Articles | Volume 16, issue 6
https://doi.org/10.5194/tc-16-2163-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-2163-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jun 2022
Research article |
| 09 Jun 2022
| 09 Jun 2022
Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation
Joëlle Voglimacci-Stephanopoli
CORRESPONDING AUTHOR
Département de géomatique appliquée, Centre d'Applications et de Recherches en
Télédétection, Université de Sherbrooke, Sherbrooke, J1K
2R1, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Québec, G1V 0A6, Canada
Anna Wendleder
German Remote Sensing Data Center, German Aerospace Center,
Oberpfaffenhofen, Germany
Hugues Lantuit
Institute of Geosciences, University of Potsdam, Potsdam, Germany
Alfred Wegener Institute Helmholtz Centre for Polar and Marine
Research, 14473 Potsdam, Germany
Alexandre Langlois
Département de géomatique appliquée, Centre d'Applications et de Recherches en
Télédétection, Université de Sherbrooke, Sherbrooke, J1K
2R1, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Québec, G1V 0A6, Canada
Samuel Stettner
German Remote Sensing Data Center, German Aerospace Center,
Oberpfaffenhofen, Germany
German Space Agency, German Aerospace Center, Bonn, Germany
Andreas Schmitt
Institute for Applications of Machine Learning and Intelligent
Systems, Munich University of Applied Sciences, Munich, Germany
Jean-Pierre Dedieu
Centre d'Études Nordiques, Université Laval, Québec,
Québec, G1V 0A6, Canada
Institute of Environmental Geosciences, Université
Grenoble-Alpes/CNRS/IRD, 38058 Grenoble, France
Achim Roth
German Remote Sensing Data Center, German Aerospace Center,
Oberpfaffenhofen, Germany
Alain Royer
Département de géomatique appliquée, Centre d'Applications et de Recherches en
Télédétection, Université de Sherbrooke, Sherbrooke, J1K
2R1, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Québec, G1V 0A6, Canada
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-277, https://doi.org/10.5194/essd-2026-277, 2026
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We generated a high‑resolution global coastline dataset, called the TanDEM‑X coastline, which marks the boundary between land and ocean. It is derived from elevation data. First, we produced the coastline automatically, and then we manually modified it to ensure consistent quality worldwide. To demonstrate its accuracy, we compared it with other coastlines across a range of coastal settings. The final vector dataset can be used for coastal spatial planning, or as input for hydrological models.
Alex Gélinas, Benoît Montpetit, Julien Meloche, Peter Toose, Zeinab Akhavan, Wei Wang, Richard Kelly, Alexandre Langlois, and Alexandre Roy
EGUsphere, https://doi.org/10.5194/egusphere-2026-656, https://doi.org/10.5194/egusphere-2026-656, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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This research validates a method to link radar measurements to soil properties beneath snow in a temperate farming region. By using multiple radar sensors and computer models, we successfully decoupled the ground's interference from the snow signal. Our results show that radar captures unique information that traditional ground tools miss during freeze-thaw cycles. This work provides a vital framework for the future Canadian Terrestrial Snow Mass Mission to monitor water resources.
Dakota Pyles, Marcel Dreier, Anna Wendleder, Will Kochtitzky, Nora Gourmelon, Vincent Christlein, and Thorsten Seehaus
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-273, https://doi.org/10.5194/essd-2026-273, 2026
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Monthly frontal ablation is quantified at Svalbard tidewater glaciers from 2015–2024 using terminus positions derived from a segmentation model's predictions of satellite radar images. Our high spatio-temporal resolution results will improve the process understanding of frontal ablation, provide reference data for the modeling community, and deliver an ideal dataset for studying controls of frontal ablation.
Julia Wagner, Juliane Wolter, Justine Ramage, Victoria Martin, Andreas Richter, Niek Jesse Speetjens, Jorien E. Vonk, Rachele Lodi, Annett Bartsch, Michael Fritz, Hugues Lantuit, and Gustaf Hugelius
SOIL, 12, 113–132, https://doi.org/10.5194/soil-12-113-2026, https://doi.org/10.5194/soil-12-113-2026, 2026
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Permafrost soils store vast amounts of organic carbon, key to understanding climate change. This study uses machine learning and combines existing data with new field data to create detailed regional maps of soil carbon and nitrogen stocks for the Yukon coastal plain. The results show how soil properties vary across the landscape highlighting the importance of data selection for accurate predictions. These findings improve carbon storage estimates and may aid regional carbon budget assessments.
Vincent Vionnet, Nicolas R. Leroux, Vincent Fortin, Maria Abrahamowicz, Georgina Woolley, Giulia Mazzotti, Manon Gaillard, Matthieu Lafaysse, Alain Royer, Florent Domine, Nathalie Gauthier, Nick Rutter, Chris Derksen, and Stéphane Bélair
Geosci. Model Dev., 18, 9119–9147, https://doi.org/10.5194/gmd-18-9119-2025, https://doi.org/10.5194/gmd-18-9119-2025, 2025
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Snow microstructure controls snowpack properties, but most land surface models overlook this factor. To support future satellite missions, we created a new land surface model based on the Crocus scheme that simulates snow microstructure. Key improvements include better snow albedo representation, enhanced Arctic snow modeling, and improved forest module to capture Canada's diverse snow conditions. Results demonstrate improved simulations of snow density and melt across large regions of Canada.
Juliette Ortet, Arnaud Mialon, Alain Royer, Mike Schwank, Manu Holmberg, Kimmo Rautiainen, Simone Bircher-Adrot, Andreas Colliander, Yann Kerr, and Alexandre Roy
The Cryosphere, 19, 3571–3598, https://doi.org/10.5194/tc-19-3571-2025, https://doi.org/10.5194/tc-19-3571-2025, 2025
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We propose a new method to determine the ground surface temperature under the snowpack in the Arctic area from satellite observations. The obtained ground temperature time series were evaluated over 21 reference sites in Northern Alaska and compared with ground temperatures obtained with global models. The method is extremely promising for monitoring ground temperature below the snowpack and studying the spatio-temporal variability thanks to 15 years of observations over the whole Arctic area.
Zacharie Barrou Dumont, Simon Gascoin, Jordi Inglada, Andreas Dietz, Jonas Köhler, Matthieu Lafaysse, Diego Monteiro, Carlo Carmagnola, Arthur Bayle, Jean-Pierre Dedieu, Olivier Hagolle, and Philippe Choler
The Cryosphere, 19, 2407–2429, https://doi.org/10.5194/tc-19-2407-2025, https://doi.org/10.5194/tc-19-2407-2025, 2025
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We generated annual maps of snow melt-out days at 20 m resolution over a period of 38 years from 10 different satellites. This study fills a knowledge gap regarding the evolution of mountain snow in Europe by covering a much longer period and characterizing trends at much higher resolutions than previous studies. We found a trend for earlier melt-out with average reductions of 5.51 d per decade over the French Alps and 4.04 d per decade over the Pyrenees for the period 1986–2023.
Charlotte Crevier, Alexandre Langlois, Chris Derksen, and Alexandre Roy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3580, https://doi.org/10.5194/egusphere-2024-3580, 2025
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A multisensor C-Band SAR near-daily time series in an Arctic environment was developed to create a high-resolution freeze/thaw algorithm with an accuracy of 96 %. The FT detection was highly correlated to near-surface state as measured by soil temperature. Small but significant FT date differences were identified for different Arctic ecotypes, showing the spatial variability of freeze/thaw process in Arctic environment.
Nina Nesterova, Marina Leibman, Alexander Kizyakov, Hugues Lantuit, Ilya Tarasevich, Ingmar Nitze, Alexandra Veremeeva, and Guido Grosse
The Cryosphere, 18, 4787–4810, https://doi.org/10.5194/tc-18-4787-2024, https://doi.org/10.5194/tc-18-4787-2024, 2024
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Retrogressive thaw slumps (RTSs) are widespread in the Arctic permafrost landforms. RTSs present a big interest for researchers because of their expansion due to climate change. There are currently different scientific schools and terminology used in the literature on this topic. We have critically reviewed existing concepts and terminology and provided clarifications to present a useful base for experts in the field and ease the introduction to the topic for scientists who are new to it.
Melody Sandells, Nick Rutter, Kirsty Wivell, Richard Essery, Stuart Fox, Chawn Harlow, Ghislain Picard, Alexandre Roy, Alain Royer, and Peter Toose
The Cryosphere, 18, 3971–3990, https://doi.org/10.5194/tc-18-3971-2024, https://doi.org/10.5194/tc-18-3971-2024, 2024
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Benoit Montpetit, Joshua King, Julien Meloche, Chris Derksen, Paul Siqueira, J. Max Adam, Peter Toose, Mike Brady, Anna Wendleder, Vincent Vionnet, and Nicolas R. Leroux
The Cryosphere, 18, 3857–3874, https://doi.org/10.5194/tc-18-3857-2024, https://doi.org/10.5194/tc-18-3857-2024, 2024
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This paper validates the use of free open-source models to link distributed snow measurements to radar measurements in the Canadian Arctic. Using multiple radar sensors, we can decouple the soil from the snow contribution. We then retrieve the "microwave snow grain size" to characterize the interaction between the snow mass and the radar signal. This work supports future satellite mission development to retrieve snow mass information such as the future Canadian Terrestrial Snow Mass Mission.
Paul Billecocq, Alexandre Langlois, and Benoit Montpetit
The Cryosphere, 18, 2765–2782, https://doi.org/10.5194/tc-18-2765-2024, https://doi.org/10.5194/tc-18-2765-2024, 2024
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Snow covers a vast part of the globe, making snow water equivalent (SWE) crucial for climate science and hydrology. SWE can be inversed from satellite data, but the snow's complex structure highly affects the signal, and thus an educated first guess is mandatory. In this study, a subgridding framework was developed to model snow at the local scale from model weather data. The framework enhanced snow parameter modeling, paving the way for SWE inversion algorithms from satellite data.
Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Richard Essery, Ghislain Picard, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Jérôme Bouffard, Alessandro Di Bella, and Michele Scagliola
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Preprint archived
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Sea ice thickness is essential for climate studies. Radar altimetry has provided sea ice thickness measurement, but uncertainty arises from interaction of the signal with the snow cover. Therefore, modelling the signal interaction with the snow is necessary to improve retrieval. A radar model was used to simulate the radar signal from the snow-covered sea ice. This work paved the way to improved physical algorithm to retrieve snow depth and sea ice thickness for radar altimeter missions.
Francis Meloche, Francis Gauthier, and Alexandre Langlois
The Cryosphere, 18, 1359–1380, https://doi.org/10.5194/tc-18-1359-2024, https://doi.org/10.5194/tc-18-1359-2024, 2024
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Snow avalanches are a dangerous natural hazard. Backcountry recreationists and avalanche practitioners try to predict avalanche hazard based on the stability of snow cover. However, snow cover is variable in space, and snow stability observations can vary within several meters. We measure the snow stability several times on a small slope to create high-resolution maps of snow cover stability. These results help us to understand the snow variation for scientists and practitioners.
Anna Wendleder, Jasmin Bramboeck, Jamie Izzard, Thilo Erbertseder, Pablo d'Angelo, Andreas Schmitt, Duncan J. Quincey, Christoph Mayer, and Matthias H. Braun
The Cryosphere, 18, 1085–1103, https://doi.org/10.5194/tc-18-1085-2024, https://doi.org/10.5194/tc-18-1085-2024, 2024
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This study analyses the basal sliding and the hydrological drainage of Baltoro Glacier, Pakistan. The surface velocity was characterized by a spring speed-up, summer peak, and autumn speed-up. Snow melt has the largest impact on the spring speed-up, summer velocity peak, and the transition from inefficient to efficient drainage. Drainage from supraglacial lakes contributed to the fall speed-up. Increased summer temperatures will intensify the magnitude of meltwater and thus surface velocities.
Eliot Sicaud, Daniel Fortier, Jean-Pierre Dedieu, and Jan Franssen
Hydrol. Earth Syst. Sci., 28, 65–86, https://doi.org/10.5194/hess-28-65-2024, https://doi.org/10.5194/hess-28-65-2024, 2024
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For vast northern watersheds, hydrological data are often sparse and incomplete. Our study used remote sensing and clustering to produce classifications of the George River watershed (GRW). Results show two types of subwatersheds with different hydrological behaviors. The GRW experienced a homogenization of subwatershed types likely due to an increase in vegetation productivity, which could explain the measured decline of 1 % (~0.16 km3 y−1) in the George River’s discharge since the mid-1970s.
Nele Lehmann, Hugues Lantuit, Michael Ernst Böttcher, Jens Hartmann, Antje Eulenburg, and Helmuth Thomas
Biogeosciences, 20, 3459–3479, https://doi.org/10.5194/bg-20-3459-2023, https://doi.org/10.5194/bg-20-3459-2023, 2023
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Riverine alkalinity in the silicate-dominated headwater catchment at subarctic Iskorasfjellet, northern Norway, was almost entirely derived from weathering of minor carbonate occurrences in the riparian zone. The uphill catchment appeared limited by insufficient contact time of weathering agents and weatherable material. Further, alkalinity increased with decreasing permafrost extent. Thus, with climate change, alkalinity generation is expected to increase in this permafrost-degrading landscape.
Martine Lizotte, Bennet Juhls, Atsushi Matsuoka, Philippe Massicotte, Gaëlle Mével, David Obie James Anikina, Sofia Antonova, Guislain Bécu, Marine Béguin, Simon Bélanger, Thomas Bossé-Demers, Lisa Bröder, Flavienne Bruyant, Gwénaëlle Chaillou, Jérôme Comte, Raoul-Marie Couture, Emmanuel Devred, Gabrièle Deslongchamps, Thibaud Dezutter, Miles Dillon, David Doxaran, Aude Flamand, Frank Fell, Joannie Ferland, Marie-Hélène Forget, Michael Fritz, Thomas J. Gordon, Caroline Guilmette, Andrea Hilborn, Rachel Hussherr, Charlotte Irish, Fabien Joux, Lauren Kipp, Audrey Laberge-Carignan, Hugues Lantuit, Edouard Leymarie, Antonio Mannino, Juliette Maury, Paul Overduin, Laurent Oziel, Colin Stedmon, Crystal Thomas, Lucas Tisserand, Jean-Éric Tremblay, Jorien Vonk, Dustin Whalen, and Marcel Babin
Earth Syst. Sci. Data, 15, 1617–1653, https://doi.org/10.5194/essd-15-1617-2023, https://doi.org/10.5194/essd-15-1617-2023, 2023
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Permafrost thaw in the Mackenzie Delta region results in the release of organic matter into the coastal marine environment. What happens to this carbon-rich organic matter as it transits along the fresh to salty aquatic environments is still underdocumented. Four expeditions were conducted from April to September 2019 in the coastal area of the Beaufort Sea to study the fate of organic matter. This paper describes a rich set of data characterizing the composition and sources of organic matter.
Niek Jesse Speetjens, Gustaf Hugelius, Thomas Gumbricht, Hugues Lantuit, Wouter R. Berghuijs, Philip A. Pika, Amanda Poste, and Jorien E. Vonk
Earth Syst. Sci. Data, 15, 541–554, https://doi.org/10.5194/essd-15-541-2023, https://doi.org/10.5194/essd-15-541-2023, 2023
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The Arctic is rapidly changing. Outside the Arctic, large databases changed how researchers look at river systems and land-to-ocean processes. We present the first integrated pan-ARctic CAtchments summary DatabasE (ARCADE) (> 40 000 river catchments draining into the Arctic Ocean). It incorporates information about the drainage area with 103 geospatial, environmental, climatic, and physiographic properties and covers small watersheds , which are especially subject to change, at a high resolution
Niek Jesse Speetjens, George Tanski, Victoria Martin, Julia Wagner, Andreas Richter, Gustaf Hugelius, Chris Boucher, Rachele Lodi, Christian Knoblauch, Boris P. Koch, Urban Wünsch, Hugues Lantuit, and Jorien E. Vonk
Biogeosciences, 19, 3073–3097, https://doi.org/10.5194/bg-19-3073-2022, https://doi.org/10.5194/bg-19-3073-2022, 2022
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Climate change and warming in the Arctic exceed global averages. As a result, permanently frozen soils (permafrost) which store vast quantities of carbon in the form of dead plant material (organic matter) are thawing. Our study shows that as permafrost landscapes degrade, high concentrations of organic matter are released. Partly, this organic matter is degraded rapidly upon release, while another significant fraction enters stream networks and enters the Arctic Ocean.
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, and Evan J. Wilcox
The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, https://doi.org/10.5194/tc-16-87-2022, 2022
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To estimate snow water equivalent from space, model predictions of the satellite measurement (brightness temperature in our case) have to be used. These models allow us to estimate snow properties from the brightness temperature by inverting the model. To improve SWE estimate, we proposed incorporating the variability of snow in these model as it has not been taken into account yet. A new parameter (coefficient of variation) is proposed because it improved simulation of brightness temperature.
Birgit Wessel, Martin Huber, Christian Wohlfart, Adina Bertram, Nicole Osterkamp, Ursula Marschalk, Astrid Gruber, Felix Reuß, Sahra Abdullahi, Isabel Georg, and Achim Roth
The Cryosphere, 15, 5241–5260, https://doi.org/10.5194/tc-15-5241-2021, https://doi.org/10.5194/tc-15-5241-2021, 2021
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We present a new digital elevation model (DEM) of Antarctica derived from the TanDEM-X DEM, with new interferometric radar acquisitions incorporated and edited elevations, especially at the coast. A strength of this DEM is its homogeneity and completeness. Extensive validation work shows a vertical accuracy of just -0.3 m ± 2.5 m standard deviation on blue ice surfaces compared to ICESat laser altimeter heights. The new TanDEM-X PolarDEM 90 m of Antarctica is freely available.
Alain Royer, Alexandre Roy, Sylvain Jutras, and Alexandre Langlois
The Cryosphere, 15, 5079–5098, https://doi.org/10.5194/tc-15-5079-2021, https://doi.org/10.5194/tc-15-5079-2021, 2021
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Dense spatially distributed networks of autonomous instruments for continuously measuring the amount of snow on the ground are needed for operational water resource and flood management and the monitoring of northern climate change. Four new-generation non-invasive sensors are compared. A review of their advantages, drawbacks and accuracy is discussed. This performance analysis is intended to help researchers and decision-makers choose the one system that is best suited to their needs.
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Short summary
Changes in the state of the snowpack in the context of observed global warming must be considered to improve our understanding of the processes within the cryosphere. This study aims to characterize an arctic snowpack using the TerraSAR-X satellite. Using a high-spatial-resolution vegetation classification, we were able to quantify the variability in snow depth, as well as the topographic soil wetness index, which provided a better understanding of the electromagnetic wave–ground interaction.
Changes in the state of the snowpack in the context of observed global warming must be...
