Articles | Volume 20, issue 3
https://doi.org/10.5194/tc-20-1635-2026
© Author(s) 2026. 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-20-1635-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Mar 2026
Research article |
| 19 Mar 2026
| 19 Mar 2026
In situ monitoring of seasonally frozen ground using soil freezing characteristic curve in permittivity–temperature space
Department of Environmental Sciences, University of Quebec in Trois-Rivières, Trois-Rivières, Quebec, Canada
Centre d'Études Nordiques, Université Laval, Québec, Quebec, Canada
Renato Pardo Lara
Department of Geography, Environment & Geomatics, University of Guelph, Guelph, Ontario, Canada
Aaron Berg
Department of Geography, Environment & Geomatics, University of Guelph, Guelph, Ontario, Canada
Alex Mavrovic
Department of Environmental Sciences, University of Quebec in Trois-Rivières, Trois-Rivières, Quebec, Canada
Centre d'Études Nordiques, Université Laval, Québec, Quebec, Canada
Department of Physics, Cégep de Sherbrooke, Sherbrooke, Quebec, Canada
Chelene Hanes
Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sault Ste. Marie, Ontario, Canada
Benoit Montpetit
Climate Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
Alexandre Roy
Department of Environmental Sciences, University of Quebec in Trois-Rivières, Trois-Rivières, Quebec, Canada
Centre d'Études Nordiques, Université Laval, Québec, Quebec, Canada
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Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Julien Meloche, Benoit Montpetit, Nicolas R. Leroux, Richard Essery, Gabriel Hould Gosselin, and Philip Marsh
The Cryosphere, 20, 1315–1338, https://doi.org/10.5194/tc-20-1315-2026, https://doi.org/10.5194/tc-20-1315-2026, 2026
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The impact of uncertainties in the simulation of density and specific surface area (SSA) by the snow model Crocus (embedded in the Soil, Vegetation and Snow v2 land surface model) on the simulation of snow backscatter (13.5 GHz) using the Snow Microwave Radiative Transfer model were quantified. The simulation of SSA was found to be a key model uncertainty. Underestimated SSA values lead to high errors in the simulation of backscatter, reduced by implementing a minimum SSA value (8.7 m2 kg−1).
Rémi Madelon, K. Arthur Endsley, John S. Kimball, Gabriëlle J. M. De Lannoy, Oliver Sonnentag, Haley Alcock, Alex Mavrovic, Scott N. Williamson, Vincent Maire, Arnaud Mialon, and Alexandre Roy
EGUsphere, https://doi.org/10.5194/egusphere-2026-720, https://doi.org/10.5194/egusphere-2026-720, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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This study aims to improve estimates of carbon dioxide release and uptake in the North American Arctic and subarctic regions. Several modeling approaches were tested, showing that a better representation of sunlight and temperature effects on ecosystems leads to improved estimates. This work provides new perspectives to better assess whether these regions act as sources or sinks of greenhouse gases and how they may influence the climate system by amplifying or slowing global warming.
Dan K. Thompson, Ellen Whitman, Mark Hafer, Oleksandra Hararuk, Chelene Hanes, Vinicius Manvailer Goncalves, and Ben Hudson
EGUsphere, https://doi.org/10.5194/egusphere-2025-5739, https://doi.org/10.5194/egusphere-2025-5739, 2026
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Emissions from forest fires are tallied in Canada's National Forest Carbon Monitoring Accounting and Reporting System. Mapped fire extents and regional carbon stock estimates are used, but a fixed and high fire severity is assumed. This paper calculates fire emissions based on mapped fire severity. Using mapped fire severity, emissions are 10 to 20% higher, with more variation in emissions per hectare. This new method compares well against independent measurements for the 2023 fires in Canada.
Nicolas R. Leroux, Vincent Vionnet, Courtney Bayer, Julien Meloche, Arlan Dirkson, Franck Lespinas, Mark Buehner, Marco Carrera, Benoit Montpetit, Bernard Bilodeau, Maria Abrahamowicz, and Chris Derksen
EGUsphere, https://doi.org/10.5194/egusphere-2025-5790, https://doi.org/10.5194/egusphere-2025-5790, 2025
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This study evaluates the assimilation of Ku-band radar backscatter into a multilayer snowpack model to support the upcoming Terrestrial Snow Mass Mission. Synthetic experiments were conducted at Arctic, continental, and alpine sites over three winters using a particle filter. Results show that assimilating backscatter improves estimates of snow water equivalent, depth, and vertical snow properties, laying the groundwork for future satellite missions focused on radar-based snow monitoring.
Benoit Montpetit, Julien Meloche, Vincent Vionnet, Chris Derksen, Georgina Woolley, Nicolas R. Leroux, Paul Siqueira, J. Max Adam, and Mike Brady
The Cryosphere, 19, 5465–5484, https://doi.org/10.5194/tc-19-5465-2025, https://doi.org/10.5194/tc-19-5465-2025, 2025
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This paper presents the workflow to retrieve snow water equivalent from radar measurements for the future Canadian radar satellite mission, Terrestrial Snow Mass Mission. The workflow is validated by using airborne radar data collected at Trail Valley Creek, Canada, during winter 2018–2019. We detail important considerations to have in the context of a satellite mission over a vast region such as Canada. Results show that it is possible to achieve the desired accuracy over an Arctic environment.
Anna-Maria Virkkala, Isabel Wargowsky, Judith Vogt, McKenzie A. Kuhn, Simran Madaan, Richard O'Keefe, Tiffany Windholz, Kyle A. Arndt, Brendan M. Rogers, Jennifer D. Watts, Kelcy Kent, Mathias Göckede, David Olefeldt, Gerard Rocher-Ros, Edward A. G. Schuur, David Bastviken, Kristoffer Aalstad, Kelly Aho, Joonatan Ala-Könni, Haley Alcock, Inge Althuizen, Christopher D. Arp, Jun Asanuma, Katrin Attermeyer, Mika Aurela, Sivakiruthika Balathandayuthabani, Alan Barr, Maialen Barret, Ochirbat Batkhishig, Christina Biasi, Mats P. Björkman, Andrew Black, Elena Blanc-Betes, Pascal Bodmer, Julia Boike, Abdullah Bolek, Frédéric Bouchard, Ingeborg Bussmann, Lea Cabrol, Eleonora Canfora, Sean Carey, Karel Castro-Morales, Namyi Chae, Andres Christen, Torben R. Christensen, Casper T. Christiansen, Housen Chu, Graham Clark, Francois Clayer, Patrick Crill, Christopher Cunada, Scott J. Davidson, Joshua F. Dean, Sigrid Dengel, Matteo Detto, Catherine Dieleman, Florent Domine, Egor Dyukarev, Colin Edgar, Bo Elberling, Craig A. Emmerton, Eugenie Euskirchen, Grant Falvo, Thomas Friborg, Michelle Garneau, Mariasilvia Giamberini, Mikhail V. Glagolev, Miquel A. Gonzalez-Meler, Gustaf Granath, Jón Guðmundsson, Konsta Happonen, Yoshinobu Harazono, Lorna Harris, Josh Hashemi, Nicholas Hasson, Janna Heerah, Liam Heffernan, Manuel Helbig, Warren Helgason, Michal Heliasz, Greg Henry, Geert Hensgens, Tetsuya Hiyama, Macall Hock, David Holl, Beth Holmes, Jutta Holst, Thomas Holst, Gabriel Hould-Gosselin, Elyn Humphreys, Jacqueline Hung, Jussi Huotari, Hiroki Ikawa, Danil V. Ilyasov, Mamoru Ishikawa, Go Iwahana, Hiroki Iwata, Marcin Antoni Jackowicz-Korczynski, Joachim Jansen, Järvi Järveoja, Vincent E. J. Jassey, Rasmus Jensen, Katharina Jentzsch, Robert G. Jespersen, Carl-Fredrik Johannesson, Chersity P. Jones, Anders Jonsson, Ji Young Jung, Sari Juutinen, Evan Kane, Jan Karlsson, Sergey Karsanaev, Kuno Kasak, Julia Kelly, Kasha Kempton, Marcus Klaus, George W. Kling, Natacha Kljun, Jacqueline Knutson, Hideki Kobayashi, John Kochendorfer, Kukka-Maaria Kohonen, Pasi Kolari, Mika Korkiakoski, Aino Korrensalo, Pirkko Kortelainen, Egle Koster, Kajar Koster, Ayumi Kotani, Praveena Krishnan, Juliya Kurbatova, Lars Kutzbach, Min Jung Kwon, Ethan D. Kyzivat, Jessica Lagroix, Theodore Langhorst, Elena Lapshina, Tuula Larmola, Klaus S. Larsen, Isabelle Laurion, Justin Ledman, Hanna Lee, A. Joshua Leffler, Lance Lesack, Anders Lindroth, David Lipson, Annalea Lohila, Efrén López-Blanco, Vincent L. St. Louis, Erik Lundin, Misha Luoto, Takashi Machimura, Marta Magnani, Avni Malhotra, Marja Maljanen, Ivan Mammarella, Elisa Männistö, Luca Belelli Marchesini, Phil Marsh, Pertti J. Martkainen, Maija E. Marushchak, Mikhail Mastepanov, Alex Mavrovic, Trofim Maximov, Christina Minions, Marco Montemayor, Tomoaki Morishita, Patrick Murphy, Daniel F. Nadeau, Erin Nicholls, Mats B. Nilsson, Anastasia Niyazova, Jenni Nordén, Koffi Dodji Noumonvi, Hannu Nykanen, Walter Oechel, Anne Ojala, Tomohiro Okadera, Sujan Pal, Alexey V. Panov, Tim Papakyriakou, Dario Papale, Sang-Jong Park, Frans-Jan W. Parmentier, Gilberto Pastorello, Mike Peacock, Matthias Peichl, Roman Petrov, Kyra St. Pierre, Norbert Pirk, Jessica Plein, Vilmantas Preskienis, Anatoly Prokushkin, Jukka Pumpanen, Hilary A. Rains, Niklas Rakos, Aleski Räsänen, Helena Rautakoski, Riika Rinnan, Janne Rinne, Adrian Rocha, Nigel Roulet, Alexandre Roy, Anna Rutgersson, Aleksandr F. Sabrekov, Torsten Sachs, Erik Sahlée, Alejandro Salazar, Henrique Oliveira Sawakuchi, Christopher Schulze, Roger Seco, Armando Sepulveda-Jauregui, Svetlana Serikova, Abbey Serrone, Hanna M. Silvennoinen, Sofie Sjogersten, June Skeeter, Jo Snöälv, Sebastian Sobek, Oliver Sonnentag, Emily H. Stanley, Maria Strack, Lena Strom, Patrick Sullivan, Ryan Sullivan, Anna Sytiuk, Torbern Tagesson, Pierre Taillardat, Julie Talbot, Suzanne E. Tank, Mario Tenuta, Irina Terenteva, Frederic Thalasso, Antoine Thiboult, Halldor Thorgeirsson, Fenix Garcia Tigreros, Margaret Torn, Amy Townsend-Small, Claire Treat, Alain Tremblay, Carlo Trotta, Eeva-Stiina Tuittila, Merritt Turetsky, Masahito Ueyama, Muhammad Umair, Aki Vähä, Lona van Delden, Maarten van Hardenbroek, Andrej Varlagin, Ruth K. Varner, Elena Veretennikova, Timo Vesala, Tarmo Virtanen, Carolina Voigt, Jorien E. Vonk, Robert Wagner, Katey Walter Anthony, Qinxue Wang, Masataka Watanabe, Hailey Webb, Jeffrey M. Welker, Andreas Westergaard-Nielsen, Sebastian Westermann, Jeffrey R. White, Christian Wille, Scott N. Williamson, Scott Zolkos, Donatella Zona, and Susan M. Natali
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-585, https://doi.org/10.5194/essd-2025-585, 2025
Preprint under review for ESSD
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This dataset includes monthly measurements of carbon dioxide and methane exchange between land, water, and the atmosphere from over 1,000 sites in Arctic and boreal regions. It combines measurements from a variety of ecosystems, including wetlands, forests, tundra, lakes, and rivers, gathered by over 260 researchers from 1984–2024. This dataset can be used to improve and reduce uncertainty in carbon budgets in order to strengthen our understanding of climate feedbacks in a warming world.
Renato Pardo Lara, Andreas Colliander, Erica Tetlock, Jarret Powers, Jaison Thomas Ambadan, and Aaron Berg
EGUsphere, https://doi.org/10.5194/egusphere-2025-3630, https://doi.org/10.5194/egusphere-2025-3630, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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Frozen ground affects ecosystems, infrastructure, and farming, yet detecting it worldwide remains a challenge. To improve soil freeze/thaw detection from space, we adapted a laboratory tool called the soil freezing curve for use with NASA’s Soil Moisture Active Passive (SMAP) satellite and temperature records. This new “surface freezing curve” method can identify thresholds tied to moisture phase changes, improving the accuracy and stability of freeze/thaw monitoring in agricultural regions.
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.
Julien Meloche, Nicolas R. Leroux, Benoit Montpetit, Vincent Vionnet, and Chris Derksen
The Cryosphere, 19, 2949–2962, https://doi.org/10.5194/tc-19-2949-2025, https://doi.org/10.5194/tc-19-2949-2025, 2025
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Measuring snow mass from radar measurements is possible with information on snow and a radar model to link the measurements to snow. A key variable in a retrieval is the number of snow layers, with more layers yielding richer information but at increased computational cost. Here, we show the capabilities of a new method for simplifying a complex snowpack while preserving the scattering behavior of the snowpack and conserving its mass.
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.
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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Satellite microwave observations are used for weather forecasting. In Arctic regions this is complicated by natural emission from snow. By simulating airborne observations from in situ measurements of snow, this study shows how snow properties affect the signal within the atmosphere. Fresh snowfall between flights changed airborne measurements. Good knowledge of snow layering and structure can be used to account for the effects of snow and could unlock these data to improve forecasts.
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.
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024, https://doi.org/10.5194/tc-18-2321-2024, 2024
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The CAA serves as both a source and a sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay. It 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 Parry Channel, which spans the central region of the Northwest Passage.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Carolina Voigt, Nick Rutter, Paul Mann, Jean-Daniel Sylvain, and Alexandre Roy
Biogeosciences, 20, 5087–5108, https://doi.org/10.5194/bg-20-5087-2023, https://doi.org/10.5194/bg-20-5087-2023, 2023
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We present an analysis of soil CO2 emissions in boreal and tundra regions during the non-growing season. We show that when the soil is completely frozen, soil temperature is the main control on CO2 emissions. When the soil is around the freezing point, with a mix of liquid water and ice, the liquid water content is the main control on CO2 emissions. This study highlights that the vegetation–snow–soil interactions must be considered to understand soil CO2 emissions during the non-growing season.
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.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer L. Baltzer, Christophe Kinnard, and Alexandre Roy
Biogeosciences, 20, 2941–2970, https://doi.org/10.5194/bg-20-2941-2023, https://doi.org/10.5194/bg-20-2941-2023, 2023
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This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag
EGUsphere, https://doi.org/10.5194/egusphere-2023-1167, https://doi.org/10.5194/egusphere-2023-1167, 2023
Preprint archived
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Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.
Sara Sadri, James S. Famiglietti, Ming Pan, Hylke E. Beck, Aaron Berg, and Eric F. Wood
Hydrol. Earth Syst. Sci., 26, 5373–5390, https://doi.org/10.5194/hess-26-5373-2022, https://doi.org/10.5194/hess-26-5373-2022, 2022
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A farm-scale hydroclimatic machine learning framework to advise farmers was developed. FarmCan uses remote sensing data and farmers' input to forecast crop water deficits. The 8 d composite variables are better than daily ones for forecasting water deficit. Evapotranspiration (ET) and potential ET are more effective than soil moisture at predicting crop water deficit. FarmCan uses a crop-specific schedule to use surface or root zone soil moisture.
Chang-Hwan Park, Aaron Berg, Michael H. Cosh, Andreas Colliander, Andreas Behrendt, Hida Manns, Jinkyu Hong, Johan Lee, Runze Zhang, and Volker Wulfmeyer
Hydrol. Earth Syst. Sci., 25, 6407–6420, https://doi.org/10.5194/hess-25-6407-2021, https://doi.org/10.5194/hess-25-6407-2021, 2021
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In this study, we proposed an inversion of the dielectric mixing model for a 50 Hz soil sensor for agricultural organic soil. This model can reflect the variability of soil organic matter (SOM) in wilting point and porosity, which play a critical role in improving the accuracy of SM estimation, using a dielectric-based soil sensor. The results of statistical analyses demonstrated a higher performance of the new model than the factory setting probe algorithm.
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.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
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This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Cited articles
Ala-Aho, P., Autio, A., Bhattacharjee, J., Isokangas, E., Kujala, K., Marttila, H., Menberu, M., Meriö, L.-J., Postila, H., Rauhala, A., Ronkanen, A.-K., Rossi, P. M., Saari, M., Haghighi, A. T., and Kløve, B.: What conditions favor the influence of seasonally frozen ground on hydrological partitioning? A systematic review, Environ. Res. Lett., 16, 043008, https://doi.org/10.1088/1748-9326/abe82c, 2021. a, b
Amankwah, S. K., Ireson, A. M., and Brannen, R.: An improved model and field calibration technique for measuring liquid water content in unfrozen and frozen soils with dielectric probes, Vadose Zone J., 21, e20225, https://doi.org/10.1002/vzj2.20225, 2022. a, b, c
Arndt, K. A., Hashemi, J., Natali, S. M., Schiferl, L. D., and Virkkala, A.-M.: Recent Advances and Challenges in Monitoring and Modeling Non-Growing Season Carbon Dioxide Fluxes from the Arctic Boreal Zone, Current Climate Change Reports, 9, 27–40, https://doi.org/10.1007/s40641-023-00190-4, 2023. a
Azizi-Rad, M., Guggenberger, G., Ma, Y., and Sierra, C. A.: Sensitivity of soil respiration rate with respect to temperature, moisture and oxygen under freezing and thawing, Soil Biol. Biochem., 165, 108488, https://doi.org/10.1016/j.soilbio.2021.108488, 2022. a
Bi, J., Wang, G., Wu, Z., Wen, H., Zhang, Y., Lin, G., and Sun, T.: Investigation on unfrozen water content models of freezing soils, Frontiers in Earth Science, 10, 1039330, https://doi.org/10.3389/feart.2022.1039330, 2023a. a
Bi, J., Wu, Z., Lu, Y., Wen, H., Zhang, Y., Shen, Y., Wei, T., and Wang, G.: Study on soil freezing characteristic curve during a freezing-thawing process, Frontiers in Earth Science, 10, 1007342, https://doi.org/10.3389/feart.2022.1007342, 2023b. a, b
C3S: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/CDS.ADBB2D47, 2018. a
Chai, M., Zhang, J., Zhang, H., Mu, Y., Sun, G., and Yin, Z.: A method for calculating unfrozen water content of silty clay with consideration of freezing point, Applied Clay Science, 161, 474–481, https://doi.org/10.1016/j.clay.2018.05.015, 2018. a
Cominelli, S., Rivera, L. D., Brown, W. G., Ochsner, T. E., and Patrignani, A.: Calibration of TEROS 10 and TEROS 12 electromagnetic soil moisture sensors, Soil Sci. Soc. Am. J., 88, 2104–2122, https://doi.org/10.1002/saj2.20777, 2024. a, b, c, d
Davidson, E. A. and Janssens, I. A.: Temperature sensitivity of soil carbon decomposition and feedbacks to climate change, Nature, 440, 165–173, https://doi.org/10.1038/nature04514, 2006. a
Decker, K. L. M., Wang, D., Waite, C., and Scherbatskoy, T.: Snow Removal and Ambient Air Temperature Effects on Forest Soil Temperatures in Northern Vermont, Soil Sci. Soc. Am. J., 67, 1234–1242, https://doi.org/10.2136/sssaj2003.1234, 2003. a
Derksen, C., Xu, X., Scott D. R., Colliander, A., Kim, Y., Kimball, J. S., Black, T. A., Euskirchen, E., Langlois, A., Loranty, M. M., Marsh, P., Rautiainen, K., Roy, A., Royer, A., and Stephens, J.: Retrieving landscape freeze/thaw state from Soil Moisture Active Passive (SMAP) radar and radiometer measurements, Remote Sens. Environ., 194, https://doi.org/10.1016/j.rse.2017.03.007, 2017. a
Donahue, K., Kimball, J. S., Du, J., Bunt, F., Colliander, A., Moghaddam, M., Johnson, J., Kim, Y., and Rawlins, M. A.: Deep learning estimation of northern hemisphere soil freeze-thaw dynamics using satellite multi-frequency microwave brightness temperature observations, Frontiers in Big Data, 6, 1243559, https://doi.org/10.3389/fdata.2023.1243559, 2023. a, b
Fragkos, A., Loukatos, D., Kargas, G., and Arvanitis, K. G.: Response of the TEROS 12 Soil Moisture Sensor under Different Soils and Variable Electrical Conductivity, Sensors, 24, 2206, https://doi.org/10.3390/s24072206, 2024. a, b, c
Fu, Q., Hou, R., Li, T., Jiang, R., Yan, P., Ma, Z., and Zhou, Z.: Effects of soil water and heat relationship under various snow cover during freezing-thawing periods in Songnen Plain, China, Sci. Rep., 8, 1325, https://doi.org/10.1038/s41598-018-19467-y, 2018. a
Gao, H., Nie, N., Zhang, W., and Chen, H.: Monitoring the spatial distribution and changes in permafrost with passive microwave remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 170, 142–155, https://doi.org/10.1016/j.isprsjprs.2020.10.011, 2020. a, b
Geng, X., He, J., Grima, V., Jiang, Y., Tetreau, M., Crittenden, S., Kiley, S., VandenBygaart, A. J., and Vanrobaeys, J.: 100 m soil landscape grids of Canada, Scientific Data, 12, 1178, https://doi.org/10.1038/s41597-025-05460-4, 2025. a
Hanes, C. C., Wotton, M., Bourgeau-Chavez, L., Woolford, D. G., Bélair, S., Martell, D., and Flannigan, M. D.: Evaluation of new methods for drought estimation in the Canadian Forest Fire Danger Rating System, Int. J. Wildland Fire, 32, 836–853, https://doi.org/10.1071/WF22112, 2023. a
Hansson, K. and Lundin, L.-C.: Water Content Reflectometer Application to Construction Materials and its Relation to Time Domain Reflectometry, Vadose Zone J., 5, 459–468, https://doi.org/10.2136/vzj2005.0053, 2006. a, b, c, d
Hayashi, M.: The Cold Vadose Zone: Hydrological and Ecological Significance of Frozen-Soil Processes, Vadose Zone J., 12, 1–8, https://doi.org/10.2136/vzj2013.03.0064, 2013. a
He, H. and Dyck, M.: Application of Multiphase Dielectric Mixing Models for Understanding the Effective Dielectric Permittivity of Frozen Soils, Vadose Zone J., 12, vzj2012.0060, https://doi.org/10.2136/vzj2012.0060, 2013. a, b, c
Kelleners, T. J. and Norton, J. B.: Determining Water Retention in Seasonally Frozen Soils Using Hydra Impedance Sensors, Soil Sci. Soc. Am. J., 76, 36–50, https://doi.org/10.2136/sssaj2011.0222, 2012. a
Kersten, M. S.: Thermal Properties of Soils, University of Minnesota, https://hdl.handle.net/11299/124271 (last access: October 2025), 1949. a
Kim, Y., Kimball, J. S., McDonald, K. C., and Glassy, J.: Developing a Global Data Record of Daily Landscape Freeze/Thaw Status Using Satellite Passive Microwave Remote Sensing, IEEE T. Geosci. Remote, 49, 949–960, https://doi.org/10.1109/TGRS.2010.2070515, 2011. a, b
Koopmans, R. W. R. and Miller, R. D.: Soil Freezing and Soil Water Characteristic Curves, Soil Sci. Soc. Am. J., 30, 680–685, https://doi.org/10.2136/sssaj1966.03615995003000060011x, 1966. a
Kou, X., Jiang, L., Yan, S., Zhao, T., Lu, H., and Cui, H.: Detection of land surface freeze-thaw status on the Tibetan Plateau using passive microwave and thermal infrared remote sensing data, Remote Sens. Environ., 199, 291–301, https://doi.org/10.1016/j.rse.2017.06.035, 2017. a, b
Latifovic, R.: Canada's land cover, Tech. Rep., 119e, version 2015, Natural Resources Canada, https://doi.org/10.4095/315659, 2019. a
Lawrence, D. M., Slater, A. G., Romanovsky, V. E., and Nicolsky, D. J.: Sensitivity of a model projection of near-surface permafrost degradation to soil column depth and representation of soil organic matter, J. Geophys. Res.: Earth Surf., 113, 2007JF000883, https://doi.org/10.1029/2007JF000883, 2008. a
Lei, D., Yang, Y., Cai, C., Chen, Y., and Wang, S.: The Modelling of Freezing Process in Saturated Soil Based on the Thermal-Hydro-Mechanical Multi-Physics Field Coupling Theory, Water, 12, 2684, https://doi.org/10.3390/w12102684, 2020. a
Lei, N., Wang, H., Zhang, Y., and Chen, T.: Components of respiration and their temperature sensitivity in four reconstructed soils, Sci. Rep., 12, 6107, https://doi.org/10.1038/s41598-022-09918-y, 2022. a
Loranty, M. M., Abbott, B. W., Blok, D., Douglas, T. A., Epstein, H. E., Forbes, B. C., Jones, B. M., Kholodov, A. L., Kropp, H., Malhotra, A., Mamet, S. D., Myers-Smith, I. H., Natali, S. M., O'Donnell, J. A., Phoenix, G. K., Rocha, A. V., Sonnentag, O., Tape, K. D., and Walker, D. A.: Reviews and syntheses: Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions, Biogeosciences, 15, 5287–5313, https://doi.org/10.5194/bg-15-5287-2018, 2018. a
MacKinney, A. L.: Effects of Forest Litter on Soil Temperature and Soil Freezing in Autumn and Winter, Ecology, 10, 312–321, https://doi.org/10.2307/1929507, 1929. a
Mavrovic, A., Sonnentag, O., Lemmetyinen, J., Voigt, C., Rutter, N., Mann, P., Sylvain, J.-D., and Roy, A.: Environmental controls of winter soil carbon dioxide fluxes in boreal and tundra environments, Biogeosciences, 20, 5087–5108, https://doi.org/10.5194/bg-20-5087-2023, 2023. a
Mikan, C. J., Schimel, J. P., and Doyle, A. P.: Temperature controls of microbial respiration in arctic tundra soils above and below freezing, Soil Biol. Biochem., 34, 1785–1795, https://doi.org/10.1016/S0038-0717(02)00168-2, 2002. a
Montpetit, B., King, J., Meloche, J., Derksen, C., Siqueira, P., Adam, J. M., Toose, P., Brady, M., Wendleder, A., Vionnet, V., and Leroux, N. R.: Retrieval of airborne Ku-Band SAR Using Forward Radiative Transfer Modeling to Estimate Snow Water Equivalent: The Trail Valley Creek 2018/19 Snow Experiment, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-651, 2024. a
Montpetit, B., King, J., Meloche, J., Derksen, C., Siqueira, P., Adam, J. M., Toose, P., Brady, M., Wendleder, A., Vionnet, V., and Leroux, N. R.: Retrieval of airborne Ku-Band SAR Using Forward Radiative Transfer Modeling to Estimate Snow Water Equivalent: The Trail Valley Creek 2018/19 Snow Experiment, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-651, 2024. a
Nikrad, M. P., Kerkhof, L. J., and Häggblom, M. M.: The subzero microbiome: microbial activity in frozen and thawing soils, FEMS Microbiol. Ecol., 92, fiw081, https://doi.org/10.1093/femsec/fiw081, 2016. a
Oogathoo, S., Houle, D., Duchesne, L., and Kneeshaw, D.: Evaluation of simulated soil moisture and temperature for a Canadian boreal forest, Agr. Forest Meteorol., 323, 109078, https://doi.org/10.1016/j.agrformet.2022.109078, 2022. a
Pardo Lara, R., Berg, A. A., Warland, J., and Tetlock, E.: In Situ Estimates of Freezing/Melting Point Depression in Agricultural Soils Using Permittivity and Temperature Measurements, Water Resour. Res., 56, e2019WR026020, https://doi.org/10.1029/2019WR026020, 2020. a, b, c
Ping, C. L., Jastrow, J. D., Jorgenson, M. T., Michaelson, G. J., and Shur, Y. L.: Permafrost soils and carbon cycling, SOIL, 1, 147–171, https://doi.org/10.5194/soil-1-147-2015, 2015. a
Rautiainen, K., Holmberg, M., Cohen, J., Mialon, A., Schwank, M., Lemmetyinen, J., de la Fuente, A., and Kerr, Y.: An operational SMOS soil freeze–thaw product, Earth Syst. Sci. Data, 17, 5337–5353, https://doi.org/10.5194/essd-17-5337-2025, 2025. a, b
Roth, K., Schulin, R., Flühler, H., and Attinger, W.: Calibration of time domain reflectometry for water content measurement using a composite dielectric approach, Water Resour. Res., 26, 2267–2273, https://doi.org/10.1029/WR026i010p02267, 1990. a
Roy, A., Toose, P., Mavrovic, A., Pappas, C., Royer, A., Derksen, C., Berg, A., Rowlandson, T., El-Amine, M., Barr, A., Black, A., Langlois, A., and Sonnentag, O.: L-Band response to freeze/thaw in a boreal forest stand from ground- and tower-based radiometer observations, Remote Sens. Environ., 237, 111542, https://doi.org/10.1016/j.rse.2019.111542, 2020. a, b
Salmabadi, H.: Development of New Microwave Multi-Sensor Freeze/Thaw Products for Improving Growing Season Monitoring in North America, Doctoral Research Scholarship, Fonds de recherche du Quebec – Nature et technologies (FRQNT), 330450, https://doi.org/10.69777/330450, 2025. a
Salmabadi, H., Berg, A., Mavrovic, A., Gorrab ep El Khedhri, A., MacRae, H. C., Hanes, C., and Roy, A.: Improving Seasonally Frozen Ground Monitoring Using Soil Freezing Characteristic Curve in Permittivity-Temperature Space: Sites Metadata, version Number: v1.1, Zenodo, https://doi.org/10.5281/ZENODO.14837416, 2025. a
Seyfried, M. S. and Murdock, M. D.: Calibration of time domain reflectometry for measurement of liquid water in frozen soils, Soil Sci., 161, 87–98, https://doi.org/10.1097/00010694-199602000-00002, 1996. a
Seyfried, M. S. and Murdock, M. D.: Measurement of Soil Water Content with a 50-MHz Soil Dielectric Sensor, Soil Sci. Soc. Am. J., 68, 394–403, https://doi.org/10.2136/sssaj2004.3940, 2004. a, b, c, d
Seyfried, M. S., Grant, L. E., Du, E., and Humes, K.: Dielectric Loss and Calibration of the Hydra Probe Soil Water Sensor, Vadose Zone J., 4, 1070–1079, https://doi.org/10.2136/vzj2004.0148, 2005. a, b, c
Smith, M. W. and Tice, A. R.: Measurement of the Unfrozen Water Content of Soils. Comparison of NMR (Nuclear Magnetic Resonance) and TDR (Time Domain Reflectometry) Methods, CRREL Rep. 88-18, U.S. Army Corps of Engineers, Cold Regions Research and Engineering Lab, Hannover, NH, https://apps.dtic.mil/sti/tr/pdf/ADA203082.pdf (last access: 20 September 2024), 1988. a
Spaans, E. J. A. and Baker, J. M.: The Soil Freezing Characteristic: Its Measurement and Similarity to the Soil Moisture Characteristic, Soil Sci. Soc. Am. J., 60, 13–19, https://doi.org/10.2136/sssaj1996.03615995006000010005x, 1996. a
Taghipourjavi, S., Kinnard, C., and Roy, A.: Sentinel-1-Based Soil Freeze–Thaw Detection in Agro-Forested Areas: A Case Study in Southern Québec, Canada, Remote Sensing, 16, 1294, https://doi.org/10.3390/rs16071294, 2024. a, b
Tetlock, E., Toth, B., Berg, A., Rowlandson, T., and Ambadan, J. T.: An 11-year (2007–2017) soil moisture and precipitation dataset from the Kenaston Network in the Brightwater Creek basin, Saskatchewan, Canada, Earth Syst. Sci. Data, 11, 787–796, https://doi.org/10.5194/essd-11-787-2019, 2019. a
Tian, H., Wei, C., Wei, H., and Zhou, J.: Freezing and thawing characteristics of frozen soils: Bound water content and hysteresis phenomenon, Cold Reg. Sci. Technol., 103, 74–81, https://doi.org/10.1016/j.coldregions.2014.03.007, 2014. a, b
Topp, G. C., Davis, J. L., and Annan, A. P.: Electromagnetic determination of soil water content: Measurements in coaxial transmission lines, Water Resour. Res., 16, 574–582, https://doi.org/10.1029/WR016i003p00574, 1980. a
U. S. National Ice Center: IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions, Version 1, https://doi.org/10.7265/N52R3PMC, 2004. a
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., Van Der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, I., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., Van Mulbregt, P., Vijaykumar, A., Bardelli, A. P., Rothberg, A., Hilboll, A., Kloeckner, A., Scopatz, A., Lee, A., Rokem, A., Woods, C. N., Fulton, C., Masson, C., Häggström, C., Fitzgerald, C., Nicholson, D. A., Hagen, D. R., Pasechnik, D. V., Olivetti, E., Martin, E., Wieser, E., Silva, F., Lenders, F., Wilhelm, F., Young, G., Price, G. A., Ingold, G.-L., Allen, G. E., Lee, G. R., Audren, H., Probst, I., Dietrich, J. P., Silterra, J., Webber, J. T., Slavič, J., Nothman, J., Buchner, J., Kulick, J., Schönberger, J. L., De Miranda Cardoso, J. V., Reimer, J., Harrington, J., Rodríguez, J. L. C., Nunez-Iglesias, J., Kuczynski, J., Tritz, K., Thoma, M., Newville, M., Kümmerer, M., Bolingbroke, M., Tartre, M., Pak, M., Smith, N. J., Nowaczyk, N., Shebanov, N., Pavlyk, O., Brodtkorb, P. A., Lee, P., McGibbon, R. T., Feldbauer, R., Lewis, S., Tygier, S., Sievert, S., Vigna, S., Peterson, S., More, S., Pudlik, T., Oshima, T., Pingel, T. J., Robitaille, T. P., Spura, T., Jones, T. R., Cera, T., Leslie, T., Zito, T., Krauss, T., Upadhyay, U., Halchenko, Y. O., and Vázquez-Baeza, Y.: SciPy 1.0: fundamental algorithms for scientific computing in Python, Nature Methods, 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020. a
von Hippel, A. R.: Dielectrics and Waves, The MIT Press, Journal of The Electrochemical Society, 102, 68C, 1955. a
Williams, P. J. and Smith, M. W.: The Frozen Earth: Fundamentals of Geocryology, 1st edn., Cambridge University Press, https://doi.org/10.1017/CBO9780511564437, 1989. a
Yoshikawa, K. and Overduin, P. P.: Comparing unfrozen water content measurements of frozen soil using recently developed commercial sensors, Cold Reg. Sci. Technol., 42, 250–256, https://doi.org/10.1016/j.coldregions.2005.03.001, 2005. a
Zhang, M., Zhang, X., Lu, J., Pei, W., and Wang, C.: Analysis of volumetric unfrozen water contents in freezing soils, Experimental Heat Transfer, 32, 426–438, https://doi.org/10.1080/08916152.2018.1535528, 2019. a, b, c
Zhang, T.: Influence of the seasonal snow cover on the ground thermal regime: An overview, Rev. Geophys., 43, 2004RG000157, https://doi.org/10.1029/2004RG000157, 2005. a
Zhang, T. and Armstrong, R. L.: Soil freeze/thaw cycles over snow-free land detected by passive microwave remote sensing, Geophys. Res. Lett., 28, 763–766, https://doi.org/10.1029/2000GL011952, 2001. a, b
Zhang, T.: Distributing of seasonally and perennially frozen ground in the northern hemisphere, Proceedings of the 8th International Conference on Permafrost, 21–25 July 2003, Zurich, Switzerland, AA Balkema, 1289–1294, 2003. a
Zhou, X., Zhou, J., Kinzelbach, W., and Stauffer, F.: Simultaneous measurement of unfrozen water content and ice content in frozen soil using gamma ray attenuation and TDR, Water Resour. Res., 50, 9630–9655, https://doi.org/10.1002/2014WR015640, 2014. a
Short summary
Current satellite monitoring often oversimplifies soil freezing by assuming it happens exactly at 0°C. We analyzed ground data across Canada and found that soil often stays in a partially frozen state for months, even when air temperatures are well below freezing, revealing a major gap in how we track seasonally frozen ground.
Current satellite monitoring often oversimplifies soil freezing by assuming it happens exactly...
