Articles | Volume 6, issue 6
https://doi.org/10.5194/tc-6-1527-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-6-1527-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
19 Dec 2012
Research article |
| 19 Dec 2012
Linking glacier annual mass balance and glacier albedo retrieved from MODIS data
M. Dumont
Université Joseph Fourier, Grenoble I/CNRS, LGGE – UMR5183, Grenoble, France
now at: Météo France/CRNS, CNRM-GAME – URA1357, CEN, Grenoble, France
J. Gardelle
Université Joseph Fourier, Grenoble I/CNRS, LGGE – UMR5183, Grenoble, France
P. Sirguey
School of Surveying, University of Otago, P.O. Box 56, Dunedin, New Zealand
A. Guillot
Université Joseph Fourier, Grenoble I/CNRS, LGGE – UMR5183, Grenoble, France
D. Six
Université Joseph Fourier, Grenoble I/CNRS, LGGE – UMR5183, Grenoble, France
A. Rabatel
Université Joseph Fourier, Grenoble I/CNRS, LGGE – UMR5183, Grenoble, France
Y. Arnaud
Université Joseph Fourier/IRD/CNRS/Grenoble INP, LTHE – UMR5564, Grenoble, France
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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
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Computer models, like those used in climate change studies, are written by modelers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modeling as an example, we examine the process behind the decisions to understand what motivates or limits modelers in their decision-making. We found that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency into our research practice.
Romilly Harris Stuart, Amaëlle Landais, Laurent Arnaud, Christo Buizert, Emilie Capron, Marie Dumont, Quentin Libois, Robert Mulvaney, Anaïs Orsi, Ghislain Picard, Frédéric Prié, Jeffery Severinghaus, Barbara Stenni, and Patricia Martinerie
EGUsphere, https://doi.org/10.5194/egusphere-2023-2585, https://doi.org/10.5194/egusphere-2023-2585, 2023
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The influence of local accumulation rate and temperature on δO2/N2 ice core records, a key dating tool, are not fully understood, but required for a full mechanistic understanding. We show evidence that mean δO2/N2 is strongly dependent on local 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.
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.
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamp-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
EGUsphere, https://doi.org/10.5194/egusphere-2023-2604, https://doi.org/10.5194/egusphere-2023-2604, 2023
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Our study addresses the complex challenge of evaluating distributed alpine snow simulations by disentangling error contributions between blowing snow, precipitation forcings and unresolved subgrid variability. We evaluated simulated snow cover against snow depths from Pléiades stereo-imagery and Snow Melt-Out Dates from Sentinel 2. The simulation of snow transport enhances the snow spatial variance at high elevations while precipitation biases are the prevailing error source in other areas.
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.
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.
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.
Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont
The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022, https://doi.org/10.5194/tc-16-1281-2022, 2022
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The mountainous snow cover is highly variable at all temporal and spatial scales. Snow cover models suffer from large errors, while snowpack observations are sparse. Data assimilation combines them into a better estimate of the snow cover. A major challenge is to propagate information from observed into unobserved areas. This paper presents a spatialized version of the particle filter, in which information from in situ snow depth observations is successfully used to constrain nearby simulations.
Georg Lackner, Florent Domine, Daniel F. Nadeau, Annie-Claude Parent, François Anctil, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 127–142, https://doi.org/10.5194/tc-16-127-2022, https://doi.org/10.5194/tc-16-127-2022, 2022
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The surface energy budget is the sum of all incoming and outgoing energy fluxes at the Earth's surface and has a key role in the climate. We measured all these fluxes for an Arctic snowpack and found that most incoming energy from radiation is counterbalanced by thermal radiation and heat convection while sublimation was negligible. Overall, the snow model Crocus was able to simulate the observed energy fluxes well.
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.
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.
Daniela Krampe, Frank Kauker, Marie Dumont, and Andreas Herber
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-100, https://doi.org/10.5194/tc-2021-100, 2021
Manuscript not accepted for further review
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Reliable and detailed Arctic snow data are limited. Evaluation of the performance of atmospheric reanalysis compared to measurements in northeast Greenland generally show good agreement. Both data sets are applied to an Alpine snow model and the performance for Arctic conditions is investigated: Simulated snow depth evolution is reliable, but vertical snow profiles show weaknesses. These are smaller with an adapted parametrisation for the density of newly fallen snow for harsh Arctic conditions.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev., 14, 1595–1614, https://doi.org/10.5194/gmd-14-1595-2021, https://doi.org/10.5194/gmd-14-1595-2021, 2021
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In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
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This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
Maxim Lamare, Marie Dumont, Ghislain Picard, Fanny Larue, François Tuzet, Clément Delcourt, and Laurent Arnaud
The Cryosphere, 14, 3995–4020, https://doi.org/10.5194/tc-14-3995-2020, https://doi.org/10.5194/tc-14-3995-2020, 2020
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Terrain features found in mountainous regions introduce large errors into the calculation of the physical properties of snow using optical satellite images. We present a new model performing rapid calculations of solar radiation over snow-covered rugged terrain that we tested over a site in the French Alps. The results of the study show that all the interactions between sunlight and the terrain should be accounted for over snow-covered surfaces to correctly estimate snow properties from space.
César Deschamps-Berger, Simon Gascoin, Etienne Berthier, Jeffrey Deems, Ethan Gutmann, Amaury Dehecq, David Shean, and Marie Dumont
The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, https://doi.org/10.5194/tc-14-2925-2020, 2020
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We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it with accurate airborne laser-scanning measurements in the Sierra Nevada, USA. We find that satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountains.
Fanny Larue, Ghislain Picard, Laurent Arnaud, Inès Ollivier, Clément Delcourt, Maxim Lamare, François Tuzet, Jesus Revuelto, and Marie Dumont
The Cryosphere, 14, 1651–1672, https://doi.org/10.5194/tc-14-1651-2020, https://doi.org/10.5194/tc-14-1651-2020, 2020
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The effect of surface roughness on snow albedo is often overlooked,
although a small change in albedo may strongly affect the surface energy
budget. By carving artificial roughness in an initially smooth snowpack,
we highlight albedo reductions of 0.03–0.04 at 700 nm and 0.06–0.10 at 1000 nm. A model using photon transport is developed to compute albedo considering roughness and applied to understand the impact of roughness as a function of snow properties and illumination conditions.
Ghislain Picard, Marie Dumont, Maxim Lamare, François Tuzet, Fanny Larue, Roberta Pirazzini, and Laurent Arnaud
The Cryosphere, 14, 1497–1517, https://doi.org/10.5194/tc-14-1497-2020, https://doi.org/10.5194/tc-14-1497-2020, 2020
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Surface albedo is an essential variable of snow-covered areas. The measurement of this variable over a tilted terrain with levelled sensors is affected by artefacts that need to be corrected. Here we develop a theory of spectral albedo measurement over slopes from which we derive four correction algorithms. The comparison to in situ measurements taken in the Alps shows the adequacy of the theory, and the application of the algorithms shows systematic improvements.
Pascal Hagenmuller, Frederic Flin, Marie Dumont, François Tuzet, Isabel Peinke, Philippe Lapalus, Anne Dufour, Jacques Roulle, Laurent Pézard, Didier Voisin, Edward Ando, Sabine Rolland du Roscoat, and Pascal Charrier
The Cryosphere, 13, 2345–2359, https://doi.org/10.5194/tc-13-2345-2019, https://doi.org/10.5194/tc-13-2345-2019, 2019
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Light–absorbing particles (LAPs, e.g. dust or black carbon) in snow are a potent climate forcing agent. Their presence darkens the snow surface and leads to higher solar energy absorption. Several studies have quantified this radiative impact by assuming that LAPs were motionless in dry snow, without any clear evidence of this assumption. Using time–lapse X–ray tomography, we show that temperature gradient metamorphism of snow induces downward motion of LAPs, leading to self–cleaning of snow.
Francois Tuzet, Marie Dumont, Laurent Arnaud, Didier Voisin, Maxim Lamare, Fanny Larue, Jesus Revuelto, and Ghislain Picard
The Cryosphere, 13, 2169–2187, https://doi.org/10.5194/tc-13-2169-2019, https://doi.org/10.5194/tc-13-2169-2019, 2019
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Here we present a novel method to estimate the impurity content (e.g. black carbon or mineral dust) in Alpine snow based on measurements of light extinction profiles. This method is proposed as an alternative to chemical measurements, allowing rapid retrievals of vertical concentrations of impurities in the snowpack. In addition, the results provide a better understanding of the impact of impurities on visible light extinction in snow.
Cécile B. Ménard, Richard Essery, Alan Barr, Paul Bartlett, Jeff Derry, Marie Dumont, Charles Fierz, Hyungjun Kim, Anna Kontu, Yves Lejeune, Danny Marks, Masashi Niwano, Mark Raleigh, Libo Wang, and Nander Wever
Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, https://doi.org/10.5194/essd-11-865-2019, 2019
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This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
Biagio Di Mauro, Roberto Garzonio, Micol Rossini, Gianluca Filippa, Paolo Pogliotti, Marta Galvagno, Umberto Morra di Cella, Mirco Migliavacca, Giovanni Baccolo, Massimiliano Clemenza, Barbara Delmonte, Valter Maggi, Marie Dumont, François Tuzet, Matthieu Lafaysse, Samuel Morin, Edoardo Cremonese, and Roberto Colombo
The Cryosphere, 13, 1147–1165, https://doi.org/10.5194/tc-13-1147-2019, https://doi.org/10.5194/tc-13-1147-2019, 2019
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The snow albedo reduction due to dust from arid regions alters the melting dynamics of the snowpack, resulting in earlier snowmelt. We estimate up to 38 days of anticipated snow disappearance for a season that was characterized by a strong dust deposition event. This process has a series of further impacts. For example, earlier snowmelts may alter the hydrological cycle in the Alps, induce higher sensitivity to late summer drought, and finally impact vegetation and animal phenology.
Yves Lejeune, Marie Dumont, Jean-Michel Panel, Matthieu Lafaysse, Philippe Lapalus, Erwan Le Gac, Bernard Lesaffre, and Samuel Morin
Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, https://doi.org/10.5194/essd-11-71-2019, 2019
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This paper introduces and provides access to a daily (1960–2017) and an hourly (1993–2017) dataset of snow and meteorological data measured at the Col de Porte site, 1325 m a.s.l, Charteuse, France. The daily dataset can be used to quantify the effect of climate change at this site, with a reduction of the mean snow depth of 39 cm from 1960–1990 to 1990–2017. The daily and hourly datasets are useful and appropriate for driving and evaluating a snowpack model over such a long period.
Alexander Kokhanovsky, Maxim Lamare, Biagio Di Mauro, Ghislain Picard, Laurent Arnaud, Marie Dumont, François Tuzet, Carsten Brockmann, and Jason E. Box
The Cryosphere, 12, 2371–2382, https://doi.org/10.5194/tc-12-2371-2018, https://doi.org/10.5194/tc-12-2371-2018, 2018
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This work presents a new technique with which to derive the snow microphysical and optical properties from snow spectral reflectance measurements. The technique is robust and easy to use, and it does not require the extraction of snow samples from a given snowpack. It can be used in processing satellite imagery over extended fresh dry, wet and polluted snowfields.
Thomas Condom, Marie Dumont, Lise Mourre, Jean Emmanuel Sicart, Antoine Rabatel, Alessandra Viani, and Alvaro Soruco
Geosci. Instrum. Method. Data Syst., 7, 169–178, https://doi.org/10.5194/gi-7-169-2018, https://doi.org/10.5194/gi-7-169-2018, 2018
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This study presents a new instrument called a low-cost albedometer (LCA) composed of two illuminance sensors. The ratio between reflected vs. incident illuminances is called the albedo index and can be compared with actual albedo values. We demonstrate that our system performs well and thus provides relevant opportunities to document spatiotemporal changes in the surface albedo from direct observations at the scale of an entire catchment at a low cost.
Marion Réveillet, Delphine Six, Christian Vincent, Antoine Rabatel, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Vincent Vionnet, and Maxime Litt
The Cryosphere, 12, 1367–1386, https://doi.org/10.5194/tc-12-1367-2018, https://doi.org/10.5194/tc-12-1367-2018, 2018
Lucas Davaze, Antoine Rabatel, Yves Arnaud, Pascal Sirguey, Delphine Six, Anne Letreguilly, and Marie Dumont
The Cryosphere, 12, 271–286, https://doi.org/10.5194/tc-12-271-2018, https://doi.org/10.5194/tc-12-271-2018, 2018
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About 150 of the 250 000 inventoried glaciers are currently monitored with surface mass balance (SMB) measurements. To increase this number, we propose a method to retrieve annual and summer SMB from optical satellite imagery, with an application over 30 glaciers in the French Alps. Computing the glacier-wide averaged albedo allows us to reconstruct annual and summer SMB of most of the studied glaciers, highlighting the potential of this method to retrieve SMB of unmonitored glaciers.
Francois Tuzet, Marie Dumont, Matthieu Lafaysse, Ghislain Picard, Laurent Arnaud, Didier Voisin, Yves Lejeune, Luc Charrois, Pierre Nabat, and Samuel Morin
The Cryosphere, 11, 2633–2653, https://doi.org/10.5194/tc-11-2633-2017, https://doi.org/10.5194/tc-11-2633-2017, 2017
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Light-absorbing impurities deposited on snow, such as soot or dust, strongly modify its evolution. We implemented impurity deposition and evolution in a detailed snowpack model, thereby expanding the reach of such models into addressing the subtle interplays between snow physics and impurities' optical properties. Model results were evaluated based on innovative field observations at an Alpine site. This allows future investigations in the fields of climate, hydrology and avalanche prediction.
Jesús Revuelto, Grégoire Lecourt, Matthieu Lafaysse, Isabella Zin, Luc Charrois, Vincent Vionnet, Marie Dumont, Antoine Rabatel, Delphine Six, Thomas Condom, Samuel Morin, Alessandra Viani, and Pascal Sirguey
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-184, https://doi.org/10.5194/tc-2017-184, 2017
Revised manuscript not accepted
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We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope.
Matthieu Lafaysse, Bertrand Cluzet, Marie Dumont, Yves Lejeune, Vincent Vionnet, and Samuel Morin
The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, https://doi.org/10.5194/tc-11-1173-2017, 2017
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Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC by implementing new representations of different physical processes in a coupled multilayer ground/snowpack model. This system is a promising tool to integrate snow modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack modelling applications.
Marie Dumont, Laurent Arnaud, Ghislain Picard, Quentin Libois, Yves Lejeune, Pierre Nabat, Didier Voisin, and Samuel Morin
The Cryosphere, 11, 1091–1110, https://doi.org/10.5194/tc-11-1091-2017, https://doi.org/10.5194/tc-11-1091-2017, 2017
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Snow spectral albedo in the visible/near-infrared range has been continuously measured during a winter season at Col de Porte alpine site (French Alps; 45.30° N, 5.77°E; 1325 m a.s.l.). This study highlights that the variations of spectral albedo can be successfully explained by variations of the following snow surface variables: snow-specific surface area, effective light-absorbing impurities content, presence of liquid water and slope.
Pascal Sirguey, Holly Still, Nicolas J. Cullen, Marie Dumont, Yves Arnaud, and Jonathan P. Conway
The Cryosphere, 10, 2465–2484, https://doi.org/10.5194/tc-10-2465-2016, https://doi.org/10.5194/tc-10-2465-2016, 2016
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Fourteen years of satellite observations are used to monitor the albedo of Brewster Glacier, New Zealand and estimate annual and seasonal balances. This confirms the governing role of the summer balance in the annual balance and allows the reconstruction of the annual balance to 1977 using a photographic record of the snowline. The longest mass balance record for a New Zealand glacier shows negative balances after 2008, yielding a loss of 35 % of the gain accumulated over the previous 30 years.
Louis Quéno, Vincent Vionnet, Ingrid Dombrowski-Etchevers, Matthieu Lafaysse, Marie Dumont, and Fatima Karbou
The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, https://doi.org/10.5194/tc-10-1571-2016, 2016
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Simulations are carried out in the Pyrenees with the snowpack model Crocus, driven by meteorological forecasts from the model AROME at kilometer resolution. The evaluation is done with ground-based measurements, satellite data and reference simulations. Studying daily snow depth variations allows to separate different physical processes affecting the snowpack. We show the benefits of AROME kilometric resolution and dynamical behavior in terms of snowpack spatial variability in a mountain range.
Ghislain Picard, Quentin Libois, Laurent Arnaud, Gauthier Verin, and Marie Dumont
The Cryosphere, 10, 1297–1316, https://doi.org/10.5194/tc-10-1297-2016, https://doi.org/10.5194/tc-10-1297-2016, 2016
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Albedo of snow surfaces depends on snow grain size. By measuring albedo during 3 years at Dome C in Antarctica with an automatic spectroradiometer, we were able to monitor the snow specific surface area and show an overall growth of the grains in spring and summer followed by an accumulation of small-grained snow from mid-summer. This study focuses on the uncertainties due to the spectroradiometer and concludes that the observed variations are significant with respect to the precision.
Richard Essery, Anna Kontu, Juha Lemmetyinen, Marie Dumont, and Cécile B. Ménard
Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016, https://doi.org/10.5194/gi-5-219-2016, 2016
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Physically based models that predict the properties of snow on the ground are used in many applications, but meteorological input data required by these models are hard to obtain in cold regions. Monitoring at the Sodankyla research station allows construction of model input and evaluation datasets covering several years for the first time in the Arctic. The data are used to show that a sophisticated snow model developed for warmer and wetter sites can perform well in very different conditions.
Luc Charrois, Emmanuel Cosme, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Quentin Libois, and Ghislain Picard
The Cryosphere, 10, 1021–1038, https://doi.org/10.5194/tc-10-1021-2016, https://doi.org/10.5194/tc-10-1021-2016, 2016
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This study investigates the assimilation of optical reflectances, snowdepth data and both combined into a multilayer snowpack model. Data assimilation is performed with an ensemble-based method, the Sequential Importance Resampling Particle filter. Experiments assimilating only synthetic data are conducted at one point in the French Alps, the Col du Lautaret, over five hydrological years. Results of the assimilation experiments show improvements of the snowpack bulk variables estimates.
Lucie Bazin, Amaelle Landais, Emilie Capron, Valérie Masson-Delmotte, Catherine Ritz, Ghislain Picard, Jean Jouzel, Marie Dumont, Markus Leuenberger, and Frédéric Prié
Clim. Past, 12, 729–748, https://doi.org/10.5194/cp-12-729-2016, https://doi.org/10.5194/cp-12-729-2016, 2016
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We present new measurements of δO2⁄N2 and δ18Oatm performed on well-conserved ice from EDC covering MIS5 and between 380 and 800 ka. The combination of the observation of a 100 ka periodicity in the new δO2⁄N2 record with a MIS5 multi-site multi-proxy study has revealed a potential influence of local climatic parameters on δO2⁄N2. Moreover, we propose that the varying delay between d18Oatm and precession for the last 800 ka is affected by the occurrence of ice sheet discharge events.
Q. Libois, G. Picard, L. Arnaud, M. Dumont, M. Lafaysse, S. Morin, and E. Lefebvre
The Cryosphere, 9, 2383–2398, https://doi.org/10.5194/tc-9-2383-2015, https://doi.org/10.5194/tc-9-2383-2015, 2015
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The albedo and surface energy budget of the Antarctic Plateau are largely determined by snow specific surface area. The latter experiences substantial daily-to-seasonal variations in response to meteorological conditions. In particular, it decreases by a factor three in summer, causing a drop in albedo. These variations are monitored from in situ and remote sensing observations at Dome C. For the first time, they are also simulated with a snowpack evolution model adapted to Antarctic conditions.
F. Brun, M. Dumont, P. Wagnon, E. Berthier, M. F. Azam, J. M. Shea, P. Sirguey, A. Rabatel, and Al. Ramanathan
The Cryosphere, 9, 341–355, https://doi.org/10.5194/tc-9-341-2015, https://doi.org/10.5194/tc-9-341-2015, 2015
X. V. Phan, L. Ferro-Famil, M. Gay, Y. Durand, M. Dumont, S. Morin, S. Allain, G. D'Urso, and A. Girard
The Cryosphere, 8, 1975–1987, https://doi.org/10.5194/tc-8-1975-2014, https://doi.org/10.5194/tc-8-1975-2014, 2014
P. Ginot, M. Dumont, S. Lim, N. Patris, J.-D. Taupin, P. Wagnon, A. Gilbert, Y. Arnaud, A. Marinoni, P. Bonasoni, and P. Laj
The Cryosphere, 8, 1479–1496, https://doi.org/10.5194/tc-8-1479-2014, https://doi.org/10.5194/tc-8-1479-2014, 2014
J.-C. Gallet, F. Domine, J. Savarino, M. Dumont, and E. Brun
The Cryosphere, 8, 1205–1215, https://doi.org/10.5194/tc-8-1205-2014, https://doi.org/10.5194/tc-8-1205-2014, 2014
J.-C. Gallet, F. Domine, and M. Dumont
The Cryosphere, 8, 1139–1148, https://doi.org/10.5194/tc-8-1139-2014, https://doi.org/10.5194/tc-8-1139-2014, 2014
H. C. Steen-Larsen, V. Masson-Delmotte, M. Hirabayashi, R. Winkler, K. Satow, F. Prié, N. Bayou, E. Brun, K. M. Cuffey, D. Dahl-Jensen, M. Dumont, M. Guillevic, S. Kipfstuhl, A. Landais, T. Popp, C. Risi, K. Steffen, B. Stenni, and A. E. Sveinbjörnsdottír
Clim. Past, 10, 377–392, https://doi.org/10.5194/cp-10-377-2014, https://doi.org/10.5194/cp-10-377-2014, 2014
Q. Libois, G. Picard, J. L. France, L. Arnaud, M. Dumont, C. M. Carmagnola, and M. D. King
The Cryosphere, 7, 1803–1818, https://doi.org/10.5194/tc-7-1803-2013, https://doi.org/10.5194/tc-7-1803-2013, 2013
P. Wagnon, C. Vincent, Y. Arnaud, E. Berthier, E. Vuillermoz, S. Gruber, M. Ménégoz, A. Gilbert, M. Dumont, J. M. Shea, D. Stumm, and B. K. Pokhrel
The Cryosphere, 7, 1769–1786, https://doi.org/10.5194/tc-7-1769-2013, https://doi.org/10.5194/tc-7-1769-2013, 2013
C. M. Carmagnola, F. Domine, M. Dumont, P. Wright, B. Strellis, M. Bergin, J. Dibb, G. Picard, Q. Libois, L. Arnaud, and S. Morin
The Cryosphere, 7, 1139–1160, https://doi.org/10.5194/tc-7-1139-2013, https://doi.org/10.5194/tc-7-1139-2013, 2013
M. Geyer, D. Salas Y Melia, E. Brun, and M. Dumont
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-3163-2013, https://doi.org/10.5194/tcd-7-3163-2013, 2013
Revised manuscript has not been submitted
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-2926, https://doi.org/10.5194/egusphere-2023-2926, 2024
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Computer models, like those used in climate change studies, are written by modelers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modeling as an example, we examine the process behind the decisions to understand what motivates or limits modelers in their decision-making. We found that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency into our research practice.
Romilly Harris Stuart, Amaëlle Landais, Laurent Arnaud, Christo Buizert, Emilie Capron, Marie Dumont, Quentin Libois, Robert Mulvaney, Anaïs Orsi, Ghislain Picard, Frédéric Prié, Jeffery Severinghaus, Barbara Stenni, and Patricia Martinerie
EGUsphere, https://doi.org/10.5194/egusphere-2023-2585, https://doi.org/10.5194/egusphere-2023-2585, 2023
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The influence of local accumulation rate and temperature on δO2/N2 ice core records, a key dating tool, are not fully understood, but required for a full mechanistic understanding. We show evidence that mean δO2/N2 is strongly dependent on local 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.
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.
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamp-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
EGUsphere, https://doi.org/10.5194/egusphere-2023-2604, https://doi.org/10.5194/egusphere-2023-2604, 2023
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Our study addresses the complex challenge of evaluating distributed alpine snow simulations by disentangling error contributions between blowing snow, precipitation forcings and unresolved subgrid variability. We evaluated simulated snow cover against snow depths from Pléiades stereo-imagery and Snow Melt-Out Dates from Sentinel 2. The simulation of snow transport enhances the snow spatial variance at high elevations while precipitation biases are the prevailing error source in other areas.
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.
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.
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.
Aubrey Miller, Pascal Sirguey, Simon Morris, Perry Bartelt, Nicolas Cullen, Todd Redpath, Kevin Thompson, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 2673–2701, https://doi.org/10.5194/nhess-22-2673-2022, https://doi.org/10.5194/nhess-22-2673-2022, 2022
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Natural hazard modelers simulate mass movements to better anticipate the risk to people and infrastructure. These simulations require accurate digital elevation models. We test the sensitivity of a well-established snow avalanche model (RAMMS) to the source and spatial resolution of the elevation model. We find key differences in the digital representation of terrain greatly affect the simulated avalanche results, with implications for hazard planning.
Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont
The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022, https://doi.org/10.5194/tc-16-1281-2022, 2022
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The mountainous snow cover is highly variable at all temporal and spatial scales. Snow cover models suffer from large errors, while snowpack observations are sparse. Data assimilation combines them into a better estimate of the snow cover. A major challenge is to propagate information from observed into unobserved areas. This paper presents a spatialized version of the particle filter, in which information from in situ snow depth observations is successfully used to constrain nearby simulations.
Georg Lackner, Florent Domine, Daniel F. Nadeau, Annie-Claude Parent, François Anctil, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 127–142, https://doi.org/10.5194/tc-16-127-2022, https://doi.org/10.5194/tc-16-127-2022, 2022
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The surface energy budget is the sum of all incoming and outgoing energy fluxes at the Earth's surface and has a key role in the climate. We measured all these fluxes for an Arctic snowpack and found that most incoming energy from radiation is counterbalanced by thermal radiation and heat convection while sublimation was negligible. Overall, the snow model Crocus was able to simulate the observed energy fluxes well.
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.
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.
Daniela Krampe, Frank Kauker, Marie Dumont, and Andreas Herber
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-100, https://doi.org/10.5194/tc-2021-100, 2021
Manuscript not accepted for further review
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Reliable and detailed Arctic snow data are limited. Evaluation of the performance of atmospheric reanalysis compared to measurements in northeast Greenland generally show good agreement. Both data sets are applied to an Alpine snow model and the performance for Arctic conditions is investigated: Simulated snow depth evolution is reliable, but vertical snow profiles show weaknesses. These are smaller with an adapted parametrisation for the density of newly fallen snow for harsh Arctic conditions.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev., 14, 1595–1614, https://doi.org/10.5194/gmd-14-1595-2021, https://doi.org/10.5194/gmd-14-1595-2021, 2021
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In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Lucie A. Eberhard, Pascal Sirguey, Aubrey Miller, Mauro Marty, Konrad Schindler, Andreas Stoffel, and Yves Bühler
The Cryosphere, 15, 69–94, https://doi.org/10.5194/tc-15-69-2021, https://doi.org/10.5194/tc-15-69-2021, 2021
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In spring 2018 in the alpine Dischma valley (Switzerland), we tested different industrial photogrammetric platforms for snow depth mapping. These platforms were high-resolution satellites, an airplane, unmanned aerial systems and a terrestrial system. Therefore, this study gives a general overview of the accuracy and precision of the different photogrammetric platforms available in space and on earth and their use for snow depth mapping.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
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This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
Maxim Lamare, Marie Dumont, Ghislain Picard, Fanny Larue, François Tuzet, Clément Delcourt, and Laurent Arnaud
The Cryosphere, 14, 3995–4020, https://doi.org/10.5194/tc-14-3995-2020, https://doi.org/10.5194/tc-14-3995-2020, 2020
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Terrain features found in mountainous regions introduce large errors into the calculation of the physical properties of snow using optical satellite images. We present a new model performing rapid calculations of solar radiation over snow-covered rugged terrain that we tested over a site in the French Alps. The results of the study show that all the interactions between sunlight and the terrain should be accounted for over snow-covered surfaces to correctly estimate snow properties from space.
Angus J. Dowson, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 14, 3425–3448, https://doi.org/10.5194/tc-14-3425-2020, https://doi.org/10.5194/tc-14-3425-2020, 2020
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Satellite observations over 19 years are used to characterise the spatial and temporal variability of surface albedo across the gardens of Eden and Allah, two of New Zealand’s largest ice fields. The variability in response of individual glaciers reveals the role of topographic setting and suggests that glaciers in the Southern Alps do not behave as a single climatic unit. There is evidence that the timing of the minimum surface albedo has shifted to later in the summer on 10 of the 12 glaciers.
César Deschamps-Berger, Simon Gascoin, Etienne Berthier, Jeffrey Deems, Ethan Gutmann, Amaury Dehecq, David Shean, and Marie Dumont
The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, https://doi.org/10.5194/tc-14-2925-2020, 2020
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We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it with accurate airborne laser-scanning measurements in the Sierra Nevada, USA. We find that satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountains.
Fanny Larue, Ghislain Picard, Laurent Arnaud, Inès Ollivier, Clément Delcourt, Maxim Lamare, François Tuzet, Jesus Revuelto, and Marie Dumont
The Cryosphere, 14, 1651–1672, https://doi.org/10.5194/tc-14-1651-2020, https://doi.org/10.5194/tc-14-1651-2020, 2020
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The effect of surface roughness on snow albedo is often overlooked,
although a small change in albedo may strongly affect the surface energy
budget. By carving artificial roughness in an initially smooth snowpack,
we highlight albedo reductions of 0.03–0.04 at 700 nm and 0.06–0.10 at 1000 nm. A model using photon transport is developed to compute albedo considering roughness and applied to understand the impact of roughness as a function of snow properties and illumination conditions.
Ghislain Picard, Marie Dumont, Maxim Lamare, François Tuzet, Fanny Larue, Roberta Pirazzini, and Laurent Arnaud
The Cryosphere, 14, 1497–1517, https://doi.org/10.5194/tc-14-1497-2020, https://doi.org/10.5194/tc-14-1497-2020, 2020
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Surface albedo is an essential variable of snow-covered areas. The measurement of this variable over a tilted terrain with levelled sensors is affected by artefacts that need to be corrected. Here we develop a theory of spectral albedo measurement over slopes from which we derive four correction algorithms. The comparison to in situ measurements taken in the Alps shows the adequacy of the theory, and the application of the algorithms shows systematic improvements.
Louise Mimeau, Michel Esteves, Isabella Zin, Hans-Werner Jacobi, Fanny Brun, Patrick Wagnon, Devesh Koirala, and Yves Arnaud
Hydrol. Earth Syst. Sci., 23, 3969–3996, https://doi.org/10.5194/hess-23-3969-2019, https://doi.org/10.5194/hess-23-3969-2019, 2019
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In a context of climate change, the quantification of the contributions of glacier melt, snowmelt, and rain to the river streamflow is a key issue for assessing the current and future water resource availability. This study discusses the representation of the snow and glacier processes in hydrological models and its impact on the estimated flow components, and also addresses the issue of defining the glacier contribution to the river streamflow.
Pascal Hagenmuller, Frederic Flin, Marie Dumont, François Tuzet, Isabel Peinke, Philippe Lapalus, Anne Dufour, Jacques Roulle, Laurent Pézard, Didier Voisin, Edward Ando, Sabine Rolland du Roscoat, and Pascal Charrier
The Cryosphere, 13, 2345–2359, https://doi.org/10.5194/tc-13-2345-2019, https://doi.org/10.5194/tc-13-2345-2019, 2019
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Light–absorbing particles (LAPs, e.g. dust or black carbon) in snow are a potent climate forcing agent. Their presence darkens the snow surface and leads to higher solar energy absorption. Several studies have quantified this radiative impact by assuming that LAPs were motionless in dry snow, without any clear evidence of this assumption. Using time–lapse X–ray tomography, we show that temperature gradient metamorphism of snow induces downward motion of LAPs, leading to self–cleaning of snow.
Francois Tuzet, Marie Dumont, Laurent Arnaud, Didier Voisin, Maxim Lamare, Fanny Larue, Jesus Revuelto, and Ghislain Picard
The Cryosphere, 13, 2169–2187, https://doi.org/10.5194/tc-13-2169-2019, https://doi.org/10.5194/tc-13-2169-2019, 2019
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Here we present a novel method to estimate the impurity content (e.g. black carbon or mineral dust) in Alpine snow based on measurements of light extinction profiles. This method is proposed as an alternative to chemical measurements, allowing rapid retrievals of vertical concentrations of impurities in the snowpack. In addition, the results provide a better understanding of the impact of impurities on visible light extinction in snow.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
Hydrol. Earth Syst. Sci., 23, 3189–3217, https://doi.org/10.5194/hess-23-3189-2019, https://doi.org/10.5194/hess-23-3189-2019, 2019
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Spatio-temporal variability of seasonal snow cover is characterised from 16 years of MODIS data for the Clutha Catchment, New Zealand. No trend was detected in snow-covered area. Spatial modes of variability reveal the role of anomalous winter airflow. The sensitivity of snow cover duration to temperature and precipitation variability is found to vary spatially across the catchment. These findings provide new insight into seasonal snow processes in New Zealand and guidance for modelling efforts.
Cécile B. Ménard, Richard Essery, Alan Barr, Paul Bartlett, Jeff Derry, Marie Dumont, Charles Fierz, Hyungjun Kim, Anna Kontu, Yves Lejeune, Danny Marks, Masashi Niwano, Mark Raleigh, Libo Wang, and Nander Wever
Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, https://doi.org/10.5194/essd-11-865-2019, 2019
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This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
Biagio Di Mauro, Roberto Garzonio, Micol Rossini, Gianluca Filippa, Paolo Pogliotti, Marta Galvagno, Umberto Morra di Cella, Mirco Migliavacca, Giovanni Baccolo, Massimiliano Clemenza, Barbara Delmonte, Valter Maggi, Marie Dumont, François Tuzet, Matthieu Lafaysse, Samuel Morin, Edoardo Cremonese, and Roberto Colombo
The Cryosphere, 13, 1147–1165, https://doi.org/10.5194/tc-13-1147-2019, https://doi.org/10.5194/tc-13-1147-2019, 2019
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The snow albedo reduction due to dust from arid regions alters the melting dynamics of the snowpack, resulting in earlier snowmelt. We estimate up to 38 days of anticipated snow disappearance for a season that was characterized by a strong dust deposition event. This process has a series of further impacts. For example, earlier snowmelts may alter the hydrological cycle in the Alps, induce higher sensitivity to late summer drought, and finally impact vegetation and animal phenology.
Yves Lejeune, Marie Dumont, Jean-Michel Panel, Matthieu Lafaysse, Philippe Lapalus, Erwan Le Gac, Bernard Lesaffre, and Samuel Morin
Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, https://doi.org/10.5194/essd-11-71-2019, 2019
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This paper introduces and provides access to a daily (1960–2017) and an hourly (1993–2017) dataset of snow and meteorological data measured at the Col de Porte site, 1325 m a.s.l, Charteuse, France. The daily dataset can be used to quantify the effect of climate change at this site, with a reduction of the mean snow depth of 39 cm from 1960–1990 to 1990–2017. The daily and hourly datasets are useful and appropriate for driving and evaluating a snowpack model over such a long period.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 12, 3477–3497, https://doi.org/10.5194/tc-12-3477-2018, https://doi.org/10.5194/tc-12-3477-2018, 2018
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A remotely piloted aircraft system (RPAS) is evaluated for mapping seasonal snow depth across an alpine basin. RPAS photogrammetry performs well at providing maps of snow depth at high spatial resolution, outperforming field measurements for resolving spatial variability. Uncertainty and error analysis reveal limitations and potential pitfalls of photogrammetric surface-change analysis. Ultimately, RPAS can be a useful tool for understanding snow processes and improving snow modelling efforts.
Alexander Kokhanovsky, Maxim Lamare, Biagio Di Mauro, Ghislain Picard, Laurent Arnaud, Marie Dumont, François Tuzet, Carsten Brockmann, and Jason E. Box
The Cryosphere, 12, 2371–2382, https://doi.org/10.5194/tc-12-2371-2018, https://doi.org/10.5194/tc-12-2371-2018, 2018
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This work presents a new technique with which to derive the snow microphysical and optical properties from snow spectral reflectance measurements. The technique is robust and easy to use, and it does not require the extraction of snow samples from a given snowpack. It can be used in processing satellite imagery over extended fresh dry, wet and polluted snowfields.
Thomas Condom, Marie Dumont, Lise Mourre, Jean Emmanuel Sicart, Antoine Rabatel, Alessandra Viani, and Alvaro Soruco
Geosci. Instrum. Method. Data Syst., 7, 169–178, https://doi.org/10.5194/gi-7-169-2018, https://doi.org/10.5194/gi-7-169-2018, 2018
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This study presents a new instrument called a low-cost albedometer (LCA) composed of two illuminance sensors. The ratio between reflected vs. incident illuminances is called the albedo index and can be compared with actual albedo values. We demonstrate that our system performs well and thus provides relevant opportunities to document spatiotemporal changes in the surface albedo from direct observations at the scale of an entire catchment at a low cost.
Marion Réveillet, Delphine Six, Christian Vincent, Antoine Rabatel, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Vincent Vionnet, and Maxime Litt
The Cryosphere, 12, 1367–1386, https://doi.org/10.5194/tc-12-1367-2018, https://doi.org/10.5194/tc-12-1367-2018, 2018
Lucas Davaze, Antoine Rabatel, Yves Arnaud, Pascal Sirguey, Delphine Six, Anne Letreguilly, and Marie Dumont
The Cryosphere, 12, 271–286, https://doi.org/10.5194/tc-12-271-2018, https://doi.org/10.5194/tc-12-271-2018, 2018
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About 150 of the 250 000 inventoried glaciers are currently monitored with surface mass balance (SMB) measurements. To increase this number, we propose a method to retrieve annual and summer SMB from optical satellite imagery, with an application over 30 glaciers in the French Alps. Computing the glacier-wide averaged albedo allows us to reconstruct annual and summer SMB of most of the studied glaciers, highlighting the potential of this method to retrieve SMB of unmonitored glaciers.
Francois Tuzet, Marie Dumont, Matthieu Lafaysse, Ghislain Picard, Laurent Arnaud, Didier Voisin, Yves Lejeune, Luc Charrois, Pierre Nabat, and Samuel Morin
The Cryosphere, 11, 2633–2653, https://doi.org/10.5194/tc-11-2633-2017, https://doi.org/10.5194/tc-11-2633-2017, 2017
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Light-absorbing impurities deposited on snow, such as soot or dust, strongly modify its evolution. We implemented impurity deposition and evolution in a detailed snowpack model, thereby expanding the reach of such models into addressing the subtle interplays between snow physics and impurities' optical properties. Model results were evaluated based on innovative field observations at an Alpine site. This allows future investigations in the fields of climate, hydrology and avalanche prediction.
Jesús Revuelto, Grégoire Lecourt, Matthieu Lafaysse, Isabella Zin, Luc Charrois, Vincent Vionnet, Marie Dumont, Antoine Rabatel, Delphine Six, Thomas Condom, Samuel Morin, Alessandra Viani, and Pascal Sirguey
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-184, https://doi.org/10.5194/tc-2017-184, 2017
Revised manuscript not accepted
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We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope.
Matthieu Lafaysse, Bertrand Cluzet, Marie Dumont, Yves Lejeune, Vincent Vionnet, and Samuel Morin
The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, https://doi.org/10.5194/tc-11-1173-2017, 2017
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Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC by implementing new representations of different physical processes in a coupled multilayer ground/snowpack model. This system is a promising tool to integrate snow modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack modelling applications.
Marie Dumont, Laurent Arnaud, Ghislain Picard, Quentin Libois, Yves Lejeune, Pierre Nabat, Didier Voisin, and Samuel Morin
The Cryosphere, 11, 1091–1110, https://doi.org/10.5194/tc-11-1091-2017, https://doi.org/10.5194/tc-11-1091-2017, 2017
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Snow spectral albedo in the visible/near-infrared range has been continuously measured during a winter season at Col de Porte alpine site (French Alps; 45.30° N, 5.77°E; 1325 m a.s.l.). This study highlights that the variations of spectral albedo can be successfully explained by variations of the following snow surface variables: snow-specific surface area, effective light-absorbing impurities content, presence of liquid water and slope.
Pascal Bohleber, Leo Sold, Douglas R. Hardy, Margit Schwikowski, Patrick Klenk, Andrea Fischer, Pascal Sirguey, Nicolas J. Cullen, Mariusz Potocki, Helene Hoffmann, and Paul Mayewski
The Cryosphere, 11, 469–482, https://doi.org/10.5194/tc-11-469-2017, https://doi.org/10.5194/tc-11-469-2017, 2017
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Our study is the first to use ground-penetrating radar (GPR) to investigate ice thickness and internal layering at Kilimanjaro’s largest ice body, the Northern Ice Field (NIF). For monitoring the ongoing ice loss, our ice thickness soundings allowed us to estimate the total ice volume remaining at NIF's southern portion. Englacial GPR reflections indicate undisturbed layers within NIF's center and provide a first link between age information obtained from ice coring and vertical wall sampling.
Pascal Sirguey, Holly Still, Nicolas J. Cullen, Marie Dumont, Yves Arnaud, and Jonathan P. Conway
The Cryosphere, 10, 2465–2484, https://doi.org/10.5194/tc-10-2465-2016, https://doi.org/10.5194/tc-10-2465-2016, 2016
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Fourteen years of satellite observations are used to monitor the albedo of Brewster Glacier, New Zealand and estimate annual and seasonal balances. This confirms the governing role of the summer balance in the annual balance and allows the reconstruction of the annual balance to 1977 using a photographic record of the snowline. The longest mass balance record for a New Zealand glacier shows negative balances after 2008, yielding a loss of 35 % of the gain accumulated over the previous 30 years.
Christian Vincent, Patrick Wagnon, Joseph M. Shea, Walter W. Immerzeel, Philip Kraaijenbrink, Dibas Shrestha, Alvaro Soruco, Yves Arnaud, Fanny Brun, Etienne Berthier, and Sonam Futi Sherpa
The Cryosphere, 10, 1845–1858, https://doi.org/10.5194/tc-10-1845-2016, https://doi.org/10.5194/tc-10-1845-2016, 2016
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Approximately 25 % of the glacierized area in the Everest region is covered by debris, yet the surface mass balance of these glaciers has not been measured directly. From terrestrial photogrammetry and unmanned aerial vehicle (UAV) methods, this study shows that the ablation is strongly reduced by the debris cover. The insulating effect of the debris cover has a larger effect on total mass loss than the enhanced ice ablation due to supraglacial ponds and exposed ice cliffs.
Louis Quéno, Vincent Vionnet, Ingrid Dombrowski-Etchevers, Matthieu Lafaysse, Marie Dumont, and Fatima Karbou
The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, https://doi.org/10.5194/tc-10-1571-2016, 2016
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Simulations are carried out in the Pyrenees with the snowpack model Crocus, driven by meteorological forecasts from the model AROME at kilometer resolution. The evaluation is done with ground-based measurements, satellite data and reference simulations. Studying daily snow depth variations allows to separate different physical processes affecting the snowpack. We show the benefits of AROME kilometric resolution and dynamical behavior in terms of snowpack spatial variability in a mountain range.
Ghislain Picard, Quentin Libois, Laurent Arnaud, Gauthier Verin, and Marie Dumont
The Cryosphere, 10, 1297–1316, https://doi.org/10.5194/tc-10-1297-2016, https://doi.org/10.5194/tc-10-1297-2016, 2016
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Albedo of snow surfaces depends on snow grain size. By measuring albedo during 3 years at Dome C in Antarctica with an automatic spectroradiometer, we were able to monitor the snow specific surface area and show an overall growth of the grains in spring and summer followed by an accumulation of small-grained snow from mid-summer. This study focuses on the uncertainties due to the spectroradiometer and concludes that the observed variations are significant with respect to the precision.
Richard Essery, Anna Kontu, Juha Lemmetyinen, Marie Dumont, and Cécile B. Ménard
Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016, https://doi.org/10.5194/gi-5-219-2016, 2016
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Physically based models that predict the properties of snow on the ground are used in many applications, but meteorological input data required by these models are hard to obtain in cold regions. Monitoring at the Sodankyla research station allows construction of model input and evaluation datasets covering several years for the first time in the Arctic. The data are used to show that a sophisticated snow model developed for warmer and wetter sites can perform well in very different conditions.
Luc Charrois, Emmanuel Cosme, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Quentin Libois, and Ghislain Picard
The Cryosphere, 10, 1021–1038, https://doi.org/10.5194/tc-10-1021-2016, https://doi.org/10.5194/tc-10-1021-2016, 2016
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This study investigates the assimilation of optical reflectances, snowdepth data and both combined into a multilayer snowpack model. Data assimilation is performed with an ensemble-based method, the Sequential Importance Resampling Particle filter. Experiments assimilating only synthetic data are conducted at one point in the French Alps, the Col du Lautaret, over five hydrological years. Results of the assimilation experiments show improvements of the snowpack bulk variables estimates.
Lucie Bazin, Amaelle Landais, Emilie Capron, Valérie Masson-Delmotte, Catherine Ritz, Ghislain Picard, Jean Jouzel, Marie Dumont, Markus Leuenberger, and Frédéric Prié
Clim. Past, 12, 729–748, https://doi.org/10.5194/cp-12-729-2016, https://doi.org/10.5194/cp-12-729-2016, 2016
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We present new measurements of δO2⁄N2 and δ18Oatm performed on well-conserved ice from EDC covering MIS5 and between 380 and 800 ka. The combination of the observation of a 100 ka periodicity in the new δO2⁄N2 record with a MIS5 multi-site multi-proxy study has revealed a potential influence of local climatic parameters on δO2⁄N2. Moreover, we propose that the varying delay between d18Oatm and precession for the last 800 ka is affected by the occurrence of ice sheet discharge events.
Q. Libois, G. Picard, L. Arnaud, M. Dumont, M. Lafaysse, S. Morin, and E. Lefebvre
The Cryosphere, 9, 2383–2398, https://doi.org/10.5194/tc-9-2383-2015, https://doi.org/10.5194/tc-9-2383-2015, 2015
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The albedo and surface energy budget of the Antarctic Plateau are largely determined by snow specific surface area. The latter experiences substantial daily-to-seasonal variations in response to meteorological conditions. In particular, it decreases by a factor three in summer, causing a drop in albedo. These variations are monitored from in situ and remote sensing observations at Dome C. For the first time, they are also simulated with a snowpack evolution model adapted to Antarctic conditions.
H.-W. Jacobi, S. Lim, M. Ménégoz, P. Ginot, P. Laj, P. Bonasoni, P. Stocchi, A. Marinoni, and Y. Arnaud
The Cryosphere, 9, 1685–1699, https://doi.org/10.5194/tc-9-1685-2015, https://doi.org/10.5194/tc-9-1685-2015, 2015
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We detected up to 70 ppb of black carbon (BC) in surface snow in the upper Khumbu Valley, Nepal. With an upgraded snowpack model, including radiative transfer inside the snow, we studied the impact of BC on snow albedo, melting and radiative forcing for the sensitive high altitude regions of the Himalayas. We found that due to BC, the melting of the snow can be shifted by several days up to several weeks depending on meteorological conditions. The impact of BC is larger in dirty snow.
A. E. Racoviteanu, Y. Arnaud, M. W. Williams, and W. F. Manley
The Cryosphere, 9, 505–523, https://doi.org/10.5194/tc-9-505-2015, https://doi.org/10.5194/tc-9-505-2015, 2015
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An overall negative glacier surface area change of 0.5±0.2% yr-1 was observed for the eastern Himalaya since 1962 based on remote sensing data. There were higher rates of area loss for clean glaciers (-34%, or -0.7% yr-1) compared to debris-covered glaciers (-14.3% or -0.3 yr-1) on a glacier-by-glacier basis. Patterns of area change are heterogenous and depend on topographic and climatic factors, glacier altitude (maximum, median, altitudinal range), glacier size, slope and aspect.
F. Brun, M. Dumont, P. Wagnon, E. Berthier, M. F. Azam, J. M. Shea, P. Sirguey, A. Rabatel, and Al. Ramanathan
The Cryosphere, 9, 341–355, https://doi.org/10.5194/tc-9-341-2015, https://doi.org/10.5194/tc-9-341-2015, 2015
X. V. Phan, L. Ferro-Famil, M. Gay, Y. Durand, M. Dumont, S. Morin, S. Allain, G. D'Urso, and A. Girard
The Cryosphere, 8, 1975–1987, https://doi.org/10.5194/tc-8-1975-2014, https://doi.org/10.5194/tc-8-1975-2014, 2014
P. Ginot, M. Dumont, S. Lim, N. Patris, J.-D. Taupin, P. Wagnon, A. Gilbert, Y. Arnaud, A. Marinoni, P. Bonasoni, and P. Laj
The Cryosphere, 8, 1479–1496, https://doi.org/10.5194/tc-8-1479-2014, https://doi.org/10.5194/tc-8-1479-2014, 2014
J.-C. Gallet, F. Domine, J. Savarino, M. Dumont, and E. Brun
The Cryosphere, 8, 1205–1215, https://doi.org/10.5194/tc-8-1205-2014, https://doi.org/10.5194/tc-8-1205-2014, 2014
J.-C. Gallet, F. Domine, and M. Dumont
The Cryosphere, 8, 1139–1148, https://doi.org/10.5194/tc-8-1139-2014, https://doi.org/10.5194/tc-8-1139-2014, 2014
H. C. Steen-Larsen, V. Masson-Delmotte, M. Hirabayashi, R. Winkler, K. Satow, F. Prié, N. Bayou, E. Brun, K. M. Cuffey, D. Dahl-Jensen, M. Dumont, M. Guillevic, S. Kipfstuhl, A. Landais, T. Popp, C. Risi, K. Steffen, B. Stenni, and A. E. Sveinbjörnsdottír
Clim. Past, 10, 377–392, https://doi.org/10.5194/cp-10-377-2014, https://doi.org/10.5194/cp-10-377-2014, 2014
Q. Libois, G. Picard, J. L. France, L. Arnaud, M. Dumont, C. M. Carmagnola, and M. D. King
The Cryosphere, 7, 1803–1818, https://doi.org/10.5194/tc-7-1803-2013, https://doi.org/10.5194/tc-7-1803-2013, 2013
P. Wagnon, C. Vincent, Y. Arnaud, E. Berthier, E. Vuillermoz, S. Gruber, M. Ménégoz, A. Gilbert, M. Dumont, J. M. Shea, D. Stumm, and B. K. Pokhrel
The Cryosphere, 7, 1769–1786, https://doi.org/10.5194/tc-7-1769-2013, https://doi.org/10.5194/tc-7-1769-2013, 2013
C. L. Stevens, P. Sirguey, G. H. Leonard, and T. G. Haskell
The Cryosphere, 7, 1333–1337, https://doi.org/10.5194/tc-7-1333-2013, https://doi.org/10.5194/tc-7-1333-2013, 2013
J. Gardelle, E. Berthier, Y. Arnaud, and A. Kääb
The Cryosphere, 7, 1263–1286, https://doi.org/10.5194/tc-7-1263-2013, https://doi.org/10.5194/tc-7-1263-2013, 2013
C. M. Carmagnola, F. Domine, M. Dumont, P. Wright, B. Strellis, M. Bergin, J. Dibb, G. Picard, Q. Libois, L. Arnaud, and S. Morin
The Cryosphere, 7, 1139–1160, https://doi.org/10.5194/tc-7-1139-2013, https://doi.org/10.5194/tc-7-1139-2013, 2013
M. Geyer, D. Salas Y Melia, E. Brun, and M. Dumont
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-3163-2013, https://doi.org/10.5194/tcd-7-3163-2013, 2013
Revised manuscript has not been submitted
C. Vincent, Al. Ramanathan, P. Wagnon, D. P. Dobhal, A. Linda, E. Berthier, P. Sharma, Y. Arnaud, M. F. Azam, P. G. Jose, and J. Gardelle
The Cryosphere, 7, 569–582, https://doi.org/10.5194/tc-7-569-2013, https://doi.org/10.5194/tc-7-569-2013, 2013
N. J. Cullen, P. Sirguey, T. Mölg, G. Kaser, M. Winkler, and S. J. Fitzsimons
The Cryosphere, 7, 419–431, https://doi.org/10.5194/tc-7-419-2013, https://doi.org/10.5194/tc-7-419-2013, 2013
A. Rabatel, B. Francou, A. Soruco, J. Gomez, B. Cáceres, J. L. Ceballos, R. Basantes, M. Vuille, J.-E. Sicart, C. Huggel, M. Scheel, Y. Lejeune, Y. Arnaud, M. Collet, T. Condom, G. Consoli, V. Favier, V. Jomelli, R. Galarraga, P. Ginot, L. Maisincho, J. Mendoza, M. Ménégoz, E. Ramirez, P. Ribstein, W. Suarez, M. Villacis, and P. Wagnon
The Cryosphere, 7, 81–102, https://doi.org/10.5194/tc-7-81-2013, https://doi.org/10.5194/tc-7-81-2013, 2013
Related subject area
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Lead fractions from SAR-derived sea ice divergence during MOSAiC
Bayesian physical–statistical retrieval of snow water equivalent and snow depth from X- and Ku-band synthetic aperture radar – demonstration using airborne SnowSAr in SnowEx'17
A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography
Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry
Passive microwave remote-sensing-based high-resolution snow depth mapping for Western Himalayan zones using multifactor modeling approach
Refined glacial lake extraction in a high-Asia region by deep neural network and superpixel-based conditional random field methods
Retrieval of snow water equivalent from dual-frequency radar measurements: using time series to overcome the need for accurate a priori information
Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach
Annual to seasonal glacier mass balance in High Mountain Asia derived from Pléiades stereo images: examples from the Pamir and the Tibetan Plateau
Snow accumulation, albedo and melt patterns following road construction on permafrost, Inuvik–Tuktoyaktuk Highway, Canada
Co-registration and residual correction of digital elevation models: a comparative study
Out-of-the-box calving-front detection method using deep learning
Sea ice transport and replenishment across and within the Canadian Arctic Archipelago: 2016–2022
Mapping the extent of giant Antarctic icebergs with deep learning
Allometric scaling of retrogressive thaw slumps
MMSeaIce: Multi-task Mapping of Sea Ice Parameters from AI4Arctic Sea Ice Challenge Dataset
Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 1: Measurements, processing, and accuracy assessment
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
Evaluating Snow Microwave Radiative Transfer (SMRT) model emissivities with 89 to 243 GHz observations of Arctic tundra snow
Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2021
Brief communication: Identification of tundra topsoil frozen/thawed state from SMAP and GCOM-W1 radiometer measurements using the spectral gradient method
New estimates of pan-Arctic sea ice–atmosphere neutral drag coefficients from ICESat-2 elevation data
GLAcier Feature Tracking testkit (GLAFT): a statistically and physically based framework for evaluating glacier velocity products derived from optical satellite image feature tracking
Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign
Evaluating the utility of active microwave observations as a snow mission concept using observing system simulation experiments
Relevance of warm air intrusions for Arctic satellite sea ice concentration time series
Observing the evolution of summer melt on multiyear sea ice with ICESat-2 and Sentinel-2
Cast shadows reveal changes in glacier surface elevation
AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini
Lake Ice Break-Up in Greenland: Timing and Spatio-Temporal Variability
Characterizing the surge behaviour and associated ice-dammed lake evolution of the Kyagar Glacier in the Karakoram
Spaceborne thermal infrared observations of Arctic sea ice leads at 30 m resolution
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?
SAR Deep Learning Sea Ice Retrieval Trained with Airborne Laser Scanner Measurements from the MOSAiC Expedition
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments
Constraining regional glacier reconstructions using past ice thickness of deglaciating areas – a case study in the European Alps
Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice
Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)
Bedfast and floating-ice dynamics of thermokarst lakes using a temporal deep-learning mapping approach: case study of the Old Crow Flats, Yukon, Canada
First observations of sea ice flexural–gravity waves with ground-based radar interferometry in Utqiaġvik, Alaska
Climatic control on seasonal variations in mountain glacier surface velocity
Snowmelt characterization from optical and synthetic-aperture radar observations in the La Joie Basin, British Columbia
Recent changes in drainage route and outburst magnitude of the Russell Glacier ice-dammed lake, West Greenland
Feasibility of retrieving Arctic sea ice thickness from the Chinese HY-2B Ku-band radar altimeter
Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture
Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar
High-resolution debris-cover mapping using UAV-derived thermal imagery: limits and opportunities
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, https://doi.org/10.5194/tc-18-1259-2024, 2024
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Leads (openings in sea ice cover) are created by sea ice dynamics. Because they are important for many processes in the Arctic winter climate, we aim to detect them with satellites. We present two new techniques to detect lead widths of a few hundred meters at high spatial resolution (700 m) and independent of clouds or sun illumination. We use the MOSAiC drift 2019–2020 in the Arctic for our case study and compare our new products to other existing lead products.
Siddharth Singh, Michael Durand, Edward Kim, and Ana P. Barros
The Cryosphere, 18, 747–773, https://doi.org/10.5194/tc-18-747-2024, https://doi.org/10.5194/tc-18-747-2024, 2024
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Seasonal snowfall accumulation plays a critical role in climate. The water stored in it is measured by the snow water equivalent (SWE), the amount of water released after completely melting. We demonstrate a Bayesian physical–statistical framework to estimate SWE from airborne X- and Ku-band synthetic aperture radar backscatter measurements constrained by physical snow hydrology and radar models. We explored spatial resolutions and vertical structures that agree well with ground observations.
Jérôme Messmer and Alexander Raphael Groos
The Cryosphere, 18, 719–746, https://doi.org/10.5194/tc-18-719-2024, https://doi.org/10.5194/tc-18-719-2024, 2024
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The lower part of mountain glaciers is often covered with debris. Knowing the thickness of the debris is important as it influences the melting and future evolution of the affected glaciers. We have developed an open-source approach to map variations in debris thickness on glaciers using a low-cost drone equipped with a thermal infrared camera. The resulting high-resolution maps of debris surface temperature and thickness enable more accurate monitoring and modelling of debris-covered glaciers.
Shadi Oveisgharan, Robert Zinke, Zachary Hoppinen, and Hans Peter Marshall
The Cryosphere, 18, 559–574, https://doi.org/10.5194/tc-18-559-2024, https://doi.org/10.5194/tc-18-559-2024, 2024
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The seasonal snowpack provides water resources to billions of people worldwide. Large-scale mapping of snow water equivalent (SWE) with high resolution is critical for many scientific and economics fields. In this work we used the radar remote sensing interferometric synthetic aperture radar (InSAR) to estimate the SWE change between 2 d. The error in the estimated SWE change is less than 2 cm for in situ stations. Additionally, the retrieved SWE using InSAR is correlated with lidar snow depth.
Dhiraj Kumar Singh, Srinivasarao Tanniru, Kamal Kant Singh, Harendra Singh Negi, and RAAJ Ramsankaran
The Cryosphere, 18, 451–474, https://doi.org/10.5194/tc-18-451-2024, https://doi.org/10.5194/tc-18-451-2024, 2024
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In situ techniques for snow depth (SD) measurement are not adequate to represent the spatiotemporal variability in SD in the Western Himalayan region. Therefore, this study focuses on the high-resolution mapping of daily snow depth in the Indian Western Himalayan region using passive microwave remote-sensing-based algorithms. Overall, the proposed multifactor SD models demonstrated substantial improvement compared to the operational products. However, there is a scope for further improvement.
Yungang Cao, Rumeng Pan, Meng Pan, Ruodan Lei, Puying Du, and Xueqin Bai
The Cryosphere, 18, 153–168, https://doi.org/10.5194/tc-18-153-2024, https://doi.org/10.5194/tc-18-153-2024, 2024
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This study built a glacial lake dataset with 15376 samples in seven types and proposed an automatic method by two-stage (the semantic segmentation network and post-processing) optimizations to detect glacial lakes. The proposed method for glacial lake extraction has achieved the best results so far, in which the F1 score and IoU reached 0.945 and 0.907, respectively. The area of the minimum glacial lake that can be entirely and correctly extracted has been raised to the 100 m2 level.
Michael Durand, Joel T. Johnson, Jack Dechow, Leung Tsang, Firoz Borah, and Edward J. Kim
The Cryosphere, 18, 139–152, https://doi.org/10.5194/tc-18-139-2024, https://doi.org/10.5194/tc-18-139-2024, 2024
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Seasonal snow accumulates each winter, storing water to release later in the year and modulating both water and energy cycles, but the amount of seasonal snow is one of the most poorly measured components of the global water cycle. Satellite concepts to monitor snow accumulation have been proposed but not selected. This paper shows that snow accumulation can be measured using radar, and that (contrary to previous studies) does not require highly accurate information about snow microstructure.
Qin Zhang and Nick Hughes
The Cryosphere, 17, 5519–5537, https://doi.org/10.5194/tc-17-5519-2023, https://doi.org/10.5194/tc-17-5519-2023, 2023
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To alleviate tedious manual image annotations for training deep learning (DL) models in floe instance segmentation, we employ a classical image processing technique to automatically label floes in images. We then apply a DL semantic method for fast and adaptive floe instance segmentation from high-resolution airborne and satellite images. A post-processing algorithm is also proposed to refine the segmentation and further to derive acceptable floe size distributions at local and global scales.
Daniel Falaschi, Atanu Bhattacharya, Gregoire Guillet, Lei Huang, Owen King, Kriti Mukherjee, Philipp Rastner, Tandong Yao, and Tobias Bolch
The Cryosphere, 17, 5435–5458, https://doi.org/10.5194/tc-17-5435-2023, https://doi.org/10.5194/tc-17-5435-2023, 2023
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Because glaciers are crucial freshwater sources in the lowlands surrounding High Mountain Asia, constraining short-term glacier mass changes is essential. We investigate the potential of state-of-the-art satellite elevation data to measure glacier mass changes in two selected regions. The results demonstrate the ability of our dataset to characterize glacier changes of different magnitudes, allowing for an increase in the number of inaccessible glaciers that can be readily monitored.
Jennika Hammar, Inge Grünberg, Steven V. Kokelj, Jurjen van der Sluijs, and Julia Boike
The Cryosphere, 17, 5357–5372, https://doi.org/10.5194/tc-17-5357-2023, https://doi.org/10.5194/tc-17-5357-2023, 2023
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Roads on permafrost have significant environmental effects. This study assessed the Inuvik to Tuktoyaktuk Highway (ITH) in Canada and its impact on snow accumulation, albedo and snowmelt timing. Our findings revealed that snow accumulation increased by up to 36 m from the road, 12-day earlier snowmelt within 100 m due to reduced albedo, and altered snowmelt patterns in seemingly undisturbed areas. Remote sensing aids in understanding road impacts on permafrost.
Tao Li, Yuanlin Hu, Bin Liu, Liming Jiang, Hansheng Wang, and Xiang Shen
The Cryosphere, 17, 5299–5316, https://doi.org/10.5194/tc-17-5299-2023, https://doi.org/10.5194/tc-17-5299-2023, 2023
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Raw DEMs are often misaligned with each other due to georeferencing errors, and a co-registration process is required before DEM differencing. We present a comparative analysis of the two classical DEM co-registration and three residual correction algorithms. The experimental results show that rotation and scale biases should be considered in DEM co-registration. The new non-parametric regression technique can eliminate the complex systematic errors, which existed in the co-registration results.
Oskar Herrmann, Nora Gourmelon, Thorsten Seehaus, Andreas Maier, Johannes J. Fürst, Matthias H. Braun, and Vincent Christlein
The Cryosphere, 17, 4957–4977, https://doi.org/10.5194/tc-17-4957-2023, https://doi.org/10.5194/tc-17-4957-2023, 2023
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Delineating calving fronts of marine-terminating glaciers in satellite images is a labour-intensive task. We propose a method based on deep learning that automates this task. We choose a deep learning framework that adapts to any given dataset without needing deep learning expertise. The method is evaluated on a benchmark dataset for calving-front detection and glacier zone segmentation. The framework can beat the benchmark baseline without major modifications.
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
EGUsphere, https://doi.org/10.5194/egusphere-2023-2366, https://doi.org/10.5194/egusphere-2023-2366, 2023
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The CAA serves as both a source and sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay and is also an important region with respect to navigating the Northwest Passage. Here, we quantify sea ice transport and replenishment across and within the CAA from 2016 to 2022. We also provide the first estimates of the ice area and volume flux within the CAA from the Queen Elizabeth Islands to the Parry Channel which spans the central region of the Northwest Passage.
Anne Braakmann-Folgmann, Andrew Shepherd, David Hogg, and Ella Redmond
The Cryosphere, 17, 4675–4690, https://doi.org/10.5194/tc-17-4675-2023, https://doi.org/10.5194/tc-17-4675-2023, 2023
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In this study, we propose a deep neural network to map the extent of giant Antarctic icebergs in Sentinel-1 images automatically. While each manual delineation requires several minutes, our U-net takes less than 0.01 s. In terms of accuracy, we find that U-net outperforms two standard segmentation techniques (Otsu, k-means) in most metrics and is more robust to challenging scenes with sea ice, coast and other icebergs. The absolute median deviation in iceberg area across 191 images is 4.1 %.
Jurjen van der Sluijs, Steven V. Kokelj, and Jon F. Tunnicliffe
The Cryosphere, 17, 4511–4533, https://doi.org/10.5194/tc-17-4511-2023, https://doi.org/10.5194/tc-17-4511-2023, 2023
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There is an urgent need to obtain size and erosion estimates of climate-driven landslides, such as retrogressive thaw slumps. We evaluated surface interpolation techniques to estimate slump erosional volumes and developed a new inventory method by which the size and activity of these landslides are tracked through time. Models between slump area and volume reveal non-linear intensification, whereby model coefficients improve our understanding of how permafrost landscapes may evolve over time.
Xinwei Chen, Muhammed Patel, Fernando Pena Cantu, Jinman Park, Javier Noa Turnes, Linlin Xu, K. Andrea Scott, and David A. Clausi
EGUsphere, https://doi.org/10.5194/egusphere-2023-1297, https://doi.org/10.5194/egusphere-2023-1297, 2023
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This paper introduces an automated sea ice mapping pipeline utilizing a multi-task U-Net architecture. It attained the top score of 86.3 % in the AutoIce challenge. Ablation studies revealed that incorporating brightness temperature data and spatial-temporal information significantly enhanced model accuracy. Accurate sea ice mapping is vital for comprehending the Arctic environment and its global climate effects, underscoring the potential of deep learning.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, and David C. Hogg
The Cryosphere, 17, 4421–4445, https://doi.org/10.5194/tc-17-4421-2023, https://doi.org/10.5194/tc-17-4421-2023, 2023
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The presence of crevasses in Antarctica influences how the ice sheet behaves. It is important, therefore, to collect data on the spatial distribution of crevasses and how they are changing. We present a method of mapping crevasses from satellite radar imagery and apply it to 7.5 years of images, covering Antarctica's floating and grounded ice. We develop a method of measuring change in the density of crevasses and quantify increased fracturing in important parts of the West Antarctic Ice Sheet.
Anssi Rauhala, Leo-Juhani Meriö, Anton Kuzmin, Pasi Korpelainen, Pertti Ala-aho, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4343–4362, https://doi.org/10.5194/tc-17-4343-2023, https://doi.org/10.5194/tc-17-4343-2023, 2023
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Snow conditions in the Northern Hemisphere are rapidly changing, and information on snow depth is important for decision-making. We present snow depth measurements using different drones throughout the winter at a subarctic site. Generally, all drones produced good estimates of snow depth in open areas. However, differences were observed in the accuracies produced by the different drones, and a reduction in accuracy was observed when moving from an open mire area to forest-covered areas.
Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4363–4380, https://doi.org/10.5194/tc-17-4363-2023, https://doi.org/10.5194/tc-17-4363-2023, 2023
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Information on seasonal snow cover is essential in understanding snow processes and operational forecasting. We study the spatiotemporal variability in snow depth and snow processes in a subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the applicability of the drones to be used for a detailed study of snow depth in multiple land cover types and snow–vegetation interactions.
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
The Cryosphere, 17, 4325–4341, https://doi.org/10.5194/tc-17-4325-2023, https://doi.org/10.5194/tc-17-4325-2023, 2023
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Satellite microwave observations improve weather forecasts, but to use these observations in the Arctic, snow emission must be known. This study uses airborne and in situ snow observations to validate emissivity simulations for two- and three-layer snowpacks at key frequencies for weather prediction. We assess the impact of thickness, grain size and density in key snow layers, which will help inform development of physical snow models that provide snow profile input to emissivity simulations.
Jiahui Xu, Yao Tang, Linxin Dong, Shujie Wang, Bailang Yu, Jianping Wu, Zhaojun Zheng, and Yan Huang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-135, https://doi.org/10.5194/tc-2023-135, 2023
Revised manuscript accepted for TC
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Understanding snow phenology (SP) and its possible feedback are important. We reveal dynamic variability in SP and the mediating effects from meteorological, topographic, and environmental factors on the Tibetan Plateau (TP). SP is spatiotemporal heterogeneous and its interannual variation is elevation-dependent. The importance of temperature versus precipitation to SP shifted across elevation. This study contributes to understanding past global warming and predicting future trends on the TP.
Konstantin Muzalevskiy, Zdenek Ruzicka, Alexandre Roy, Michael Loranty, and Alexander Vasiliev
The Cryosphere, 17, 4155–4164, https://doi.org/10.5194/tc-17-4155-2023, https://doi.org/10.5194/tc-17-4155-2023, 2023
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A new all-weather method for determining the frozen/thawed (FT) state of soils in the Arctic region based on satellite data was proposed. The method is based on multifrequency measurement of brightness temperatures by the SMAP and GCOM-W1/AMSR2 satellites. The created method was tested at sites in Canada, Finland, Russia, and the USA, based on climatic weather station data. The proposed method identifies the FT state of Arctic soils with better accuracy than existing methods.
Alexander Mchedlishvili, Christof Lüpkes, Alek Petty, Michel Tsamados, and Gunnar Spreen
The Cryosphere, 17, 4103–4131, https://doi.org/10.5194/tc-17-4103-2023, https://doi.org/10.5194/tc-17-4103-2023, 2023
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In this study we looked at sea ice–atmosphere drag coefficients, quantities that help with characterizing the friction between the atmosphere and sea ice, and vice versa. Using ICESat-2, a laser altimeter that measures elevation differences by timing how long it takes for photons it sends out to return to itself, we could map the roughness, i.e., how uneven the surface is. From roughness we then estimate drag force, the frictional force between sea ice and the atmosphere, across the Arctic.
Whyjay Zheng, Shashank Bhushan, Maximillian Van Wyk De Vries, William Kochtitzky, David Shean, Luke Copland, Christine Dow, Renette Jones-Ivey, and Fernando Pérez
The Cryosphere, 17, 4063–4078, https://doi.org/10.5194/tc-17-4063-2023, https://doi.org/10.5194/tc-17-4063-2023, 2023
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We design and propose a method that can evaluate the quality of glacier velocity maps. The method includes two numbers that we can calculate for each velocity map. Based on statistics and ice flow physics, velocity maps with numbers close to the recommended values are considered to have good quality. We test the method using the data from Kaskawulsh Glacier, Canada, and release an open-sourced software tool called GLAcier Feature Tracking testkit (GLAFT) to help users assess their velocity maps.
Steven J. Pestana, C. Chris Chickadel, and Jessica D. Lundquist
EGUsphere, https://doi.org/10.5194/egusphere-2023-1784, https://doi.org/10.5194/egusphere-2023-1784, 2023
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We compared infrared images taken by GOES-R satellites of an area with snow and forests against surface temperature measurements taken on the ground, from an aircraft, and by another satellite. We found that GOES-R measured warmer temperatures than the other measurements, especially in areas with more forest, and when the sun was behind the satellite. From this work, we’ve learned that the position of the sun and surface features such as trees that can cast shadows impact GOES-R infrared images.
Eunsang Cho, Carrie M. Vuyovich, Sujay V. Kumar, Melissa L. Wrzesien, and Rhae Sung Kim
The Cryosphere, 17, 3915–3931, https://doi.org/10.5194/tc-17-3915-2023, https://doi.org/10.5194/tc-17-3915-2023, 2023
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As a future snow mission concept, active microwave sensors have the potential to measure snow water equivalent (SWE) in deep snowpack and forested environments. We used a modeling and data assimilation approach (a so-called observing system simulation experiment) to quantify the usefulness of active microwave-based SWE retrievals over western Colorado. We found that active microwave sensors with a mature retrieval algorithm can improve SWE simulations by about 20 % in the mountainous domain.
Philip Rostosky and Gunnar Spreen
The Cryosphere, 17, 3867–3881, https://doi.org/10.5194/tc-17-3867-2023, https://doi.org/10.5194/tc-17-3867-2023, 2023
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During winter, storms entering the Arctic region can bring warm air into the cold environment. Strong increases in air temperature modify the characteristics of the Arctic snow and ice cover. The Arctic sea ice cover can be monitored by satellites observing the natural emission of the Earth's surface. In this study, we show that during warm air intrusions the change in the snow characteristics influences the satellite-derived sea ice cover, leading to a false reduction of the estimated ice area.
Ellen M. Buckley, Sinéad L. Farrell, Ute C. Herzfeld, Melinda A. Webster, Thomas Trantow, Oliwia N. Baney, Kyle A. Duncan, Huilin Han, and Matthew Lawson
The Cryosphere, 17, 3695–3719, https://doi.org/10.5194/tc-17-3695-2023, https://doi.org/10.5194/tc-17-3695-2023, 2023
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In this study, we use satellite observations to investigate the evolution of melt ponds on the Arctic sea ice surface. We derive melt pond depth from ICESat-2 measurements of the pond surface and bathymetry and melt pond fraction (MPF) from the classification of Sentinel-2 imagery. MPF increases to a peak of 16 % in late June and then decreases, while depth increases steadily. This work demonstrates the ability to track evolving melt conditions in three dimensions throughout the summer.
Monika Pfau, Georg Veh, and Wolfgang Schwanghart
The Cryosphere, 17, 3535–3551, https://doi.org/10.5194/tc-17-3535-2023, https://doi.org/10.5194/tc-17-3535-2023, 2023
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Cast shadows have been a recurring problem in remote sensing of glaciers. We show that the length of shadows from surrounding mountains can be used to detect gains or losses in glacier elevation.
Enze Zhang, Ginny Catania, and Daniel T. Trugman
The Cryosphere, 17, 3485–3503, https://doi.org/10.5194/tc-17-3485-2023, https://doi.org/10.5194/tc-17-3485-2023, 2023
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Glacier termini are essential for studying why glaciers retreat, but they need to be mapped automatically due to the volume of satellite images. Existing automated mapping methods have been limited due to limited automation, lack of quality control, and inadequacy in highly diverse terminus environments. We design a fully automated, deep-learning-based method to produce termini with quality control. We produced 278 239 termini in Greenland and provided a way to deliver new termini regularly.
Christoph Posch, Jakob Abermann, and Tiago Manuel Ferreira da Silva
EGUsphere, https://doi.org/10.5194/egusphere-2023-1762, https://doi.org/10.5194/egusphere-2023-1762, 2023
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Radar beams from satellites exhibit different reflection behaviors between water and ice. Utilizing this conditions and the comprehensive coverage and high temporal resolution of the Sentinel-1 radar satellite mission, the timing when ice cover of lakes in Greenland disappear can be automatically detected. We found that per 100 m elevation gain, lake ice breaks up 3 days later because of lower air temperatures with increasing elevation, while latitude has no influence on their break-up timing.
Guanyu Li, Mingyang Lv, Duncan J. Quincey, Liam S. Taylor, Xinwu Li, Shiyong Yan, Yidan Sun, and Huadong Guo
The Cryosphere, 17, 2891–2907, https://doi.org/10.5194/tc-17-2891-2023, https://doi.org/10.5194/tc-17-2891-2023, 2023
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Kyagar Glacier in the Karakoram is well known for its surge history and its frequent blocking of the downstream valley, leading to a series of high-magnitude glacial lake outburst floods. Using it as a test bed, we develop a new approach for quantifying surge behaviour using successive digital elevation models. This method could be applied to other surge studies. Combined with the results from optical satellite images, we also reconstruct the surge process in unprecedented detail.
Yujia Qiu, Xiao-Ming Li, and Huadong Guo
The Cryosphere, 17, 2829–2849, https://doi.org/10.5194/tc-17-2829-2023, https://doi.org/10.5194/tc-17-2829-2023, 2023
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Spaceborne thermal infrared sensors with kilometer-scale resolution cannot support adequate parameterization of Arctic leads. For the first time, we applied the 30 m resolution data from the Thermal Infrared Spectrometer (TIS) on the emerging SDGSAT-1 to detect Arctic leads. Validation with Sentinel-2 data shows high accuracy for the three TIS bands. Compared to MODIS, the TIS presents more narrow leads, demonstrating its great potential for observing previously unresolvable Arctic leads.
César Deschamps-Berger, Simon Gascoin, David Shean, Hannah Besso, Ambroise Guiot, and Juan Ignacio López-Moreno
The Cryosphere, 17, 2779–2792, https://doi.org/10.5194/tc-17-2779-2023, https://doi.org/10.5194/tc-17-2779-2023, 2023
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The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.
Edward H. Bair, Jeff Dozier, Karl Rittger, Timbo Stillinger, William Kleiber, and Robert E. Davis
The Cryosphere, 17, 2629–2643, https://doi.org/10.5194/tc-17-2629-2023, https://doi.org/10.5194/tc-17-2629-2023, 2023
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To test the title question, three snow cover products were used in a snow model. Contrary to previous work, higher-spatial-resolution snow cover products only improved the model accuracy marginally. Conclusions are as follows: (1) snow cover and albedo from moderate-resolution sensors continue to provide accurate forcings and (2) finer spatial and temporal resolutions are the future for Earth observations, but existing moderate-resolution sensors still offer value.
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-72, https://doi.org/10.5194/tc-2023-72, 2023
Revised manuscript accepted for TC
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A dataset of 20 radar satellite acquisitions and near simultaneous helicopter-based measurements of the ice topography during an expedition is constructed and used to train a variety of deep learning algorithms. The results show, that the ice types derived directly from the helicopter measurement are harder to retrieve than those from human annotations. Models that can learn from the spatial distribution of measured sea ice classes are shown to have a clear advantage over those that cannot.
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-85, https://doi.org/10.5194/tc-2023-85, 2023
Revised manuscript accepted for TC
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We developed an algorithm to estimate snow mass using X- and dual-Ku band radar and tested it in a ground-based experiment. The algorithm, called the Bayesian-based Algorithm for SWE Estimation (BASE) using active microwaves (AM), achieved an RMSE of 30 mm. These results demonstrate the potential of radar, a highly promising sensor to map snow mass in high spatial resolution.
Valentina Premier, Carlo Marin, Giacomo Bertoldi, Riccardo Barella, Claudia Notarnicola, and Lorenzo Bruzzone
The Cryosphere, 17, 2387–2407, https://doi.org/10.5194/tc-17-2387-2023, https://doi.org/10.5194/tc-17-2387-2023, 2023
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The large amount of information regularly acquired by satellites can provide important information about SWE. We explore the use of multi-source satellite data, in situ observations, and a degree-day model to reconstruct daily SWE at 25 m. The results show spatial patterns that are consistent with the topographical features as well as with a reference product. Being able to also reproduce interannual variability, the method has great potential for hydrological and ecological applications.
Christian Sommer, Johannes J. Fürst, Matthias Huss, and Matthias H. Braun
The Cryosphere, 17, 2285–2303, https://doi.org/10.5194/tc-17-2285-2023, https://doi.org/10.5194/tc-17-2285-2023, 2023
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Knowledge on the volume of glaciers is important to project future runoff. Here, we present a novel approach to reconstruct the regional ice thickness distribution from easily available remote-sensing data. We show that past ice thickness, derived from spaceborne glacier area and elevation datasets, can constrain the estimated ice thickness. Based on the unique glaciological database of the European Alps, the approach will be most beneficial in regions without direct thickness measurements.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
The Cryosphere, 17, 1997–2019, https://doi.org/10.5194/tc-17-1997-2023, https://doi.org/10.5194/tc-17-1997-2023, 2023
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Mountain snowmelt provides water for billions of people across the globe. Despite its importance, we cannot currently measure the amount of water in mountain snowpacks from satellites. In this research, we test the ability of an experimental snow remote sensing technique from an airplane in preparation for the same sensor being launched on a future NASA satellite. We found that the method worked better than expected for estimating important snowpack properties.
Maria Shaposhnikova, Claude Duguay, and Pascale Roy-Léveillée
The Cryosphere, 17, 1697–1721, https://doi.org/10.5194/tc-17-1697-2023, https://doi.org/10.5194/tc-17-1697-2023, 2023
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We explore lake ice in the Old Crow Flats, Yukon, Canada, using a novel approach that employs radar imagery and deep learning. Results indicate an 11 % increase in the fraction of lake ice that grounds between 1992/1993 and 2020/2021. We believe this is caused by widespread lake drainage and fluctuations in water level and snow depth. This transition is likely to have implications for permafrost beneath the lakes, with a potential impact on methane ebullition and the regional carbon budget.
Dyre Oliver Dammann, Mark A. Johnson, Andrew R. Mahoney, and Emily R. Fedders
The Cryosphere, 17, 1609–1622, https://doi.org/10.5194/tc-17-1609-2023, https://doi.org/10.5194/tc-17-1609-2023, 2023
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We investigate the GAMMA Portable Radar Interferometer (GPRI) as a tool for evaluating flexural–gravity waves in sea ice in near real time. With a GPRI mounted on grounded ice near Utqiaġvik, Alaska, we identify 20–50 s infragravity waves in landfast ice with ~1 mm amplitude during 23–24 April 2021. Observed wave speed and periods compare well with modeled wave propagation and on-ice accelerometers, confirming the ability to track propagation and properties of waves over hundreds of meters.
Ugo Nanni, Dirk Scherler, Francois Ayoub, Romain Millan, Frederic Herman, and Jean-Philippe Avouac
The Cryosphere, 17, 1567–1583, https://doi.org/10.5194/tc-17-1567-2023, https://doi.org/10.5194/tc-17-1567-2023, 2023
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Surface melt is a major factor driving glacier movement. Using satellite images, we have tracked the movements of 38 glaciers in the Pamirs over 7 years, capturing their responses to rapid meteorological changes with unprecedented resolution. We show that in spring, glacier accelerations propagate upglacier, while in autumn, they propagate downglacier – all resulting from changes in meltwater input. This provides critical insights into the interplay between surface melt and glacier movement.
Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber
The Cryosphere, 17, 1457–1473, https://doi.org/10.5194/tc-17-1457-2023, https://doi.org/10.5194/tc-17-1457-2023, 2023
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We use synthetic-aperture radar (SAR) and optical observations to map snowmelt timing and duration on the watershed scale. We found that Sentinel-1 SAR time series can be used to approximate snowmelt onset over diverse terrain and land cover types, and we present a low-cost workflow for SAR processing over large, mountainous regions. Our approach provides spatially distributed observations of the snowpack necessary for model calibration and can be used to monitor snowmelt in ungauged basins.
Mads Dømgaard, Kristian K. Kjeldsen, Flora Huiban, Jonathan L. Carrivick, Shfaqat A. Khan, and Anders A. Bjørk
The Cryosphere, 17, 1373–1387, https://doi.org/10.5194/tc-17-1373-2023, https://doi.org/10.5194/tc-17-1373-2023, 2023
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Sudden releases of meltwater from glacier-dammed lakes can influence ice flow, cause flooding hazards and landscape changes. This study presents a record of 14 drainages from 2007–2021 from a lake in west Greenland. The time series reveals how the lake fluctuates between releasing large and small amounts of drainage water which is caused by a weakening of the damming glacier following the large events. We also find a shift in the water drainage route which increases the risk of flooding hazards.
Zhaoqing Dong, Lijian Shi, Mingsen Lin, Yongjun Jia, Tao Zeng, and Suhui Wu
The Cryosphere, 17, 1389–1410, https://doi.org/10.5194/tc-17-1389-2023, https://doi.org/10.5194/tc-17-1389-2023, 2023
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We try to explore the application of SGDR data in polar sea ice thickness. Through this study, we find that it seems difficult to obtain reasonable results by using conventional methods. So we use the 15 lowest points per 25 km to estimate SSHA to retrieve more reasonable Arctic radar freeboard and thickness. This study also provides reference for reprocessing L1 data. We will release products that are more reasonable and suitable for polar sea ice thickness retrieval to better evaluate HY-2B.
Wenkai Guo, Polona Itkin, Suman Singha, Anthony P. Doulgeris, Malin Johansson, and Gunnar Spreen
The Cryosphere, 17, 1279–1297, https://doi.org/10.5194/tc-17-1279-2023, https://doi.org/10.5194/tc-17-1279-2023, 2023
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Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
Vasana Dharmadasa, Christophe Kinnard, and Michel Baraër
The Cryosphere, 17, 1225–1246, https://doi.org/10.5194/tc-17-1225-2023, https://doi.org/10.5194/tc-17-1225-2023, 2023
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This study highlights the successful usage of UAV lidar to monitor small-scale snow depth distribution. Our results show that underlying topography and wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. This emphasizes the importance of including and better representing these processes in physically based models for accurate snowpack estimates.
Deniz Tobias Gök, Dirk Scherler, and Leif Stefan Anderson
The Cryosphere, 17, 1165–1184, https://doi.org/10.5194/tc-17-1165-2023, https://doi.org/10.5194/tc-17-1165-2023, 2023
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We performed high-resolution debris-thickness mapping using land surface temperature (LST) measured from an unpiloted aerial vehicle (UAV) at various times of the day. LSTs from UAVs require calibration that varies in time. We test two approaches to quantify supraglacial debris cover, and we find that the non-linearity of the relationship between LST and debris thickness increases with LST. Choosing the best model to predict debris thickness depends on the time of the day and the terrain aspect.
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