Articles | Volume 17, issue 8
https://doi.org/10.5194/tc-17-3137-2023
© 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-17-3137-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Aug 2023
Research article |
| 04 Aug 2023
| 04 Aug 2023
Monitoring snow water equivalent using the phase of RFID signals
Mathieu Le Breton
CORRESPONDING AUTHOR
Institut des Sciences de la Terre, Université Grenoble Alpes,
CNRS, 38000, Grenoble, France
Géolithe Innov, Géolithe, Crolles, 38920, France
Éric Larose
Institut des Sciences de la Terre, Université Grenoble Alpes,
CNRS, 38000, Grenoble, France
Laurent Baillet
Institut des Sciences de la Terre, Université Grenoble Alpes,
CNRS, 38000, Grenoble, France
Yves Lejeune
CEN-CNRM, Météo-France, CNRS, Saint-Martin-d'Hères,
38400, France
Alec van Herwijnen
WSL Institute for Snow and Avalanche Research SLF, Davos, 7260, Switzerland
Related authors
No articles found.
Gwendolyn Dasser, Valentin T. Bickel, Marius Rüetschi, Mylène Jacquemart, Mathias Bavay, Elisabeth D. Hafner, Alec van Herwijnen, and Andrea Manconi
EGUsphere, https://doi.org/10.5194/egusphere-2024-1510, https://doi.org/10.5194/egusphere-2024-1510, 2024
Short summary
Short summary
Understanding snowpack wetness is crucial for predicting wet snow avalanches, but detailed data is often limited to certain locations. Using satellite radar, we monitor snow wetness spatially continuously. By combining different radar tracks from Sentinel-1, we improved spatial resolution and tracked snow wetness over several seasons. Our results indicate higher snow wetness to correlate with increased wet snow avalanche activity, suggesting our method can help identify potential risk areas.
Mohit Mishra, Gildas Besançon, Guillaume Chambon, and Laurent Baillet
EGUsphere, https://doi.org/10.5194/egusphere-2024-1227, https://doi.org/10.5194/egusphere-2024-1227, 2024
Short summary
Short summary
This work was initiated in the context of a large interdisciplinary research project about Risk at Grenoble University, France. It relates to the challenging topic of landslide monitoring, and combines geotechnical sciences with techniques from control system engineering. Considering a specific modelling approach, the study provides a methodology towards estimation of some landslide parameters and their use in motion prediction. This could then be extended to the design of alert systems.
Andri Simeon, Cristina Pérez-Guillén, Michele Volpi, Christine Seupel, and Alec van Herwijnen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-76, https://doi.org/10.5194/gmd-2024-76, 2024
Preprint under review for GMD
Short summary
Short summary
Avalanche seismic detection systems are key for forecasting, but distinguishing avalanches from other seismic sources remains challenging. We propose novel autoencoder models to automatically extract features and compare them with standard seismic attributes. These features are then used to classify avalanches and noise events. The autoencoder feature classifiers have the highest sensitivity to detect avalanches, while the standard seismic classifier performs better overall.
Stephanie Mayer, Martin Hendrick, Adrien Michel, Bettina Richter, Jürg Schweizer, Heini Wernli, and Alec van Herwijnen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1026, https://doi.org/10.5194/egusphere-2024-1026, 2024
Short summary
Short summary
Understanding the impact of climate change on snow avalanche activity is crucial for safeguarding lives and infrastructure. Here, we project changes in avalanche activity in the Swiss Alps throughout the 21st century. Our findings reveal elevation-dependent patterns of change, indicating a decrease in dry-snow avalanches alongside an increase in wet-snow avalanches at elevations above the current tree line. These results underscore the necessity to revisit measures for avalanche risk mitigation.
Grégoire Bobillier, Bertil Trottet, Bastian Bergfeld, Ron Simenhois, Alec van Herwijnen, Jürg Schweizer, and Johan Gaume
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-70, https://doi.org/10.5194/nhess-2024-70, 2024
Preprint under review for NHESS
Short summary
Short summary
Our study focuses on the initiation process of snow slab avalanches. By combining experimental data and numerical simulations, we show that on gentle slopes, a crack forms and propagates due to compression fracture within a weak layer, and on steep slopes, the crack velocity can increase dramatically after about 5 meters due to a fracture mode transition (compression to shear). Understanding these dynamics represents an essential additional piece in the dry-snow slab avalanche formation puzzle.
Bastian Bergfeld, Karl W. Birkeland, Valentin Adam, Philipp L. Rosendahl, and Alec van Herwijnen
EGUsphere, https://doi.org/10.5194/egusphere-2024-690, https://doi.org/10.5194/egusphere-2024-690, 2024
Short summary
Short summary
To release a slab avalanche, a crack in a weak snow layer beneath a cohesive slab has to propagate. Information on that is essential for assessing avalanche risk. In the field, information can be gathered with the Propagation Saw Test (PST). However, there are different standards on how to cut the PST. In this study, we experimentally investigate the effect of these different column geometries and provide models to correct for imprecise field test geometry effects on the critical cut length.
Amelie Fees, Alec van Herwijnen, Michael Lombardo, Jürg Schweizer, and Peter Lehmann
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-34, https://doi.org/10.5194/nhess-2024-34, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
Glide-snow avalanches release at the ground-snow interface and their release process is poorly understood. To investigate the influence of spatial variability (snowpack and basal friction) on avalanche release, we developed a 3D, mechanical, threshold-based model that reproduces an observed release area distribution. A sensitivity analysis showed that the distribution was mostly influenced by the basal friction homogeneity while the variations in snowpack properties had little influence.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
Short summary
Short summary
Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Stephanie Mayer, Frank Techel, Jürg Schweizer, and Alec van Herwijnen
Nat. Hazards Earth Syst. Sci., 23, 3445–3465, https://doi.org/10.5194/nhess-23-3445-2023, https://doi.org/10.5194/nhess-23-3445-2023, 2023
Short summary
Short summary
We present statistical models to estimate the probability for natural dry-snow avalanche release and avalanche size based on the simulated layering of the snowpack. The benefit of these models is demonstrated in comparison with benchmark models based on the amount of new snow. From the validation with data sets of quality-controlled avalanche observations and danger levels, we conclude that these models may be valuable tools to support forecasting natural dry-snow avalanche activity.
Bastian Bergfeld, Alec van Herwijnen, Grégoire Bobillier, Philipp L. Rosendahl, Philipp Weißgraeber, Valentin Adam, Jürg Dual, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 23, 293–315, https://doi.org/10.5194/nhess-23-293-2023, https://doi.org/10.5194/nhess-23-293-2023, 2023
Short summary
Short summary
For a slab avalanche to release, the snowpack must facilitate crack propagation over large distances. Field measurements on crack propagation at this scale are very scarce. We performed a series of experiments, up to 10 m long, over a period of 10 weeks. Beside the temporal evolution of the mechanical properties of the snowpack, we found that crack speeds were highest for tests resulting in full propagation. Based on these findings, an index for self-sustained crack propagation is proposed.
Stephanie Mayer, Alec van Herwijnen, Frank Techel, and Jürg Schweizer
The Cryosphere, 16, 4593–4615, https://doi.org/10.5194/tc-16-4593-2022, https://doi.org/10.5194/tc-16-4593-2022, 2022
Short summary
Short summary
Information on snow instability is crucial for avalanche forecasting. We introduce a novel machine-learning-based method to assess snow instability from snow stratigraphy simulated with the snow cover model SNOWPACK. To develop the model, we compared observed and simulated snow profiles. Our model provides a probability of instability for every layer of a simulated snow profile, which allows detection of the weakest layer and assessment of its degree of instability with one single index.
Cristina Pérez-Guillén, Frank Techel, Martin Hendrick, Michele Volpi, Alec van Herwijnen, Tasko Olevski, Guillaume Obozinski, Fernando Pérez-Cruz, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 22, 2031–2056, https://doi.org/10.5194/nhess-22-2031-2022, https://doi.org/10.5194/nhess-22-2031-2022, 2022
Short summary
Short summary
A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
Antoine Guillemot, Alec van Herwijnen, Eric Larose, Stephanie Mayer, and Laurent Baillet
The Cryosphere, 15, 5805–5817, https://doi.org/10.5194/tc-15-5805-2021, https://doi.org/10.5194/tc-15-5805-2021, 2021
Short summary
Short summary
Ambient noise correlation is a broadly used method in seismology to monitor tiny changes in subsurface properties. Some environmental forcings may influence this method, including snow. During one winter season, we studied this snow effect on seismic velocity of the medium, recorded by a pair of seismic sensors. We detected and modeled a measurable effect during early snowfalls: the fresh new snow layer modifies rigidity and density of the medium, thus decreasing the recorded seismic velocity.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
Short summary
Short summary
The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Bastian Bergfeld, Alec van Herwijnen, Benjamin Reuter, Grégoire Bobillier, Jürg Dual, and Jürg Schweizer
The Cryosphere, 15, 3539–3553, https://doi.org/10.5194/tc-15-3539-2021, https://doi.org/10.5194/tc-15-3539-2021, 2021
Short summary
Short summary
The modern picture of the snow slab avalanche release process involves a
dynamic crack propagation phasein which a whole slope becomes detached. The present work contains the first field methodology which provides the temporal and spatial resolution necessary to study this phase. We demonstrate the versatile capabilities and accuracy of our method by revealing intricate dynamics and present how to determine relevant characteristics of crack propagation such as crack speed.
Antoine Guillemot, Laurent Baillet, Stéphane Garambois, Xavier Bodin, Agnès Helmstetter, Raphaël Mayoraz, and Eric Larose
The Cryosphere, 15, 501–529, https://doi.org/10.5194/tc-15-501-2021, https://doi.org/10.5194/tc-15-501-2021, 2021
Short summary
Short summary
Among mountainous permafrost landforms, rock glaciers are composed of boulders, fine frozen materials, water and ice in various proportions. Displacement rates of active rock glaciers can reach several m/yr, contributing to emerging risks linked to gravitational hazards. Thanks to passive seismic monitoring, resonance effects related to seasonal freeze–thawing processes of the shallower layers have been monitored and modeled. This method is an accurate tool for studying rock glaciers at depth.
Michaela Wenner, Clément Hibert, Alec van Herwijnen, Lorenz Meier, and Fabian Walter
Nat. Hazards Earth Syst. Sci., 21, 339–361, https://doi.org/10.5194/nhess-21-339-2021, https://doi.org/10.5194/nhess-21-339-2021, 2021
Short summary
Short summary
Mass movements constitute a risk to property and human life. In this study we use machine learning to automatically detect and classify slope failure events using ground vibrations. We explore the influence of non-ideal though commonly encountered conditions: poor network coverage, small number of events, and low signal-to-noise ratios. Our approach enables us to detect the occurrence of rare events of high interest in a large data set of more than a million windowed seismic signals.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Bettina Richter, Alec van Herwijnen, Mathias W. Rotach, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 20, 2873–2888, https://doi.org/10.5194/nhess-20-2873-2020, https://doi.org/10.5194/nhess-20-2873-2020, 2020
Short summary
Short summary
We investigated the sensitivity of modeled snow instability to uncertainties in meteorological input, typically found in complex terrain. The formation of the weak layer was very robust due to the long dry period, indicated by a widespread avalanche problem. Once a weak layer has formed, precipitation mostly determined slab and weak layer properties and hence snow instability. When spatially assessing snow instability for avalanche forecasting, accurate precipitation patterns have to be known.
Louis Quéno, Charles Fierz, Alec van Herwijnen, Dylan Longridge, and Nander Wever
The Cryosphere, 14, 3449–3464, https://doi.org/10.5194/tc-14-3449-2020, https://doi.org/10.5194/tc-14-3449-2020, 2020
Short summary
Short summary
Deep ice layers may form in the snowpack due to preferential water flow with impacts on the snowpack mechanical, hydrological and thermodynamical properties. We studied their formation and evolution at a high-altitude alpine site, combining a comprehensive observation dataset at a daily frequency (with traditional snowpack observations, penetration resistance and radar measurements) and detailed snowpack modeling, including a new parameterization of ice formation in the 1-D SNOWPACK model.
Frank Techel, Kurt Winkler, Matthias Walcher, Alec van Herwijnen, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 20, 1941–1953, https://doi.org/10.5194/nhess-20-1941-2020, https://doi.org/10.5194/nhess-20-1941-2020, 2020
Short summary
Short summary
Snow instability tests, like the extended column test (ECT), provide valuable information regarding point snow instability. A large data set of ECT – together with information on slope instability – was explored. The findings clearly show that combining information regarding propagation propensity and fracture initiation provided the best correlation with slope instability. A new four-class stability interpretation scheme is proposed for ECT results.
Neige Calonne, Bettina Richter, Henning Löwe, Cecilia Cetti, Judith ter Schure, Alec Van Herwijnen, Charles Fierz, Matthias Jaggi, and Martin Schneebeli
The Cryosphere, 14, 1829–1848, https://doi.org/10.5194/tc-14-1829-2020, https://doi.org/10.5194/tc-14-1829-2020, 2020
Short summary
Short summary
During winter 2015–2016, the standard program to monitor the structure and stability of the snowpack at Weissflujoch, Swiss Alps, was complemented by additional measurements to compare between various traditional and newly developed techniques. Snow micro-penetrometer measurements allowed monitoring of the evolution of the snowpack's internal structure at a daily resolution throughout the winter. We show the potential of such high-resolution data for detailed evaluations of snowpack models.
Emanuele Marchetti, Alec van Herwijnen, Marc Christen, Maria Cristina Silengo, and Giulia Barfucci
Earth Surf. Dynam., 8, 399–411, https://doi.org/10.5194/esurf-8-399-2020, https://doi.org/10.5194/esurf-8-399-2020, 2020
Short summary
Short summary
We present infrasonic and seismic array data of a powder snow avalanche, that was released on 5 February 2016, in the Dischma valley nearby Davos, Switzerland. Combining information derived from both arrays, we show how infrasound and seismic energy are radiated from different sources acting along the path. Moreover, infrasound transmits to the ground and affects the recorded seismic signal. Results highlight the benefits of combined seismo-acoustic array analyses for monitoring and research.
Nora Helbig, David Moeser, Michaela Teich, Laure Vincent, Yves Lejeune, Jean-Emmanuel Sicart, and Jean-Matthieu Monnet
Hydrol. Earth Syst. Sci., 24, 2545–2560, https://doi.org/10.5194/hess-24-2545-2020, https://doi.org/10.5194/hess-24-2545-2020, 2020
Short summary
Short summary
Snow retained in the forest canopy (snow interception) drives spatial variability of the subcanopy snow accumulation. As such, accurately describing snow interception in models is of importance for various applications such as hydrological, weather, and climate predictions. We developed descriptions for the spatial mean and variability of snow interception. An independent evaluation demonstrated that the novel models can be applied in coarse land surface model grid cells.
Grégoire Bobillier, Bastian Bergfeld, Achille Capelli, Jürg Dual, Johan Gaume, Alec van Herwijnen, and Jürg Schweizer
The Cryosphere, 14, 39–49, https://doi.org/10.5194/tc-14-39-2020, https://doi.org/10.5194/tc-14-39-2020, 2020
Bettina Richter, Jürg Schweizer, Mathias W. Rotach, and Alec van Herwijnen
The Cryosphere, 13, 3353–3366, https://doi.org/10.5194/tc-13-3353-2019, https://doi.org/10.5194/tc-13-3353-2019, 2019
Short summary
Short summary
Information on snow stability is important for avalanche forecasting. To improve the stability estimation in the snow cover model SNOWPACK, we suggested an improved parameterization for the critical crack length. We compared 3 years of field data to SNOWPACK simulations. The match between observed and modeled critical crack lengths greatly improved, and critical weak layers appear more prominently in the modeled vertical profile of critical crack length.
Cécile B. Ménard, Richard Essery, Alan Barr, Paul Bartlett, Jeff Derry, Marie Dumont, Charles Fierz, Hyungjun Kim, Anna Kontu, Yves Lejeune, Danny Marks, Masashi Niwano, Mark Raleigh, Libo Wang, and Nander Wever
Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, https://doi.org/10.5194/essd-11-865-2019, 2019
Short summary
Short summary
This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
Matthias Heck, Alec van Herwijnen, Conny Hammer, Manuel Hobiger, Jürg Schweizer, and Donat Fäh
Earth Surf. Dynam., 7, 491–503, https://doi.org/10.5194/esurf-7-491-2019, https://doi.org/10.5194/esurf-7-491-2019, 2019
Short summary
Short summary
We used continuous seismic data from two small aperture geophone arrays deployed in the region above Davos in the eastern Swiss Alps to develop a machine learning workflow to automatically identify signals generated by snow avalanches. Our results suggest that the method presented could be used to identify major avalanche periods and highlight the importance of array processing techniques for the automatic classification of avalanches in seismic data.
Yves Lejeune, Marie Dumont, Jean-Michel Panel, Matthieu Lafaysse, Philippe Lapalus, Erwan Le Gac, Bernard Lesaffre, and Samuel Morin
Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, https://doi.org/10.5194/essd-11-71-2019, 2019
Short summary
Short summary
This paper introduces and provides access to a daily (1960–2017) and an hourly (1993–2017) dataset of snow and meteorological data measured at the Col de Porte site, 1325 m a.s.l, Charteuse, France. The daily dataset can be used to quantify the effect of climate change at this site, with a reduction of the mean snow depth of 39 cm from 1960–1990 to 1990–2017. The daily and hourly datasets are useful and appropriate for driving and evaluating a snowpack model over such a long period.
Floriane Provost, Jean-Philippe Malet, Clément Hibert, Agnès Helmstetter, Mathilde Radiguet, David Amitrano, Nadège Langet, Eric Larose, Clàudia Abancó, Marcel Hürlimann, Thomas Lebourg, Clara Levy, Gaëlle Le Roy, Patrice Ulrich, Maurin Vidal, and Benjamin Vial
Earth Surf. Dynam., 6, 1059–1088, https://doi.org/10.5194/esurf-6-1059-2018, https://doi.org/10.5194/esurf-6-1059-2018, 2018
Short summary
Short summary
Seismic sources generated by the deformation of unstable slopes are diverse in terms of signal properties and mechanisms. Standardized catalogues of landslide endogenous seismicity can help understanding the physical processes controlling slope dynamics. We propose a generic typology of seismic sources based on the analysis of signals recorded at various instrumented slopes. We demonstrate that the seismic signals present similar features at different sites and discuss their mechanical sources.
Deborah Verfaillie, Matthieu Lafaysse, Michel Déqué, Nicolas Eckert, Yves Lejeune, and Samuel Morin
The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, https://doi.org/10.5194/tc-12-1249-2018, 2018
Short summary
Short summary
This article addresses local changes of seasonal snow and its meteorological drivers, at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps, for the period 1960–2100. We use an ensemble of adjusted RCM outputs consistent with IPCC AR5 GCM outputs (RCPs 2.6, 4.5 and 8.5) and the snowpack model Crocus. Beyond scenario-based approach, global temperature levels on the order of 1.5 °C and 2 °C above preindustrial levels correspond to 25 and 32% reduction of mean snow depth.
Matthias Heck, Conny Hammer, Alec van Herwijnen, Jürg Schweizer, and Donat Fäh
Nat. Hazards Earth Syst. Sci., 18, 383–396, https://doi.org/10.5194/nhess-18-383-2018, https://doi.org/10.5194/nhess-18-383-2018, 2018
Short summary
Short summary
In this study we use hidden Markov models, a machine learning algorithm to automatically identify avalanche events in a continuous seismic data set recorded during the winter 2010. With additional post processing steps, we detected around 70 avalanche events. Although not every detection could be confirmed as an avalanche, we clearly identified the two main avalanche periods of the winter season 2010 in our classification results.
Francois Tuzet, Marie Dumont, Matthieu Lafaysse, Ghislain Picard, Laurent Arnaud, Didier Voisin, Yves Lejeune, Luc Charrois, Pierre Nabat, and Samuel Morin
The Cryosphere, 11, 2633–2653, https://doi.org/10.5194/tc-11-2633-2017, https://doi.org/10.5194/tc-11-2633-2017, 2017
Short summary
Short summary
Light-absorbing impurities deposited on snow, such as soot or dust, strongly modify its evolution. We implemented impurity deposition and evolution in a detailed snowpack model, thereby expanding the reach of such models into addressing the subtle interplays between snow physics and impurities' optical properties. Model results were evaluated based on innovative field observations at an Alpine site. This allows future investigations in the fields of climate, hydrology and avalanche prediction.
Matthieu Lafaysse, Bertrand Cluzet, Marie Dumont, Yves Lejeune, Vincent Vionnet, and Samuel Morin
The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, https://doi.org/10.5194/tc-11-1173-2017, 2017
Short summary
Short summary
Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC by implementing new representations of different physical processes in a coupled multilayer ground/snowpack model. This system is a promising tool to integrate snow modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack modelling applications.
Marie Dumont, Laurent Arnaud, Ghislain Picard, Quentin Libois, Yves Lejeune, Pierre Nabat, Didier Voisin, and Samuel Morin
The Cryosphere, 11, 1091–1110, https://doi.org/10.5194/tc-11-1091-2017, https://doi.org/10.5194/tc-11-1091-2017, 2017
Short summary
Short summary
Snow spectral albedo in the visible/near-infrared range has been continuously measured during a winter season at Col de Porte alpine site (French Alps; 45.30° N, 5.77°E; 1325 m a.s.l.). This study highlights that the variations of spectral albedo can be successfully explained by variations of the following snow surface variables: snow-specific surface area, effective light-absorbing impurities content, presence of liquid water and slope.
Johan Gaume, Alec van Herwijnen, Guillaume Chambon, Nander Wever, and Jürg Schweizer
The Cryosphere, 11, 217–228, https://doi.org/10.5194/tc-11-217-2017, https://doi.org/10.5194/tc-11-217-2017, 2017
Short summary
Short summary
Based on DEM simulations we developed a new model for the onset of crack propagation in snow slab avalanche release. The model reconciles past approaches by considering the complex interplay between slab elasticity and the mechanical behavior of the weak layer including its structural collapse. The model agrees with extensive field data and can reproduce crack propagation on low-angle terrain and the decrease in critical crack length with increasing slope angle observed in numerical experiments.
Jürg Schweizer, Benjamin Reuter, Alec van Herwijnen, Bettina Richter, and Johan Gaume
The Cryosphere, 10, 2637–2653, https://doi.org/10.5194/tc-10-2637-2016, https://doi.org/10.5194/tc-10-2637-2016, 2016
Fabiano Monti, Johan Gaume, Alec van Herwijnen, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 16, 775–788, https://doi.org/10.5194/nhess-16-775-2016, https://doi.org/10.5194/nhess-16-775-2016, 2016
Short summary
Short summary
We propose a new approach based on a simplification of the multi-layered elasticity theory in order to easily compute the additional stress due to a skier at the depth of the weak layer, taking into account the layering of the snow slab and the substratum. The method was tested on simplified snow profiles, then on manually observed snow profiles including a stability test and, finally, on simulated snow profiles, thereby showing the promise of our approach.
J. Gaume, A. van Herwijnen, G. Chambon, K. W. Birkeland, and J. Schweizer
The Cryosphere, 9, 1915–1932, https://doi.org/10.5194/tc-9-1915-2015, https://doi.org/10.5194/tc-9-1915-2015, 2015
Short summary
Short summary
We proposed a new approach to characterize the dynamic phase of crack propagation in weak snowpack layers as well as fracture arrest propensity by means of numerical "propagation saw test" simulations based on the discrete element method. Crack propagation speed and distance before fracture arrest were derived from the simulations for different snowpack configurations and mechanical properties. Numerical and experimental results were compared and the mechanical processes at play were discussed.
B. Reuter, J. Schweizer, and A. van Herwijnen
The Cryosphere, 9, 837–847, https://doi.org/10.5194/tc-9-837-2015, https://doi.org/10.5194/tc-9-837-2015, 2015
Short summary
Short summary
We present a novel approach to estimate point snow instability based on snow mechanical properties from snow micro-penetrometer measurements. This is the first approach that takes into account the essential processes involved in dry-snow slab avalanche release: failure initiation and crack propagation. Comparison with field observations confirms that the two-step calculation of a stability criterion and a critical crack length is suited to describe point snow instability.
M. Stähli, M. Sättele, C. Huggel, B. W. McArdell, P. Lehmann, A. Van Herwijnen, A. Berne, M. Schleiss, A. Ferrari, A. Kos, D. Or, and S. M. Springman
Nat. Hazards Earth Syst. Sci., 15, 905–917, https://doi.org/10.5194/nhess-15-905-2015, https://doi.org/10.5194/nhess-15-905-2015, 2015
Short summary
Short summary
This review paper describes the state of the art in monitoring and predicting rapid mass movements for early warning. It further presents recent innovations in observation technologies and modelling to be used in future early warning systems (EWS). Finally, the paper proposes avenues towards successful implementation of next-generation EWS.
N. Helbig, A. van Herwijnen, J. Magnusson, and T. Jonas
Hydrol. Earth Syst. Sci., 19, 1339–1351, https://doi.org/10.5194/hess-19-1339-2015, https://doi.org/10.5194/hess-19-1339-2015, 2015
E. H. Bair, R. Simenhois, A. van Herwijnen, and K. Birkeland
The Cryosphere, 8, 1407–1418, https://doi.org/10.5194/tc-8-1407-2014, https://doi.org/10.5194/tc-8-1407-2014, 2014
C. M. Carmagnola, S. Morin, M. Lafaysse, F. Domine, B. Lesaffre, Y. Lejeune, G. Picard, and L. Arnaud
The Cryosphere, 8, 417–437, https://doi.org/10.5194/tc-8-417-2014, https://doi.org/10.5194/tc-8-417-2014, 2014
A. Rabatel, B. Francou, A. Soruco, J. Gomez, B. Cáceres, J. L. Ceballos, R. Basantes, M. Vuille, J.-E. Sicart, C. Huggel, M. Scheel, Y. Lejeune, Y. Arnaud, M. Collet, T. Condom, G. Consoli, V. Favier, V. Jomelli, R. Galarraga, P. Ginot, L. Maisincho, J. Mendoza, M. Ménégoz, E. Ramirez, P. Ribstein, W. Suarez, M. Villacis, and P. Wagnon
The Cryosphere, 7, 81–102, https://doi.org/10.5194/tc-7-81-2013, https://doi.org/10.5194/tc-7-81-2013, 2013
Related subject area
Discipline: Snow | Subject: Instrumentation
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
Measuring prairie snow water equivalent with combined UAV-borne gamma spectrometry and lidar
Brief communication: Comparison of in situ ephemeral snow depth measurements over a mixed-use temperate forest landscape
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
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
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
Short summary
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
Short summary
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.
Phillip Harder, Warren Helgason, and John Pomeroy
EGUsphere, https://doi.org/10.5194/egusphere-2023-2586, https://doi.org/10.5194/egusphere-2023-2586, 2023
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-meter resolutions which is a new opportunity to improve the measurement of shallow snowpacks.
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
Short summary
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.
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
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.
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.
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
Short summary
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
Short summary
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
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.
Alain Royer, Alexandre Roy, Sylvain Jutras, and Alexandre Langlois
The Cryosphere, 15, 5079–5098, https://doi.org/10.5194/tc-15-5079-2021, https://doi.org/10.5194/tc-15-5079-2021, 2021
Short summary
Short summary
Dense spatially distributed networks of autonomous instruments for continuously measuring the amount of snow on the ground are needed for operational water resource and flood management and the monitoring of northern climate change. Four new-generation non-invasive sensors are compared. A review of their advantages, drawbacks and accuracy is discussed. This performance analysis is intended to help researchers and decision-makers choose the one system that is best suited to their needs.
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
Short summary
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
Short summary
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
Short summary
Short summary
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
Short summary
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
Arnitz, D., Muehlmann, U., and Witrisal, K.: Characterization and Modeling
of UHF RFID Channels for Ranging and Localization,
IEEE T. Antenn. Propag., 60, 2491–2501,
https://doi.org/10.1109/TAP.2012.2189705, 2012.
Bagshaw, E. A., Karlsson, N. B., Lok, L. B., Lishman, B., Clare, L.,
Nicholls, K. W., Burrow, S., Wadham, J. L., Eisen, O., Corr, H., Brennan,
P., and Dahl-Jensen, D.: Prototype wireless sensors for monitoring
subsurface processes in snow and firn, J. Glaciol., 64, 887–896,
https://doi.org/10.1017/jog.2018.76, 2018.
Balanis, C. A.: Advanced Engineering Electromagnetics, Second Edition, John
Wiley and Sons, ISBN: 978-0-470-58948-9, 2012.
Barbot, N. and Perret, E.: A Chipless RFID Method of 2D Localization Based
on Phase Acquisition, J. Sensors, 2018, 7484265,
https://doi.org/10.1155/2018/7484265, 2018.
Beaumont, R. T.: Mt. Hood Pressure Pillow Snow Gage,
J. Appl. Meteorol. Clim., 4, 626–631,
https://doi.org/10.1175/1520-0450(1965)004<0626:MHPPSG>2.0.CO;2, 1965.
Bhattacharyya, R., Floerkemeier, C., and Sarma, S.: Low-Cost, Ubiquitous
RFID-Tag-Antenna-Based Sensing, P. IEEE, 98, 1593–1600,
https://doi.org/10.1109/JPROC.2010.2051790, 2010.
Bradford, J. H., Harper, J. T., and Brown, J.: Complex dielectric permittivity measurements from ground-penetrating radar data to estimate snow liquid water content in the pendular regime,
Water Resour. Res., 45, W08403, https://doi.org/10.1029/2008WR007341, 2009.
Brandt, R. E. and Warren, S. G.: Temperature measurements and heat transfer
in near-surface snow at the South Pole, J. Glaciol., 43, 339–351,
https://doi.org/10.3189/S0022143000003294, 1997.
Burns, S. P., Molotch, N. P., Williams, M. W., Knowles, J. F., Seok, B.,
Monson, R. K., Turnipseed, A. A., and Blanken, P. D.: Snow Temperature
Changes within a Seasonal Snowpack and Their Relationship to Turbulent
Fluxes of Sensible and Latent Heat, J. Hydrometeorol., 15,
117–142, https://doi.org/10.1175/JHM-D-13-026.1, 2014.
Caccami, M. C. and Marrocco, G.: Electromagnetic Modeling of Self-Tuning
RFID Sensor Antennas in Linear and Nonlinear Regimes, IEEE T.
Antenn. Propag., 66, 2779–2787,
https://doi.org/10.1109/TAP.2018.2820322, 2018.
Caccami, M. C., Manzari, S., and Marrocco, G.: Phase-Oriented Sensing by
Means of Loaded UHF RFID Tags, IEEE T. Antenn.
Propag., 63, 4512–4520, https://doi.org/10.1109/TAP.2015.2465891, 2015.
Camera, F. and Marrocco, G.: Electromagnetic-Based Correction of
Bio-Integrated RFID Sensors for Reliable Skin Temperature Monitoring,
IEEE Sens. J., 21, 421–429, https://doi.org/10.1109/JSEN.2020.3014404,
2021.
Charléty, A., Le Breton, M., Larose, E., and Baillet, L.: 2D Phase-Based
RFID Localization for On-Site Landslide Monitoring, Remote Sensing, 14,
3577, https://doi.org/10.3390/rs14153577, 2022.
Charléty, A., Le Breton, M., Baillet, L., and Larose, É.: RFID
landslide monitoring: long-term outdoor signal processing and phase
unwrapping, IEEE J. Radio Freq. Identif., 7, 319–329,
https://doi.org/10.1109/JRFID.2023.3256560, 2023.
Cheng, Y., Cheng, B., Zheng, F., Vihma, T., Kontu, A., Yang, Q., and Liao,
Z.: Air/snow, snow/ice and ice/water interfaces detection from
high-resolution vertical temperature profiles measured by ice mass-balance
buoys on an Arctic lake, Ann. Glaciol., 61, 309–319,
https://doi.org/10.1017/aog.2020.51, 2020.
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, 931–936, http://arc.lib.montana.edu/snow-science/item/1770 (last access: 24 July 2023), 2013.
Confidex: Survivor B – Product datasheet, Confidex, https://www.confidex.com/wp-content/uploads/Survivor_B_Datasheet.pdf (last access: July 2023), 2019.
Costa, F., Genovesi, S., Borgese, M., Michel, A., Dicandia, F. A., and
Manara, G.: A Review of RFID Sensors, the New Frontier of Internet of
Things, Sensors, 21, 3138, https://doi.org/10.3390/s21093138, 2021.
Dafflon, B., Wielandt, S., Lamb, J., McClure, P., Shirley, I., Uhlemann, S., Wang, C., Fiolleau, S., Brunetti, C., Akins, F. H., Fitzpatrick, J., Pullman, S., Busey, R., Ulrich, C., Peterson, J., and Hubbard, S. S.: A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature, The Cryosphere, 16, 719–736, https://doi.org/10.5194/tc-16-719-2022, 2022.
Denoth, A., Foglar, A., Weiland, P., Mätzler, C., Aebisher, H., Tiuri, M., and
Sihvola, A.: A comparative study of instruments for measuring the liquid
water content of snow, J. Appl. Phys., 56, 2154–2160,
https://doi.org/10.1063/1.334215, 1984.
Dey, S., Bhattacharyya, R., Karmakar, N., and Sarma, S.: A Folded Monopole
Shaped Novel Soil Moisture and Salinity Sensor for Precision Agriculture
Based Chipless RFID Applications, in: 2019 IEEE MTT-S International
Microwave and RF Conference (IMARC), 2019 IEEE MTT-S International Microwave
and RF Conference (IMARC), Mumbai, India, 13–15 December 2019, 1–4,
https://doi.org/10.1109/IMaRC45935.2019.9118618, 2019.
EPC-Gen2: EPC™ Radio-Frequency Identity Protocols Generation-2 UHF RFID, Version 2.01,
GS1 EPC Global, https://www.gs1.org/sites/default/files/docs/epc/Gen2_Protocol_Standard.pdf (last access: 24 July 2023), 2015.
Espin-Lopez, P. F. and Pasian, M.: Determination of Snow Water Equivalent
for Dry Snowpacks Using the Multipath Propagation of Ground-Based Radars,
IEEE Geosci. Remote S., 18, 276–280, https://doi.org/10.1109/LGRS.2020.2974546, 2021.
Essery, R., Morin, S., Lejeune, Y., and B Ménard, C.: A comparison of
1701 snow models using observations from an alpine site, Adv. Water
Resour., 55, 131–148, https://doi.org/10.1016/j.advwatres.2012.07.013,
2013.
Fierz, C., Amstrong, R. L., Durand, Y., Etchevers, P., Greene, E., McClung,
D. M., Nishimura, K., Satyawali, P. K., and Sokratov, S. A.: The
International Classification for Seasonal Snow on the Ground, IHP-VII Technical Documents in Hydrology No. 83 UNESCO-IHP,
Paris, https://unesdoc.unesco.org/ark:/48223/pf0000186462 (last access: 24 July 2023), 2009.
Fonseca, N., Freire, R., Fontgalland, G., Arruda, B., and Tedjini, S.: A
Fully Passive UHF RFID Soil Moisture Time-Domain Transmissometry Based
Sensor, in: 2018 3rd International Symposium on Instrumentation Systems,
Circuits and Transducers (INSCIT), 3rd International Symposium on
Instrumentation Systems, Circuits and Transducers (INSCIT), Bento Goncalves, Brazil, 27–31 August 2018, 1–6,
https://doi.org/10.1109/INSCIT.2018.8546707, 2018.
Grasegger, K., Strapazzon, G., Procter, E., Brugger, H., and Soteras, I.:
Avalanche Survival After Rescue With the RECCO Rescue System: A Case Report,
Wild. Environ. Med., 27, 282–286,
https://doi.org/10.1016/j.wem.2016.02.004, 2016.
Grebien, S., Galler, F., Neunteufel, D., Muhlmann, U., Maier, S. J.,
Arthaber, H., and Witrisal, K.: Experimental Evaluation of a UHF-MIMO RFID
System for Positioning in Multipath Channels, in: 2019 IEEE International
Conference on RFID Technology and Applications (RFID-TA), 2019 IEEE
International Conference on RFID Technology and Applications (RFID-TA),
Pisa, Italy, 25–27 September 2019, 95–100, https://doi.org/10.1109/RFID-TA.2019.8892179, 2019.
Harris, C. R., Millman, K. J., van der Walt, S. J., et al.: Array programming with NumPy,
Nature, 585, 357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020.
Hechenberger, S., Neunteufel, D., and Arthaber, H.: Ray Tracing and
Measurement based Evaluation of a UHF RFID Ranging System, in: 2022 IEEE
International Conference on RFID (RFID), 2022 IEEE International Conference
on RFID (RFID), Las Vegas, NV, USA, 17–19 May 2022, 75–80, https://doi.org/10.1109/RFID54732.2022.9795977,
2022.
Helbig, N., Schirmer, M., Magnusson, J., Mäder, F., van Herwijnen, A., Quéno, L., Bühler, Y., Deems, J. S., and Gascoin, S.: A seasonal algorithm of the snow-covered area fraction for mountainous terrain, The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, 2021.
Helfricht, K., Hartl, L., Koch, R., Marty, C., and Olefs, M.: Obtaining sub-daily new snow density from automated measurements in high mountain regions, Hydrol. Earth Syst. Sci., 22, 2655–2668, https://doi.org/10.5194/hess-22-2655-2018, 2018.
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng.,
9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007.
Jedermann, R., Ruiz-Garcia, L., and Lang, W.: Spatial temperature profiling
by semi-passive RFID loggers for perishable food transportation,
Comput. Electron. Agr., 65, 145–154,
https://doi.org/10.1016/j.compag.2008.08.006, 2009.
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.
Koch, F., Prasch, M., Schmid, L., Schweizer, J., and Mauser, W.: Measuring
Snow Liquid Water Content with Low-Cost GPS Receivers, Sensors, 14,
20975–20999, https://doi.org/10.3390/s141120975, 2014.
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.
Kodama, M., Nakai, K., Kawasaki, S., and Wada, M.: An application of
cosmic-ray neutron measurements to the determination of the snow-water
equivalent, J. Hydrol., 41, 85–92,
https://doi.org/10.1016/0022-1694(79)90107-0, 1979.
Kulsoom, F., Dell'Acqua, F., Pasian, M., and Espín-López, P. F.:
Snow Layer Detection by Pattern Matching in a Multipath Radar Interference
Scenario, Int. J. Remote Sens., 42, 3193–3218,
https://doi.org/10.1080/01431161.2020.1854890, 2021.
Larson, K. M., Gutmann, E. D., Zavorotny, V. U., Braun, J. J., Williams, M.
W., and Nievinski, F. G.: Can we measure snow depth with GPS receivers?,
Geophys. Res. Lett., 36, L17502, https://doi.org/10.1029/2009GL039430, 2009.
Lazaro, A., Girbau, D., and Salinas, D.: Radio Link Budgets for UHF RFID on
Multipath Environments, IEEE Trans. Antennas Propagat., 57, 1241–1251,
https://doi.org/10.1109/TAP.2009.2015818, 2009.
Le Breton, M.: Suivi temporel d'un glissement de terrain à l'aide
d'étiquettes RFID passives, couplé à l'observation de
pluviométrie et de bruit sismique ambiant, PhD Thesis, Université
Grenoble Alpes, ISTerre, Grenoble, France, https://doi.org/10.13140/RG.2.2.20636.00649, 2019.
Le Breton, M.: Increased ranging accuracy of RFID tags in ETSI regions using 53 MHz wide dual bands, TechRxiv [preprint], https://doi.org/10.36227/techrxiv.23538405,
18 June 2023.
Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D.,
and Guyoton, F.: Outdoor UHF RFID: Phase Stabilization for Real-World
Applications, IEEE Journal of Radio Frequency Identification, 1, 279–290,
https://doi.org/10.1109/JRFID.2017.2786745, 2017.
Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D.,
Guyoton, F., and Jaboyedoff, M.: Passive radio-frequency identification
ranging, a dense and weather-robust technique for landslide displacement
monitoring, Eng. Geol., 250, 1–10,
https://doi.org/10.1016/j.enggeo.2018.12.027, 2019.
Le Breton, M., Liébault, F., Baillet, L., Charléty, A., Larose,
É., and Tedjini, S.: Dense and long-term monitoring of earth surface
processes with passive RFID – a review, Earth-Sci. Rev., 234,
104225, https://doi.org/10.1016/j.earscirev.2022.104225, 2022.
Le Breton, M., Baillet, L., and Larose, É.: Tomography of the quantity of grass using RFID propagation-based sensing, TechRxiv [preprint],
https://doi.org/10.36227/techrxiv.23538381, 18 June 2023.
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.
Lucas, C., Leinss, S., Bühler, Y., Marino, A., and Hajnsek, I.:
Multipath Interferences in Ground-Based Radar Data: A Case Study, Remote
Sensing, 9, 1260, https://doi.org/10.3390/rs9121260, 2017.
Luvisi, A., Panattoni, A., and Materazzi, A.: RFID temperature sensors for
monitoring soil solarization with biodegradable films,
Comput. Electron. Agr., 123, 135–141,
https://doi.org/10.1016/j.compag.2016.02.023, 2016.
Manzari, S. and Marrocco, G.: Modeling and Applications of a Chemical-Loaded
UHF RFID Sensing Antenna With Tuning Capability,
IEEE T. Antenn. Propag., 62, 94–101,
https://doi.org/10.1109/TAP.2013.2287008, 2014.
Marchenko, S. A., Pelt, W. J. J. van, Pettersson, R., Pohjola, V. A., and
Reijmer, C. H.: Water content of firn at Lomonosovfonna, Svalbard, derived
from subsurface temperature measurements, J. Glaciol., 67,
921–932, https://doi.org/10.1017/jog.2021.43, 2021.
Mätzler, C.: Applications of the interaction of microwaves with the
natural snow cover, Remote Sensing Reviews, 2, 259–387,
https://doi.org/10.1080/02757258709532086, 1987.
Mellor, M.: Engineering Properties of Snow, J. Glaciol., 19,
15–66, https://doi.org/10.1017/S002214300002921X, 1977.
Miesen, R., Parr, A., Schleu, J., and Vossiek, M.: 360∘ carrier
phase measurement for UHF RFID local positioning, in: 2013 IEEE
International Conference on RFID-Technologies and Applications (RFID-TA),
2013 IEEE International Conference on RFID-Technologies and Applications
(RFID-TA), Johor Bahru, Malaysia, 4–5 September 2013, 00002, 1–6, https://doi.org/10.1109/RFID-TA.2013.6694499, 2013.
Mike Stanford: Use of Recco System to Locate Buried Roads in a Winter
Environment, in: Proceedings of the 1994 International Snow Science
Workshop, Snowbird, Utah, USA, 30 October–3 November 1994, 601–605, https://arc.lib.montana.edu/snow-science/item/1379 (last access: 26 July 2023), 1994.
Mondal, S., Kumar, D., and Chahal, P.: A Wireless Passive pH Sensor With
Clutter Rejection Scheme, IEEE Sens. J., 19, 3399–3407,
https://doi.org/10.1109/JSEN.2019.2893869, 2019.
Nikitin, P. V. and Rao, K. V. S.: Performance limitations of passive UHF
RFID systems, in: IEEE Antennas and Propagation Soc. Int. Symp., Albuquerque, NM, USA, 14 July 2006, 00285, https://doi.org/10.1109/APS.2006.1710704,
2006.
Nikitin, P. V., Martinez, R., Ramamurthy, S., Leland, H., Spiess, G., and
Rao, K. V. S.: Phase based spatial identification of UHF RFID tags, in: IEEE
Int. Conf. RFID, IEEE International Conference on RFID, Orlando, FL, USA, 16 April 2010,
00325, 102–109, https://doi.org/10.1109/RFID.2010.5467253, 2010.
Oldroyd, H. J., Higgins, C. W., Huwald, H., Selker, J. S., and Parlange, M.
B.: Thermal diffusivity of seasonal snow determined from temperature
profiles, Adv. Water Resour., 55, 121–130,
https://doi.org/10.1016/j.advwatres.2012.06.011, 2013.
Pirazzini, R., Leppänen, L., Picard, G., Lopez-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-Basel, 18, https://doi.org/10.3390/s18072016, 2018.
Proksch, M., Mätzler, C., Wiesmann, A., Lemmetyinen, J., Schwank, M., Löwe, H., and Schneebeli, M.: MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering, Geosci. Model Dev., 8, 2611–2626, https://doi.org/10.5194/gmd-8-2611-2015, 2015.
Reusser, D. E. and Zehe, E.: Low-cost monitoring of snow height and thermal
properties with inexpensive temperature sensors, Hydrol. Process., 25,
1841–1852, https://doi.org/10.1002/hyp.7937, 2011.
Royer, A., Roy, A., Jutras, S., and Langlois, A.: Review article: Performance assessment of radiation-based field sensors for monitoring the water equivalent of snow cover (SWE), The Cryosphere, 15, 5079–5098, https://doi.org/10.5194/tc-15-5079-2021, 2021.
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.
Schmid, L., Heilig, A., Mitterer, C., Schweizer, J., Maurer, H., Okorn, R.,
and Eisen, O.: Continuous snowpack monitoring using upward-looking
ground-penetrating radar technology, J. Glaciol., 60, 509–525,
https://doi.org/10.3189/2014JoG13J084, 2014.
Schmid, L., Koch, F., Heilig, A., Prasch, M., Eisen, O., Mauser, W., and
Schweizer, J.: A novel sensor combination (upGPR-GPS) to continuously and
nondestructively derive snow cover properties, Geophys. Res. Lett.,
42, 3397–3405, https://doi.org/10.1002/2015GL063732, 2015.
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.
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.
Techel, F. and Pielmeier, C.: Point observations of liquid water content in wet snow – investigating methodical, spatial and temporal aspects, The Cryosphere, 5, 405–418, https://doi.org/10.5194/tc-5-405-2011, 2011.
Tedesco, M.: Electromagnetic properties of components of the cryosphere, in:
Remote Sensing of the Cryosphere, Wiley, https://doi.org/10.1002/9781118368909.ch2, 2015.
Tedesco, M., Derksen, C., Deems, J. S., and Foster, J. L.: Remote sensing of
snow depth and snow water equivalent, in: Remote Sensing of the Cryosphere,
John Wiley & Sons, Ltd, 73–98,
https://doi.org/10.1002/9781118368909.ch5, 2014.
The Pandas Development Team: pandas-dev/pandas: Pandas,
Zenodo [software], https://doi.org/10.5281/zenodo.3509134, 2020.
Tiuri, M., Sihvola, A., Nyfors, E., and Hallikaiken, M.: The complex
dielectric constant of snow at microwave frequencies,
IEEE J. Oceanic Eng., 9, 377–382, https://doi.org/10.1109/JOE.1984.1145645,
1984.
Wagih, M. and Shi, J.: Wireless Ice Detection and Monitoring Using Flexible
UHF RFID Tags, IEEE Sens. J., 21, 18715–18724,
https://doi.org/10.1109/JSEN.2021.3087326, 2021.
Xu, J., Li, Z., Zhang, K., Yang, J., Gao, N., Zhang, Z., and Meng, Z.: The
Principle, Methods and Recent Progress in RFID Positioning Techniques: A
Review, IEEE Journal of Radio Frequency Identification, 7, 50–63,
https://doi.org/10.1109/JRFID.2022.3233855, 2023.
Short summary
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.
We monitor the amount of snow on the ground using passive radiofrequency identification (RFID)...
