Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2367-2023
© Author(s) 2023. 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-17-2367-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mapping snow depth on Canadian sub-arctic lakes using ground-penetrating radar
Remote Sensing of Environmental Change (ReSEC) Research Group,
Department of Geography and Environmental Studies, Wilfrid Laurier
University, Waterloo, N2L 3C5, Canada
Cold Regions Research Centre, Wilfrid Laurier University, Waterloo,
N2L 3C5, Canada
Homa Kheyrollah Pour
Remote Sensing of Environmental Change (ReSEC) Research Group,
Department of Geography and Environmental Studies, Wilfrid Laurier
University, Waterloo, N2L 3C5, Canada
Cold Regions Research Centre, Wilfrid Laurier University, Waterloo,
N2L 3C5, Canada
Alex MacLean
Remote Sensing of Environmental Change (ReSEC) Research Group,
Department of Geography and Environmental Studies, Wilfrid Laurier
University, Waterloo, N2L 3C5, Canada
Cold Regions Research Centre, Wilfrid Laurier University, Waterloo,
N2L 3C5, Canada
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Gifty Attiah, Homa Kheyrollah Pour, and K. Andrea Scott
Earth Syst. Sci. Data, 15, 1329–1355, https://doi.org/10.5194/essd-15-1329-2023, https://doi.org/10.5194/essd-15-1329-2023, 2023
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Lake surface temperature (LST) is a significant indicator of climate change and influences local weather and climate. This study developed a LST dataset retrieved from Landsat archives for 535 lakes across the North Slave Region, NWT, Canada. The data consist of individual NetCDF files for all observed days for each lake. The North Slave LST dataset will provide communities, scientists, and stakeholders with the changing spatiotemporal trends of LST for the past 38 years (1984–2021).
Hannah Adams, Jane Ye, Bhaleka D. Persaud, Stephanie Slowinski, Homa Kheyrollah Pour, and Philippe Van Cappellen
Earth Syst. Sci. Data, 14, 5139–5156, https://doi.org/10.5194/essd-14-5139-2022, https://doi.org/10.5194/essd-14-5139-2022, 2022
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Climate warming and land-use changes are altering the environmental factors that control the algal
productivityin lakes. To predict how environmental factors like nutrient concentrations, ice cover, and water temperature will continue to influence lake productivity in this changing climate, we created a dataset of chlorophyll-a concentrations (a compound found in algae), associated water quality parameters, and solar radiation that can be used to for a wide range of research questions.
Kiana Zolfaghari, Claude R. Duguay, and Homa Kheyrollah Pour
Hydrol. Earth Syst. Sci., 21, 377–391, https://doi.org/10.5194/hess-21-377-2017, https://doi.org/10.5194/hess-21-377-2017, 2017
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A remotely-sensed water clarity value (Kd) was applied to improve FLake model simulations of Lake Erie thermal structure using a time-invariant (constant) annual value as well as monthly values of Kd. The sensitivity of FLake model to Kd values was studied. It was shown that the model is very sensitive to variations in Kd when the value is less than 0.5 m-1.
Related subject area
Discipline: Snow | Subject: Instrumentation
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
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
Snow water equivalent measurement in the Arctic based on cosmic ray neutron attenuation
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
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.
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.
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
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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.
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
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.
Collecting spatial lake snow depth data is essential for improving lake ice models. Lake ice...