Articles | Volume 23, issue 5
https://doi.org/10.5194/nhess-23-1755-2023
© Author(s) 2023. 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-23-1755-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 May 2023
Research article |
| 12 May 2023
| 12 May 2023
Reduced-order digital twin and latent data assimilation for global wildfire prediction
Caili Zhong
Department of Earth Science and Engineering, Imperial College London, London, United Kingdom
Data Science Institute, Imperial College London, London, United
Kingdom
Matthew Kasoar
Department of Physics, Imperial College London, London, United Kingdom
Rossella Arcucci
Department of Earth Science and Engineering, Imperial College London, London, United Kingdom
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Arianna Olivelli, Rossella Arcucci, Mark Rehkämper, and Tina van de Flierdt
Earth Syst. Sci. Data, 17, 3679–3699, https://doi.org/10.5194/essd-17-3679-2025, https://doi.org/10.5194/essd-17-3679-2025, 2025
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In this study, we use machine learning models to produce the first global maps of Pb concentrations and isotope compositions in the ocean. In line with observations, we find that (i) the surface Indian Ocean has the highest levels of pollution, (ii) pollution from previous decades is sinking in the North Atlantic and Pacific oceans, and (iii) waters carrying Pb pollution are spreading from the Southern Ocean throughout the Southern Hemisphere at intermediate depths.
Wenbo Yu, Anirbit Ghosh, Tobias Sebastian Finn, Rossella Arcucci, Marc Bocquet, and Sibo Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2025-2836, https://doi.org/10.5194/egusphere-2025-2836, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We introduce the first denoising diffusion model for wildfire spread prediction, a new kind of generative AI model that learns to simulate fires not just as one fixed outcome, but as a range of possible scenarios. This allows us to capture the inherent uncertainty of wildfire dynamics. Our model produces ensembles of forecasts that reflect physically meaningful distributions of where fire might go next.
Anastasios Rovithakis, Eleanor Burke, Chantelle Burton, Matthew Kasoar, Manolis G. Grillakis, Konstantinos D. Seiradakis, and Apostolos Voulgarakis
EGUsphere, https://doi.org/10.5194/egusphere-2025-274, https://doi.org/10.5194/egusphere-2025-274, 2025
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JULES-INFERNO captures observed burned area across Greece fairly well for the present-day. Drastic future changes in burnt area in Eastern continental and southern Greece, especially under severe climate change scenarios. Static vegetation leads to larger burnt area compared to dynamic vegetation due to the lower concentration of flammable needleleaf trees.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Christopher D. Wells, Matthew Kasoar, Majid Ezzati, and Apostolos Voulgarakis
Atmos. Chem. Phys., 24, 1025–1039, https://doi.org/10.5194/acp-24-1025-2024, https://doi.org/10.5194/acp-24-1025-2024, 2024
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Human-driven emissions of air pollutants, mostly caused by burning fossil fuels, impact both the climate and human health. Millions of deaths each year are caused by air pollution globally, and the future trends are uncertain. Here, we use a global climate model to study the effect of African pollutant emissions on surface level air pollution, and resultant impacts on human health, in several future emission scenarios. We find much lower health impacts under cleaner, lower-emission futures.
Christopher D. Wells, Matthew Kasoar, Nicolas Bellouin, and Apostolos Voulgarakis
Atmos. Chem. Phys., 23, 3575–3593, https://doi.org/10.5194/acp-23-3575-2023, https://doi.org/10.5194/acp-23-3575-2023, 2023
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The climate is altered by greenhouse gases and air pollutant particles, and such emissions are likely to change drastically in the future over Africa. Air pollutants do not travel far, so their climate effect depends on where they are emitted. This study uses a climate model to find the climate impacts of future African pollutant emissions being either high or low. The particles absorb and scatter sunlight, causing the ground nearby to be cooler, but elsewhere the increased heat causes warming.
Yawei Qu, Apostolos Voulgarakis, Tijian Wang, Matthew Kasoar, Chris Wells, Cheng Yuan, Sunil Varma, and Laura Mansfield
Atmos. Chem. Phys., 21, 5705–5718, https://doi.org/10.5194/acp-21-5705-2021, https://doi.org/10.5194/acp-21-5705-2021, 2021
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The meteorological effect of aerosols on tropospheric ozone is investigated using global atmospheric modelling. We found that aerosol-induced meteorological effects act to reduce modelled ozone concentrations over China, which brings the simulation closer to observed levels. Our work sheds light on understudied processes affecting the levels of tropospheric gaseous pollutants and provides a basis for evaluating such processes using a combination of observations and model sensitivity experiments.
Øivind Hodnebrog, Gunnar Myhre, Bjørn H. Samset, Kari Alterskjær, Timothy Andrews, Olivier Boucher, Gregory Faluvegi, Dagmar Fläschner, Piers M. Forster, Matthew Kasoar, Alf Kirkevåg, Jean-Francois Lamarque, Dirk Olivié, Thomas B. Richardson, Dilshad Shawki, Drew Shindell, Keith P. Shine, Philip Stier, Toshihiko Takemura, Apostolos Voulgarakis, and Duncan Watson-Parris
Atmos. Chem. Phys., 19, 12887–12899, https://doi.org/10.5194/acp-19-12887-2019, https://doi.org/10.5194/acp-19-12887-2019, 2019
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Different greenhouse gases (e.g. CO2) and aerosols (e.g. black carbon) impact the Earth’s water cycle differently. Here we investigate how various gases and particles impact atmospheric water vapour and its lifetime, i.e., the average number of days that water vapour stays in the atmosphere after evaporation and before precipitation. We find that this lifetime could increase substantially by the end of this century, indicating that important changes in precipitation patterns are excepted.
Tao Tang, Drew Shindell, Bjørn H. Samset, Oliviér Boucher, Piers M. Forster, Øivind Hodnebrog, Gunnar Myhre, Jana Sillmann, Apostolos Voulgarakis, Timothy Andrews, Gregory Faluvegi, Dagmar Fläschner, Trond Iversen, Matthew Kasoar, Viatcheslav Kharin, Alf Kirkevåg, Jean-Francois Lamarque, Dirk Olivié, Thomas Richardson, Camilla W. Stjern, and Toshihiko Takemura
Atmos. Chem. Phys., 18, 8439–8452, https://doi.org/10.5194/acp-18-8439-2018, https://doi.org/10.5194/acp-18-8439-2018, 2018
Matthew Kasoar, Apostolos Voulgarakis, Jean-François Lamarque, Drew T. Shindell, Nicolas Bellouin, William J. Collins, Greg Faluvegi, and Kostas Tsigaridis
Atmos. Chem. Phys., 16, 9785–9804, https://doi.org/10.5194/acp-16-9785-2016, https://doi.org/10.5194/acp-16-9785-2016, 2016
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Computer models are our primary tool to investigate how fossil-fuel emissions are affecting the climate. Here, we used three different climate models to see how they simulate the response to removing sulfur dioxide emissions from China. We found that the models disagreed substantially on how large the climate effect is from the emissions in this region. This range of outcomes is concerning if scientists or policy makers have to rely on any one model when performing their own studies.
Mathew A. Stiller-Reeve, Céline Heuzé, William T. Ball, Rachel H. White, Gabriele Messori, Karin van der Wiel, Iselin Medhaug, Annemarie H. Eckes, Amee O'Callaghan, Mike J. Newland, Sian R. Williams, Matthew Kasoar, Hella Elisa Wittmeier, and Valerie Kumer
Hydrol. Earth Syst. Sci., 20, 2965–2973, https://doi.org/10.5194/hess-20-2965-2016, https://doi.org/10.5194/hess-20-2965-2016, 2016
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Scientific writing must improve and the key to long-term improvement of scientific writing lies with the early-career scientist (ECS). We introduce the ClimateSnack project, which aims to motivate ECSs to start writing groups around the world to improve their skills together. Writing groups offer many benefits but can be a challenge to keep going. Several ClimateSnack writing groups formed, and this paper examines why some of the groups flourished and others dissolved.
Related subject area
Other Hazards (e.g., Glacial and Snow Hazards, Karst, Wildfires Hazards, and Medical Geo-Hazards)
Simulation of cold-powder snow avalanches considering daily snowpack and weather situations
Supershear crack propagation in snow slab avalanche release: new insights from numerical simulations and field measurements
The effect of slab touchdown on anticrack arrest in propagation saw tests
Proglacial lake development and outburst flood hazard at Fjallsjökull glacier, southeast Iceland
Assessing the performance and explainability of an avalanche danger forecast model
Development of operational decision support tools for mechanized ski guiding using avalanche terrain modeling, GPS tracking, and machine learning
Causes, consequences and implications of the 2023 landslide-induced Lake Rasac glacial lake outburst flood (GLOF), Cordillera Huayhuash, Peru
The Avalanche Terrain Exposure Scale (ATES) v.2
Estimating future wildfire burnt area over Greece using the JULES-INFERNO model
Review article: A scoping review of human factors in avalanche decision-making
A quantitative module of avalanche hazard – comparing forecaster assessments of storm and persistent slab avalanche problems with information derived from distributed snowpack simulations
Modelling current and future forest fire susceptibility in north-eastern Germany
The effect of propagation saw test geometries on critical cut length
Statistical calibration of probabilistic medium-range Fire Weather Index forecasts in Europe
Failure of Marmolada Glacier (Dolomites, Italy) in 2022: Data-based back analysis of possible collapse mechanisms as related to recent morpho-climatic evolution and possible trigger factors
Seismic Signal Classification of Snow Avalanches using Distributed Acoustic Sensing in Grasdalen, Western Norway
Glide-snow avalanches: a mechanical, threshold-based release area model
Particle and front tracking in experimental and computational avalanche dynamics
Improving fire severity prediction in south-eastern Australia using vegetation-specific information
Forecasting avalanche danger: human-made forecasts vs. fully automated model-driven predictions
How hard do avalanche practitioners tap during snow stability tests?
A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers
Review article: Understanding the placement of fire emissions from the Brazilian Cerrado biome in the atmospheric carbon budget
A glacial lake outburst flood risk assessment for the Phochhu river basin, Bhutan
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 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
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
Julia Glaus, Katreen Wikstrom Jones, Perry Bartelt, Marc Christen, Lukas Stoffel, Johan Gaume, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 2399–2419, https://doi.org/10.5194/nhess-25-2399-2025, https://doi.org/10.5194/nhess-25-2399-2025, 2025
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This study assesses RAMMS::EXTENDED's predictive power in estimating avalanche runout distances critical for mountain road safety. Leveraging meteorological data and sensitivity analyses, it offers meaningful predictions, aiding near real-time hazard assessments and future model refinement for improved decision-making.
Grégoire Bobillier, Bertil Trottet, Bastian Bergfeld, Ron Simenhois, Alec van Herwijnen, Jürg Schweizer, and Johan Gaume
Nat. Hazards Earth Syst. Sci., 25, 2215–2223, https://doi.org/10.5194/nhess-25-2215-2025, https://doi.org/10.5194/nhess-25-2215-2025, 2025
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Our study investigates the initiation of snow slab avalanches. Combining experimental data with numerical simulations, we show that on gentle slopes, cracks form and propagate due to compressive fractures within a weak layer. On steeper slopes, crack velocity can increase dramatically after approximately 5 m due to a fracture mode transition from compression to shear. Understanding these dynamics provides a crucial missing piece in the puzzle of dry-snow slab avalanche formation.
Philipp L. Rosendahl, Johannes Schneider, Grégoire Bobillier, Florian Rheinschmidt, Bastian Bergfeld, Alec van Herwijnen, and Philipp Weißgraeber
Nat. Hazards Earth Syst. Sci., 25, 1975–1991, https://doi.org/10.5194/nhess-25-1975-2025, https://doi.org/10.5194/nhess-25-1975-2025, 2025
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Avalanche formation depends on crack propagation in weak snow layers, but the conditions that stop a crack remain unclear. We show that slab touchdown reduces the energy driving crack growth, which can halt propagation even under static conditions. This suggests that crack arrest is influenced not only by snowpack variability or dynamics but also by mechanical interactions within the snowpack. Our findings refine avalanche prediction models and improve hazard assessment.
Greta H. Wells, Þorsteinn Sæmundsson, Finnur Pálsson, Guðfinna Aðalgeirsdóttir, Eyjólfur Magnússon, Reginald L. Hermanns, and Snævarr Guðmundsson
Nat. Hazards Earth Syst. Sci., 25, 1913–1936, https://doi.org/10.5194/nhess-25-1913-2025, https://doi.org/10.5194/nhess-25-1913-2025, 2025
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Glacier retreat elevates the risk of landslides released into proglacial lakes, which can trigger glacial lake outburst floods (GLOFs). This study maps proglacial lake evolution and GLOF hazard scenarios at Fjallsjökull glacier, Iceland. Lake volume increased from 1945 to 2021 and is estimated to triple over the next century. Three slopes are prone to landslides that may trigger GLOFs. Results will mitigate flood hazard at this popular tourism site and advance GLOF research in Iceland and globally.
Cristina Pérez-Guillén, Frank Techel, Michele Volpi, and Alec van Herwijnen
Nat. Hazards Earth Syst. Sci., 25, 1331–1351, https://doi.org/10.5194/nhess-25-1331-2025, https://doi.org/10.5194/nhess-25-1331-2025, 2025
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This study assesses the performance and explainability of a random-forest classifier for predicting dry-snow avalanche danger levels during initial live testing. The model achieved ∼ 70 % agreement with human forecasts, performing equally well in nowcast and forecast modes, while capturing the temporal dynamics of avalanche forecasting. The explainability approach enhances the transparency of the model's decision-making process, providing a valuable tool for operational avalanche forecasting.
John Sykes, Pascal Haegeli, Roger Atkins, Patrick Mair, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 1255–1292, https://doi.org/10.5194/nhess-25-1255-2025, https://doi.org/10.5194/nhess-25-1255-2025, 2025
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We model the decision-making of professional ski guides and develop decision support tools to assist with determining appropriate terrain based on current conditions. Our approach compares a manually constructed Bayesian network with machine learning classification models. 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.
Adam Emmer, Oscar Vilca, Cesar Salazar Checa, Sihan Li, Simon Cook, Elena Pummer, Jan Hrebrina, and Wilfried Haeberli
Nat. Hazards Earth Syst. Sci., 25, 1207–1228, https://doi.org/10.5194/nhess-25-1207-2025, https://doi.org/10.5194/nhess-25-1207-2025, 2025
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We describe in detail the most recent large landslide-triggered glacial lake outburst flood (GLOF) in the Peruvian Andes (the 2023 Rasac GLOF), analysing its preconditions and consequences, as well as the role of the changing climate. Our study contributes to understanding GLOF occurrence patterns in space and time and corroborates reports detailing the increasing frequency of such events in changing mountains.
Grant Statham and Cam Campbell
Nat. Hazards Earth Syst. Sci., 25, 1113–1137, https://doi.org/10.5194/nhess-25-1113-2025, https://doi.org/10.5194/nhess-25-1113-2025, 2025
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The Avalanche Terrain Exposure Scale (ATES) is an avalanche terrain rating system used for terrain assessment and risk communication in public and workplace avalanche safety practices. This paper introduces ATES v.2, an update that expands the original scale from three levels to five by including Class 0 – Non-avalanche terrain and Class 4 – Extreme terrain. The updated models for assessment and communication are described in detail, along with guidance for the application of ATES.
Anastasios Rovithakis, Eleanor Burke, Chantelle Burton, Matthew Kasoar, Manolis G. Grillakis, Konstantinos D. Seiradakis, and Apostolos Voulgarakis
EGUsphere, https://doi.org/10.5194/egusphere-2025-274, https://doi.org/10.5194/egusphere-2025-274, 2025
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JULES-INFERNO captures observed burned area across Greece fairly well for the present-day. Drastic future changes in burnt area in Eastern continental and southern Greece, especially under severe climate change scenarios. Static vegetation leads to larger burnt area compared to dynamic vegetation due to the lower concentration of flammable needleleaf trees.
Audun Hetland, Rebecca A. Hetland, Tarjei Tveito Skille, and Andrea Mannberg
Nat. Hazards Earth Syst. Sci., 25, 929–948, https://doi.org/10.5194/nhess-25-929-2025, https://doi.org/10.5194/nhess-25-929-2025, 2025
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Research on human factors in avalanche decision-making has become increasingly popular in the past 2 decades. The studies span a wide range of disciplines and are published in a variety of journals. To provide an overview of this literature, this study provides a systematic scoping review of human factors in avalanche decision-making. A total of 70 papers fulfilled the search criteria. We extracted data and sorted the papers according to their main themes.
Florian Herla, Pascal Haegeli, Simon Horton, and Patrick Mair
Nat. Hazards Earth Syst. Sci., 25, 625–646, https://doi.org/10.5194/nhess-25-625-2025, https://doi.org/10.5194/nhess-25-625-2025, 2025
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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 agreement in seasonal summary statistics, a comparison of daily assessments revealed considerable differences, while it remained unclear which data source represented reality the best. We discuss how snowpack simulations can add value to the forecasting process.
Katharina H. Horn, Stenka Vulova, Hanyu Li, and Birgit Kleinschmit
Nat. Hazards Earth Syst. Sci., 25, 383–401, https://doi.org/10.5194/nhess-25-383-2025, https://doi.org/10.5194/nhess-25-383-2025, 2025
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In this study we applied a random forest machine learning algorithm to model current and future forest fire susceptibility (FFS) in north-eastern Germany using anthropogenic, climatic, topographic, soil, and vegetation variables. Model accuracy ranged between 69 % and 71 %, showing moderately high model reliability for predicting FFS. The model results underline the importance of anthropogenic and vegetation parameters. This study will support regional forest fire prevention and management.
Bastian Bergfeld, Karl W. Birkeland, Valentin Adam, Philipp L. Rosendahl, and Alec van Herwijnen
Nat. Hazards Earth Syst. Sci., 25, 321–334, https://doi.org/10.5194/nhess-25-321-2025, https://doi.org/10.5194/nhess-25-321-2025, 2025
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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.
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.
Roberto Giovanni Francese, Roberto Valentino, Wilfried Haeberli, Aldino Bondesan, Massimo Giorgi, Stefano Picotti, Franco Pettenati, Denis Sandron, Gianni Ramponi, and Mauro Valt
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-212, https://doi.org/10.5194/nhess-2024-212, 2024
Revised manuscript accepted for NHESS
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The deadly collapse of the Marmolada Glacier in Italy in July 2022, is part of a global trend of rapid glacial retreat due to climate change. The event was influenced by permafrost degradation and abnormal warming. Historical data, geophysical surveys, and numerical simulations were used to analyze the collapse. Ice fracturing, water infiltration, and basal lubrication were key contributors. Predicting glacier instability is rather complex but monitoring is vital to cope with the hazard.
Franz Kleine, Charlotte Bruland, Andreas Wüstefeld, Volker Oye, and Martin Landrø
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-202, https://doi.org/10.5194/nhess-2024-202, 2024
Revised manuscript accepted for NHESS
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We used a fiber optic cable along a road in western Norway to study snow avalanches signals. Our study shows that avalanches create distinct signals in the 20–50 Hz frequency range, with larger ones having weak early warning signals. However, road traffic interference complicates automatic detection. This research highlights the potential of using existing infrastructure for avalanche monitoring. Further improvements are needed for automated detection.
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.
Michael Neuhauser, Anselm Köhler, Anna Wirbel, Felix Oesterle, Wolfgang Fellin, Johannes Gerstmayr, Falko Dressler, and Jan-Thomas Fischer
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-164, https://doi.org/10.5194/nhess-2024-164, 2024
Revised manuscript under review for NHESS
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This study examines how particles move in snow avalanches. The researchers used AvaNodes, a sensor system that tracks particle movement, in combination with radar data and simulations from the open avalanche framework AvaFrame. By comparing measurements and simulations, particle velocity and avalanche front position were matched with high accuracy. The study illustrates how multiple parameter sets can yield appropriate results and highlights the complexity of avalanche simulation.
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.
Frank Techel, Stephanie Mayer, Ross S. Purves, Günter Schmudlach, and Kurt Winkler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-158, https://doi.org/10.5194/nhess-2024-158, 2024
Revised manuscript accepted for NHESS
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We evaluate fully data- and model-driven predictions of avalanche danger in Switzerland and compare them with human-made avalanche forecasts as a benchmark. We show that model predictions perform similarly to human forecasts calling for a systematic integration of forecast chains into the forecasting process.
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.
Florian Herla, Pascal Haegeli, Simon Horton, and Patrick Mair
Nat. Hazards Earth Syst. Sci., 24, 2727–2756, https://doi.org/10.5194/nhess-24-2727-2024, https://doi.org/10.5194/nhess-24-2727-2024, 2024
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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.
Renata Moura da Veiga, Celso von Randow, Chantelle Burton, Douglas Kelley, Manoel Cardoso, and Fabiano Morelli
EGUsphere, https://doi.org/10.5194/egusphere-2024-2348, https://doi.org/10.5194/egusphere-2024-2348, 2024
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We systematically reviewed 69 papers on fire emissions from the Brazilian Cerrado biome to provide insights into its placement in the atmospheric carbon budget and support future improved estimation. We find that estimating fire emissions in the Cerrado requires a comprehensive approach, combining quantitative and qualitative aspects of fire. A pathway towards this is the inclusion of fire management representation in land surface models and the integration of observational and modelling data.
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.
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.
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 accepted 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.
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.
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Short summary
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.
This paper introduces a digital twin fire model using machine learning techniques to improve the...
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