Articles | Volume 22, issue 10
https://doi.org/10.5194/nhess-22-3501-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-22-3501-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Oct 2022
Research article |
| 24 Oct 2022
| 24 Oct 2022
What weather variables are important for wet and slab avalanches under a changing climate in a low-altitude mountain range in Czechia?
Markéta Součková
CORRESPONDING AUTHOR
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague – Suchdol, Czechia
Department of Hydrology, T. G. Masaryk Water Research Institute, Podbabská 2582/30, 160 00 Prague 6, Czechia
Roman Juras
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague – Suchdol, Czechia
Kryštof Dytrt
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague – Suchdol, Czechia
Vojtěch Moravec
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague – Suchdol, Czechia
Department of Hydrology, T. G. Masaryk Water Research Institute, Podbabská 2582/30, 160 00 Prague 6, Czechia
Johanna Ruth Blöcher
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague – Suchdol, Czechia
Martin Hanel
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague – Suchdol, Czechia
Department of Hydrology, T. G. Masaryk Water Research Institute, Podbabská 2582/30, 160 00 Prague 6, Czechia
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A statistical significance of changes in correlations of daily precipitation in six RCM simulations is assessed. The effect of outliers is explored and a concept of dependence outliers is presented. We show that correlation estimates can be strongly affected by a few outliers; therefore any statistical correction relying on sample correlation can provide misleading results. An exploratory procedure is proposed to detect and evaluate the dependence outliers in multivariate data.
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The paper investigates primarily the changes of the cross- and auto-correlation structures of daily precipitation in an ensemble of climate models. The changes vary in a range from −0.08 to 0.08 and individual models differ considerably. The analysis of significance revealed the strong influence of outliers on correlation structures, which can bring severe artefacts into the climate impact studies. An exploratory procedure is proposed to detect the correlation outliers in multi-variate data.
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Hydrol. Earth Syst. Sci., 21, 4973–4987, https://doi.org/10.5194/hess-21-4973-2017, https://doi.org/10.5194/hess-21-4973-2017, 2017
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Sebastian Würzer, Nander Wever, Roman Juras, Michael Lehning, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 1741–1756, https://doi.org/10.5194/hess-21-1741-2017, https://doi.org/10.5194/hess-21-1741-2017, 2017
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We discuss a dual-domain water transport model in a physics-based snowpack model to account for preferential flow (PF) in addition to matrix flow. So far no operationally used snow model has explicitly accounted for PF. The new approach is compared to existing water transport models and validated against in situ data from sprinkling and natural rain-on-snow (ROS) events. Our work demonstrates the benefit of considering PF in modelling hourly snowpack runoff, especially during ROS conditions.
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Tandin Wangchuk and Ryota Tsubaki
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Elisabeth D. Hafner, Frank Techel, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
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Gerardo Romano, Marco Antonellini, Domenico Patella, Agata Siniscalchi, Andrea Tallarico, Simona Tripaldi, and Antonello Piombo
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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.
Kang He, Xinyi Shen, Cory Merow, Efthymios Nikolopoulos, Rachael V. Gallagher, Feifei Yang, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-69, https://doi.org/10.5194/nhess-2023-69, 2023
Revised manuscript accepted for NHESS
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A framework combines 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 future projected climate conditions.
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
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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.
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.
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.
Matthew C. Perry, Emilie Vanvyve, Richard A. Betts, and Erika J. Palin
Nat. Hazards Earth Syst. Sci., 22, 559–575, https://doi.org/10.5194/nhess-22-559-2022, https://doi.org/10.5194/nhess-22-559-2022, 2022
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In the past, wildfires in the UK have occurred mainly in spring, with occasional events during hot, dry summers. Climate models predict a large future increase in hazardous fire weather conditions in summer. Wildfire can be considered an
emergent riskfor the UK, as past events have not had widespread major impacts, but this could change. The large increase in risk between the 2 °C and 4 °C levels of global warming highlights the importance of global efforts to keep warming below 2 °C.
Philip A. Ebert and Peter Milne
Nat. Hazards Earth Syst. Sci., 22, 539–557, https://doi.org/10.5194/nhess-22-539-2022, https://doi.org/10.5194/nhess-22-539-2022, 2022
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There is no consensus about how to assess the quality of binary (yes or no) rare and severe event forecasts, i.e. forecasts involving natural hazards like tornadoes or avalanches. We offer a comprehensive overview of the challenges we face when making such an assessment and provide a critical review of existing solutions. We argue against all but one existing solution to assess the quality of such forecasts and present practical consequences to improve forecasting services.
Jacques Mourey, Pascal Lacroix, Pierre-Allain Duvillard, Guilhem Marsy, Marco Marcer, Emmanuel Malet, and Ludovic Ravanel
Nat. Hazards Earth Syst. Sci., 22, 445–460, https://doi.org/10.5194/nhess-22-445-2022, https://doi.org/10.5194/nhess-22-445-2022, 2022
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More frequent rockfalls in high alpine environments due to climate change are a growing threat to mountaineers. This hazard is particularly important on the classic route up Mont Blanc. Our results show that rockfalls are most frequent during snowmelt periods and the warmest hours of the day, and that mountaineers do not adapt to the local rockfall hazard when planning their ascent. Disseminating the knowledge acquired from our study caused management measures to be implemented for the route.
Tomàs Artés, Marc Castellnou, Tracy Houston Durrant, and Jesús San-Miguel
Nat. Hazards Earth Syst. Sci., 22, 509–522, https://doi.org/10.5194/nhess-22-509-2022, https://doi.org/10.5194/nhess-22-509-2022, 2022
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During the last 20 years extreme wildfires have challenged firefighting capabilities. Several fire danger indices are routinely used by firefighting services but are not suited to forecast convective extreme wildfire behaviour at the global scale. This article proposes a new fire danger index for deep moist convection, the extreme-fire behaviour index (EFBI), based on the analysis of the vertical profiles of the atmosphere above wildfires to use along with traditional fire danger indices.
Veronika Hutter, Frank Techel, and Ross S. Purves
Nat. Hazards Earth Syst. Sci., 21, 3879–3897, https://doi.org/10.5194/nhess-21-3879-2021, https://doi.org/10.5194/nhess-21-3879-2021, 2021
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How is avalanche danger described in public avalanche forecasts? We analyzed 6000 textual descriptions of avalanche danger in Switzerland, taking the perspective of the forecaster. Avalanche danger was described rather consistently, although the results highlight the difficulty of communicating conditions that are neither rare nor frequent, neither small nor large. The study may help to refine the ways in which avalanche danger could be communicated to the public.
Edilia Jaque Castillo, Alfonso Fernández, Rodrigo Fuentes Robles, and Carolina G. Ojeda
Nat. Hazards Earth Syst. Sci., 21, 3663–3678, https://doi.org/10.5194/nhess-21-3663-2021, https://doi.org/10.5194/nhess-21-3663-2021, 2021
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Wildfires pose risks to lives and livelihoods in many regions of the world. Particularly in Chile's central-south region, climate change, widespread land use change, and urban growth tend to increase the likelihood of fire occurrence. Our work focused on the Concepción metropolitan area, where we developed a model using machine learning in order to map wildfire risks. We found that the interface between urban areas and forestry plantations presents the highest risks.
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Short summary
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.
Avalanches are natural hazards that threaten people and infrastructure. With climate change,...
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