631-2022, https://doi.org/10.5194/cp-18-631-2022, 2022
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Carbon monoxide (CO) is a regulated pollutant and one of the key components determining the oxidizing capacity of the atmosphere. In this study, we analyzed five ice cores from Greenland at high resolution for CO concentrations by coupling laser spectrometry with continuous melting. By combining these new datasets, we produced an upper-bound estimate of past atmospheric CO abundance since preindustrial times for the Northern Hemisphere high latitudes, covering the period from 1700 to 1957 CE.
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.
Thomas Frank, Henning Åkesson, Basile de Fleurian, Mathieu Morlighem, and Kerim H. Nisancioglu
The Cryosphere, 16, 581–601, https://doi.org/10.5194/tc-16-581-2022, https://doi.org/10.5194/tc-16-581-2022, 2022
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The shape of a fjord can promote or inhibit glacier retreat in response to climate change. We conduct experiments with a synthetic setup under idealized conditions in a numerical model to study and quantify the processes involved. We find that friction between ice and fjord is the most important factor and that it is possible to directly link ice discharge and grounding line retreat to fjord topography in a quantitative way.
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.
Florent Veillon, Marie Dumont, Charles Amory, and Mathieu Fructus
Geosci. Model Dev., 14, 7329–7343, https://doi.org/10.5194/gmd-14-7329-2021, https://doi.org/10.5194/gmd-14-7329-2021, 2021
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In climate models, the snow albedo scheme generally calculates only a narrowband or broadband albedo. Therefore, we have developed the VALHALLA method to optimize snow spectral albedo calculations through the determination of spectrally fixed radiative variables. The development of VALHALLA v1.0 with the use of the snow albedo model TARTES and the spectral irradiance model SBDART indicates a considerable reduction in calculation time while maintaining an adequate accuracy of albedo values.
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.
Vincent Vionnet, Colleen Mortimer, Mike Brady, Louise Arnal, and Ross Brown
Earth Syst. Sci. Data, 13, 4603–4619, https://doi.org/10.5194/essd-13-4603-2021, https://doi.org/10.5194/essd-13-4603-2021, 2021
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Water equivalent of snow cover (SWE) is a key variable for water management, hydrological forecasting and climate monitoring. A new Canadian SWE dataset (CanSWE) is presented in this paper. It compiles data collected by multiple agencies and companies at more than 2500 different locations across Canada over the period 1928–2020. Snow depth and derived bulk snow density are also included when available.
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.
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.
Luca Palchetti, Marco Barucci, Claudio Belotti, Giovanni Bianchini, Bertrand Cluzet, Francesco D'Amato, Samuele Del Bianco, Gianluca Di Natale, Marco Gai, Dina Khordakova, Alessio Montori, Hilke Oetjen, Markus Rettinger, Christian Rolf, Dirk Schuettemeyer, Ralf Sussmann, Silvia Viciani, Hannes Vogelmann, and Frank Gunther Wienhold
Earth Syst. Sci. Data, 13, 4303–4312, https://doi.org/10.5194/essd-13-4303-2021, https://doi.org/10.5194/essd-13-4303-2021, 2021
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The FIRMOS far-infrared (IR) prototype, developed for the preparation of the ESA FORUM mission, was deployed for the first time at Mt. Zugspitze at 3000 m altitude to measure the far-IR spectrum of atmospheric emissions. The measurements, including co-located radiometers, lidars, radio soundings, weather, and surface properties, provide a unique dataset to study radiative properties of water vapour, cirrus clouds, and snow emissivity over the IR emissions, including the under-explored far-IR.
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.
Marie Dumont, Frederic Flin, Aleksey Malinka, Olivier Brissaud, Pascal Hagenmuller, Philippe Lapalus, Bernard Lesaffre, Anne Dufour, Neige Calonne, Sabine Rolland du Roscoat, and Edward Ando
The Cryosphere, 15, 3921–3948, https://doi.org/10.5194/tc-15-3921-2021, https://doi.org/10.5194/tc-15-3921-2021, 2021
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The role of snow microstructure in snow optical properties is only partially understood despite the importance of snow optical properties for the Earth system. We present a dataset combining bidirectional reflectance measurements and 3D images of snow. We show that the snow reflectance is adequately simulated using the distribution of the ice chord lengths in the snow microstructure and that the impact of the morphological type of snow is especially important when ice is highly absorptive.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Cited articles
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Brun, E., Vionnet, V., Boone, A., Decharme, B., Peings, Y., Valette, R., Karbou, F., and Morin, S.: Simulation of northern Eurasian local snow depth, mass and density using a detailed snowpack model and meteorological reanalysis, J. Hydrometeorol., 14, 203–219, https://doi.org/10.1175/JHM-D-12-012.1, 2013. a, b
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Calonne, N., Richter, B., Löwe, H., Cetti, C., ter Schure, J., Van Herwijnen, A., Fierz, C., Jaggi, M., and Schneebeli, M.: The RHOSSA campaign: multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack, The Cryosphere, 14, 1829–1848, https://doi.org/10.5194/tc-14-1829-2020, 2020. a
Caponi, L., Formenti, P., Massabó, D., Di Biagio, C., Cazaunau, M., Pangui, E., Chevaillier, S., Landrot, G., Andreae, M. O., Kandler, K., Piketh, S., Saeed, T., Seibert, D., Williams, E., Balkanski, Y., Prati, P., and Doussin, J.-F.: Spectral- and size-resolved mass absorption efficiency of mineral dust aerosols in the shortwave spectrum: a simulation chamber study, Atmos. Chem. Phys., 17, 7175–7191, https://doi.org/10.5194/acp-17-7175-2017, 2017. a
Carmagnola, C. M., Morin, S., Lafaysse, M., Domine, F., Lesaffre, B., Lejeune, Y., Picard, G., and Arnaud, L.: Implementation and evaluation of prognostic representations of the optical diameter of snow in the SURFEX/ISBA-Crocus detailed snowpack model, The Cryosphere, 8, 417–437, https://doi.org/10.5194/tc-8-417-2014, 2014. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s
Castebrunet, H., Eckert, N., Giraud, G., Durand, Y., and Morin, S.: Projected changes of snow conditions and avalanche activity in a warming climate: the French Alps over the 2020–2050 and 2070–2100 periods, The Cryosphere, 8, 1673–1697, https://doi.org/10.5194/tc-8-1673-2014, 2014. a
Charrois, L., Cosme, E., Dumont, M., Lafaysse, M., Morin, S., Libois, Q., and Picard, G.: On the assimilation of optical reflectances and snow depth observations into a detailed snowpack model, The Cryosphere, 10, 1021–1038, https://doi.org/10.5194/tc-10-1021-2016, 2016. a
Cluzet, B., Revuelto, J., Lafaysse, M., Tuzet, F., Cosme, E., Picard, G., Arnaud, L., and Dumont, M.: Towards the assimilation of satellite reflectance into semi-distributed ensemble snowpack simulations, Cold Reg. Sci. Techol., 170, 102918, https://doi.org/10.1016/j.coldregions.2019.102918, 2020. a, b
Cluzet, B., Lafaysse, M., Cosme, E., Albergel, C., Meunier, L.-F., and Dumont, M.: CrocO_v1.0: a particle filter to assimilate snowpack observations in a spatialised framework, Geosci. Model Dev., 14, 1595–1614, https://doi.org/10.5194/gmd-14-1595-2021, 2021. a, b
Cluzet, B., Lafaysse, M., Deschamps-Berger, C., Vernay, M., and Dumont, M.: Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network, The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022, 2022. a
D'Amboise, C. J. L., Müller, K., Oxarango, L., Morin, S., and Schuler, T. V.: Implementation of a physically based water percolation routine in the Crocus/SURFEX (V7.3) snowpack model, Geosci. Model Dev., 10, 3547–3566, https://doi.org/10.5194/gmd-10-3547-2017, 2017. a
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Decharme, B., Brun, E., Boone, A., Delire, C., Le Moigne, P., and Morin, S.: Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model, The Cryosphere, 10, 853–877, https://doi.org/10.5194/tc-10-853-2016, 2016. a
Deschamps-Berger, C., Cluzet, B., Dumont, M., Lafaysse, M., Berthier, E., Fanise, P., and Gascoin, S.: Improving the Spatial Distribution of Snow Cover Simulations by Assimilation of Satellite Stereoscopic Imagery, Water Resour. Res., 58, e2021WR030271, https://doi.org/10.1029/2021WR030271, 2022. a, b
Dick, O., Viallon-Galinier, L., Tuzet, F., Hagenmuller, P., Fructus, M., Reuter, B., Lafaysse, M., and Dumont, M.: Can Saharan dust deposition impact snowpack stability in the French Alps?, The Cryosphere, 17, 1755–1773, https://doi.org/10.5194/tc-17-1755-2023, 2023. a
Di Mauro, B., Garzonio, R., Rossini, M., Filippa, G., Pogliotti, P., Galvagno, M., Morra di Cella, U., Migliavacca, M., Baccolo, G., Clemenza, M., Delmonte, B., Maggi, V., Dumont, M., Tuzet, F., Lafaysse, M., Morin, S., Cremonese, E., and Colombo, R.: Saharan dust events in the European Alps: role in snowmelt and geochemical characterization, The Cryosphere, 13, 1147–1165, https://doi.org/10.5194/tc-13-1147-2019, 2019. a
Domine, F., Morin, S., Brun, E., Lafaysse, M., and Carmagnola, C. M.: Seasonal evolution of snow permeability under equi-temperature and temperature-gradient conditions, The Cryosphere, 7, 1915–1929, https://doi.org/10.5194/tc-7-1915-2013, 2013. a
Domine, F., Barrere, M., and Morin, S.: The growth of shrubs on high Arctic tundra at Bylot Island: impact on snow physical properties and permafrost thermal regime, Biogeosciences, 13, 6471–6486, https://doi.org/10.5194/bg-13-6471-2016, 2016. a
Dumont, M., Tuzet, F., Gascoin, S., Picard, G., Kutuzov, S., Lafaysse, M., Cluzet, B., Nheili, R., and Painter, T. H.: Accelerated Snow Melt in the Russian Caucasus Mountains After the Saharan Dust Outbreak in March 2018, J. Geophys. Res.-Earth, 125, e2020JF005641, https://doi.org/10.1029/2020JF005641, 2020. a, b
Durand, Y., Giraud, G., Brun, E., Mérindol, L., and Martin, E.: A computer-based system simulating snowpack structures as a tool for regional avalanche forecasting, J. Glaciol., 45, 469–484, https://doi.org/10.3189/S0022143000001337, 1999. a
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Durand, Y., Giraud, G., Laternser, M., Etchevers, P., Mérindol, L., and Lesaffre, B.: Reanalysis of 44 Yr of Climate in the French Alps (1958–2002): Methodology, Model Validation, Climatology, and Trends for Air Temperature and Precipitation, J. Appl. Meteorol. Clim., 48, 429–449, https://doi.org/10.1175/2008JAMC1808.1, 2009. a
Eckert, N., Coleou, C., Castebrunet, H., Deschatres, M., Giraud, G., and Gaume, J.: Cross-comparison of meteorological and avalanche data for characterising avalanche cycles: The example of December 2008 in the eastern part of the French Alps, Cold Reg. Sci. Technol., 64, 119–136, https://doi.org/10.1016/j.coldregions.2010.08.009, 2010. a
Eidhammer, T., Booth, A., Decker, S., Li, L., Barlage, M., Gochis, D., Rasmussen, R., Melvold, K., Nesje, A., and Sobolowski, S.: Mass balance and hydrological modeling of the Hardangerjøkulen ice cap in south-central Norway, Hydrol. Earth Syst. Sci., 25, 4275–4297, https://doi.org/10.5194/hess-25-4275-2021, 2021. a
Essery, R., Martin, E., Douville, H., Fernandez, A., and Brun, E.: A comparison of four snow models using observations from an alpine site, Clim. Dynam., 15, 583–593, https://doi.org/10.1007/s003820050302, 1999. a
Essery, R., Morin, S., Lejeune, Y., and Bauduin-Ménard, C.: A comparison of 1701 snow models using observations from an alpine site, Adv. Water Resour., 55, 131–148, https://doi.org/10.1016/j.advwatres.2012.07.013, 2013. a
Essery, R., Mazzotti, G., Barr, S., Jonas, T., Quaife, T., and Rutter, N.: A Flexible Snow Model (FSM 2.1.1) including a forest canopy, Geosci. Model Dev., 18, 3583–3605, https://doi.org/10.5194/gmd-18-3583-2025, 2025. a
Etchevers, P., Martin, E., Brown, R., Fierz, C., Lejeune, Y., Bazile, E., Boone, A., Dai, Y.-J., Essery, R., Fernandez, A., Gusev, Y., Jordan, R., Koren, V., Kowalczyk, E., Nasonova, N. O., Pyles, R. D., Schlosser, A., Shmakin, A. B., Smirnova, T. G., Strasser, U., Verseghy, D., Yamazaki, T., and Yang, Z.-L.: Intercomparison of the surface energy budget simulated by several snow models (SNOWMIP project), Ann. Glaciol., 38, 150–158, https://doi.org/10.3189/172756404781814825, 2004. a, b
Evin, G., Lafaysse, M., Taillardat, M., and Zamo, M.: Calibrated ensemble forecasts of the height of new snow using quantile regression forests and ensemble model output statistics, Nonlin. Processes Geophys., 28, 467–480, https://doi.org/10.5194/npg-28-467-2021, 2021. a
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. a
Fierz, C., Armstrong, R. L., Durand, Y., Etchevers, P., Greene, E., McClung, D. M., Nishimura, K., Satyawali, P. K., and Sokratov, S. A.: The international classification for seasonal snow on the ground, IHP-VII Technical Documents in Hydrology no. 83, IACS Contribution no. 1, UNESCO, https://unesdoc.unesco.org/ark:/48223/pf0000186462 (last access: 17 June 2026), 2009. a
Flanner, M., Liu, X., Zhou, C., and Penner, J.: Enhanced solar energy absorption by internally-mixed black carbon in snow grains, Atmos. Chem. Phys., 12, 4699–4721, https://doi.org/10.5194/acp-12-4699-2012, 2012. a
Flanner, M. G. and Zender, C. S.: Linking snowpack microphysics and albedo evolution, J. Geophys. Res., 111, D12208, https://doi.org/10.1029/2005JD006834, 2006. a, b
Fourteau, K., Brondex, J., Brun, F., and Dumont, M.: A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers, Geosci. Model Dev., 17, 1903–1929, https://doi.org/10.5194/gmd-17-1903-2024, 2024. a, b, c
Fourteau, K., Brondex, J., Cancès, C., and Dumont, M.: Numerical strategies for representing Richards' equation and its couplings in snowpack models, Geosci. Model Dev., 19, 3193–3212, https://doi.org/10.5194/gmd-19-3193-2026, 2026a. a
Fourteau, K., Jondeau, K., Cancès, C., and Dumont, M.: Some insights from the second principle of thermodynamics for snowpack modeling, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-510, 2026b. a
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Short summary
This article is a comprehensive description of the 3.0.2 stable release of the Crocus snowpack model. It describes various new implementations since the last reference article in 2012 and a review of the available scientific evaluations and applications of the model. This provides guidance for the future of numerical snow modelling.
This article is a comprehensive description of the 3.0.2 stable release of the Crocus snowpack...
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