Articles | Volume 15, issue 11
https://doi.org/10.5194/tc-15-5079-2021
© 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/tc-15-5079-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
04 Nov 2021
Review article |
| 04 Nov 2021
| 04 Nov 2021
Review article: Performance assessment of radiation-based field sensors for monitoring the water equivalent of snow cover (SWE)
Alain Royer
CORRESPONDING AUTHOR
Centre d'applications et de recherche en télédétection
(CARTEL), Université de Sherbrooke, Sherbrooke, Quebec, Canada
Centre d'études nordiques (CEN), Quebec, Canada
Alexandre Roy
Centre d'études nordiques (CEN), Quebec, Canada
Département des sciences de l'environnement, Université du
Québec à Trois-Rivières, Trois-Rivières, Quebec,
Canada
Sylvain Jutras
Département des sciences du bois et de la forêt,
Université Laval, Québec City, Quebec, Canada
Alexandre Langlois
Centre d'applications et de recherche en télédétection
(CARTEL), Université de Sherbrooke, Sherbrooke, Quebec, Canada
Centre d'études nordiques (CEN), Quebec, Canada
Related authors
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
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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.
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
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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
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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.
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Short summary
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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.
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
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Short summary
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Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Michael Prince, Alexandre Roy, Ludovic Brucker, Alain Royer, Youngwook Kim, and Tianjie Zhao
Earth Syst. Sci. Data, 10, 2055–2067, https://doi.org/10.5194/essd-10-2055-2018, https://doi.org/10.5194/essd-10-2055-2018, 2018
Short summary
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This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the EASE-Grid 2.0 with a resolution of 36 km. To evaluate the product, we compared it with the resampled 37 GHz FT Earth Science Data Record during the overlapping period between 2011 and 2014. The FT-AP ensures, with the SMAP mission that is still in operation, an L-band passive FT monitoring continuum with NASA’s space-borne radiometers, for a period beginning in August 2011.
Fanny Larue, Alain Royer, Danielle De Sève, Alexandre Roy, and Emmanuel Cosme
Hydrol. Earth Syst. Sci., 22, 5711–5734, https://doi.org/10.5194/hess-22-5711-2018, https://doi.org/10.5194/hess-22-5711-2018, 2018
Short summary
Short summary
A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by updating meteorological forcings and snowpack states using passive microwave satellite observations. A chain of models was first calibrated to simulate satellite observations over northeastern Canada. The assimilation was then validated over 12 stations where daily SWE measurements were acquired during 4 winters (2012–2016). The overall SWE bias is reduced by 68 % compared to original SWE simulations.
Alex Mavrovic, Alexandre Roy, Alain Royer, Bilal Filali, François Boone, Christoforos Pappas, and Oliver Sonnentag
Geosci. Instrum. Method. Data Syst., 7, 195–208, https://doi.org/10.5194/gi-7-195-2018, https://doi.org/10.5194/gi-7-195-2018, 2018
Short summary
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To improve microwave satellite and airborne observation products in forest environments, a precise and reliable estimation of the permittivity of trees is required. We developed a probe suitable to measure the permittivity of tree trunks at L band in the field. The system is easily transportable in the field, low energy consuming, operational at low temperatures and weatherproof. The permittivity of seven tree species in both frozen and thawed states was measured, showing important contrast.
Yann Blanchard, Alain Royer, Norman T. O'Neill, David D. Turner, and Edwin W. Eloranta
Atmos. Meas. Tech., 10, 2129–2147, https://doi.org/10.5194/amt-10-2129-2017, https://doi.org/10.5194/amt-10-2129-2017, 2017
Short summary
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Multiband thermal measurements of zenith sky radiance were used in a retrieval algorithm, to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. The retrieval technique was validated using a synergy lidar and radar data. Inversions were performed across three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of thin ice clouds.
Peter Toose, Alexandre Roy, Frederick Solheim, Chris Derksen, Tom Watts, Alain Royer, and Anne Walker
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Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers used for monitoring essential climate variables. A 385-channel hyperspectral L-band radiometer system was designed with the means to quantify the strength and type of RFI. The compact design makes it ideal for mounting on both surface and airborne platforms to be used for calibrating and validating measurement from spaceborne sensors.
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C. Papasodoro, E. Berthier, A. Royer, C. Zdanowicz, and A. Langlois
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Located at the far south (~62.5° N) of the Canadian Arctic, Grinnell and Terra Nivea Ice Caps are good climate proxies in this scarce data region. Multiple data sets (in situ, airborne and spaceborne) reveal changes in area, elevation and mass over the past 62 years. Ice wastage sharply accelerated during the last decade for both ice caps, as illustrated by the strongly negative mass balance of Terra Nivea over 2007-2014 (-1.77 ± 0.36 m a-1 w.e.). Possible climatic drivers are also discussed.
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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.
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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.
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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.
Francis Lessard, Naïm Perreault, and Sylvain Jutras
Hydrol. Earth Syst. Sci., 28, 1027–1040, https://doi.org/10.5194/hess-28-1027-2024, https://doi.org/10.5194/hess-28-1027-2024, 2024
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Headwaters streams, which are small streams at the top of a watershed, represent two-thirds of the total length of streams, yet their exact locations are still unknown. This article compares different techniques in order to remotely detect the position of these streams. Thus, a database of more than 464 km of headwaters was used to explain what drives their presence. A technique developed in this article makes it possible to detect headwater streams with more accuracy, despite the land uses.
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.
Maxime Beaudoin-Galaise and Sylvain Jutras
The Cryosphere, 16, 3199–3214, https://doi.org/10.5194/tc-16-3199-2022, https://doi.org/10.5194/tc-16-3199-2022, 2022
Short summary
Short summary
Our study presents an analysis of the uncertainty and measurement error of manual measurement methods of the snow water equivalent (SWE). Snow pit and snow sampler measurements were taken during five consecutive winters. Our results show that, although the snow pit is considered a SWE reference in the literature, it is a method with higher uncertainty and measurement error than large diameter samplers, considered according to our results as the most appropriate reference in a boreal biome.
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.
Alex Mavrovic, Renato Pardo Lara, Aaron Berg, François Demontoux, Alain Royer, and Alexandre Roy
Hydrol. Earth Syst. Sci., 25, 1117–1131, https://doi.org/10.5194/hess-25-1117-2021, https://doi.org/10.5194/hess-25-1117-2021, 2021
Short summary
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.
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.
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
The Cryosphere, 13, 3045–3059, https://doi.org/10.5194/tc-13-3045-2019, https://doi.org/10.5194/tc-13-3045-2019, 2019
Short summary
Short summary
Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Michael Prince, Alexandre Roy, Ludovic Brucker, Alain Royer, Youngwook Kim, and Tianjie Zhao
Earth Syst. Sci. Data, 10, 2055–2067, https://doi.org/10.5194/essd-10-2055-2018, https://doi.org/10.5194/essd-10-2055-2018, 2018
Short summary
Short summary
This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the EASE-Grid 2.0 with a resolution of 36 km. To evaluate the product, we compared it with the resampled 37 GHz FT Earth Science Data Record during the overlapping period between 2011 and 2014. The FT-AP ensures, with the SMAP mission that is still in operation, an L-band passive FT monitoring continuum with NASA’s space-borne radiometers, for a period beginning in August 2011.
Fanny Larue, Alain Royer, Danielle De Sève, Alexandre Roy, and Emmanuel Cosme
Hydrol. Earth Syst. Sci., 22, 5711–5734, https://doi.org/10.5194/hess-22-5711-2018, https://doi.org/10.5194/hess-22-5711-2018, 2018
Short summary
Short summary
A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by updating meteorological forcings and snowpack states using passive microwave satellite observations. A chain of models was first calibrated to simulate satellite observations over northeastern Canada. The assimilation was then validated over 12 stations where daily SWE measurements were acquired during 4 winters (2012–2016). The overall SWE bias is reduced by 68 % compared to original SWE simulations.
E. Guilbert, S. Jutras, and T. Badard
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 241–247, https://doi.org/10.5194/isprs-archives-XLII-4-241-2018, https://doi.org/10.5194/isprs-archives-XLII-4-241-2018, 2018
Alex Mavrovic, Alexandre Roy, Alain Royer, Bilal Filali, François Boone, Christoforos Pappas, and Oliver Sonnentag
Geosci. Instrum. Method. Data Syst., 7, 195–208, https://doi.org/10.5194/gi-7-195-2018, https://doi.org/10.5194/gi-7-195-2018, 2018
Short summary
Short summary
To improve microwave satellite and airborne observation products in forest environments, a precise and reliable estimation of the permittivity of trees is required. We developed a probe suitable to measure the permittivity of tree trunks at L band in the field. The system is easily transportable in the field, low energy consuming, operational at low temperatures and weatherproof. The permittivity of seven tree species in both frozen and thawed states was measured, showing important contrast.
Yann Blanchard, Alain Royer, Norman T. O'Neill, David D. Turner, and Edwin W. Eloranta
Atmos. Meas. Tech., 10, 2129–2147, https://doi.org/10.5194/amt-10-2129-2017, https://doi.org/10.5194/amt-10-2129-2017, 2017
Short summary
Short summary
Multiband thermal measurements of zenith sky radiance were used in a retrieval algorithm, to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. The retrieval technique was validated using a synergy lidar and radar data. Inversions were performed across three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of thin ice clouds.
Peter Toose, Alexandre Roy, Frederick Solheim, Chris Derksen, Tom Watts, Alain Royer, and Anne Walker
Geosci. Instrum. Method. Data Syst., 6, 39–51, https://doi.org/10.5194/gi-6-39-2017, https://doi.org/10.5194/gi-6-39-2017, 2017
Short summary
Short summary
Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers used for monitoring essential climate variables. A 385-channel hyperspectral L-band radiometer system was designed with the means to quantify the strength and type of RFI. The compact design makes it ideal for mounting on both surface and airborne platforms to be used for calibrating and validating measurement from spaceborne sensors.
Alexandre Roy, Alain Royer, Olivier St-Jean-Rondeau, Benoit Montpetit, Ghislain Picard, Alex Mavrovic, Nicolas Marchand, and Alexandre Langlois
The Cryosphere, 10, 623–638, https://doi.org/10.5194/tc-10-623-2016, https://doi.org/10.5194/tc-10-623-2016, 2016
C. Papasodoro, E. Berthier, A. Royer, C. Zdanowicz, and A. Langlois
The Cryosphere, 9, 1535–1550, https://doi.org/10.5194/tc-9-1535-2015, https://doi.org/10.5194/tc-9-1535-2015, 2015
Short summary
Short summary
Located at the far south (~62.5° N) of the Canadian Arctic, Grinnell and Terra Nivea Ice Caps are good climate proxies in this scarce data region. Multiple data sets (in situ, airborne and spaceborne) reveal changes in area, elevation and mass over the past 62 years. Ice wastage sharply accelerated during the last decade for both ice caps, as illustrated by the strongly negative mass balance of Terra Nivea over 2007-2014 (-1.77 ± 0.36 m a-1 w.e.). Possible climatic drivers are also discussed.
G. Picard, A. Royer, L. Arnaud, and M. Fily
The Cryosphere, 8, 1105–1119, https://doi.org/10.5194/tc-8-1105-2014, https://doi.org/10.5194/tc-8-1105-2014, 2014
G. Picard, L. Brucker, A. Roy, F. Dupont, M. Fily, A. Royer, and C. Harlow
Geosci. Model Dev., 6, 1061–1078, https://doi.org/10.5194/gmd-6-1061-2013, https://doi.org/10.5194/gmd-6-1061-2013, 2013
A. Roy, A. Royer, B. Montpetit, P. A. Bartlett, and A. Langlois
The Cryosphere, 7, 961–975, https://doi.org/10.5194/tc-7-961-2013, https://doi.org/10.5194/tc-7-961-2013, 2013
Related subject area
Discipline: Snow | Subject: Instrumentation
Measuring prairie snow water equivalent with combined UAV-borne gamma spectrometry and lidar
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Phillip Harder, Warren D. Helgason, and John W. Pomeroy
The Cryosphere, 18, 3277–3295, https://doi.org/10.5194/tc-18-3277-2024, https://doi.org/10.5194/tc-18-3277-2024, 2024
Short summary
Short summary
Remote sensing the amount of water in snow (SWE) at high spatial resolutions is an unresolved challenge. In this work, we tested a drone-mounted passive gamma spectrometer to quantify SWE. We found that the gamma observations could resolve the average and spatial variability of SWE down to 22.5 m resolutions. Further, by combining drone gamma SWE and lidar snow depth we could estimate SWE at sub-metre resolutions which is a new opportunity to improve the measurement of shallow snowpacks.
Frederieke Miesner, William Lambert Cable, Pier Paul Overduin, and Julia Boike
The Cryosphere, 18, 2603–2611, https://doi.org/10.5194/tc-18-2603-2024, https://doi.org/10.5194/tc-18-2603-2024, 2024
Short summary
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The temperature in the sediment below Arctic lakes determines the stability of the permafrost and microbial activity. However, measurements are scarce because of the remoteness. We present a robust and portable device to fill this gap. Test campaigns have demonstrated its utility in a range of environments during winter and summer. The measured temperatures show a great variability within and across locations. The data can be used to validate models and estimate potential emissions.
Giulia Blandini, Francesco Avanzi, Simone Gabellani, Denise Ponziani, Hervé Stevenin, Sara Ratto, Luca Ferraris, and Alberto Viglione
The Cryosphere, 17, 5317–5333, https://doi.org/10.5194/tc-17-5317-2023, https://doi.org/10.5194/tc-17-5317-2023, 2023
Short summary
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Automatic snow depth data are a valuable source of information for hydrologists, but they also tend to be noisy. To maximize the value of these measurements for real-world applications, we developed an automatic procedure to differentiate snow cover from grass or bare ground data, as well as to detect random errors. This procedure can enhance snow data quality, thus providing more reliable data for snow models.
Holly Proulx, Jennifer M. Jacobs, Elizabeth A. Burakowski, Eunsang Cho, Adam G. Hunsaker, Franklin B. Sullivan, Michael Palace, and Cameron Wagner
The Cryosphere, 17, 3435–3442, https://doi.org/10.5194/tc-17-3435-2023, https://doi.org/10.5194/tc-17-3435-2023, 2023
Short summary
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This study compares snow depth measurements from two manual instruments in a field and forest. Snow depths measured using a magnaprobe were typically 1 to 3 cm deeper than those measured using a snow tube. These differences were greater in the forest than in the field.
Mathieu Le Breton, Éric Larose, Laurent Baillet, Yves Lejeune, and Alec van Herwijnen
The Cryosphere, 17, 3137–3156, https://doi.org/10.5194/tc-17-3137-2023, https://doi.org/10.5194/tc-17-3137-2023, 2023
Short summary
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We monitor the amount of snow on the ground using passive radiofrequency identification (RFID) tags. These small and inexpensive tags are wirelessly read by a stationary reader placed above the snowpack. Variations in the radiofrequency phase delay accurately reflect variations in snow amount, known as snow water equivalent. Additionally, each tag is equipped with a sensor that monitors the snow temperature.
Alicia F. Pouw, Homa Kheyrollah Pour, and Alex MacLean
The Cryosphere, 17, 2367–2385, https://doi.org/10.5194/tc-17-2367-2023, https://doi.org/10.5194/tc-17-2367-2023, 2023
Short summary
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Collecting spatial lake snow depth data is essential for improving lake ice models. Lake ice growth is directly affected by snow on the lake. However, snow on lake ice is highly influenced by wind redistribution, making it important but challenging to measure accurately in a fast and efficient way. This study utilizes ground-penetrating radar on lakes in Canada's sub-arctic to capture spatial lake snow depth and shows success within 10 % error when compared to manual snow depth measurements.
Maxime Beaudoin-Galaise and Sylvain Jutras
The Cryosphere, 16, 3199–3214, https://doi.org/10.5194/tc-16-3199-2022, https://doi.org/10.5194/tc-16-3199-2022, 2022
Short summary
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Our study presents an analysis of the uncertainty and measurement error of manual measurement methods of the snow water equivalent (SWE). Snow pit and snow sampler measurements were taken during five consecutive winters. Our results show that, although the snow pit is considered a SWE reference in the literature, it is a method with higher uncertainty and measurement error than large diameter samplers, considered according to our results as the most appropriate reference in a boreal biome.
Rebecca Gugerli, Darin Desilets, and Nadine Salzmann
The Cryosphere, 16, 799–806, https://doi.org/10.5194/tc-16-799-2022, https://doi.org/10.5194/tc-16-799-2022, 2022
Short summary
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Monitoring the snow water equivalent (SWE) in high mountain regions is highly important and a challenge. We explore the use of muon counts to infer SWE temporally continuously. We deployed muonic cosmic ray snow gauges (µ-CRSG) on a Swiss glacier over the winter 2020/21. Evaluated with manual SWE measurements and SWE estimates inferred from neutron counts, we conclude that the µ-CRSG is a highly promising method for remote high mountain regions with several advantages over other current methods.
Achille Capelli, Franziska Koch, Patrick Henkel, Markus Lamm, Florian Appel, Christoph Marty, and Jürg Schweizer
The Cryosphere, 16, 505–531, https://doi.org/10.5194/tc-16-505-2022, https://doi.org/10.5194/tc-16-505-2022, 2022
Short summary
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Snow occurrence, snow amount, snow density and liquid water content (LWC) can vary considerably with climatic conditions and elevation. We show that low-cost Global Navigation Satellite System (GNSS) sensors as GPS can be used for reliably measuring the amount of water stored in the snowpack or snow water equivalent (SWE), snow depth and the LWC under a broad range of climatic conditions met at different elevations in the Swiss Alps.
Anton Jitnikovitch, Philip Marsh, Branden Walker, and Darin Desilets
The Cryosphere, 15, 5227–5239, https://doi.org/10.5194/tc-15-5227-2021, https://doi.org/10.5194/tc-15-5227-2021, 2021
Short summary
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Conventional methods used to measure snow have many limitations which hinder our ability to document annual cycles, test predictive models, or analyze the impact of climate change. A modern snow measurement method using in situ cosmic ray neutron sensors demonstrates the capability of continuously measuring spatially variable snowpacks with considerable accuracy. These sensors can provide important data for testing models, validating remote sensing, and water resource management applications.
Ghislain Picard, Marie Dumont, Maxim Lamare, François Tuzet, Fanny Larue, Roberta Pirazzini, and Laurent Arnaud
The Cryosphere, 14, 1497–1517, https://doi.org/10.5194/tc-14-1497-2020, https://doi.org/10.5194/tc-14-1497-2020, 2020
Short summary
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Surface albedo is an essential variable of snow-covered areas. The measurement of this variable over a tilted terrain with levelled sensors is affected by artefacts that need to be corrected. Here we develop a theory of spectral albedo measurement over slopes from which we derive four correction algorithms. The comparison to in situ measurements taken in the Alps shows the adequacy of the theory, and the application of the algorithms shows systematic improvements.
Rebecca Gugerli, Nadine Salzmann, Matthias Huss, and Darin Desilets
The Cryosphere, 13, 3413–3434, https://doi.org/10.5194/tc-13-3413-2019, https://doi.org/10.5194/tc-13-3413-2019, 2019
Short summary
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The snow water equivalent (SWE) in high mountain regions is crucial for many applications. Yet its quantification remains difficult. We present autonomous daily SWE observations by a cosmic ray sensor (CRS) deployed on a Swiss glacier for two winter seasons. Combined with snow depth observations, we derive the daily bulk snow density. The validation with manual field observations and its measurement reliability show that the CRS is a promising device for high alpine cryospheric environments.
Adam Schneider, Mark Flanner, Roger De Roo, and Alden Adolph
The Cryosphere, 13, 1753–1766, https://doi.org/10.5194/tc-13-1753-2019, https://doi.org/10.5194/tc-13-1753-2019, 2019
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To study the process of snow aging, we engineered a prototype instrument called the Near-Infrared Emitting and Reflectance-Monitoring Dome (NERD). Using the NERD, we observed rapid snow aging in experiments with added light absorbing particles (LAPs). Particulate matter deposited on the snow increased absorption of solar energy and enhanced snow melt. These results indicate the role of LAPs' indirect effect on snow aging through a positive feedback mechanism related to the snow grain size.
Ladina Steiner, Michael Meindl, Charles Fierz, and Alain Geiger
The Cryosphere, 12, 3161–3175, https://doi.org/10.5194/tc-12-3161-2018, https://doi.org/10.5194/tc-12-3161-2018, 2018
Short summary
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The amount of water stored in snow cover is of high importance for flood risks, climate change, and early-warning systems. We evaluate the potential of using GPS to estimate the stored water. We use GPS antennas buried underneath the snowpack and develop a model based on the path elongation of the GPS signals while propagating through the snowpack. The method works well over full seasons, including melt periods. Results correspond within 10 % to the state-of-the-art reference data.
Cited articles
Alonso, R., del Pozo, J. M. G., Buisaìn, S. T., and Aìlvarez, J. A:
Analysis of the Snow Water Equivalent at the AEMet-Formigal Field Laboratory
(Spanish Pyrenees) during the 2019/2020 winter season using a
Stepped-Frequency Continuous Wave Radar (SFCW), Remote Sens., 13, 616,
https://doi.org/10.3390/rs13040616, 2021.
Andreasen, M., Jensen, K. H., Desilets, D., Franz, T., Zreda, M., Bogena,
H., and Looms, M. C.: Status and perspectives of the cosmic-ray neutron
method for soil moisture estimation and other environmental science
applications, Vadose Zone J., 16, 1–11, https://doi.org/10.2136/vzj2017.04.0086, 2017.
Appel, F., Koch, F., Rösel, A., Klug, P., Henkel, P., Lamm, M., Mauser,
W., and Bach, H.: Advances in Snow Hydrology Using a Combined Approach of
GNSS In Situ Stations, Hydrological Modelling and Earth Observation – A Case
Study in Canada, Geosciences, 9, 44, https://doi.org/10.3390/geosciences9010044, 2019.
Berezovskaya, S. and Kane, D. L.: Strategies for measuring snow water
equivalent for hydrological applications: Part 1, accuracy of measurements.
Proceedings of 16th Northern Research Basin Symposium, Petrozavodsk, Russia,
22–35, 2007.
Bissell, V. C. and Peck, E. L.: Monitoring snow water equivalent by using
natural soil radioactivity, Water Resour. Res., 9, 885–890, 1973.
Bogena, H. R., Herrmann, F., Jakobi, J., Brogi, C., Ilias, A., Huisman, J. A.,
Panagopoulos, A., and Pisinaras, V.: Monitoring of Snowpack Dynamics with
Cosmic-Ray Neutron Probes: A Comparison of Four Conversion Methods, Front.
Water, 2, 19, https://doi.org/10.3389/frwa.2020.00019, 2020.
Bormann, K. J., Westra, S., Evans, J. P., and McCabe, M. F: Spatial and
temporal variability in seasonal snow density, J. Hydrol., 484, 63–73,
2013.
Brown, R. D., Fang, B., and Mudryk, L.: Update of Canadian Historical Snow
Survey Data and Analysis of Snow Water Equivalent Trends, 1967–2016,
Atmos.-Ocean, 57, 149–156, https://doi.org/10.1080/07055900.2019.1598843, 2019.
Brown, R. D., Smith, C., Derksen, C., and Mudryk, L.: Canadian In Situ Snow
Cover Trends for 1955–2017 Including an Assessment of the Impact of
Automation, Atmos.-Ocean, 59, 77–92, https://doi.org/10.1080/07055900.2021.1911781, 2021.
Carroll, T. R.: Airborne Gamma Radiation Snow Survey Program: A user's
guide, Version 5.0. National Operational Hydrologic Remote Sensing Center
(NOHRSC), Chanhassen, 14, available at: https://www.nohrsc.noaa.gov/snowsurvey/ (last access: 25 October 2021), 2001.
Choquette, Y., Ducharme, P., and Rogoza, J.: CS725, an accurate sensor for
the snow water equivalent and soil moisture measurements, in: Proceedings of
the International Snow Science Workshop, Grenoble, France, 7–11 October
2013, 2013.
Clark, M. P., Hendrikx, J., Slater, A. G., Kavetski, D., Anderson, B.,
Cullen, N. J., Kerr, T., Hreinsson, E. Ö., and Woods, R. A.:
Representing spatial variability of snow water equivalent in hydrologic and
land-surface models: A review, Water Resour. Res., 47, W07539,
https://doi.org/10.1029/2011WR010745, 2011.
Delunel, R., Bourles, D. L., van der Beek, P. A., Schlunegger, F., Leya, I.,
Masarik, J., and Paquet, E.: Snow shielding factors for cosmogenic nuclide
dating inferred from long-term neutron detector monitoring, Quat.
Geochronol., 24, 16–26, https://doi.org/10.1016/j.quageo.2014.07.003, 2014.
Desilets, D.: Calibrating a non-invasive cosmic ray soil moisture probe for
snow water equivalent, Hydroinnova Technical Document 17-01, Zenodo,
https://doi.org/10.5281/zenodo.439105, 2017.
Dixon, D. and Boon, S.: Comparison of the SnowHydro snow sampler with
existing snow tube designs, Hydrol. Process., 20, 2555–2562,
https://doi.org/10.1002/hyp.9317, 2012.
Desilets, D. and Zreda, M.: Footprint diameter for a cosmic-ray soil
moisture probe: Theory and Monte Carlo simulations, Water Resour. Res., 49,
3566–3575, 2013.
Desilets, D., Zreda, M., and Ferreì, T. P. A.: Nature's neutron probe:
Land surface hydrology at an elusive scale with cosmic rays, Water Resour.
Res., 46, 1–7, 2010.
Dong, C.: Remote sensing, hydrological modeling and in situ observations in
snow cover research: A review, J. Hydrol., 561, 573–583, 2018.
Ducharme, P., Houdayer, A., Choquette, Y., Kapfer, B., and Martin, J. P.:
Numerical Simulation of Terrestrial Radiation over A Snow Cover, J. Atmos.
Ocean. Tech., 32, 1478–1485, 2015.
Ellerbruch, D. and Boyne, H.: Snow Stratigraphy and Water Equivalence
Measured with an Active Microwave System, J. Glaciol., 26, 225–233, 1980.
Evans, J. G., Ward, H. C., Blake, J. R., Hewitt, E. J., Morrison, R., Fry,
M., Ball, L. A., Doughty, L. C., Libre, J. W., Hitt, O. E., Rylett, D.,
Ellis, R. J., Warwick, A. C., Brooks., M., Parkes, M. A., Wright, G. M. H.,
Singer, A. C., Boorman, D. B., and Jenkins, A.: Soil water content in
southern England derived from a cosmic-ray soil moisture observing system –
COSMOS-UK, Hydrol. Process., 30, 4987–4999, https://doi.org/10.1002/hyp.10929, 2016.
Fujino, K., Wakahama, G., Suzuki, M., Matsumoto, T., and Kuroiwa, D.: Snow
stratigraphy measured by an active microwave sensor, Ann. Glaciol., 6,
207–210, 1985.
GCOS-WMO: The global observing system for climate: implementation needs,
World Meteorological Organization, Geneva, Switzerland, available at:
https://public.wmo.int/en/programmes/global-climate-observing-system (last access: 25 October 2021), 2016.
Goodison, B., Ferguson, H., and McKay, G.: Measurement and data analysis, in
handbook of snow: principles, processes, management, and use, Pergamon press
Canada, Toronto, Canada, 191–274, 1981.
Goodison, B. E., Glynn, J. E., Harvey, K. D., and Slater, J. E.: Snow Surveying
in Canada: A Perspective, Can. Water Resour. J., 12, 27–42, https://doi.org/10.4296/cwrj1202027, 1987.
Gottardi, F., Carrier, P., Paquet, E., Laval, M.-T., Gailhard, J., and
Garçon, R.: Le NRC: Une décennie de mesures de l’équivalent, in: Proceedings
of the International Snow Science Workshop Grenoble, 7–11 October 2013,
926–930, 2013.
Gray, D. M., Granger, R. J., and Dyck, G. E.: Over winter soil moisture
changes, T. ASAE, 28, 442–447, 1985.
Gray, D. M., Toth, B., Zhao, L., Pomeroy, J. W., and Granger, R. J.:
Estimating areal snowmelt infiltration into frozen soils, Hydrol. Process.,
15, 3095–3111, 2001.
GPRI brochure: GAMMA Portable Radar Interferometer (GPRI), available at: https://gamma-rs.ch/uploads/media/Instruments_Info/gpri2_brochure_20160708.pdf, last access: 25 October 2021.
Gugerli, R., Salzmann, N., Huss, M., and Desilets, D.: Continuous and autonomous snow water equivalent measurements by a cosmic ray sensor on an alpine glacier, The Cryosphere, 13, 3413–3434, https://doi.org/10.5194/tc-13-3413-2019, 2019.
Gunn, G. E., Duguay, C. R., Brown, L. C., King, J., Atwood, D., and Kasurak,
A.: Freshwater Lake Ice Thickness Derived Using Surface-based X- and Ku-band
FMCW Scatterometers, Cold Reg. Sci. Technol., 120, 115–126, 2015.
Haberkorn, A. (Eds.): European Snow Booklet – an Inventory of Snow
Measurements in Europe, 363 pp., 2019.
Henkel, P., Koch, F., Appel, F., Bach, H., Prasch, M., Schmid, L.,
Schweizer, J., and Mauser, W.: Snow water equivalent of dry snow derived
from GNSS Carrier Phases. IEEE T. Geosci. Remote, 56,
3561–3572, https://doi.org/10.1109/TGRS.2018.2802494, 2018.
Hu, X., Ma, C., Hu, R., and Yeo, T. S.: Imaging for Small UAV-Borne FMCW
SAR. Sensors, 19, 87, https://doi.org/10.3390/s19010087, 2019.
IMST: IMST sentireTM Radar Module 24 GHz sR-1200 Series User Manual.
available at: http://www.radar-sensor.com/, last access: 25 October 2021.
Jitnikovitch, A., Marsh, P., Walker, B., and Desilets, D.: Cosmic-ray neutron method for the continuous measurement of Arctic snow accumulation and melt, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-124, in review, 2021.
Key, J., Goodison, B., Schöner, W., Godøy, Ø., Ondráš, M., and
Snorrason, Á.: A Global Cryosphere Watch. Arctic, 68, 1, 48–58,
https://doi.org/10.14430/arctic4476, 2015.
Key, J., Schöner, W., Fierz, C., Citterio, M., and Ondráš, M.:
Global Cryosphere Watch (GCW) implementation plan, World Meteorological
Organization, Geneva, Switzerland, available at: https://globalcryospherewatch.org/reference/documents/files/GCW_IP_v1.7.pdf (last access: 25 October 2021), 2016.
Kinar, N. J. and Pomeroy, J. W.: Measurement of the physical properties of
the snowpack, Rev. Geophys., 53, 481–544, https://doi.org/10.1002/2015RG000481, 2015.
King, J., Kelly, R., Kasurak, A., Duguay, C., Gunn, G., Rutter, N., Watts,
T., and Derksen, C.: Spatio-temporal influence of tundra snow properties on
Ku-band (17.2 GHz) backscatter, J. Glaciol., 61, 267–279, https://doi.org/10.3189/2015JoG14J020, 2015.
Kirkham, J. D., Koch, I., Saloranta, T. M., Litt, M., Stigter, E. E., Møen,
K., Thapa, A., Melvold, K., and Immerzeel, W. W.: Near Real-Time Measurement
of Snow Water Equivalent in the Nepal Himalayas, Front. Earth Sci., 7, 177,
https://doi.org/10.3389/feart.2019.00177, 2019.
Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M.,
Schweizer, J., and Mauser, W.: Retrieval of snow
water equivalent, liquid water content, and snow height of dry and wet snow
by combining GPS signal attenuation and time delay, Water Resour. Res., 55,
4465–4487, https://doi.org/10.1029/2018WR024431, 2019.
Koh, G., Yankielun, N. E., and Baptista, A. I.: Snow cover characterization
using multiband FMCW radars, Hydrol. Process., 10, 1609–1617, 1996.
Laliberté, J., Langlois, A., Royer, A., Madore, J.-B., and Gauthier, F.:
Retrieving high contrasted interfaces in dry snow using a frequency
modulated continuous wave (FMCW) Ka-band radar: a context for dry snow
stability, Phys. Geogr., in press, 2021.
Langlois, A.: Applications of the PR Series Radiometers for Cryospheric and
Soil Moisture Research, Radiometrics Corporation, available at: https://www.researchgate.net/publication/299372180_Applications_ of_the_PR_Series_Radiometers_for_Cryospheric_ and_Soil_Moisture_Research (last access: 25 October 2021), 2015.
Langlois, A., Royer, A., and Goïta, K.: Analysis of
simulated and spaceborne passive microwave brightness temperature using in
situ measurements of snow and vegetation properties, Can. J. Remote Sens.,
36, 135–148, https://doi.org/10.5589/m10-016, 2010.
Larson, K., Gutmann, E., Zavorotny, V., Braun, J., Williams, M., and
Nievinski, F.: Can we measure snow depth with GPS receivers? Geophys. Res.
Lett., 36, L17502, https://doi.org/10.1029/2009GL039430, 2009.
Larson, K. M.: GPS interferometric reflectometry: Applications to surface
soil moisture, snow depth, and vegetation water content in the western
United States, Wiley Interdisciplinary Reviews: Water, 3, 775–787,
https://doi.org/10.1002/wat2.1167, 2016.
Larson, K. M. and Small, E. E.: Normalized microwave reflection index: A
vegetation measurement derived from GPS networks, IEEE J. Sel. Top. Appl., 7, 1501–1511, https://doi.org/10.1109/JSTARS.2014.2300116, 2014.
Larue, F., Royer, A., De Sève, D., Roy, A., Picard, G., and Vionnet, V.:
Simulation and assimilation of passive microwave data using a snowpack model
coupled to a calibrated radiative transfer model over North-Eastern Canada,
Water Resour. Res., 54, 4823–4848, https://doi.org/10.1029/2017WR022132,
2018.
Leinss, S., Wiesmann, A., Lemmetyinen, J., and Hajnsek, I.: Snow Water
Equivalent of Dry Snow Measured by Differential Interferometry, IEEE J. Sel.
Top. Appl., 8, 3773–379, 2015.
Lejeune, Y., Dumont, M., Panel, J.-M., Lafaysse, M., Lapalus, P., Le Gac, E., Lesaffre, B., and Morin, S.: 57 years (1960–2017) of snow and meteorological observations from a mid-altitude mountain site (Col de Porte, France, 1325 m of altitude), Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, 2019.
López-Moreno, J. I., Leppänen, L., Luks, B., Holko, L., Picard, G.,
Sanmiguel-Vallelado, A., Alonso-González, E., Finger, D.C., Arslan,
A. N., Gillemot, K., Sensoy, A., Sorman, A., Ertaş, M. C., Fassnacht,
S. R., Fierz, C., and Marty, C.: Intercomparison of measurements of bulk
snow density and water equivalent of snow cover with snow core samplers:
Instrumental bias and variability induced by observers, Hydrol.
Process., 34, 3120-3133, https://doi.org/10.1002/hyp.13785, 2020.
Marshall, H.-P. and Koh, G.: FMCW radars for snow research, Cold Reg. Sci.
Technol., 52, 118–131, 2008.
Marshall, H.-P., Koh, G., and Forster, R.: Estimating alpine snowpack
properties using FMCW radar, Ann. Glaciol., 40, 157–162, 2005.
Marshall, H.-P., Schneebeli, M., and Koh, G.: Snow stratigraphy measurements
with high-frequency FMCW radar: Comparison with snow micro-penetrometer,
Cold Reg. Sci. Technol., 47, 108–117, 2007.
Martin, J.-P., Houdayer, A., Lebel, C., Choquette, Y., Lavigne, P., and
Ducharme, P.: An unattended gamma monitor for the determination of snow
water equivalent (SWE) using the natural ground gamma radiation. 2008 IEEE
Nuclear Science Symposium and Medical Conference, edited by: Sellin, P., IEEE, 983–988, 2008.
Matzler, C.: Microwave permittivity of dry snow, IEEE T. Geosci. Remote
Sens., 34, 573–581, https://doi.org/10.1109/36.485133, 1996.
Meloche, J., Langlois, A., Rutter, N., Royer, A., King, J., and Walker, B.: Characterizing Tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-156, in review, 2021.
Meredith, M., Sommerkorn, M., Cassotta, S., Derksen, C., Ekaykin, A.,
Hollowed, A., Kofinas, G., Mackintosh, A., Melbourne-Thomas, J., Muelbert,
M. M. C., Ottersen, G., Pritchard, H., and Schuur, E. A. G.: Polar Regions, in: IPCC
Special Report on the Ocean and Cryosphere in a Changing Climate, edited by:
Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V., Zhai, P.,
Tignor, M., Poloczanska, E., Mintenbeck, K., Alegriìa, A., Nicolai, M.,
Okem, A., Petzold, J., Rama, B., and Weyer, N. M., available at: https://www.ipcc.ch/srocc/chapter/chapter-3-2/ (last access: 25 October 2021), 2019.
Murray, R. M. and Holbert, K. E.: Nuclear Energy: An Introduction to the
Concepts, Systems, and Applications of Nuclear Processes, Eighth Edition,
Imprint Butterworth-Heinemann, Elsevier Inc., 624 pp., https://doi.org/10.1016/C2016-0-04041-X, 2020.
Okorn, R., Brunnhofer, G., Platzer, T., Heilig, A., Schmid, L., Mitterer,
C., Schweizer, J., and Eisen, O.: Upward-looking L-band FMCW radar for snow
cover monitoring, Cold Reg. Sci. Technol., 103, 31–40, 2014.
Paquet, E. and Laval, M. T.: Retour d'expeìrience et perspectives
d'exploitation des NivomeÌtres aÌ Rayonnement Cosmique d'EDF/Operation feedback and prospects of EDF Cosmic-Ray Snow Sensors, Houille
Blanche, 2, 113–119, 2006.
Paquet, E., Laval, M., Basalaev, L. M., Belov, A., Eroshenko, E., Kartyshov,
V., Struminsky, A., and Yanke, V.: An application of cosmic-ray neutron
measurements to the determination of the snow-water equivalent, Proc. 30th
Int. Cosm. Ray Conf., Mexico City, Mexico, 2008, 1, 761–764, 2008.
Peng, Z. and Li, C.: Portable Microwave Radar Systems for Short-Range
Localization and Life Tracking: A Review, Sensors, 19, 1136, https://doi.org/10.3390/s19051136, 2019.
Peterson, N. and Brown, J.: Accuracy of snow measurements, in: Proceedings
of the 43rd Annual Meeting of the Western Snow Conference, Coronado,
California, 1–5, 1975.
Pieraccini, M. and Miccinesi, L.: Ground-Based Radar Interferometry: A
Bibliographic Review, Remote Sens., 11, 1029,
https://doi.org/10.3390/rs11091029, 2019.
Pirazzini, R., Leppänen, L., Picard, G., López-Moreno, J. I., Marty,
C., Macelloni, G., Kontu, A., von Lerber, A., Tanis, C. M., Schneebeli, M.,
de Rosnay, P., and Arslan, A. N.: European in-situ snow measurements:
practices and purposes, Sensors, 8, 2016, https://doi.org/10.3390/s18072016, 2018.
Pomerleau, P., Royer, A., Langlois, A., Cliche, P., Courtemanche, B.,
Madore, J.B., Picard, G., and Lefebvre, É.: Low Cost and Compact FMCW 24 GHz Radar Applications for Snowpack and Ice Thickness
Measurements, Sensors, 20, 3909, https://doi.org/10.3390/s20143909,
2020.
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.
Proksch, M., Rutter, N., Fierz, C., and Schneebeli, M.: Intercomparison of snow density measurements: bias, precision, and vertical resolution, The Cryosphere, 10, 371–384, https://doi.org/10.5194/tc-10-371-2016, 2016.
Rasmussen, R., Baker, B., Kochendorfer, J., Meyers, T., Landolt, S.,
Fischer, A. P., Black, J., Theìriault, J. M., Kucera, P., Gochis, D.,
Smith, C., Nitu, R., Hall, M., Ikeda, K., and Gutmann, E.: How Well Are We
Measuring Snow: The NOAA/FAA/NCAR Winter Precipitation Test Bed, B. Am.
Meteorol. Soc., 93, 811–829, 2012.
Rodriguez-Morales, F., Gogineni, S., Leuschen, C. J., Paden, J. D., Li, J.,
Lewis, C. C., Panzer, B., Alvestegui, D. G.-G., Patel, A., Byers, K.,
Crowe, R., Player, K., Hale, R., Arnold, E., Smith, L., Gifford, C.,
Braaten, D., and Panton, C.: Advanced multifrequency radar instrumentation
for polar research, IEEE T. Geosci. Remote, 52, 2824–2842, 2014.
Roy, A., Royer, A., St-Jean-Rondeau, O., Montpetit, B., Picard, G., Mavrovic, A., Marchand, N., and Langlois, A.: Microwave snow emission modeling uncertainties in boreal and subarctic environments, The Cryosphere, 10, 623–638, https://doi.org/10.5194/tc-10-623-2016, 2016.
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,
2017.
Royer, A., Domine, F., Roy, A., Langlois, A., Marchand, N., and Davesne G.: New northern snowpack classification linked to vegetation cover on a latitudinal mega-transect across northeastern Canada, Écoscience, https://doi.org/10.1080/11956860.2021.1898775, 2021.
Rutter, N., Sandells, M., Derksen, C., Toose, P., Royer, A., Montpetit, B.,
Lemmetyinen, J., and Pulliainen, J.: Snow stratigraphic heterogeneity within
ground-based passive microwave radiometer footprints: implications for
emission modeling, J. Geophys. Res.-Earth, 199, 550–565,
https://doi.org/10.1002/2013JF003017, 2014.
Rutter, N., Sandells, M. J., Derksen, C., King, J., Toose, P., Wake, L., Watts, T., Essery, R., Roy, A., Royer, A., Marsh, P., Larsen, C., and Sturm, M.: Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals, The Cryosphere, 13, 3045–3059, https://doi.org/10.5194/tc-13-3045-2019, 2019.
Schattan, P., Baroni, G., Oswald, S. E., Schöber, J., Fey, C., Kormann,
C., Huttenlau, M., and Achleitner, S.: Continuous monitoring of snowpack
dynamics in alpine terrain by aboveground neutron sensing, Water Resour.
Res., 53, 3615–3634, https://doi.org/10.1002/2016WR020234, 2017.
Schneider, M.: Automotive radar – Status and trends, in: Proceedings of the
German Microwave Conference, Ulm, Germany, 5–7 April 2005, 144–147,
2005.
Shah, R., Xiaolan Xu, Yueh, S., Sik Chae, C., Elder, K., Starr, B., and Kim,
Y.: Remote Sensing of Snow Water Equivalent Using P-Band Coherent
Reflection, IEEE Geosci. Remote S., 14, 309–313, https://doi.org/10.1109/LGRS.2016. 2636664, 2017.
Sigouin, M. J. P. and Si, B. C.: Calibration of a non-invasive cosmic-ray probe for wide area snow water equivalent measurement, The Cryosphere, 10, 1181–1190, https://doi.org/10.5194/tc-10-1181-2016, 2016.
Smith, C. D., Kontu, A., Laffin, R., and Pomeroy, J. W.: An assessment of two automated snow water equivalent instruments during the WMO Solid Precipitation Intercomparison Experiment, The Cryosphere, 11, 101–116, https://doi.org/10.5194/tc-11-101-2017, 2017.
Steiner, L., Meindl, M., Fierz, C., and Geiger, A.: An assessment of sub-snow GPS for quantification of snow water equivalent, The Cryosphere, 12, 3161–3175, https://doi.org/10.5194/tc-12-3161-2018, 2018.
Steiner, L., Meindl, M., and Geiger, A.: Characteristics and limitations of
GPS L1 observations from submerged antennas, J. Geodesy, 93, 267–280,
https://doi.org/10.1007/s00190-018-1147-x, 2019.
Stranden, H. B., Ree, B. L., and Møen, K. M.: Recommendations for
Automatic Measurements of Snow Water Equivalent in NVE. Report of the
Norwegian Water Resources and Energy Directorate, Majorstua, Oslo, Noway, 34 pp., 2015.
Stuefer, S., Kane, L. D., and Liston, G. E.: In situ snow water equivalent
observations in the US Arctic, Hydrol. Res., 44, 21–34,
https://doi.org/10.2166/nh.2012.177, 2013.
Sturm, M., Taras, B., Liston, G., Derksen, C., Jones, T., and Lea, J.:
Estimating snow water equivalent using snow depth data and climate classes,
J. Hydrometeorol., 11, 1380–1394, 2010.
Tiuri, M., Sihvola, A., Nyfors, E., and Hallikainen, M.: The complex
dielectric constant of snow at microwave frequencies, IEEE J. Oceanic Eng.,
9, 377–382, 1984.
Turcan, J. and Loijens, J.: Accuracy of snow survey data and errors in snow
sampler measurements, Proc. 32nd East. Snow. Conf., 2–11, 1975.
Vather, T., Everson, C. S., and Franz, T. E.: The applicability of the
cosmic ray neutron sensor to simultaneously monitor soil water content and
biomass in an Acacia mearnsii Forest, Hydrology, 7, 48,
https://doi.org/10.3390/hydrology7030048, 2020.
Vriend, N. M., McElwaine, J. N., Sovilla, B., Keylock, C. J., Ash, M., and
Brennan, P. V.: High-resolution radar measurements of snow avalanches,
Geophys. Res. Lett., 40, 727–731, 2013.
Wallbank, J. R., Cole, S. J., Moore, R. J., Anderson, S. R., and Mellor, E. J.:
Estimating snow water equivalent using cosmic-ray neutron sensors from the
COSMOS-UK network, Hydrol. Process., 35, e14048.
https://doi.org/10.1002/hyp.14048, 2021.
Werner, C., Wiesmann, A., Strozzi, T., Schneebeli, M., and
Mätzler, C.: The SnowScat ground-based polarimetric
scatterometer: Calibration and initial measurements from Davos Switzerland,
in: Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS'10), Jul. 2010,
2363–2366, 2010.
Werner, C., Suess, M., Wegmüller, U., Frey, O., and Wiesmann A.: The Esa
Wideband Microwave Scatterometer (Wbscat): Design and Implementation, in:
Proc. IGARSS 2019 – IEEE International Geoscience and Remote Sensing
Symposium, 8339–8342, https://doi.org/10.1109/IGARSS.2019.8900459, 2019.
Wiesmann, A., Werner, C., Strozzi, T., Matzler, C., Nagler, T., Rott, H.,
Schneebeli, M., and Wegmüller, U.: SnowScat, X- to
Ku-Band Scatterometer Development, in Proc. of ESA Living Planet Symposium,
Bergen 28.6.–2.7., available at: https://gamma-rs.ch/uploads/media/Instruments_Info/gamma_snowscat.pdf (last access: 25 October 2021), 2010.
Wiesmann, A., Werner, C., Wegmüller, U., Schwank, M., and Matzler, C.:
ELBARA II, L-band Radiometer for SMOS Cal/Val Purposes, available at:
https://gamma-rs.ch/uploads/media/Instruments_Info/ELBARAII_poster.pdf, last access: 25 October 2021.
Wigneron, J. P., Jackson, T. J., O'Neill, P., De Lannoy, G. J., 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., 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
& SMAP soil moisture retrieval algorithms, Remote Sens. Environ., 192,
238–262, 2017.
Work, R. A., Stockwell, H. J., Freeman, T. G., and Beaumont, R. T.: Accuracy
of field snow surveys, western United States, including Alaska, Cold Regions
Research and Engineering Laboratory (U.S.) Technical report, 163, 49 pp.,
available at: https://hdl.handle.net/11681/5580 (last access: 25 October 2021), 1965.
Wright, M., Kavanaugh, K., and Labine, C.: Performance Analysis of the GMON3
Snow Water Equivalency Sensor. Proceedings of The Western Snow Conference.
Stateline, NV, USA, April 2011, Poster on line, available at: https://s.campbellsci.com/documents/us/miscellaneous/performance-analysis-cs725.pdf (last access: 25 October 2021), 2011.
Wright, M.: CS725 Frozen Potential: The Ability to Predict Snow Water
Equivalent is Essential. METEOROLOGICAL TEChnOLOGy InTERnATIOnAL, August
2013, 122–123, available at: https://www.meteorologicaltechnologyinternational.com (last access: 25 October 2021), 2013.
Xu, X., Baldi, C., Bleser, J.-W., Lei, Y., Yueh, S., and Esteban-Fernandez,
D.: Multi-Frequency Tomography Radar Observations of Snow Stratigraphy at
Fraser During SnowEx, in Proceedings of the IGARSS 2018-2018 IEEE
International Geoscience and Remote Sensing Symposium, Valencia, Spain,
22–27 July 2018, 2018.
Yankielun, N., Rosenthal, W., and Robert, D.: Alpine snow depth measurements
from aerial FMCW radar, Cold Reg. Sci. Technol., 40, 123–134, 2004.
Yankielun, N. E., Ferrick, M. G., and Weyrick, P. B.: Development of an
airborne millimeter-wave FM-CW radar for mapping river ice, Can. J. Civil.
Eng., 20, 1057–1064, 1993.
Yao, H., Field, T., McConnell, C., Beaton, A., and James, A.L.: Comparison of
five snow water equivalent estimation methods across categories, Hydrol.
Process., 32, 1894–1908, https://doi.org/10.1002/hyp.13129, 2018.
Zreda, M., Desilets, D., Ferré, T. P., and Scott, R. L.: Measuring soil moisture content non‐invasively at intermediate spatial scale using cosmic‐ray neutrons, Geophys. Res. Lett., 35, L21402, https://doi.org/10.1029/2008GL035655, 2008.
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.
Dense spatially distributed networks of autonomous instruments for continuously measuring the...
