Articles | Volume 15, issue 11
https://doi.org/10.5194/tc-15-5227-2021
© 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-15-5227-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2021
Research article |
| 25 Nov 2021
| 25 Nov 2021
Snow water equivalent measurement in the Arctic based on cosmic ray neutron attenuation
Anton Jitnikovitch
CORRESPONDING AUTHOR
Cold Regions Research Centre, Wilfrid Laurier University, 75 University Avenue, Waterloo, ON, N2L 3C5, Canada
Philip Marsh
Cold Regions Research Centre, Wilfrid Laurier University, 75 University Avenue, Waterloo, ON, N2L 3C5, Canada
Branden Walker
Cold Regions Research Centre, Wilfrid Laurier University, 75 University Avenue, Waterloo, ON, N2L 3C5, Canada
Darin Desilets
Hydroinnova LLC, 1401 Morningside Drive NE, Albuquerque, NM, 87110, USA
Related authors
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Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Julien Meloche, Benoit Montpetit, Nicolas R. Leroux, Richard Essery, Gabriel Hould Gosselin, and Philip Marsh
EGUsphere, https://doi.org/10.5194/egusphere-2025-1498, https://doi.org/10.5194/egusphere-2025-1498, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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The impact of uncertainties in the simulation of snow density and SSA by the snow model Crocus (embedded within the Soil, Vegetation and Snow version 2 land surface model) on the simulation of snow backscatter (13.5 GHz) using the Snow Microwave Radiative Transfer model were quantified. The simulation of SSA was found to be a key model uncertainty. Underestimated SSA values lead to high errors in the simulation of snow backscatter, reduced by implementing a minimum SSA value (8.7 m2 kg-1).
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024, https://doi.org/10.5194/tc-18-5685-2024, 2024
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Parameterisations of Arctic snow processes were implemented into the multi-physics ensemble version of the snow model Crocus (embedded within the Soil, Vegetation, and Snow version 2 land surface model) and evaluated at an Arctic tundra site. Optimal combinations of parameterisations that improved the simulation of density and specific surface area featured modifications that raise wind speeds to increase compaction in surface layers, prevent snowdrift, and increase viscosity in basal layers.
Charles E. Miller, Peter C. Griffith, Elizabeth Hoy, Naiara S. Pinto, Yunling Lou, Scott Hensley, Bruce D. Chapman, Jennifer Baltzer, Kazem Bakian-Dogaheh, W. Robert Bolton, Laura Bourgeau-Chavez, Richard H. Chen, Byung-Hun Choe, Leah K. Clayton, Thomas A. Douglas, Nancy French, Jean E. Holloway, Gang Hong, Lingcao Huang, Go Iwahana, Liza Jenkins, John S. Kimball, Tatiana Loboda, Michelle Mack, Philip Marsh, Roger J. Michaelides, Mahta Moghaddam, Andrew Parsekian, Kevin Schaefer, Paul R. Siqueira, Debjani Singh, Alireza Tabatabaeenejad, Merritt Turetsky, Ridha Touzi, Elizabeth Wig, Cathy J. Wilson, Paul Wilson, Stan D. Wullschleger, Yonghong Yi, Howard A. Zebker, Yu Zhang, Yuhuan Zhao, and Scott J. Goetz
Earth Syst. Sci. Data, 16, 2605–2624, https://doi.org/10.5194/essd-16-2605-2024, https://doi.org/10.5194/essd-16-2605-2024, 2024
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NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne synthetic aperture radar (SAR) surveys of over 120 000 km2 in Alaska and northwestern Canada during 2017, 2018, 2019, and 2022. This paper summarizes those results and provides links to details on ~ 80 individual flight lines. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band SAR data.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Evan J. Wilcox, Brent B. Wolfe, and Philip Marsh
Hydrol. Earth Syst. Sci., 27, 2173–2188, https://doi.org/10.5194/hess-27-2173-2023, https://doi.org/10.5194/hess-27-2173-2023, 2023
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The Arctic is warming quickly and influencing lake water balances. We used water isotope concentrations taken from samples of 25 lakes in the Canadian Arctic and estimated the average ratio of evaporation to inflow (E / I) for each lake. The ratio of watershed area (the area that flows into the lake) to lake area (WA / LA) strongly predicted E / I, as lakes with relatively smaller watersheds received less inflow. The WA / LA could be used to predict the vulnerability of Arctic lakes to future change.
Evan J. Wilcox, Brent B. Wolfe, and Philip Marsh
Hydrol. Earth Syst. Sci., 26, 6185–6205, https://doi.org/10.5194/hess-26-6185-2022, https://doi.org/10.5194/hess-26-6185-2022, 2022
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We estimated how much of the water flowing into lakes during snowmelt replaced the pre-snowmelt lake water. Our data show that, as lake depth increases, the amount of water mixed into lakes decreased, because vertical mixing is reduced as lake depth increases. Our data also show that the water mixing into lakes is not solely snow-sourced but is a mixture of snowmelt and soil water. These results are relevant for lake biogeochemistry given the unique properties of snowmelt runoff.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, and Julia Boike
The Cryosphere, 16, 4201–4222, https://doi.org/10.5194/tc-16-4201-2022, https://doi.org/10.5194/tc-16-4201-2022, 2022
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Measurements of the properties of the snow and soil were compared to simulations of the Community Land Model to see how well the model represents snow insulation. Simulations underestimated snow thermal conductivity and wintertime soil temperatures. We test two approaches to reduce the transfer of heat through the snowpack and bring simulated soil temperatures closer to measurements, with an alternative parameterisation of snow thermal conductivity being more appropriate.
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
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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.
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, and Evan J. Wilcox
The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, https://doi.org/10.5194/tc-16-87-2022, 2022
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To estimate snow water equivalent from space, model predictions of the satellite measurement (brightness temperature in our case) have to be used. These models allow us to estimate snow properties from the brightness temperature by inverting the model. To improve SWE estimate, we proposed incorporating the variability of snow in these model as it has not been taken into account yet. A new parameter (coefficient of variation) is proposed because it improved simulation of brightness temperature.
Daniel Power, Miguel Angel Rico-Ramirez, Sharon Desilets, Darin Desilets, and Rafael Rosolem
Geosci. Model Dev., 14, 7287–7307, https://doi.org/10.5194/gmd-14-7287-2021, https://doi.org/10.5194/gmd-14-7287-2021, 2021
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Cosmic-ray neutron sensors estimate root-zone soil moisture at sub-kilometre scales. There are national-scale networks of these sensors across the globe; however, methods for converting neutron signals to soil moisture values are inconsistent. This paper describes our open-source Python tool that processes raw sensor data into soil moisture estimates. The aim is to allow a user to ensure they have a harmonized data set, along with informative metadata, to facilitate both research and teaching.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
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This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Inge Grünberg, Evan J. Wilcox, Simon Zwieback, Philip Marsh, and Julia Boike
Biogeosciences, 17, 4261–4279, https://doi.org/10.5194/bg-17-4261-2020, https://doi.org/10.5194/bg-17-4261-2020, 2020
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Based on topsoil temperature data for different vegetation types at a low Arctic tundra site, we found large small-scale variability. Winter temperatures were strongly influenced by vegetation through its effects on snow. Summer temperatures were similar below most vegetation types and not consistently related to late summer permafrost thaw depth. Given that vegetation type defines the relationship between winter and summer soil temperature and thaw depth, it controls permafrost vulnerability.
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
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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.
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
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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.
Ian M. Howat, Santiago de la Peña, Darin Desilets, and Gary Womack
The Cryosphere, 12, 2099–2108, https://doi.org/10.5194/tc-12-2099-2018, https://doi.org/10.5194/tc-12-2099-2018, 2018
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In this paper we present the first application of cosmic ray neutron sensing for continuously measuring in situ accumulation on an ice sheet. We validate these results with manual snow coring and snow stake measurements, showing that the cosmic ray observations are of similar if not better accuracy. We also present our observations of variability in accumulation over 24 months at Summit Camp, Greenland. We conclude that cosmic ray sensing has a high potential for measuring surface mass balance.
Martin Schrön, Steffen Zacharias, Gary Womack, Markus Köhli, Darin Desilets, Sascha E. Oswald, Jan Bumberger, Hannes Mollenhauer, Simon Kögler, Paul Remmler, Mandy Kasner, Astrid Denk, and Peter Dietrich
Geosci. Instrum. Method. Data Syst., 7, 83–99, https://doi.org/10.5194/gi-7-83-2018, https://doi.org/10.5194/gi-7-83-2018, 2018
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Cosmic-ray neutron sensing (CRNS) is a unique technology to monitor water storages in complex environments, non-invasively, continuously, autonomuously, and representatively in large areas. However, neutron detector signals are not comparable per se: there is statistical noise, technical differences, and locational effects. We found out what it takes to make CRNS consistent in time and space to ensure reliable data quality. We further propose a method to correct for sealed areas in the footrint.
Sabrina Marx, Katharina Anders, Sofia Antonova, Inga Beck, Julia Boike, Philip Marsh, Moritz Langer, and Bernhard Höfle
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2017-49, https://doi.org/10.5194/esurf-2017-49, 2017
Revised manuscript has not been submitted
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Global climate warming causes permafrost to warm and thaw, and, consequently, to release the carbon into the atmosphere. Terrestrial laser scanning is evaluated and current methods are extended in the context of monitoring subsidence in Arctic permafrost regions. The extracted information is important to gain a deeper understanding of permafrost-related subsidence processes and provides highly accurate ground-truth data which is necessary for further developing area-wide monitoring methods.
Mie Andreasen, Karsten H. Jensen, Darin Desilets, Marek Zreda, Heye R. Bogena, and Majken C. Looms
Hydrol. Earth Syst. Sci., 21, 1875–1894, https://doi.org/10.5194/hess-21-1875-2017, https://doi.org/10.5194/hess-21-1875-2017, 2017
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The cosmic-ray method holds a potential for quantifying canopy interception and biomass. We use measurements and modeling of thermal and epithermal neutron intensity in a forest to examine this potential. Canopy interception is a variable important to forest hydrology, yet difficult to monitor remotely. Forest growth impacts the carbon-cycle and can be used to mitigate climate changes by carbon sequestration in biomass. An efficient method to monitor tree growth is therefore of high relevance.
Xicai Pan, Daqing Yang, Yanping Li, Alan Barr, Warren Helgason, Masaki Hayashi, Philip Marsh, John Pomeroy, and Richard J. Janowicz
The Cryosphere, 10, 2347–2360, https://doi.org/10.5194/tc-10-2347-2016, https://doi.org/10.5194/tc-10-2347-2016, 2016
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This study demonstrates a robust procedure for accumulating precipitation gauge measurements and provides an analysis of bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada. It highlights the need for and importance of precipitation bias corrections at both research sites and operational networks for water balance assessment and the validation of global/regional climate–hydrology models.
Related subject area
Discipline: Snow | Subject: Instrumentation
Assessment of continuous flow analysis (CFA) for high-precision profiles of water isotopes in snow cores
Understanding biases in ICESat-2 data due to subsurface scattering using Airborne Topographic Mapper waveform data
A low-cost, autonomous system for distributed snow depth measurements on sea ice
Measuring prairie snow water equivalent with combined UAV-borne gamma spectrometry and lidar
Brief communication: Testing a portable Bullard-type temperature lance confirms highly spatially heterogeneous sediment temperatures under shallow bodies of water in the Arctic
A random forest approach to quality-checking automatic snow-depth sensor measurements
Brief communication: Comparison of in situ ephemeral snow depth measurements over a mixed-use temperate forest landscape
Monitoring snow water equivalent using the phase of RFID signals
Mapping snow depth on Canadian sub-arctic lakes using ground-penetrating radar
Comparison of manual snow water equivalent (SWE) measurements: seeking the reference for a true SWE value in a boreal biome
Brief communication: Application of a muonic cosmic ray snow gauge to monitor the snow water equivalent on alpine glaciers
GNSS signal-based snow water equivalent determination for different snowpack conditions along a steep elevation gradient
Review article: Performance assessment of radiation-based field sensors for monitoring the water equivalent of snow cover (SWE)
Spectral albedo measurements over snow-covered slopes: theory and slope effect corrections
Continuous and autonomous snow water equivalent measurements by a cosmic ray sensor on an alpine glacier
Monitoring of snow surface near-infrared bidirectional reflectance factors with added light-absorbing particles
An assessment of sub-snow GPS for quantification of snow water equivalent
Rémi Dallmayr, Hannah Meyer, Vasileios Gkinis, Thomas Laepple, Melanie Behrens, Frank Wilhelms, and Maria Hörhold
The Cryosphere, 19, 1067–1083, https://doi.org/10.5194/tc-19-1067-2025, https://doi.org/10.5194/tc-19-1067-2025, 2025
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Recent studies showed that a large number of independent vertical profiles allow for inferring a common local climate signal from the stacked stable water isotope record. Through investigating instrumental limitation and the effect of percolation of such porous samples, this study assesses the continuous flow analysis (CFA) technique in order to analyze the significant number of snow surface profiles within a reasonable time and with high quality.
Benjamin E. Smith, Michael Studinger, Tyler Sutterley, Zachary Fair, and Thomas Neumann
The Cryosphere, 19, 975–995, https://doi.org/10.5194/tc-19-975-2025, https://doi.org/10.5194/tc-19-975-2025, 2025
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This study investigates errors (biases) that may result when green lasers are used to measure the elevation of glaciers and ice sheets. These biases are important because if the snow or ice on top of the ice sheet changes, it can make the elevation of the ice appear to change by the wrong amount. We measure these biases over the Greenland Ice Sheet with a laser system on an airplane and explore how the use of satellite data can let us correct for the biases.
Ian A. Raphael, Donald K. Perovich, Christopher M. Polashenski, and Robert L. Hawley
EGUsphere, https://doi.org/10.5194/egusphere-2025-187, https://doi.org/10.5194/egusphere-2025-187, 2025
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Snow plays competing roles in the sea ice cycle by reflecting sunlight during summer (reducing melt) and insulating the ice from the cold atmosphere during winter (reducing growth). Observing where, when, and how much snow accumulates on sea ice is thus central to understanding the Arctic. Here, we describe a new snow depth observation system that is substantially cheaper and lighter than existing tools, and present a study demonstrating its potential to improve snow measurements on sea ice.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Alain Royer, Alexandre Roy, Sylvain Jutras, and Alexandre Langlois
The Cryosphere, 15, 5079–5098, https://doi.org/10.5194/tc-15-5079-2021, https://doi.org/10.5194/tc-15-5079-2021, 2021
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Dense spatially distributed networks of autonomous instruments for continuously measuring the amount of snow on the ground are needed for operational water resource and flood management and the monitoring of northern climate change. Four new-generation non-invasive sensors are compared. A review of their advantages, drawbacks and accuracy is discussed. This performance analysis is intended to help researchers and decision-makers choose the one system that is best suited to their needs.
Ghislain Picard, Marie Dumont, Maxim Lamare, François Tuzet, Fanny Larue, Roberta Pirazzini, and Laurent Arnaud
The Cryosphere, 14, 1497–1517, https://doi.org/10.5194/tc-14-1497-2020, https://doi.org/10.5194/tc-14-1497-2020, 2020
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Surface albedo is an essential variable of snow-covered areas. The measurement of this variable over a tilted terrain with levelled sensors is affected by artefacts that need to be corrected. Here we develop a theory of spectral albedo measurement over slopes from which we derive four correction algorithms. The comparison to in situ measurements taken in the Alps shows the adequacy of the theory, and the application of the algorithms shows systematic improvements.
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
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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
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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.
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Short summary
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.
Conventional methods used to measure snow have many limitations which hinder our ability to...
