Articles | Volume 16, issue 8
https://doi.org/10.5194/tc-16-3149-2022
© Author(s) 2022. 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-16-3149-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Aug 2022
Research article |
| 03 Aug 2022
| 03 Aug 2022
A data exploration tool for averaging and accessing large data sets of snow stratigraphy profiles useful for avalanche forecasting
Florian Herla
CORRESPONDING AUTHOR
Department of Geography, School of
Resource & Environmental Management, and Centre for Natural Hazards Research,
Simon Fraser University, Burnaby, BC, Canada
Pascal Haegeli
Department of Geography, School of
Resource & Environmental Management, and Centre for Natural Hazards Research,
Simon Fraser University, Burnaby, BC, Canada
Patrick Mair
Department of Psychology, Harvard University, Cambridge, MA, USA
Related authors
Florian Herla, Pascal Haegeli, Simon Horton, and Patrick Mair
EGUsphere, https://doi.org/10.5194/egusphere-2024-871, https://doi.org/10.5194/egusphere-2024-871, 2024
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We present a spatial framework for extracting information about avalanche problems from detailed snowpack simulations and compare the numerical results against operational assessments from avalanche forecasters. Despite good aggreement in seasonal summary statistics, a comparison of daily assessments revealed considerable differences while it remained unclear which data source represented reality best. We discuss how snowpack simulations can add value to the forecasting process.
Florian Herla, Pascal Haegeli, Simon Horton, and Patrick Mair
EGUsphere, https://doi.org/10.5194/egusphere-2023-420, https://doi.org/10.5194/egusphere-2023-420, 2023
Short summary
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Snowpack simulations are increasingly employed by avalanche warning services to inform about critical avalanche layers buried in the snowpack. However, validity concerns limit their operational value. We present methods that enable meaningful comparisons between snowpack simulations and regional assessments of avalanche forecasters to quantify the performance of the Canadian weather and snowpack model chain to represent thin critical avalanche layers on a large scale and in real-time.
Florian Herla, Simon Horton, Patrick Mair, and Pascal Haegeli
Geosci. Model Dev., 14, 239–258, https://doi.org/10.5194/gmd-14-239-2021, https://doi.org/10.5194/gmd-14-239-2021, 2021
Short summary
Short summary
The adoption of snowpack models in support of avalanche forecasting has been limited. To promote their operational application, we present a numerical method for processing multivariate snow stratigraphy profiles of mixed data types. Our algorithm enables applications like dynamical grouping and summarizing of model simulations, model evaluation, and data assimilation. By emulating the human analysis process, our approach will allow forecasters to familiarly interact with snowpack simulations.
Florian Herla, Pascal Haegeli, Simon Horton, and Patrick Mair
EGUsphere, https://doi.org/10.5194/egusphere-2024-871, https://doi.org/10.5194/egusphere-2024-871, 2024
Short summary
Short summary
We present a spatial framework for extracting information about avalanche problems from detailed snowpack simulations and compare the numerical results against operational assessments from avalanche forecasters. Despite good aggreement in seasonal summary statistics, a comparison of daily assessments revealed considerable differences while it remained unclear which data source represented reality best. We discuss how snowpack simulations can add value to the forecasting process.
John Sykes, Håvard Toft, Pascal Haegeli, and Grant Statham
Nat. Hazards Earth Syst. Sci., 24, 947–971, https://doi.org/10.5194/nhess-24-947-2024, https://doi.org/10.5194/nhess-24-947-2024, 2024
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The research validates and optimizes an automated approach for creating classified snow avalanche terrain maps using open-source geospatial modeling tools. Validation is based on avalanche-expert-based maps for two study areas. Our results show that automated maps have an overall accuracy equivalent to the average accuracy of three human maps. Automated mapping requires a fraction of the time and cost of traditional methods and opens the door for large-scale mapping of mountainous terrain.
Abby Morgan, Pascal Haegeli, Henry Finn, and Patrick Mair
Nat. Hazards Earth Syst. Sci., 23, 1719–1742, https://doi.org/10.5194/nhess-23-1719-2023, https://doi.org/10.5194/nhess-23-1719-2023, 2023
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The avalanche danger scale is a critical component for communicating the severity of avalanche hazard conditions to the public. We examine how backcountry recreationists in North America understand and use the danger scale for planning trips into the backcountry. Our results provide an important user perspective on the strengths and weaknesses of the existing scale and highlight opportunities for future improvements.
Florian Herla, Pascal Haegeli, Simon Horton, and Patrick Mair
EGUsphere, https://doi.org/10.5194/egusphere-2023-420, https://doi.org/10.5194/egusphere-2023-420, 2023
Short summary
Short summary
Snowpack simulations are increasingly employed by avalanche warning services to inform about critical avalanche layers buried in the snowpack. However, validity concerns limit their operational value. We present methods that enable meaningful comparisons between snowpack simulations and regional assessments of avalanche forecasters to quantify the performance of the Canadian weather and snowpack model chain to represent thin critical avalanche layers on a large scale and in real-time.
John Sykes, Pascal Haegeli, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 3247–3270, https://doi.org/10.5194/nhess-22-3247-2022, https://doi.org/10.5194/nhess-22-3247-2022, 2022
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Automated snow avalanche terrain mapping provides an efficient method for large-scale assessment of avalanche hazards, which informs risk management decisions for transportation and recreation. This research reduces the cost of developing avalanche terrain maps by using satellite imagery and open-source software as well as improving performance in forested terrain. The research relies on local expertise to evaluate accuracy, so the methods are broadly applicable in mountainous regions worldwide.
Simon Horton and Pascal Haegeli
The Cryosphere, 16, 3393–3411, https://doi.org/10.5194/tc-16-3393-2022, https://doi.org/10.5194/tc-16-3393-2022, 2022
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Snowpack models can help avalanche forecasters but are difficult to verify. We present a method for evaluating the accuracy of simulated snow profiles using readily available observations of snow depth. This method could be easily applied to understand the representativeness of available observations, the agreement between modelled and observed snow depths, and the implications for interpreting avalanche conditions.
Kathryn C. Fisher, Pascal Haegeli, and Patrick Mair
Nat. Hazards Earth Syst. Sci., 22, 1973–2000, https://doi.org/10.5194/nhess-22-1973-2022, https://doi.org/10.5194/nhess-22-1973-2022, 2022
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Avalanche bulletins include travel and terrain statements to provide recreationists with tangible guidance about how to apply the hazard information. We examined which bulletin users pay attention to these statements, what determines their usefulness, and how they could be improved. Our study shows that reducing jargon and adding simple explanations can significantly improve the usefulness of the statements for users with lower levels of avalanche awareness education who depend on this advice.
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, https://doi.org/10.5194/nhess-22-985-2022, 2022
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To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
Kathryn C. Fisher, Pascal Haegeli, and Patrick Mair
Nat. Hazards Earth Syst. Sci., 21, 3219–3242, https://doi.org/10.5194/nhess-21-3219-2021, https://doi.org/10.5194/nhess-21-3219-2021, 2021
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Avalanche warning services publish condition reports to help backcountry recreationists make informed decisions about when and where to travel in avalanche terrain. We tested how different graphic representations of terrain information can affect users’ ability to interpret and apply the provided information. Our study shows that a combined presentation of aspect and elevation information is the most effective. These results can be used to improve avalanche risk communication products.
Pascal Haegeli, Bret Shandro, and Patrick Mair
The Cryosphere, 15, 1567–1586, https://doi.org/10.5194/tc-15-1567-2021, https://doi.org/10.5194/tc-15-1567-2021, 2021
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Numerous large-scale atmosphere–ocean oscillations including the El Niño–Southern Oscillation, the Pacific Decadal Oscillation, the Pacific North American Teleconnection Pattern, and the Arctic Oscillation are known to substantially affect winter weather patterns in western Canada. Using avalanche problem information from public avalanche bulletins, this study presents a new approach for examining the effect of these atmospheric oscillations on the nature of avalanche hazard in western Canada.
Florian Herla, Simon Horton, Patrick Mair, and Pascal Haegeli
Geosci. Model Dev., 14, 239–258, https://doi.org/10.5194/gmd-14-239-2021, https://doi.org/10.5194/gmd-14-239-2021, 2021
Short summary
Short summary
The adoption of snowpack models in support of avalanche forecasting has been limited. To promote their operational application, we present a numerical method for processing multivariate snow stratigraphy profiles of mixed data types. Our algorithm enables applications like dynamical grouping and summarizing of model simulations, model evaluation, and data assimilation. By emulating the human analysis process, our approach will allow forecasters to familiarly interact with snowpack simulations.
Simon Horton, Moses Towell, and Pascal Haegeli
Nat. Hazards Earth Syst. Sci., 20, 3551–3576, https://doi.org/10.5194/nhess-20-3551-2020, https://doi.org/10.5194/nhess-20-3551-2020, 2020
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We investigate patterns in how avalanche forecasters characterize snow avalanche hazard with avalanche problem types. Decision tree analysis was used to investigate both physical influences based on weather and on snowpack variables and operational practices. The results highlight challenges with developing decision aids based on previous hazard assessments.
Simon Horton, Stan Nowak, and Pascal Haegeli
Nat. Hazards Earth Syst. Sci., 20, 1557–1572, https://doi.org/10.5194/nhess-20-1557-2020, https://doi.org/10.5194/nhess-20-1557-2020, 2020
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Numeric snowpack models currently offer limited value to operational avalanche forecasters. To improve the relevance and interpretability of model data, we introduce and discuss visualization principles that map model data into visual representations that can inform avalanche hazard assessments.
Reto Sterchi, Pascal Haegeli, and Patrick Mair
Nat. Hazards Earth Syst. Sci., 19, 2011–2026, https://doi.org/10.5194/nhess-19-2011-2019, https://doi.org/10.5194/nhess-19-2011-2019, 2019
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Mechanized skiing operations use an established process to select skiing terrain with a low risk level. However, the relationship between appropriate skiing terrain and avalanche conditions has only received limited research attention. Our study examines this relationship numerically for the first time and shows the effects of avalanche hazard, previous skiing, and previous acceptability on different types of skiing terrain and offers the foundation to develop evidence-based decision tools.
Reto Sterchi and Pascal Haegeli
Nat. Hazards Earth Syst. Sci., 19, 269–285, https://doi.org/10.5194/nhess-19-269-2019, https://doi.org/10.5194/nhess-19-269-2019, 2019
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We used a revealed preference approach and identified patterns in risk management decisions of mechanized skiing operations. Our results show that terrain choices of experienced guides depend on a much broader set of factors beyond just the avalanche hazard, including skiing experience or accessibility due to weather. The identified high-resolution ski run hierarchies provide new opportunities for examining professional avalanche risk management practices and developing meaningful decision aids.
Bret Shandro and Pascal Haegeli
Nat. Hazards Earth Syst. Sci., 18, 1141–1158, https://doi.org/10.5194/nhess-18-1141-2018, https://doi.org/10.5194/nhess-18-1141-2018, 2018
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While the concept of snow and avalanche climates is widely used to describe the general nature of avalanche hazard, no research has described the hazard character of avalanche climates in detail. We use Canadian avalanche bulletin data that use the conceptual model of avalanche hazard from 2009/2010 to 2016/2017 to identify common hazard situations and calculate their seasonal prevalence. Our results provide detailed insights into the nature and variability of avalanche hazard in western Canada.
Related subject area
Discipline: Snow | Subject: Numerical Modelling
Regime shifts in Arctic terrestrial hydrology manifested from impacts of climate warming
Exploring the sensitivity to precipitation, blowing snow, and horizontal resolution of the spatial distribution of simulated snow cover
Snow redistribution in an intermediate-complexity snow hydrology modelling framework
Microstructure-based modelling of snow mechanics: experimental evaluation on the cone penetration test
Snow cover prediction in the Italian central Apennines using weather forecast and land surface numerical models
Land–atmosphere interactions in sub-polar and alpine climates in the CORDEX flagship pilot study Land Use and Climate Across Scales (LUCAS) models – Part 1: Evaluation of the snow-albedo effect
Elements of future snowpack modeling – Part 1: A physical instability arising from the nonlinear coupling of transport and phase changes
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Assessment of neutrons from secondary cosmic rays at mountain altitudes – Geant4 simulations of environmental parameters including soil moisture and snow cover
A seasonal algorithm of the snow-covered area fraction for mountainous terrain
Snow cover duration trends observed at sites and predicted by multiple models
Deep ice layer formation in an alpine snowpack: monitoring and modeling
Multi-physics ensemble snow modelling in the western Himalaya
Micromechanical modeling of snow failure
Changing characteristics of runoff and freshwater export from watersheds draining northern Alaska
Winter tourism under climate change in the Pyrenees and the French Alps: relevance of snowmaking as a technical adaptation
A simulation of a large-scale drifting snowstorm in the turbulent boundary layer
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Michael A. Rawlins and Ambarish V. Karmalkar
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Flows of water, carbon, and materials by Arctic rivers are being altered by climate warming. We used simulations from a permafrost hydrology model to investigate future changes in quantities influencing river exports. By 2100 Arctic rivers will receive more runoff from the far north where abundant soil carbon can leach in. More water will enter them via subsurface pathways particularly in summer and autumn. An enhanced water cycle and permafrost thaw are changing river flows to coastal areas.
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamp-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
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Our study addresses the complex challenge of evaluating distributed alpine snow simulations by disentangling error contributions between blowing snow, precipitation forcings and unresolved subgrid variability. We evaluated simulated snow cover against snow depths from Pléiades stereo-imagery and Snow Melt-Out Dates from Sentinel 2. The simulation of snow transport enhances the snow spatial variance at high elevations while precipitation biases are the prevailing error source in other areas.
Louis Quéno, Rebecca Mott, Paul Morin, Bertrand Cluzet, Giulia Mazzotti, and Tobias Jonas
EGUsphere, https://doi.org/10.5194/egusphere-2023-2071, https://doi.org/10.5194/egusphere-2023-2071, 2023
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Snow redistribution by wind and avalanches strongly influences snow hydrology in mountains. This study presents a novel modelling approach to best represent these processes in an operational context. The evaluation of the simulations against airborne snow depth measurements showed a remarkable improvement of the snow distribution in mountains of the Eastern Swiss Alps, with a representation of snow accumulation and erosion areas, suggesting promising benefits for operational snow melt forecasts.
Clémence Herny, Pascal Hagenmuller, Guillaume Chambon, Isabel Peinke, and Jacques Roulle
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-30, https://doi.org/10.5194/tc-2023-30, 2023
Revised manuscript accepted for TC
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This paper presents the development of a numerical model to study the mechanical behaviour of snow at microscale. The numerical model has shown good capabilities to reproduce experimental Cone Penetration Test measurements. It is a promising tool for future investigation to better characterise the snow material. Applications of the numerical model are various such as snowpack characterisation, high resolution snow force profile interpretation or avalanches forecasting for instance.
Edoardo Raparelli, Paolo Tuccella, Valentina Colaiuda, and Frank S. Marzano
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We evaluate the skills of a single-layer (Noah) and a multi-layer (Alpine3D) snow model, forced with the Weather Research and Forecasting model, to reproduce snowpack properties observed in the Italian central Apennines. We found that Alpine3D reproduces the observed snow height and snow water equivalent better than Noah, while no particular model differences emerge on snow cover extent. Finally, we observed that snow settlement is mainly due to densification in Alpine3D and to melting in Noah.
Anne Sophie Daloz, Clemens Schwingshackl, Priscilla Mooney, Susanna Strada, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Michal Belda, Tomas Halenka, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 2403–2419, https://doi.org/10.5194/tc-16-2403-2022, https://doi.org/10.5194/tc-16-2403-2022, 2022
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Snow plays a major role in the regulation of the Earth's surface temperature. Together with climate change, rising temperatures are already altering snow in many ways. In this context, it is crucial to better understand the ability of climate models to represent snow and snow processes. This work focuses on Europe and shows that the melting season in spring still represents a challenge for climate models and that more work is needed to accurately simulate snow–atmosphere interactions.
Konstantin Schürholt, Julia Kowalski, and Henning Löwe
The Cryosphere, 16, 903–923, https://doi.org/10.5194/tc-16-903-2022, https://doi.org/10.5194/tc-16-903-2022, 2022
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This companion paper deals with numerical particularities of partial differential equations underlying 1D snow models. In this first part we neglect mechanical settling and demonstrate that the nonlinear coupling between diffusive transport (heat and vapor), phase changes and ice mass conservation contains a wave instability that may be relevant for weak layer formation. Numerical requirements are discussed in view of the underlying homogenization scheme.
Anna Simson, Henning Löwe, and Julia Kowalski
The Cryosphere, 15, 5423–5445, https://doi.org/10.5194/tc-15-5423-2021, https://doi.org/10.5194/tc-15-5423-2021, 2021
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This companion paper deals with numerical particularities of partial differential equations underlying one-dimensional snow models. In this second part we include mechanical settling and develop a new hybrid (Eulerian–Lagrangian) method for solving the advection-dominated ice mass conservation on a moving mesh alongside Eulerian diffusion (heat and vapor) and phase changes. The scheme facilitates a modular and extendable solver strategy while retaining controls on numerical accuracy.
Thomas Brall, Vladimir Mares, Rolf Bütikofer, and Werner Rühm
The Cryosphere, 15, 4769–4780, https://doi.org/10.5194/tc-15-4769-2021, https://doi.org/10.5194/tc-15-4769-2021, 2021
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Neutrons from secondary cosmic rays, measured at 2660 m a.s.l. at Zugspitze, Germany, are highly affected by the environment, in particular by snow, soil moisture, and mountain shielding. To quantify these effects, computer simulations were carried out, including a sensitivity analysis on snow depth and soil moisture. This provides a possibility for snow depth estimation based on the measured number of secondary neutrons. This method was applied at Zugspitze in 2018.
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
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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.
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
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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.
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
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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.
David M. W. Pritchard, Nathan Forsythe, Greg O'Donnell, Hayley J. Fowler, and Nick Rutter
The Cryosphere, 14, 1225–1244, https://doi.org/10.5194/tc-14-1225-2020, https://doi.org/10.5194/tc-14-1225-2020, 2020
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This study compares different snowpack model configurations applied in the western Himalaya. The results show how even sparse local observations can help to delineate climate input errors from model structure errors, which provides insights into model performance variation. The results also show how interactions between processes affect sensitivities to climate variability in different model configurations, with implications for model selection in climate change projections.
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
Michael A. Rawlins, Lei Cai, Svetlana L. Stuefer, and Dmitry Nicolsky
The Cryosphere, 13, 3337–3352, https://doi.org/10.5194/tc-13-3337-2019, https://doi.org/10.5194/tc-13-3337-2019, 2019
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We investigate the changing character of runoff, river discharge and other hydrological elements across watershed draining the North Slope of Alaska over the period 1981–2010. Our synthesis of observations and modeling reveals significant increases in the proportion of subsurface runoff and cold season discharge. These and other changes we describe are consistent with warming and thawing permafrost, and have implications for water, carbon and nutrient cycling in coastal environments.
Pierre Spandre, Hugues François, Deborah Verfaillie, Marc Pons, Matthieu Vernay, Matthieu Lafaysse, Emmanuelle George, and Samuel Morin
The Cryosphere, 13, 1325–1347, https://doi.org/10.5194/tc-13-1325-2019, https://doi.org/10.5194/tc-13-1325-2019, 2019
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This study investigates the snow reliability of 175 ski resorts in the Pyrenees (France, Spain and Andorra) and the French Alps under past and future conditions (1950–2100) using state-of-the-art climate projections and snowpack modelling accounting for snow management, i.e. grooming and snowmaking. The snow reliability of ski resorts shows strong elevation and regional differences, and our study quantifies changes in snow reliability induced by snowmaking under various climate scenarios.
Zhengshi Wang and Shuming Jia
The Cryosphere, 12, 3841–3851, https://doi.org/10.5194/tc-12-3841-2018, https://doi.org/10.5194/tc-12-3841-2018, 2018
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Drifting snowstorms that are hundreds of meters in depth are reproduced using a large-eddy simulation model combined with a Lagrangian particle tracking method, which also exhibits obvious spatial structures following large-scale turbulent vortexes. The horizontal snow transport flux at high altitude, previously not observed, actually occupies a significant proportion of the total flux. Thus, previous models may largely underestimate the total mass flux and consequently snow sublimation.
Franziska Gerber, Nikola Besic, Varun Sharma, Rebecca Mott, Megan Daniels, Marco Gabella, Alexis Berne, Urs Germann, and Michael Lehning
The Cryosphere, 12, 3137–3160, https://doi.org/10.5194/tc-12-3137-2018, https://doi.org/10.5194/tc-12-3137-2018, 2018
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A comparison of winter precipitation variability in operational radar measurements and high-resolution simulations reveals that large-scale variability is well captured by the model, depending on the event. Precipitation variability is driven by topography and wind. A good portion of small-scale variability is captured at the highest resolution. This is essential to address small-scale precipitation processes forming the alpine snow seasonal snow cover – an important source of water.
Edward H. Bair, Andre Abreu Calfa, Karl Rittger, and Jeff Dozier
The Cryosphere, 12, 1579–1594, https://doi.org/10.5194/tc-12-1579-2018, https://doi.org/10.5194/tc-12-1579-2018, 2018
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In Afghanistan, almost no snow measurements exist. Operational estimates use measurements from satellites, but all have limitations. We have developed a satellite-based technique called reconstruction that accurately estimates the snowpack retrospectively. To solve the problem of estimating today's snowpack, we used machine learning, trained on our reconstructed snow estimates, using predictors that are available today. Our results show low errors, demonstrating the utility of this approach.
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Short summary
We present an averaging algorithm for multidimensional snow stratigraphy profiles that elicits the predominant snow layering among large numbers of profiles and allows for compiling of informative summary statistics and distributions of snowpack layer properties. This creates new opportunities for presenting and analyzing operational snowpack simulations in support of avalanche forecasting and may inspire new ways of processing profiles and time series in other geophysical contexts.
We present an averaging algorithm for multidimensional snow stratigraphy profiles that elicits...
