Articles | Volume 25, issue 3
https://doi.org/10.5194/hess-25-1117-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-1117-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Soil dielectric characterization during freeze–thaw transitions using L-band coaxial and soil moisture probes
Alex Mavrovic
CORRESPONDING AUTHOR
Département des Sciences de l'Environnement, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, G9A 5H7, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Quebec, G1V 0A6, Canada
Renato Pardo Lara
Department of Geography, Environment & Geomatics, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
Aaron Berg
Department of Geography, Environment & Geomatics, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
François Demontoux
Laboratoire de l'Intégration du Matériau au Système,
Bordeaux, 33400 Talence, France
Alain Royer
Centre d'Applications et de Recherches en Télédétection, Université de Sherbrooke, Sherbrooke, Quebec, J1K 2R1, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Quebec, G1V 0A6, Canada
Alexandre Roy
Département des Sciences de l'Environnement, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, G9A 5H7, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Quebec, G1V 0A6, Canada
Related authors
Hesam Salmabadi, Renato Pardo Lara, Aaron Berg, Alex Mavrovic, Chelene Hanes, Benoit Montpetit, and Alexandre Roy
EGUsphere, https://doi.org/10.5194/egusphere-2025-620, https://doi.org/10.5194/egusphere-2025-620, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Our research introduces a framework for monitoring seasonally frozen ground that goes beyond simply checking whether soil temperature is above or below freezing. We found that soil often remains in a transitional state between frozen and unfrozen for as long as fully frozen periods – something traditional monitoring methods fail to capture. These findings enhance our understanding of seasonally frozen ground, its climate change impacts, and carbon release in cold regions.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Vincent Vionnet, Nicolas Romain 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
EGUsphere, https://doi.org/10.5194/egusphere-2025-3396, https://doi.org/10.5194/egusphere-2025-3396, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
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.
Hesam Salmabadi, Renato Pardo Lara, Aaron Berg, Alex Mavrovic, Chelene Hanes, Benoit Montpetit, and Alexandre Roy
EGUsphere, https://doi.org/10.5194/egusphere-2025-620, https://doi.org/10.5194/egusphere-2025-620, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Our research introduces a framework for monitoring seasonally frozen ground that goes beyond simply checking whether soil temperature is above or below freezing. We found that soil often remains in a transitional state between frozen and unfrozen for as long as fully frozen periods – something traditional monitoring methods fail to capture. These findings enhance our understanding of seasonally frozen ground, its climate change impacts, and carbon release in cold regions.
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
Short summary
Short summary
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.
Juliette Ortet, Arnaud Mialon, Alain Royer, Mike Schwank, Manu Holmberg, Kimmo Rautiainen, Simone Bircher-Adrot, Andreas Colliander, Yann Kerr, and Alexandre Roy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3963, https://doi.org/10.5194/egusphere-2024-3963, 2025
Short summary
Short summary
We propose a new method to determine the ground surface temperature under the snowpack in the Arctic area from satellite observations. The obtained ground temperatures time series were evaluated over 21 reference sites in Northern Alaska and compared with ground temperatures obtained with global models. The method is excessively promising for monitoring ground temperature below the snowpack and studying the spatiotemporal variability thanks to 15 years of observations over the whole Arctic area.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Joëlle Voglimacci-Stephanopoli, Anna Wendleder, Hugues Lantuit, Alexandre Langlois, Samuel Stettner, Andreas Schmitt, Jean-Pierre Dedieu, Achim Roth, and Alain Royer
The Cryosphere, 16, 2163–2181, https://doi.org/10.5194/tc-16-2163-2022, https://doi.org/10.5194/tc-16-2163-2022, 2022
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Nataniel M. Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, and Alexandra G. Konings
Biogeosciences, 18, 739–753, https://doi.org/10.5194/bg-18-739-2021, https://doi.org/10.5194/bg-18-739-2021, 2021
Short summary
Short summary
Microwave radiation coming from Earth's land surface is affected by both soil moisture and the water in plants that cover the soil. We measured such radiation with a sensor elevated above a forest canopy while repeatedly measuring the amount of water stored in trees at the same location. Changes in the microwave signal over time were closely related to tree water storage changes. Satellites with similar sensors could thus be used to monitor how trees in an entire region respond to drought.
Cited articles
Artemov, V. and Volkov, A.: Water and Ice Dielectric Spectra Scaling at
0 ∘C, Ferroelectr., 466, 158–165, https://doi.org/10.1080/00150193.2014.895216, 2014.
Attema, E. and Ulaby, F.: Vegetation modeled as a water cloud, Radio Sci., 13, 357–364, https://doi.org/10.1029/RS013i002p00357, 1978.
Bircher, S., Andreasen, M., Vuollet, J., Vehviläinen, J., Rautiainen, K., Jonard, F., Weihermüller, L., Zakharova, E., Wigneron, J.-P., and Kerr, Y. H.: Soil moisture sensor calibration for organic soil surface layers, Geosci. Instrum. Method. Data Syst., 5, 109–125, https://doi.org/10.5194/gi-5-109-2016, 2016a.
Bircher, S., Demontoux, F., Razafindratsima, S., Bircher, S., Zakharova, E.,
Drusch, M., Wigneron, J.-P., and Kerr, Y.: L-Band Relative Permittivity of
Organic Soil Surface Layers – A New Dataset of Resonant Cavity Measurements
and Model Evaluation, Remote Sens., 8, 1024, https://doi.org/10.3390/rs8121024, 2016b.
Bouyoucos, G.: Hydrometer method improved for making particle size analysis
of soils, Agron. J., 54, 464–465, https://doi.org/10.2134/agronj1962.00021962005400050028x, 1962.
Bracaglia, M., Ferrazzoli, P., and Guerriero, L.: A fully polarimetric multiple scattering model for crops, Remote Sens. Environ., 54, 170–179, https://doi.org/10.1016/0034-4257(95)00151-4, 1995.
Burns, T., Adams, J., and Berg, A.: Laboratory Calibration Procedures of the
Hydra Probe Soil Moisture Sensor: Infiltration Wet-Up vs. Dry-Down, Vadose
Zone J., 13, 1–10, https://doi.org/10.2136/vzj2014.07.0081, 2014.
Campbell, J.: Dielectric Properties and Influence of Conductivity in Soils at One to Fifty Megahertz, Soil Sci. Soc. Am. J., 54, 332–341,
https://doi.org/10.2136/sssaj1990.03615995005400020006x, 1990.
Campbell, J. E.: Dielectric properties of moist soils at RF and microwave frequencies, PhD thesis, Dartmouth College, Hanover, NH, 178 pp., https://doi.org/10.1349/ddlp.1563, 1988.
Colliander, A., Jackson, T., Bindlish, R., Chan, S., Das, N., Kim, S., Cosh,
M., Dunbar, R., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A., Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D., al Jassar, H., Lopez-Baeza, E., Martínez Fernández, J., González-Zamora, A., Livingston, S., McNairn, H., Pacheco, A., Moghaddam, M., Montzka, C.,
Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J., Pulliainen, J.,
Rautiainen, K., Ramos, J., Seyfried, M., Starks, P., Su, Z., Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M., Walker, J. P.,
Wu, X., Monerris, A., O'Neill, P. E., Entekhabi, D., Njoku, E.G., and Yueha,
S.: Validation of SMAP surface soil moisture products with core validation
sites, Remote Sens. Environ., 191, 215–231, https://doi.org/10.1016/j.rse.2017.01.021,
2017.
Daanen, R., Misra, D., and Thompson, A.: Frozen Soil Hydrology. Encyclopedia
of Snow, Ice and Glaciers, edited by: Singh, V., Singh, P., and Haritashya,
U., Springer Netherlands, 306–311, ISBN 978-90-481-2641-5, 2011.
Demontoux, F., Razafindratsima, S., Bircher, S., Ruffié, G., Bonnaudin, F., Jonard, F., Wigneron, J.-P., Sbartaï, M., and Kerr, Y.: Efficiency of end effect probes for in-situ permittivity measurements in the 0.5–6 GHz
frequency range and their application for organic soil horizons study, Sens.
Actuat. A, 254, 78–88, https://doi.org/10.1016/j.sna.2016.12.005, 2017.
Demontoux, F., Yaakoubi, G., Wigneron, G., Grzeskowiak, M., Sbartaï, M., Fadel, L., Ruffié, G., Bonnaudin, F., Oyhenart, L., Vignéras, V., Wigneron, J.-P., Villard, L., Le Toan, T., and Kerr, Y.: Antipodal Vivaldi antennas dedicated to in-situ broadband microwave permittivity measurements, in: EuMCE – 2019 European Microwave Conference in Central Europe, Prague, Czech Republic, 62–65, available at: https://prodinra.inra.fr/record/495910 (last access: 23 February 2021), 2019.
Demontoux, F., Tsague King, J., Bircher, S., Ruffie, G., Bonnaudin, F., Wigneron, J.-P., and Kerr, Y.: In-situ multi-frequency dielectric measurements to improve soil permittivity models for radiometric observations of soil in the high latitudes, in: 2020 16th Specialist Meeting on Microwave Radiometry and Remote Sensing for the Environment (MicroRad), Florence, Italy, https://doi.org/10.1109/MicroRad49612.2020.9342613, 2020.
Derksen, C., Xu, X., Scott Dunbar, 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, 48–62,
https://doi.org/10.1016/j.rse.2017.03.007, 2017.
Dobson, M., Ulaby, F., Hallikainen, M., and El-Rayes, M.: Microwave dielectric behavior of wet soil – Part II: Dielectric mixing models, Geosci.
Model Dev., GE-23, 35–46, https://doi.org/10.1109/TGRS.1985.289498, 1985.
Entekhabi, D., Njoku, E., O'Neill, P., Kellogg, K., Crow, W., Edelstein, W.,
Entin, J., Goodman, S., Jackson, T., Jackson, J., Kimball, J., Piepmeier, J., Koster, R., Martin, N., McDonald, K., Moghaddam, M., Moran, S., Reichle, R., Shi, J., Spencer, M., Thurman, S., Tsang, L., and Van Zyl, J.: The Soil Moisture Active Passive (SMAP) mission, Proc. IEEE, 98, 704–716,
https://doi.org/10.1109/JPROC.2010.2043918, 2010.
Fan, L., Wigneron, J.-P., Mialon, A., Rodriguez-Fernandez, N. J., Ai-Yaari,
A., Kerr, Y., Brandt, M., and Ciais, P.: SMOS-IC Vegetation Optical Depth
Index in Monitoring Aboveground Carbon Changes in the Tropical Continents
During 2010–2016, in: IGARSS 2018–2018 IEEE International Geoscience and
Remote Sensing Symposium, Valencia, Spain, 2825–2828,
https://doi.org/10.1109/igarss.2018.8518750, 2018.
Filali, B., Rhazi, J.-E., and Ballivy, G.: Measurement of the dielectric
properties of concrete by a large coaxial probe with open end, Can. J. Phys., 84, 365–379, https://doi.org/10.1139/p06-056, 2006.
Filali, B., Boone, F., Rhazi, J.-E., and Ballivy, G.: Design and calibration of a large open-ended coaxial probe for the measurement of the dielectric
properties of concrete, IEEE T. Microw. Theor. Tech., 56, 2322–2328,
https://doi.org/10.1109/TMTT.2008.2003520, 2008.
Gower S., Vogel, J., Norman, J., Kucharik, C., Steele, S., and Stow, T.: Carbon distribution and aboveground net primary production in aspen, jack pine, and black spruce stands in Saskatchewan and Manitoba, Canada, J. Geophys. Res., 102, 29029–29041, https://doi.org/10.1029/97JD02317, 1997.
Holtzman, N. M., Anderegg, L. D. L., Kraatz, S., Mavrovic, A., Sonnentag, O., Pappas, C., Cosh, M. H., Langlois, A., Lakhankar, T., Tesser, D., Steiner, N., Colliander, A., Roy, A., and Konings, A. G.: L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand, Biogeosciences, 18, 739–753, https://doi.org/10.5194/bg-18-739-2021, 2021.
Huang, J., Tsang, L., Njoku, E., Colliander, A., Liao, T., and Ding, K.:
Propagation and Scattering by a Layer of Randomly Distributed Dielectric
Cylinders Using Monte Carlo Simulations of 3D Maxwell Equations With Applications in Microwave Interactions With Vegetation, IEEE Access, 5,
11985–12003, https://doi.org/10.1109/ACCESS.2017.2714620, 2017.
HydraProbe Soil Sensor Users Manual: Revision VI, Stevens Water Monitoring Systems Inc., Portland, Oregon, USA, 63 pp., 2018.
Jonard, F., Bircher, S., Demontoux, F., Weihermüller, L., Razafindratsima, S., Wigneron, J.-P., and Vereecken, H.: Passive L-Band
Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based
Experiment, Remote Sens., 10, 304, https://doi.org/10.3390/rs10020304, 2018.
Jones, S., Wraith, J., and Or, D.: Time domain reflectometry measurement
principles and applications, Hydrol. Process., 16, 141–153, https://doi.org/10.1002/hyp.513, 2002.
Judge, J., Galantowicz, J., England, A., and Dahl, P.: Freeze/thaw classification for prairie soils using SSM/I radiobrightnesses, IEEE T. Geosci. Remote, 35, 827–832, https://doi.org/10.1109/36.602525, 1997.
Kerr, Y., Waldteufel, P., Richaume, P., Wigneron, J., Ferrazzoli, P., Mahmoodi, A., Al Bitar, A., Cabot, F., Gruhier, C., Juglea, S., Leroux, D.,
Mialon, A., and Delwart, S.: The SMOS soil moisture retrieval algorithm, IEEE T. Geosci. Remote, 50, 1384–1403, https://doi.org/10.1109/TGRS.2012.2184548, 2012.
Kerr, Y. H., Waldteufel, P., Wigneron, J. P., Delwart, S., Cabot, F. O., Boutin, J., Escorihuela, M. J., Font, J., Reul, N., Gruhier, C., and Juglea,
S. E.: The SMOS mission: New tool for monitoring key elements of the global
water cycle, IEEE T. Geosci. Remote, 98, 666–687, https://doi.org/10.1109/JPROC.2010.2043032, 2010.
Kim, Y., Kimball, K., Zhang, K., and McDonald, K.: Satellite detection of
increasing northern hemisphere non-frozen seasons from 1979 to 2008:
implications for regional vegetation growth, Remote Sens. Environ., 121,
472–487, https://doi.org/10.1016/j.rse.2012.02.014, 2012.
Klingshirn, C. F.: Semiconductor Optics – Graduate Texts in Physics, in:
chap. Kramers–Kronig Relations, Springer, Berlin, Heidelberg, 849 pp.,
https://doi.org/10.1007/b138175, 2012.
Kraft, C.: Constitutive parameter measurements of fluids and soil between 500 kHz and 5 MHz using a transmission line technique, J. Geophys. Res.-Solid, 92, 10650–10656, https://doi.org/10.1029/JB092iB10p10650, 1987.
Lemmetyinen, J., Schwank, M., Rautiainen, K., Kontu, A., Parkkinen, T.,
Mätzler, C., Wiesmann, A., Wegmüller, U., Derksen, C., Toose, P.,
Roy, A., and Pulliainen, J.: Snow density and ground permittivity retrieved
from L-band radiometry: Application to experimental data, Remote Sens.
Environ., 180, 377–391, https://doi.org/10.1016/j.rse.2016.02.002, 2016.
Le Vine, D. M., Lagerloef, G. S., and Torrusio, S.: Aquarius and remote
sensing of sea surface salinity from space, Proc. IEEE, 98, 688–703,
https://doi.org/10.1109/JPROC.2010.2040550, 2010.
Mätzler, C.: Applications of the interaction of microwaves with the natural snow cover, Remote Sens. Rev., 2, 259–387, https://doi.org/10.1080/02757258709532086, 1987.
Mavrovic, A., Roy, A., Royer, A., Filali, B., Boone, F., Pappas, C., and
Sonnentag, O.: Dielectric characterization of vegetation at L band using an
open-ended coaxial probe, Geosci. Instrum. Method. Data Syst., 7, 195–208,
https://doi.org/10.5194/gi-7-195-2018, 2018.
Mavrovic, A., Madore, J.-B., Langlois, A., Royer, A., and Roy, A.: Snow liquid water content measurement using an open-ended coaxial probe (OECP),
Cold Reg. Sci. Technol., 171, 102958, https://doi.org/10.1016/j.coldregions.2019.102958, 2020.
Melton, J., Arora, V., Wisernig-Cojoc, E., Seiler, C., Fortier, M., Chan, E., and Teckentrup, L.: CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance, Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, 2020.
Mériaux, S.: Contribution à l'étude de l'analyse granulométrique, Thèses présentées à la faculté des
sciences de l'université de Paris, Série A, 590, Institut national de recherche agronomique, Paris, France, 117 pp., 1953.
Mériaux, S.: Contribution à l'étude de l'analyse granulométrique, Ann. Agron., 5(I) 5–53 and 5(II), 149–205, 1954.
Mialon, A., Richaume, P., Leroux, D., Bircher, S., Bitar, A., Pellarin, T.,
Wigneron, J.-P., and Kerr, Y.: Comparison of Dobson and Mironov Dielectric
Models in the SMOS Soil Moisture Retrieval Algorithm, IEEE T. Geosci. Remote, 53, 3084–3094, https://doi.org/10.1109/TGRS.2014.2368585, 2015.
Mironov, V., Kosolapova, L., and Fomin, S.: Physically and Mineralogically
Based Spectroscopic Dielectric Model for Moist Soils, IEEE T. Geosci. Remote, 47, 2059–2070, https://doi.org/10.1109/TGRS.2008.2011631, 2009.
Mironov, V., De Roo, R., and Savin, I.: Temperature-Dependable Microwave
Dielectric Model for an Arctic Soil, IEEE T. Geosci. Remote, 48, 585–589, https://doi.org/10.1109/TGRS.2010.2040034, 2010.
Mironov, V., Kosolapova, L., Lukina, Y., Karavayskya, A., and Molostovb, I.:
Temperature and texture-dependent dielectric model for frozen and thawed
mineral soils at a frequency of 1.4 GHz, Remote Sens. Environ., 200, 240–249, https://doi.org/10.1016/j.rse.2017.08.007, 2017.
Mo, T., Choudhury, B., Schmugge, T., Wang, J., and Jackson, T.: A model for
microwave emission from vegetation-covered fields, J. Geophys. Res., 87,
11229–11237, https://doi.org/10.1029/JC087iC13p11229, 1982.
Montpetit, B., Royer, A., Roy, A., and Langlois, A.: In-situ passive microwave emission model parameterization of sub-arctic frozen organic soils, Remote Sens. Environ., 205, 112–118, https://doi.org/10.1016/j.rse.2017.10.033, 2018.
Moradizadeh, M. and Saradjian, M.: The effect of roughness in simultaneously retrieval of land surface parameters, Phys. Chem. Earth Pt. A/B/C, 94, 127–135, https://doi.org/10.1016/j.pce.2016.03.006, 2016.
O'Kelly, B.: Accurate Determination of Moisture Content of Organic Soils
Using the Oven Drying Method, Dry. Technol., 22, 1767–1776,
https://doi.org/10.1081/DRT-200025642, 2004.
Pardo Lara, R., Berg, 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.
Pardo Lara, R., Berg, A., Warland, J., and Parkin, G.: Implications of
measurement metrics on soil freezing curves: A simulation of freeze-thaw
hysteresis, Hydrol. Process., https://doi.org/10.22541/au.160466100.02966301/v1, in
review, 2021.
Pavlov, N. and Baloshin, Y.: Electromagnetic properties of water on GHz frequencies for medicine tasks and metamaterial applications, J. Phys. Conf. Ser., 643, 012047, https://doi.org/10.1088/1742-6596/643/1/012047, 2015.
Prince, M., Roy, A., Royer, A., and Langlois, A.: Timing and spatial
variability of fall soil freezing in boreal forest and its effect on SMAP
L-band radiometer measurements, Remote Sens. Environ., 231, 111230,
https://doi.org/10.1016/j.rse.2019.111230, 2019.
Rautiainen, K., Lemmetyinen, J., Pulliainen, J., Vehviläinen, J., Drusch, M., Kontu, A., Kainulainen, J., and Seppanen, J.: L-Band Radiometer Observations of Soil Processes in Boreal and Subarctic Environments, IEEE T. Geosci. Remote, 50, 1483–1497, https://doi.org/10.1109/TGRS.2011.2167755, 2012.
Rautiainen, K., Parkkinen, T., Lemmetyinen, J., Schwank, M., Wiesmann, A.,
Ikonen, J., Derksen, C., Davydov, S., Davydova, A., Boike, J., and Langer, M.: SMOS prototype algorithm for detecting autumn soil freezing, Remote Sens. Environ., 180, 346–360, https://doi.org/10.1016/j.rse.2016.01.012, 2016.
Rodríguez-Fernández, N. J., Mialon, A., Mermoz, S., Bouvet, A.,
Richaume, P., Al Bitar, A., Al-Yaari, A., Brandt, M., Kaminski, T., Le Toan,
T., Kerr, Y. H., and Wigneron, J.-P.: An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets: high sensitivity of L-VOD to above-ground biomass in Africa, Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, 2018.
Rowlandson, T., Berg, A., Bullock, P., Ojo, E. R., McNairn, H., Wiseman, G.,
and Cosh, M.: Evaluation of several calibration procedures for a portable soil moisture sensor, J. Hydrol., 498, 335–344, https://doi.org/10.1016/j.jhydrol.2013.05.021, 2013.
Rowlandson, T., Berg, A., Roy, A., Kim, E., Pardo Lara, R., Powers, J., Lewis, K., Houser, P., McDonald, K., Toose, P., Wu, A., De Marco, E., Derksen, C., Entin, J., Colliander, A., Xu, X., and Mavrovic, A.: Capturing
agricultural soil freeze/thaw state through remote sensing and ground
observations: A soil freeze/thaw validation campaign, Remote Sens. Environ.,
211, 59–70, https://doi.org/10.1016/j.rse.2018.04.003, 2018.
Roy, A., Royer, A., Derksen, C., Brucker, L., Langlois, A., Mialon, A., and
Kerr, Y. H.: Evaluation of Spaceborne L-Band Radiometer Measurements for
Terrestrial Freeze/Thaw Retrievals in Canada, IEEE J. Sel. Top. Appl. Earth
Obs. Remote Sens., 8, 4442–4459, https://doi.org/10.1016/j.rse.2019.111542, 2015.
Roy, A., Toose, P., Williamson, M., Rowlandson, T., Derksen, C., Royer, A.,
Berg, A., Lemmetyinen, J., and Arnold, L.: Response of L-Band brightness
temperatures to freeze/thaw and snow dynamics in a prairie environment from
ground-based radiometer measurements, Remote Sens. Environ., 191, 67–80,
https://doi.org/10.1016/j.rse.2017.01.017, 2017a.
Roy, A., Toose, P., Derksen, C., Rowlandson, T., Berg, A., Lemmetyinen, J.,
Royer, A., Tetlock, E., Helgason, W., and Sonnentag, O.: Spatial Variability
of L-Band Brightness Temperature during Freeze/Thaw Events over a Prairie
Environment, Remote Sens., 9, 894, https://doi.org/10.3390/rs9090894, 2017b.
Roy, A., Leduc-Leballeur, M., Picard, G., Royer, A., Toose, P., Derksen, C.,
Lemmetyinen, J., Berg, A., Rowlandson, T., and Schwank, M.: Modelling the
L-band snow-covered surface emission in a winter Canadian prairie environment, Remote Sens., 10, 1451, https://doi.org/10.3390/rs10091451, 2018.
Roy, A. R., 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.,
273, 111542, https://doi.org/10.1016/j.rse.2019.111542, 2020.
Seyfried, M. and Murdock, M.: 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.
Seyfried, M., Grant, L., Du, E., and Humes, K.: Dielectric Loss and Calibration of the Hydra Probe Soil Water Sensor, Vadose Zone J., 4, 1070, https://doi.org/10.2136/vzj2004.0148, 2005.
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.
Ulaby, F., Sarabandi, K., McDonald, K., Whitt, M., and Dobson, M.: Michigan
microwave canopy scattering model, Int. J. Remote Sens., 11, 1223–1253,
https://doi.org/10.1080/01431169008955090, 1990.
Wigneron, J.-P., Jackson, T. J., O'Neill, P., Lannoy, D., de Rosnay, P., Walker, J. P., Ferrazzoli, P., Mironov, V., Bircher, S., Grant, J. P., Kurum, M., Schwank, M., Munoz-Sabater, J., Das, N., Royer, A., Al-Yaari, A., Al Bitar, A., Fernandez-Moran, R., Lawrence, H., Mialon, A., Parrens, M.,
Richaume, P., Delwart, S., and Kerr, Y.: Modelling the passive microwave
signature from land surfaces: a review of recent results and application to the L-band SMOS and SMAP soil moisture retrieval algorithms, Remote Sens.
Environ., 192, 238–262, https://doi.org/10.1016/j.rse.2017.01.024, 2017.
Williamson, M., Rowlandson, T., Berg, A., Roy, A., Toose, P., Derksen, C.,
Arnold, L., and Tetlock, E.: L-band radiometry freeze/thaw validation using
air temperature and ground measurements, Remote Sens., 9, 403–410,
https://doi.org/10.1080/2150704X.2017.1422872, 2018.
Zhang, L., Shi, J., Zhang, Z., and Zhao, K.: The estimation of dielectric
constant of frozen soil-water mixture at microwave bands, in: Proceedings
IEEE Cat. No. 03CH37477, IGARSS 2003, 2003 IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 2903–2905,
https://doi.org/10.1109/IGARSS.2003.1294626, 2003.
Zhang, L., Zhao, T., Jiang, L., and Zhao, S.: Estimate of phase transition
water content in freeze–thaw process using microwave radiometer, IEEE T. Geosci. Remote, 48, 4248–4255, https://doi.org/10.1109/TGRS.2010.2051158, 2010.
Zhao, T., Zhang, L., Jiang, L., Zhao, S., Chai, L., and Jin, R.: A new soil
freeze/thaw discriminant algorithm using AMSR-E passive microwave imagery,
Hydrol. Process., 25, 1704–1716, https://doi.org/10.1002/hyp.7930, 2011.
Zuerndorfer, B., England, A., Dobson, M., and Ulaby, F.: Mapping freeze/thaw
boundaries with SMMR data, Agr. Forest Meteorol., 52, 199–225,
https://doi.org/10.1016/0168-1923(90)90106-G, 1990.
Short summary
This paper presents a new probe that measures soil microwave permittivity in the frequency range of satellite L-band sensors. The probe capacities will allow for validation and calibration of the models used to estimate landscape physical properties from raw microwave satellite datasets. Our results show important discrepancies between model estimates and instrument measurements that will need to be addressed.
This paper presents a new probe that measures soil microwave permittivity in the frequency range...