Articles | Volume 24, issue 8
https://doi.org/10.5194/nhess-24-2727-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-2727-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers
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
Simon Horton
Avalanche Canada, Revelstoke, BC, Canada
Patrick Mair
Department of Psychology, Harvard University, Cambridge, MA, USA
Related authors
Simon Horton, Florian Herla, and Pascal Haegeli
EGUsphere, https://doi.org/10.5194/egusphere-2024-1609, https://doi.org/10.5194/egusphere-2024-1609, 2024
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We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, location, and time. Tested in the Columbia Mountains during winter 2022–23, it accurately matched real forecast regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.
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
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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, and Patrick Mair
The Cryosphere, 16, 3149–3162, https://doi.org/10.5194/tc-16-3149-2022, https://doi.org/10.5194/tc-16-3149-2022, 2022
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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.
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
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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.
John Sykes, Pascal Haegeli, Roger Atkins, Patrick Mair, and Yves Bühler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-147, https://doi.org/10.5194/nhess-2024-147, 2024
Preprint under review for NHESS
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We develop decision support tools to assist professional ski guides in determining safe terrain each day based on current conditions. To understand the decision-making process we collaborate with professional guides and build three unique models to predict their decisions. The models accurately capture the real world decision-making outcomes in 85–93 % of cases. Our conclusions focus on strengths and weaknesses of each model and discuss ramifications for practical applications in ski guiding.
Simon Horton, Florian Herla, and Pascal Haegeli
EGUsphere, https://doi.org/10.5194/egusphere-2024-1609, https://doi.org/10.5194/egusphere-2024-1609, 2024
Short summary
Short summary
We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, location, and time. Tested in the Columbia Mountains during winter 2022–23, it accurately matched real forecast regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.
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
Short summary
Short summary
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.
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.
Florian Herla, Pascal Haegeli, and Patrick Mair
The Cryosphere, 16, 3149–3162, https://doi.org/10.5194/tc-16-3149-2022, https://doi.org/10.5194/tc-16-3149-2022, 2022
Short summary
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.
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.
S. Horton, M. Schirmer, and B. Jamieson
The Cryosphere, 9, 1523–1533, https://doi.org/10.5194/tc-9-1523-2015, https://doi.org/10.5194/tc-9-1523-2015, 2015
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We investigate how various meteorological and terrain factors affect surface hoar formation in complex terrain. We modelled the distribution of three surface hoar layers with a coupled NWP - snow cover model, and verified the model with field studies. The layers developed in regions and elevation bands with warm moist air, light winds, and cold snow surfaces. Possible avalanche forecasting applications are discussed.
Related subject area
Other Hazards (e.g., Glacial and Snow Hazards, Karst, Wildfires Hazards, and Medical Geo-Hazards)
Statistical calibration of probabilistic medium-range Fire Weather Index forecasts in Europe
Glide-snow avalanches: a mechanical, threshold-based release area model
Improving fire severity prediction in south-eastern Australia using vegetation-specific information
Review article: A scoping review of human factors in avalanche decision-making
How hard do avalanche practitioners tap during snow stability tests?
A glacial lake outburst flood risk assessment for the Phochhu river basin, Bhutan
Modelling Current and Future Forest Fire Susceptibility in north-east Germany
AutoATES v2.0: Automated Avalanche Terrain Exposure Scale mapping
Modelling the vulnerability of urban settings to wildland–urban interface fires in Chile
Modeling of indoor 222Rn in data-scarce regions: an interactive dashboard approach for Bogotá, Colombia
A quantitative module of avalanche hazard—comparing forecaster assessments of storm and persistent slab avalanche problems with information derived from distributed snowpack simulations
The effect of propagation saw test geometries on critical cut length
A regional early warning for slushflow hazard
A new approach for drought index adjustment to clay-shrinkage-induced subsidence over France: advantages of the interactive leaf area index
Automated Avalanche Terrain Exposure Scale (ATES) mapping – local validation and optimization in western Canada
An Efficient Method to Simulate Wildfire Propagation Using Irregular Grids
Improving the fire weather index system for peatlands using peat-specific hydrological input data
Brief communication: The Lahaina Fire disaster – how models can be used to understand and predict wildfires
Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations
Early warning system for ice collapses and river blockages in the Sedongpu Valley, southeastern Tibetan Plateau
Fire risk modeling: an integrated and data-driven approach applied to Sicily
Avalanche size estimation and avalanche outline determination by experts: reliability and implications for practice
Fluid conduits and shallow-reservoir structure defined by geoelectrical tomography at the Nirano Salse (Italy)
Estimating the effects of meteorology and land cover on fire growth in Peru using a novel difference equation model
Review article: Snow and ice avalanches in high mountain Asia – scientific, local and indigenous knowledge
Reduced-order digital twin and latent data assimilation for global wildfire prediction
A user perspective on the avalanche danger scale – insights from North America
Characterizing the rate of spread of large wildfires in emerging fire environments of northwestern Europe using Visible Infrared Imaging Radiometer Suite active fire data
Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts
Temporal evolution of crack propagation characteristics in a weak snowpack layer: conditions of crack arrest and sustained propagation
A data-driven model for Fennoscandian wildfire danger
Equivalent hazard magnitude scale
Statistical modelling of air quality impacts from individual forest fires in New South Wales, Australia
Drivers of extreme burnt area in Portugal: fire weather and vegetation
Coupling wildfire spread simulations and connectivity analysis for hazard assessment: a case study in Serra da Cabreira, Portugal
Glacial lake outburst flood hazard under current and future conditions: worst-case scenarios in a transboundary Himalayan basin
What weather variables are important for wet and slab avalanches under a changing climate in a low-altitude mountain range in Czechia?
Modelling ignition probability for human- and lightning-caused wildfires in Victoria, Australia
Automated snow avalanche release area delineation in data-sparse, remote, and forested regions
The 2017 Split wildfire in Croatia: evolution and the role of meteorological conditions
Progress and challenges in glacial lake outburst flood research (2017–2021): a research community perspective
Global assessment and mapping of ecological vulnerability to wildfires
The impact of terrain model source and resolution on snow avalanche modeling
Travel and terrain advice statements in public avalanche bulletins: a quantitative analysis of who uses this information, what makes it useful, and how it can be improved for users
Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland
On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger
Automated avalanche hazard indication mapping on a statewide scale
Forecasting the regional fire radiative power for regularly ignited vegetation fires
Environmental factors affecting wildfire-burned areas in southeastern France, 1970–2019
Detrainment and braking of snow avalanches interacting with forests
Stephanie Bohlmann and Marko Laine
Nat. Hazards Earth Syst. Sci., 24, 4225–4235, https://doi.org/10.5194/nhess-24-4225-2024, https://doi.org/10.5194/nhess-24-4225-2024, 2024
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Probabilistic ensemble forecasts of the Canadian Forest Fire Weather Index (FWI) can be used to estimate the possible wildfire risk but require post-processing to provide accurate and reliable predictions. This article presents a calibration method using non-homogeneous Gaussian regression to statistically post-process FWI forecasts up to 15 d. Calibration improves the forecast especially at short lead times and in regions with high fire risk.
Amelie Fees, Alec van Herwijnen, Michael Lombardo, Jürg Schweizer, and Peter Lehmann
Nat. Hazards Earth Syst. Sci., 24, 3387–3400, https://doi.org/10.5194/nhess-24-3387-2024, https://doi.org/10.5194/nhess-24-3387-2024, 2024
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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 uniformity, while the variations in snowpack properties had little influence.
Kang He, Xinyi Shen, Cory Merow, Efthymios Nikolopoulos, Rachael V. Gallagher, Feifei Yang, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 24, 3337–3355, https://doi.org/10.5194/nhess-24-3337-2024, https://doi.org/10.5194/nhess-24-3337-2024, 2024
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A framework combining a fire severity classification with a regression model to predict an indicator of fire severity derived from Landsat imagery (difference normalized burning ratio, dNBR) is proposed. The results show that the proposed predictive technique is capable of providing robust fire severity prediction information, which can be used for forecasting seasonal fire severity and, subsequently, impacts on biodiversity and ecosystems under projected future climate conditions.
Audun Hetland, Rebecca Anne Hetland, Tarjei Tveito Skille, and Andrea Mannberg
EGUsphere, https://doi.org/10.5194/egusphere-2024-1628, https://doi.org/10.5194/egusphere-2024-1628, 2024
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Research on human factor in avalanche decision making has become increasingly popular the past two decades. The studies span across a wide range of disciplines and is published in a variety of journals. To provide an overview of the literature this study provide a systematic scooping review of human factor in avalanche decision making. 70 papers fulfilled the search criteria. We extracted data and sorted the papers according to their main theme.
Håvard B. Toft, Samuel V. Verplanck, and Markus Landrø
Nat. Hazards Earth Syst. Sci., 24, 2757–2772, https://doi.org/10.5194/nhess-24-2757-2024, https://doi.org/10.5194/nhess-24-2757-2024, 2024
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This study investigates inconsistencies in impact force as part of extended column tests (ECTs). We measured force-time curves from 286 practitioners in Scandinavia, Central Europe, and North America. The results show a large variability in peak forces and loading rates across wrist, elbow, and shoulder taps, challenging the ECT's reliability.
Tandin Wangchuk and Ryota Tsubaki
Nat. Hazards Earth Syst. Sci., 24, 2523–2540, https://doi.org/10.5194/nhess-24-2523-2024, https://doi.org/10.5194/nhess-24-2523-2024, 2024
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A glacial lake outburst flood (GLOF) is a natural hazard in which water from a glacier-fed lake is swiftly discharged, causing serious harm to life, infrastructure, and communities. We used numerical models to predict the potential consequences of a GLOF originating from the Thorthomi glacial lake in Bhutan. We found that if a GLOF occurs, the lake could release massive flood water within 4 h, posing a considerable risk. Study findings help to mitigate the impacts of future GLOFs.
Katharina Heike Horn, Stenka Vulova, Hanyu Li, and Birgit Kleinschmit
EGUsphere, https://doi.org/10.5194/egusphere-2024-1380, https://doi.org/10.5194/egusphere-2024-1380, 2024
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In this study we applied Random Forest machine learning algorithm to model current and future forest fire susceptibility (FFS) in north-east Germany using anthropogenic, climatic, topographic, soil, and vegetation variables. Model accuracy ranged between 69 % to 71 % showing a moderately high model reliability for predicting FFS. The model results underline the importance of anthropogenic and vegetation parameters for FFS. This study will support regional forest fire prevention and management.
Håvard B. Toft, John Sykes, Andrew Schauer, Jordy Hendrikx, and Audun Hetland
Nat. Hazards Earth Syst. Sci., 24, 1779–1793, https://doi.org/10.5194/nhess-24-1779-2024, https://doi.org/10.5194/nhess-24-1779-2024, 2024
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Manual Avalanche Terrain Exposure Scale (ATES) mapping is time-consuming and inefficient for large-scale applications. The updated algorithm for automated ATES mapping overcomes previous limitations by including forest density data, improving the avalanche runout estimations in low-angle runout zones, accounting for overhead exposure and open-source software. Results show that the latest version has significantly improved its performance.
Paula Aguirre, Jorge León, Constanza González-Mathiesen, Randy Román, Manuela Penas, and Alonso Ogueda
Nat. Hazards Earth Syst. Sci., 24, 1521–1537, https://doi.org/10.5194/nhess-24-1521-2024, https://doi.org/10.5194/nhess-24-1521-2024, 2024
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Wildfires pose a significant risk to property located in the wildland–urban interface (WUI). To assess and mitigate this risk, we need to understand which characteristics of buildings and building arrangements make them more prone to damage. We used a combination of data collection and analysis methods to study the vulnerability of dwellings in the WUI for case studies in Chile and concluded that the spatial arrangement of houses has a substantial impact on their vulnerability to wildfires.
Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet
Nat. Hazards Earth Syst. Sci., 24, 1319–1339, https://doi.org/10.5194/nhess-24-1319-2024, https://doi.org/10.5194/nhess-24-1319-2024, 2024
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In this study we created a cost-effective alternative to bridge the baseline information gap on indoor radon (a highly carcinogenic gas) in regions where measurements are scarce. We model indoor radon concentrations to understand its spatial distribution and the potential influential factors. We evaluated the performance of this alternative using a small number of measurements taken in Bogotá, Colombia. Our results show that this alternative could help in the making of future studies and policy.
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.
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
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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.
Monica Sund, Heidi A. Grønsten, and Siv Å. Seljesæter
Nat. Hazards Earth Syst. Sci., 24, 1185–1201, https://doi.org/10.5194/nhess-24-1185-2024, https://doi.org/10.5194/nhess-24-1185-2024, 2024
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Slushflows are rapid mass movements of water-saturated snow released in gently sloping terrain (< 30°), often unexpectedly. Early warning is crucial to prevent casualties and damage to infrastructure. A regional early warning for slushflow hazard was established in Norway in 2013–2014 and has been operational since. We present a methodology using the ratio between water supply and snow depth by snow type to assess slushflow hazard. This approach is useful for other areas with slushflow hazard.
Sophie Barthelemy, Bertrand Bonan, Jean-Christophe Calvet, Gilles Grandjean, David Moncoulon, Dorothée Kapsambelis, and Séverine Bernardie
Nat. Hazards Earth Syst. Sci., 24, 999–1016, https://doi.org/10.5194/nhess-24-999-2024, https://doi.org/10.5194/nhess-24-999-2024, 2024
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This work presents a drought index specifically adapted to subsidence, a seasonal phenomenon of soil shrinkage that occurs frequently in France and damages buildings. The index is computed from land surface model simulations and evaluated by a rank correlation test with insurance data. With its optimal configuration, the index is able to identify years of both zero and significant loss.
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.
Conor Hackett, Rafael de Andrade Moral, Gourav Mishra, Tim McCarthy, and Charles Markham
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-27, https://doi.org/10.5194/nhess-2024-27, 2024
Revised manuscript under review for NHESS
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This paper reviews existing wildfire propagation models and a comparison of different grid types including random grids to simulate wildfires. This paper finds that irregular grids simulate wildfires more efficiently than continuous models while still retaining a reasonable level of similarity. It also shows that irregular grids tend to retain greater similarity to continuous models than regular grids at the cost of slightly longer computational times.
Jonas Mortelmans, Anne Felsberg, Gabriëlle J. M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, and Michel Bechtold
Nat. Hazards Earth Syst. Sci., 24, 445–464, https://doi.org/10.5194/nhess-24-445-2024, https://doi.org/10.5194/nhess-24-445-2024, 2024
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With global warming increasing the frequency and intensity of wildfires in the boreal region, accurate risk assessments are becoming more crucial than ever before. The Canadian Fire Weather Index (FWI) is a renowned system, yet its effectiveness in peatlands, where hydrology plays a key role, is limited. By incorporating groundwater data from numerical models and satellite observations, our modified FWI improves the accuracy of fire danger predictions, especially over summer.
Timothy W. Juliano, Fernando Szasdi-Bardales, Neil P. Lareau, Kasra Shamsaei, Branko Kosović, Negar Elhami-Khorasani, Eric P. James, and Hamed Ebrahimian
Nat. Hazards Earth Syst. Sci., 24, 47–52, https://doi.org/10.5194/nhess-24-47-2024, https://doi.org/10.5194/nhess-24-47-2024, 2024
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Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to understand the drivers of this devastating event. The simulation results show that extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making during wildfire 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
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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.
Wei Yang, Zhongyan Wang, Baosheng An, Yingying Chen, Chuanxi Zhao, Chenhui Li, Yongjie Wang, Weicai Wang, Jiule Li, Guangjian Wu, Lin Bai, Fan Zhang, and Tandong Yao
Nat. Hazards Earth Syst. Sci., 23, 3015–3029, https://doi.org/10.5194/nhess-23-3015-2023, https://doi.org/10.5194/nhess-23-3015-2023, 2023
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We present the structure and performance of the early warning system (EWS) for glacier collapse and river blockages in the southeastern Tibetan Plateau. The EWS warned of three collapse–river blockage chain events and seven small-scale events. The volume and location of the collapses and the percentage of ice content influenced the velocities of debris flows. Such a study is helpful for understanding the mechanism of glacier hazards and for establishing similar EWSs in other high-risk regions.
Alba Marquez Torres, Giovanni Signorello, Sudeshna Kumar, Greta Adamo, Ferdinando Villa, and Stefano Balbi
Nat. Hazards Earth Syst. Sci., 23, 2937–2959, https://doi.org/10.5194/nhess-23-2937-2023, https://doi.org/10.5194/nhess-23-2937-2023, 2023
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Only by mapping fire risks can we manage forest and prevent fires under current and future climate conditions. We present a fire risk map based on k.LAB, artificial-intelligence-powered and open-source software integrating multidisciplinary knowledge in near real time. Through an easy-to-use web application, we model the hazard with 84 % accuracy for Sicily, a representative Mediterranean region. Fire risk analysis reveals 45 % of vulnerable areas face a high probability of danger in 2050.
Elisabeth D. Hafner, Frank Techel, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 23, 2895–2914, https://doi.org/10.5194/nhess-23-2895-2023, https://doi.org/10.5194/nhess-23-2895-2023, 2023
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Oftentimes when objective measurements are not possible, human estimates are used instead. In our study, we investigate the reproducibility of human judgement for size estimates, the mappings of avalanches from oblique photographs and remotely sensed imagery. The variability that we found in those estimates is worth considering as it may influence results and should be kept in mind for several applications.
Gerardo Romano, Marco Antonellini, Domenico Patella, Agata Siniscalchi, Andrea Tallarico, Simona Tripaldi, and Antonello Piombo
Nat. Hazards Earth Syst. Sci., 23, 2719–2735, https://doi.org/10.5194/nhess-23-2719-2023, https://doi.org/10.5194/nhess-23-2719-2023, 2023
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The Nirano Salse (northern Apennines, Italy) is characterized by several active mud vents and hosts thousands of visitors every year. New resistivity models describe the area down to 250 m, improving our geostructural knowledge of the area and giving useful indications for a better understanding of mud volcano dynamics and for the better planning of safer tourist access to the area.
Harry Podschwit, William Jolly, Ernesto Alvarado, Andrea Markos, Satyam Verma, Sebastian Barreto-Rivera, Catherine Tobón-Cruz, and Blanca Ponce-Vigo
Nat. Hazards Earth Syst. Sci., 23, 2607–2624, https://doi.org/10.5194/nhess-23-2607-2023, https://doi.org/10.5194/nhess-23-2607-2023, 2023
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We developed a model of fire spread that assumes that fire spreads in all directions at a constant speed and is extinguished at a constant rate. The model was fitted to 1003 fires in Peru between 2001 and 2020 using satellite burned area data from the GlobFire project. We fitted statistical models that predicted the spread and extinguish rates based on weather and land cover variables and found that these variables were good predictors of the spread and extinguish rates.
Anushilan Acharya, Jakob F. Steiner, Khwaja Momin Walizada, Salar Ali, Zakir Hussain Zakir, Arnaud Caiserman, and Teiji Watanabe
Nat. Hazards Earth Syst. Sci., 23, 2569–2592, https://doi.org/10.5194/nhess-23-2569-2023, https://doi.org/10.5194/nhess-23-2569-2023, 2023
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All accessible snow and ice avalanches together with previous scientific research, local knowledge, and existing or previously active adaptation and mitigation solutions were investigated in the high mountain Asia (HMA) region to have a detailed overview of the state of knowledge and identify gaps. A comprehensive avalanche database from 1972–2022 is generated, including 681 individual events. The database provides a basis for the forecasting of avalanche hazards in different parts of HMA.
Caili Zhong, Sibo Cheng, Matthew Kasoar, and Rossella Arcucci
Nat. Hazards Earth Syst. Sci., 23, 1755–1768, https://doi.org/10.5194/nhess-23-1755-2023, https://doi.org/10.5194/nhess-23-1755-2023, 2023
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This paper introduces a digital twin fire model using machine learning techniques to improve the efficiency of global wildfire predictions. The proposed model also manages to efficiently adjust the prediction results thanks to data assimilation techniques. The proposed digital twin runs 500 times faster than the current state-of-the-art physics-based model.
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.
Adrián Cardíl, Victor M. Tapia, Santiago Monedero, Tomás Quiñones, Kerryn Little, Cathelijne R. Stoof, Joaquín Ramirez, and Sergio de-Miguel
Nat. Hazards Earth Syst. Sci., 23, 361–373, https://doi.org/10.5194/nhess-23-361-2023, https://doi.org/10.5194/nhess-23-361-2023, 2023
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This study aims to unravel large-fire behavior in northwest Europe, a temperate region with a projected increase in wildfire risk. We propose a new method to identify wildfire rate of spread from satellites because it is important to know periods of elevated fire risk for suppression methods and land management. Results indicate that there is a peak in the area burned and rate of spread in the months of March and April, and there are significant differences for forest-type land covers.
Liam S. Taylor, Duncan J. Quincey, and Mark W. Smith
Nat. Hazards Earth Syst. Sci., 23, 329–341, https://doi.org/10.5194/nhess-23-329-2023, https://doi.org/10.5194/nhess-23-329-2023, 2023
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Hazards from glaciers are becoming more likely as the climate warms, which poses a threat to communities living beneath them. We have developed a new camera system which can capture regular, high-quality 3D models to monitor small changes in glaciers which could be indicative of a future hazard. This system is far cheaper than more typical camera sensors yet produces very similar quality data. We suggest that deploying these cameras near glaciers could assist in warning communities of hazards.
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
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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.
Sigrid Jørgensen Bakke, Niko Wanders, Karin van der Wiel, and Lena Merete Tallaksen
Nat. Hazards Earth Syst. Sci., 23, 65–89, https://doi.org/10.5194/nhess-23-65-2023, https://doi.org/10.5194/nhess-23-65-2023, 2023
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In this study, we developed a machine learning model to identify dominant controls of wildfire in Fennoscandia and produce monthly fire danger probability maps. The dominant control was shallow-soil water anomaly, followed by air temperature and deep soil water. The model proved skilful with a similar performance as the existing Canadian Forest Fire Weather Index (FWI). We highlight the benefit of using data-driven models jointly with other fire models to improve fire monitoring and prediction.
Yi Victor Wang and Antonia Sebastian
Nat. Hazards Earth Syst. Sci., 22, 4103–4118, https://doi.org/10.5194/nhess-22-4103-2022, https://doi.org/10.5194/nhess-22-4103-2022, 2022
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In this article, we propose an equivalent hazard magnitude scale and a method to evaluate and compare the strengths of natural hazard events across different hazard types, including earthquakes, tsunamis, floods, droughts, forest fires, tornadoes, cold waves, heat waves, and tropical cyclones. With our method, we determine that both the February 2021 North American cold wave event and Hurricane Harvey in 2017 were equivalent to a magnitude 7.5 earthquake in hazard strength.
Michael A. Storey and Owen F. Price
Nat. Hazards Earth Syst. Sci., 22, 4039–4062, https://doi.org/10.5194/nhess-22-4039-2022, https://doi.org/10.5194/nhess-22-4039-2022, 2022
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Models are needed to understand and predict pollutant output from forest fires so fire agencies can reduce smoke-related risks to human health. We modelled air quality (PM2.5) based on fire area and weather variables. We found fire area and boundary layer height were influential on predictions, with distance, temperature, wind speed and relative humidity also important. The models predicted reasonably accurately in comparison to other existing methods but would benefit from further development.
Tomás Calheiros, Akli Benali, Mário Pereira, João Silva, and João Nunes
Nat. Hazards Earth Syst. Sci., 22, 4019–4037, https://doi.org/10.5194/nhess-22-4019-2022, https://doi.org/10.5194/nhess-22-4019-2022, 2022
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Fire weather indices are used to assess the effect of weather on wildfires. Fire weather risk was computed and combined with large wildfires in Portugal. Results revealed the influence of vegetation cover: municipalities with a prevalence of shrublands, located in eastern parts, burnt under less extreme conditions than those with higher forested areas, situated in coastal regions. These findings are a novelty for fire science in Portugal and should be considered for fire management.
Ana C. L. Sá, Bruno Aparicio, Akli Benali, Chiara Bruni, Michele Salis, Fábio Silva, Martinho Marta-Almeida, Susana Pereira, Alfredo Rocha, and José Pereira
Nat. Hazards Earth Syst. Sci., 22, 3917–3938, https://doi.org/10.5194/nhess-22-3917-2022, https://doi.org/10.5194/nhess-22-3917-2022, 2022
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Assessing landscape wildfire connectivity supported by wildfire spread simulations can improve fire hazard assessment and fuel management plans. Weather severity determines the degree of fuel patch connectivity and thus the potential to spread large and intense wildfires. Mapping highly connected patches in the landscape highlights patch candidates for prior fuel treatments, which ultimately will contribute to creating fire-resilient Mediterranean landscapes.
Simon K. Allen, Ashim Sattar, Owen King, Guoqing Zhang, Atanu Bhattacharya, Tandong Yao, and Tobias Bolch
Nat. Hazards Earth Syst. Sci., 22, 3765–3785, https://doi.org/10.5194/nhess-22-3765-2022, https://doi.org/10.5194/nhess-22-3765-2022, 2022
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This study demonstrates how the threat of a very large outburst from a future lake can be feasibly assessed alongside that from current lakes to inform disaster risk management within a transboundary basin between Tibet and Nepal. Results show that engineering measures and early warning systems would need to be coupled with effective land use zoning and programmes to strengthen local response capacities in order to effectively reduce the risk associated with current and future outburst events.
Markéta Součková, Roman Juras, Kryštof Dytrt, Vojtěch Moravec, Johanna Ruth Blöcher, and Martin Hanel
Nat. Hazards Earth Syst. Sci., 22, 3501–3525, https://doi.org/10.5194/nhess-22-3501-2022, https://doi.org/10.5194/nhess-22-3501-2022, 2022
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Avalanches are natural hazards that threaten people and infrastructure. With climate change, avalanche activity is changing. We analysed the change in frequency and size of avalanches in the Krkonoše Mountains, Czechia, and detected important variables with machine learning tools from 1979–2020. Wet avalanches in February and March have increased, and slab avalanches have decreased and become smaller. The identified variables and their threshold levels may help in avalanche decision-making.
Annalie Dorph, Erica Marshall, Kate A. Parkins, and Trent D. Penman
Nat. Hazards Earth Syst. Sci., 22, 3487–3499, https://doi.org/10.5194/nhess-22-3487-2022, https://doi.org/10.5194/nhess-22-3487-2022, 2022
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Wildfire spatial patterns are determined by fire ignition sources and vegetation fuel moisture. Fire ignitions can be mediated by humans (owing to proximity to human infrastructure) or caused by lightning (owing to fuel moisture, average annual rainfall and local weather). When moisture in dead vegetation is below 20 % the probability of a wildfire increases. The results of this research enable accurate spatial mapping of ignition probability to aid fire suppression efforts and future research.
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.
Ivana Čavlina Tomašević, Kevin K. W. Cheung, Višnjica Vučetić, Paul Fox-Hughes, Kristian Horvath, Maja Telišman Prtenjak, Paul J. Beggs, Barbara Malečić, and Velimir Milić
Nat. Hazards Earth Syst. Sci., 22, 3143–3165, https://doi.org/10.5194/nhess-22-3143-2022, https://doi.org/10.5194/nhess-22-3143-2022, 2022
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One of the most severe and impactful urban wildfire events in Croatian history has been reconstructed and analyzed. The study identified some important meteorological influences related to the event: the synoptic conditions of the Azores anticyclone, cold front, and upper-level shortwave trough all led to the highest fire weather index in 2017. A low-level jet, locally known as bura wind that can be explained by hydraulic jump theory, was the dynamic trigger of the event.
Adam Emmer, Simon K. Allen, Mark Carey, Holger Frey, Christian Huggel, Oliver Korup, Martin Mergili, Ashim Sattar, Georg Veh, Thomas Y. Chen, Simon J. Cook, Mariana Correas-Gonzalez, Soumik Das, Alejandro Diaz Moreno, Fabian Drenkhan, Melanie Fischer, Walter W. Immerzeel, Eñaut Izagirre, Ramesh Chandra Joshi, Ioannis Kougkoulos, Riamsara Kuyakanon Knapp, Dongfeng Li, Ulfat Majeed, Stephanie Matti, Holly Moulton, Faezeh Nick, Valentine Piroton, Irfan Rashid, Masoom Reza, Anderson Ribeiro de Figueiredo, Christian Riveros, Finu Shrestha, Milan Shrestha, Jakob Steiner, Noah Walker-Crawford, Joanne L. Wood, and Jacob C. Yde
Nat. Hazards Earth Syst. Sci., 22, 3041–3061, https://doi.org/10.5194/nhess-22-3041-2022, https://doi.org/10.5194/nhess-22-3041-2022, 2022
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Glacial lake outburst floods (GLOFs) have attracted increased research attention recently. In this work, we review GLOF research papers published between 2017 and 2021 and complement the analysis with research community insights gained from the 2021 GLOF conference we organized. The transdisciplinary character of the conference together with broad geographical coverage allowed us to identify progress, trends and challenges in GLOF research and outline future research needs and directions.
Fátima Arrogante-Funes, Inmaculada Aguado, and Emilio Chuvieco
Nat. Hazards Earth Syst. Sci., 22, 2981–3003, https://doi.org/10.5194/nhess-22-2981-2022, https://doi.org/10.5194/nhess-22-2981-2022, 2022
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We show that ecological value might be reduced by 50 % due to fire perturbation in ecosystems that have not developed in the presence of fire and/or that present changes in the fire regime. The biomes most affected are tropical and subtropical forests, tundra, and mangroves. Integration of biotic and abiotic fire regime and regeneration factors resulted in a powerful way to map ecological vulnerability to fire and develop assessments to generate adaptation plans of management in forest masses.
Aubrey Miller, Pascal Sirguey, Simon Morris, Perry Bartelt, Nicolas Cullen, Todd Redpath, Kevin Thompson, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 2673–2701, https://doi.org/10.5194/nhess-22-2673-2022, https://doi.org/10.5194/nhess-22-2673-2022, 2022
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Natural hazard modelers simulate mass movements to better anticipate the risk to people and infrastructure. These simulations require accurate digital elevation models. We test the sensitivity of a well-established snow avalanche model (RAMMS) to the source and spatial resolution of the elevation model. We find key differences in the digital representation of terrain greatly affect the simulated avalanche results, with implications for hazard planning.
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.
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
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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.
Frank Techel, Stephanie Mayer, Cristina Pérez-Guillén, Günter Schmudlach, and Kurt Winkler
Nat. Hazards Earth Syst. Sci., 22, 1911–1930, https://doi.org/10.5194/nhess-22-1911-2022, https://doi.org/10.5194/nhess-22-1911-2022, 2022
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Can the resolution of forecasts of avalanche danger be increased by using a combination of absolute and comparative judgments? Using 5 years of Swiss avalanche forecasts, we show that, on average, sub-levels assigned to a danger level reflect the expected increase in the number of locations with poor snow stability and in the number and size of avalanches with increasing forecast sub-level.
Yves Bühler, Peter Bebi, Marc Christen, Stefan Margreth, Lukas Stoffel, Andreas Stoffel, Christoph Marty, Gregor Schmucki, Andrin Caviezel, Roderick Kühne, Stephan Wohlwend, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 22, 1825–1843, https://doi.org/10.5194/nhess-22-1825-2022, https://doi.org/10.5194/nhess-22-1825-2022, 2022
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To calculate and visualize the potential avalanche hazard, we develop a method that automatically and efficiently pinpoints avalanche starting zones and simulate their runout for the entire canton of Grisons. The maps produced in this way highlight areas that could be endangered by avalanches and are extremely useful in multiple applications for the cantonal authorities, including the planning of new infrastructure, making alpine regions more safe.
Tero M. Partanen and Mikhail Sofiev
Nat. Hazards Earth Syst. Sci., 22, 1335–1346, https://doi.org/10.5194/nhess-22-1335-2022, https://doi.org/10.5194/nhess-22-1335-2022, 2022
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The presented method aims to forecast regional wildfire-emitted radiative power in a time-dependent manner several days in advance. The temporal fire radiative power can be converted to an emission production rate, which can be implemented in air quality forecasting simulations. It is shown that in areas with a high incidence of wildfires, the fire radiative power is quite predictable, but otherwise it is not.
Christos Bountzouklis, Dennis M. Fox, and Elena Di Bernardino
Nat. Hazards Earth Syst. Sci., 22, 1181–1200, https://doi.org/10.5194/nhess-22-1181-2022, https://doi.org/10.5194/nhess-22-1181-2022, 2022
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The study addresses the evolution of burned areas in southeastern France from 1970 to 2019 through the scope of a firefighting policy shift in 1994 that resulted in a significant decrease in the burned area. Regions with large fires were particularly impacted, whereas, in other areas, the fires remained frequent and occurred closer to built-up zones. Environmental characteristics such as south-facing slopes and low vegetation (bushes) are increasingly associated with burned areas.
Louis Védrine, Xingyue Li, and Johan Gaume
Nat. Hazards Earth Syst. Sci., 22, 1015–1028, https://doi.org/10.5194/nhess-22-1015-2022, https://doi.org/10.5194/nhess-22-1015-2022, 2022
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This study investigates how forests affect the behaviour of snow avalanches through the evaluation of the amount of snow stopped by the trees and the analysis of energy dissipation mechanisms. Different avalanche features and tree configurations have been examined, leading to the proposal of a unified law for the detrained snow mass. Outcomes from this study can be directly implemented in operational models for avalanche risk assessment and contribute to improved forest management strategy.
Cited articles
Bartelt, P., Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part I: Numerical model, Cold Reg. Sci. Technol., 35, 123–145, https://doi.org/10.1016/s0165-232x(02)00074-5, 2002. a
Bellaire, S. and Jamieson, J. B.: Forecasting the formation of critical snow layers using a coupled snow cover and weather model, Cold Reg. Sci. Technol., 94, 37–44, https://doi.org/10.1016/j.coldregions.2013.06.007, 2013. a
Bellaire, S., van Herwijnen, A., Mitterer, C., and Schweizer, J.: On forecasting wet-snow avalanche activity using simulated snow cover data, Cold Reg. Sci. Technol., 144, 28–38, https://doi.org/10.1016/j.coldregions.2017.09.013, 2017. a
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/s0022143000009552, 1992. a
Calonne, N., Richter, B., Löwe, H., Cetti, C., Ter Schure, J., Van Herwijnen, A., Fierz, C., Jaggi, M., and Schneebeli, M.: The RHOSSA campaign: Multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack, The Cryosphere, 14, 1829–1848, https://doi.org/10.5194/tc-14-1829-2020, 2020. a
Campbell, C., Conger, S., Gould, B., Haegeli, P., Jamieson, J. B., and Statham, G.: Technical Aspects of Snow Avalanche Risk Management–Resources and Guidelines for Avalanche Practitioners in Canada, Revelstoke, BC, Canada, ISBN 978-1-926497-00-6, 2016. a
Canty, A. and Ripley, B.: boot: Bootstrap R (S-Plus) Functions, CRAN [code], https://cran.r-project.org/package=boot (last access: 13 August 2024), 2022. a
Davison, A. C. and Hinkley, D. V.: Bootstrap Methods and Their Applications, Cambridge University Press, Cambridge, ISBN 0-521-57391-2, 1997. a
Durand, Y., Giraud, G., Brun, E., Mérindol, L., and Martin, E.: A computer-based system simulating snowpack structures as a tool for regional avalanche forecasting, J. Glaciol., 45, 469–484, https://doi.org/10.3189/s0022143000001337, 1999. a
Ebert, P. A. and Milne, P.: Methodological and conceptual challenges in rare and severe event forecast verification, Nat. Hazards Earth Syst. Sci., 22, 539–557, https://doi.org/10.5194/nhess-22-539-2022, 2022. a, b
Fierz, C.: Field observation and modelling of weak-layer evolution, Ann. Glaciol., 26, 7–13, https://doi.org/10.3189/1998AoG26-1-7-13, 1998. a
Fierz, C. and Lehning, M.: Verification of Snow Cover Models on Slopes, in: Proceedings of the 2004 International Snow Science Workshop, Jackson Hole, WY, USA, 94–98, https://arc.lib.montana.edu/snow-science/item/1059 (last access: 13 August 2024), 2004. a
Fierz, C., Armstrong, R. L., Durand, Y., Etchevers, P., Greene, E., McClung, D. M., Nishimura, K., Satyawali, P., and Sokratov, S. A.: The International Classification for Seasonal Snow on the Ground, vol. 5, UNESCO/IHP, https://unesdoc.unesco.org/ark:/48223/pf0000186462 (last access: 13 August 2024), 2009. a
Haegeli, P. and McClung, D. M.: Expanding the snow-climate classification with avalanche-relevant information: Initial description of avalanche winter regimes for southwestern Canada, J. Glaciol., 53, 266–276, https://doi.org/10.3189/172756507782202801, 2007. a
Herla, F., Haegeli, P., and Mair, P.: A data exploration tool for averaging and accessing large data sets of snow stratigraphy profiles useful for avalanche forecasting, The Cryosphere, 16, 3149–3162, https://doi.org/10.5194/tc-16-3149-2022, 2022. a, b
Herla, F., Haegeli, P., Horton, S., and Mair, P.: Critical Layer Validation – Data and Code, OSF [code and data set], https://doi.org/10.17605/OSF.IO/W7PJY, 2023. a
Hordowick, H. and Haegeli, P.: Understanding avalanche problem assessments: A concept mapping study with public avalanche forecasters, mathesis, http://www.avalancheresearch.ca/pubs/2022_hordowick_mrm/ (last access: 13 August 2024), 2022. a
Horton, S. and Haegeli, P.: Using snow depth observations to provide insight into the quality of snowpack simulations for regional-scale avalanche forecasting, The Cryosphere, 16, 3393–3411, https://doi.org/10.5194/tc-16-3393-2022, 2022. a, b, c
Horton, S. and Jamieson, J. B.: Modelling hazardous surface hoar layers across western Canada with a coupled weather and snow cover model, Cold Reg. Sci. Technol., 128, 22–31, https://doi.org/10.1016/j.coldregions.2016.05.002, 2016. a
Horton, S., Nowak, S., and Haegeli, P.: Enhancing the operational value of snowpack models with visualization design principles, Nat. Hazards Earth Syst. Sci., 20, 1557–1572, https://doi.org/10.5194/nhess-20-1557-2020, 2020a. a, b
Horton, S., Towell, M., and Haegeli, P.: Examining the operational use of avalanche problems with decision trees and model-generated weather and snowpack variables, Nat. Hazards Earth Syst. Sci., 20, 3551–3576, https://doi.org/10.5194/nhess-20-3551-2020, 2020b. a, b
Hothorn, T. and Zeileis, A.: Partykit: A modular toolkit for recursive partytioning in R, J. Mach. Learn. Res., 16, 3905–3909, 2015. a
Hothorn, T., Hornik, K., and Zeileis, A.: Unbiased recursive partitioning: A conditional inference framework, J. Comput. Graph. Stat., 15, 651–674, https://doi.org/10.1198/106186006X133933, 2006. a
LaChapelle, E. R.: The fundamental processes in conventional avalanche forecasting, J. Glaciol., 26, 75–84, https://doi.org/10.3189/s0022143000010601, 1980. a, b
Lafaysse, M., Morin, S., Coléou, C., Vernay, M., Serça, D., Besson, F., Willemet, J.-M., Giraud, G., and Durand, Y.: Toward a new chain of models for avalanche hazard forecasting in French mountain ranges, including low altitude mountains, in: Proceedings of the 2013 International Snow Science Workshop, 7–11 October 2013, Grenoble, France, 162–166, https://arc.lib.montana.edu/snow-science/item.php?id=1741 (last access: 13 August 2024), 2013. a
Lafaysse, M., Cluzet, B., Dumont, M., Lejeune, Y., Vionnet, V., and Morin, S.: A multiphysical ensemble system of numerical snow modelling, The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, 2017. a
Lehning, M., Fierz, C., and Lundy, C.: An objective snow profile comparison method and its application to SNOWPACK, Cold Reg. Sci. Technol., 33, 253–261, https://doi.org/10.1016/s0165-232x(01)00044-1, 2001. a
Lehning, M., Bartelt, P., Brown, B., and Fierz, C.: A physical SNOWPACK model for the Swiss avalanche warning Part III: Meteorological forcing, thin layer formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184, https://doi.org/10.1016/S0165-232X(02)00072-1, 2002a. a
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/S0165-232X(02)00073-3, 2002b. a, b
Lundquist, J., Hughes, M., Gutmann, E., and Kapnick, S.: Our skill in modeling mountain rain and snow is bypassing the skill of our observational networks, B. Am. Meteorol. Soc., 100, 2473–2490, https://doi.org/10.1175/BAMS-D-19-0001.1, 2019. a
McClung, D. M.: The Elements of Applied Avalanche Forecasting, Part I: The Human Issues, Nat. Hazards, 26, 111–129, https://doi.org/10.1023/a:1015665432221, 2002a. a, b
McClung, D. M.: The Elements of Applied Avalanche Forecasting, Part II: The Physical Issues and the Rules of Applied Avalanche Forecasting, Nat. Hazards, 26, 131–146, https://doi.org/10.1023/a:1015604600361, 2002b. a
Michlmayr, G., Lehning, M., Koboltschnig, G., Holzmann, H., Zappa, M., Mott, R., and Schöner, W.: Application of the Alpine 3D model for glacier mass balance and glacier runoff studies at Goldbergkees, Austria, in: Hydrological Processes, vol. 22, John Wiley and Sons, Ltd, 3941–3949, https://doi.org/10.1002/hyp.7102, 2008. a
Milbrandt, J. A., Bélair, S., Faucher, M., Vallée, M., Carrera, M. L., and Glazer, A.: The pan-canadian high resolution (2.5 km) deterministic prediction system, Weather Forecast., 31, 1791–1816, https://doi.org/10.1175/WAF-D-16-0035.1, 2016. a
Monti, F. and Schweizer, J.: A relative difference approach to detect potential weak layers within a snow profile, in: Proceedings of the 2013 International Snow Science Workshop, 7–11 October 2013, Grenoble, France, 339–343, https://arc.lib.montana.edu/snow-science/item.php?id=1861 (last access: 13 August 2024), 2013. a, b, c
Monti, F., Schweizer, J., Gaume, J., and Fierz, C.: Deriving snow stability information from simulated snow cover stratigraphy, in: Proceedings of the 2014 International Snow Science Workshop, Banff, AB, Canada, 465–469, https://arc.lib.montana.edu/snow-science/item.php?id=2096 (last access: 13 August 2024), 2014. a, b, c
Monti, F., Gaume, J., van Herwijnen, A., and Schweizer, J.: Snow instability evaluation: calculating the skier-induced stress in a multi-layered snowpack, Nat. Hazards Earth Syst. Sci., 16, 775–788, https://doi.org/10.5194/nhess-16-775-2016, 2016. a, b
Morin, S., Fierz, C., Horton, S., Bavay, M., Dumont, M., Hagenmuller, P., Lafaysse, M., Mitterer, C., Monti, F., Olefs, M., Snook, J. S., Techel, F., Van Herwijnen, A., and Vionnet, V.: Application of physical snowpack models in support of operational avalanche hazard forecasting : A status report on current implementations and prospects for the future, Cold Reg. Sci. Technol., 170, 1098–1107, https://doi.org/10.1016/J.COLDREGIONS.2019.102910, 2020. a, b, c
Quéno, L., Vionnet, V., Dombrowski-Etchevers, I., Lafaysse, M., Dumont, M., and Karbou, F.: Snowpack modelling in the Pyrenees driven by kilometric-resolution meteorological forecasts, The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, 2016. a
Raleigh, M. S., Lundquist, J., and Clark, M. P.: Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework, Hydrol. Earth Syst. Sci., 19, 3153–3179, https://doi.org/10.5194/hess-19-3153-2015, 2015. a
R Core Team: R: A Language and Environment for Statistical Computing, https://www.r-project.org/ (last access: 13 August 2024), 2020. a
Reuter, B. and Bellaire, S.: On combining snow cover and snow instability modelling, in: Proceedings of the 2018 international snow science workshop, Innsbruck, AUT, 949—-953, https://arc.lib.montana.edu/snow-science/item/2684 (last access: 13 August 2024), 2018. a
Reuter, B. and Schweizer, J.: Describing Snow Instability by Failure Initiation, Crack Propagation, and Slab Tensile Support, Geophys. Res. Lett., 45, 7019–7027, https://doi.org/10.1029/2018GL078069, 2018. a, b
Reuter, B., Schweizer, J., and van Herwijnen, A.: A process-based approach to estimate point snow instability, The Cryosphere, 9, 837–847, https://doi.org/10.5194/tc-9-837-2015, 2015. a, b
Reuter, B., Viallon-Galinier, L., Horton, S., van Herwijnen, A., Mayer, S., Hagenmuller, P., and Morin, S.: Characterizing snow instability with avalanche problem types derived from snow cover simulations, Cold Reg. Sci. Technol., 194, 103462, https://doi.org/10.1016/j.coldregions.2021.103462, 2021. a, b, c, d, e, f
Richter, B., Schweizer, J., Rotach, M. W., and Van Herwijnen, A.: Validating modeled critical crack length for crack propagation in the snow cover model SNOWPACK, The Cryosphere, 13, 3353–3366, https://doi.org/10.5194/tc-13-3353-2019, 2019. a, b, c
Richter, B., Van Herwijnen, A., Rotach, M. W., and Schweizer, J.: Sensitivity of modeled snow stability data to meteorological input uncertainty, Nat. Hazards Earth Syst. Sci., 20, 2873–2888, https://doi.org/10.5194/nhess-20-2873-2020, 2020. a, b
Schirmer, M., Schweizer, J., and Lehning, M.: Statistical evaluation of local to regional snowpack stability using simulated snow-cover data, Cold Reg. Sci. Technol., 64, 110–118, https://doi.org/10.1016/j.coldregions.2010.04.012, 2010. a
Schweizer, J., Jamieson, J. B., and Schneebeli, M.: Snow avalanche formation, Rev. Geophys., 41, 1016, https://doi.org/10.1029/2002rg000123, 2003. a
Schweizer, J., Bellaire, S., Fierz, C., Lehning, M., and Pielmeier, C.: Evaluating and improving the stability predictions of the snow cover model SNOWPACK, Cold Reg. Sci. Technol., 46, 52–59, https://doi.org/10.1016/j.coldregions.2006.05.007, 2006. a
Schweizer, J., Reuter, B., Van Herwijnen, A., and Gaume, J.: Avalanche Release 101, in: Proceedings of the 2016 International Snow Science Workshop, Breckenridge, CO, USA, https://arc.lib.montana.edu/snow-science/item/2235 (last access: 13 August 2024), 2016. a
Shandro, B. and Haegeli, P.: Characterizing the nature and variability of avalanche hazard in western Canada, Nat. Hazards Earth Syst. Sci., 18, 1141–1158, https://doi.org/10.5194/nhess-18-1141-2018, 2018. a, b
Sing, T., Sander, O., Beerenwinkel, N., and Lengauer, T.: ROCR: visualizing classifier performance in R, Bioinformatics, 21, 3940–3941, https://doi.org/10.1093/bioinformatics/bti623, 2005. a
Statham, G., Haegeli, P., Greene, E., Birkeland, K. W., Israelson, C., Tremper, B., Stethem, C., McMahon, B., White, B., and Kelly, J.: A conceptual model of avalanche hazard, Nat. Hazards, 90, 663–691, https://doi.org/10.1007/s11069-017-3070-5, 2018a. a, b, c, d
Statham, G., Holeczi, S., and Shandro, B.: Consistency and Accuracy of Public Avalanche Forecasts in Western Canada, in: Proceedings of the 2018 International Snow Science Workshop, Innsbruck, Austria, https://arc.lib.montana.edu/snow-science/item.php?id=2806 (last access: 13 August 2024), 2018b. a, b
Storm, I.: Public Avalanche Forecast Challenges: Canada's Large Data-Sparse Regions, in: Proceedings, 2012 International Snow Science Workshop, Anchorage, AK, USA, 908–912, https://arc.lib.montana.edu/snow-science/item.php?id=1668 (last access: 13 August 2024), 2012. a
Storm, I. and Helgeson, R. G.: Hot-spots and hot times: exploring alternatives to public avalanche forecasts in Canada's data sparse Northern Roeckies region, in: Proceedings of the 2014 International Snow Science Workshop, Banff, AB, Canada, https://arc.lib.montana.edu/snow-science/item/2034 (last access: 13 August 2024), 2014. a
Techel, F., Mitterer, C., Ceaglio, E., Coléou, C., Morin, S., Rastelli, F., and Purves, R. S.: Spatial consistency and bias in avalanche forecasts – a case study in the European Alps, Nat. Hazards Earth Syst. Sci., 18, 2697–2716, https://doi.org/10.5194/nhess-18-2697-2018, 2018. a
Vernay, M., Lafaysse, M., Mérindol, L., Giraud, G., and Morin, S.: Ensemble forecasting of snowpack conditions and avalanche hazard, Cold Reg. Sci. Technol., 120, 251–262, https://doi.org/10.1016/j.coldregions.2015.04.010, 2015. a
Viallon-Galinier, L., Hagenmuller, P., and Lafaysse, M.: Forcing and evaluating detailed snow cover models with stratigraphy observations, Cold Reg. Sci. Technol., 180, 103163, https://doi.org/10.1016/j.coldregions.2020.103163, 2020. a
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012. a
Vionnet, V., Six, D., Auger, L., Dumont, M., Lafaysse, M., Quéno, L., Réveillet, M., Dombrowski-Etchevers, I., Thibert, E., and Vincent, C.: Sub-kilometer Precipitation Datasets for Snowpack and Glacier Modeling in Alpine Terrain, Front. Earth Sci., 7, 182, https://doi.org/10.3389/feart.2019.00182, 2019. a
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Elsevier, https://doi.org/10.1016/c2017-0-03921-6, 2019. a, b, c
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.
Snowpack simulations are increasingly employed by avalanche warning services to inform about...
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