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
Sibo Cheng
CORRESPONDING AUTHOR
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
Related authors
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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.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James Millington
EGUsphere, https://doi.org/10.5194/egusphere-2023-2162, https://doi.org/10.5194/egusphere-2023-2162, 2023
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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.
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
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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
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
Modelling the vulnerability of urban settings to WUI fires in Chile
AutoATES v2.0: Automated avalanche terrain exposure scale mapping
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
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
Past and future trends in fire weather for the UK
Methodological and conceptual challenges in rare and severe event forecast verification
Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809 m a.s.l.) to encourage adaptation by mountaineers
Wildfire–atmosphere interaction index for extreme-fire behaviour
How is avalanche danger described in textual descriptions in avalanche forecasts in Switzerland? Consistency between forecasters and avalanche danger
Data-based wildfire risk model for Mediterranean ecosystems – case study of the Concepción metropolitan area in central Chile
The mud volcanoes at Santa Barbara and Aragona (Sicily, Italy): a contribution to risk assessment
Impact of information presentation on interpretability of spatial hazard information: lessons from a study in avalanche safety
ABWiSE v1.0: toward an agent-based approach to simulating wildfire spread
Multi-decadal geomorphic changes of a low-angle valley glacier in the East Kunlun Mountains: remote sensing observations and detachment hazard assessment
Spatial and temporal subsidence characteristics in Wuhan (China), during 2015–2019, inferred from Sentinel-1 synthetic aperture radar (SAR) interferometry
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.
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.
Paula Aguirre, Jorge León, Constanza González-Mathiesen, Randy Román, Manuela Penas, and Alonso Ogueda
EGUsphere, https://doi.org/10.5194/egusphere-2023-2130, https://doi.org/10.5194/egusphere-2023-2130, 2023
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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 of 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 seven case studies in Chile and concluded that the spatial arrangement of houses has substantial impact on their vulnerability to wildfires
Håvard Boutera Toft, John Sykes, Andrew Schauer, Jordy Hendrikx, and Audun Hetland
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-114, https://doi.org/10.5194/nhess-2023-114, 2023
Revised manuscript accepted for NHESS
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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.
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.
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.
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.
Alessandro Gattuso, Francesco Italiano, Giorgio Capasso, Antonino D'Alessandro, Fausto Grassa, Antonino Fabio Pisciotta, and Davide Romano
Nat. Hazards Earth Syst. Sci., 21, 3407–3419, https://doi.org/10.5194/nhess-21-3407-2021, https://doi.org/10.5194/nhess-21-3407-2021, 2021
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Santa Barbara and Aragona are affected by mud volcanism with episodic hazardous paroxysm events. Two potentially hazardous paroxysm exposed surfaces of 0.12 and 0.20 km2 were elaborated with DSMs and with historical information on the paroxysms that occurred in the past. This paper, in the end, could be a useful tool for civil protection authorities in order to take appropriate risk mitigation measurements for exposed people and for monitoring activities.
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.
Jeffrey Katan and Liliana Perez
Nat. Hazards Earth Syst. Sci., 21, 3141–3160, https://doi.org/10.5194/nhess-21-3141-2021, https://doi.org/10.5194/nhess-21-3141-2021, 2021
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Wildfires are an integral part of ecosystems worldwide, but they also pose a serious risk to human life and property. To further our understanding of wildfires and allow experimentation without recourse to live fires, this study presents an agent-based modelling approach to combine the complexity possible with physical models with the ease of computation of empirical models. Model calibration and validation show bottom-up simulation tracks the core elements of complexity of fire across scales.
Xiaowen Wang, Lin Liu, Yan Hu, Tonghua Wu, Lin Zhao, Qiao Liu, Rui Zhang, Bo Zhang, and Guoxiang Liu
Nat. Hazards Earth Syst. Sci., 21, 2791–2810, https://doi.org/10.5194/nhess-21-2791-2021, https://doi.org/10.5194/nhess-21-2791-2021, 2021
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We characterized the multi-decadal geomorphic changes of a low-angle valley glacier in the East Kunlun Mountains and assessed the detachment hazard influence. The observations reveal a slow surge-like dynamic pattern of the glacier tongue. The maximum runout distances of two endmember avalanche scenarios were presented. This study provides a reference to evaluate the runout hazards of low-angle mountain glaciers prone to detachment.
Xuguo Shi, Shaocheng Zhang, Mi Jiang, Yuanyuan Pei, Tengteng Qu, Jinhu Xu, and Chen Yang
Nat. Hazards Earth Syst. Sci., 21, 2285–2297, https://doi.org/10.5194/nhess-21-2285-2021, https://doi.org/10.5194/nhess-21-2285-2021, 2021
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We mapped the subsidence of Wuhan using Sentinel-1 synthetic aperture radar (SAR) images acquired during 2015–2019. Overall subsidence coincides with the distribution of engineered geological regions with soft soils, while the subsidence centers shifted with urban construction activities. Correlation between karst subsidence and concentrated rainfall was identified in Qingling–Jiangdi. Results indicate that interferometric SAR can be employed to routinely monitor and identify geohazards.
Cited articles
acse-cz421: DL-WG/Digital-twin-LA-global-wildfire: Reduced-order digital twin and latent data assimilation for global wildfire prediction (v1.1.1), Zenodo [data set] and [code], https://doi.org/10.5281/zenodo.7866704, 2023.
Amendola, M., Arcucci, R., Mottet, L., Casas, Q. C., Fan, S., Pain, C.,
Linden, P., and Guo, Y.: Data Assimilation in the Latent Space of a
Convolutional Autoencoder, ICCS 2021, Lect. Notes Comput. Sc.,
12746, 373–386, https://doi.org/10.1007/978-3-030-77977-1_30, 2021.
Bauer, P., Stevens, B., and Hazeleger, W.: A digital twin of Earth for the
green transition, Nat. Clim. Change, 11, 80–83,
https://doi.org/10.1038/s41558-021-00986-y, 2021.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bianchi, F. M., De Santis, E., Rizzi, A., and Sadeghian, A.: Short-Term
Electric Load Forecasting Using Echo State Networks and PCA Decomposition,
IEEE, 3, 1931–1943, https://doi.org/10.1109/ACCESS.2015.2485943, 2015.
Bonavita, M., Hólm, E., Isaksen, L., and Fisher, M.: The evolution of the
ECMWF hybrid data assimilation system, Royal Meteorological Society, 142,
287–303, https://doi.org/10.1002/qj.2652, 2015.
Burton, C., Betts, R., Cardoso, M., Feldpausch, T. R., Harper, A., Jones, C. D., Kelley, D. I., Robertson, E., and Wiltshire, A.: Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES), Geosci. Model Dev., 12, 179–193, https://doi.org/10.5194/gmd-12-179-2019, 2019.
Cheng, S., Argaud, J. P., Iooss, B., Lucor, D., and Ponçot, A.: Error
covariance tuning in variational data assimilation: application to an
operating hydrological model, Stoch. Env. Res. Risk. A., 35, 1019–1038,
https://doi.org/10.1007/s00477-020-01933-7, 2020.
Cheng, S., Prentice, I. C., Huang, Y., Jin, Y., Guo, Y. K., and Arcucci, R.:
Data-driven surrogate model with latent data assimilation: Application to
wildfire forecasting, J. Comput. Phys., 464,
111302, https://doi.org/10.1016/j.jcp.2022.111302, 2022a.
Cheng, S., Chen, J., Anastasiou, C., Angeli, P., Matar, K. O. Guo, Y. K.
Pain, C. C., and Arcucci, R.: Generalized Latent Assimilation in
Heterogeneous Reduced Spaces with Machine Learning Surrogate Models, J.
Sci. Comput.,
arXiv [preprint], https://doi.org/10.48550/arXiv.2204.03497, 2022b.
Cheng, S., Quilodrán-Casas, C., Ouala, S., Farchi, A., Liu, C., Tandeo, P., Fablet, R., Lucor, D., Iooss, B., Brajard, J., Xiao, D., Janjic, T., Ding, W., Guo, Y., Carrassi, A., Bocquet, M., and Arcucci, R.:
Machine learning with data assimilation 65 and uncertainty quantification for dynamical systems: a review, arXiv [preprint],
https://doi.org/10.48550/arXiv.2303.10462, 2023.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011.
Claussen, M., Mysak, L., Weaver, A., Crucifix, M., Fichefet, T., Loutre, M. F., Weber, S., Alcamo, J., Alexeev, V., Berger, A., Calov, R., Ganopolski, A., Goosse, H., Lohmann, G., Lunkeit, F., Mokhov, I., Petoukhov, V., Stone, P., and Wang, Z.: Earth system models of intermediate complexity:
closing the gap in the spectrum of climate system models, Clim. Dynam.,
18, 579–586, https://doi.org/10.1007/s00382-001-0200-1, 2002.
Fulton, W.: Eigenvalues, invariant factors, highest weights, and Schubert
calculus, B. Am. Math. Soc., 37, 209–250, https://doi.org/10.1090/S0273-0979-00-00865-X, 2000.
Gong, H., Yu, Y., Li, Q., and Quan, C.: An inverse-distance-based fitting
term for 3D-Var data assimilation in nuclear core simulation, Ann. Nucl. Energy, 141, 107346, https://doi.org/10.1016/j.anucene.2020.107346, 2020.
Gong, H., Cheng, S., Chen, Z., and Li, Q.: Data-Enabled Physics-Informed
Machine Learning for Reduced-Order Modeling Digital Twin: Application to
Nuclear Reactor Physics, Nucl. Sci. Eng., 196, 668–693,
https://doi.org/10.1080/00295639.2021.2014752, 2022a.
Gong, H., Cheng, S., Chen, Z., Li, Q., Quilodrán-Casas, C., Xiao, D., and
Arcucci, R.: An efficient digital twin based on machine learning SVD
autoencoder and generalised latent assimilation for nuclear reactor physics,
Ann. Nucl. Energy, 179, 109431,
https://doi.org/10.1016/j.anucene.2022.109431, 2022b.
Graves, A. and Schmidhuber, J.: Framewise phoneme classification with
bidirectional LSTM and other neural network architectures, Neural Networks,
18, 602–610, https://doi.org/10.1016/j.neunet.2005.06.042, 2005a.
Graves, A. and Schmidhuber, J.: Framewise phoneme classification with
bidirectional LSTM networks, Neural Networks, 4, 2047–2052,
https://doi.org/10.1109/IJCNN.2005.1556215, 2005b.
Grillakis, M, Voulgarakis, A., Rovithakis, A., Seiradakis, K. D., Koutroulis,
A., Field, R. D., Kasoar, M., Papadopoulos, A., and Lazaridis, M.: Climate
Drivers of Global Wildfire Burned Area, 17, 045021,
https://doi.org/10.1088/1748-9326/ac5fa1, 2022.
Huang, Z., Xue, W., Mao, Q., and Zhan, Y.: Unsupervised domain adaptation for
speech emotion recognition using PCANet, Multimed. Tools Appl.,
76, 6785–6799, https://doi.org/10.1007/s11042-016-3354-x, 2017.
Jain, P., Coogan, P. S., Subramanian, G. S., Crowley, M., Taylor, S., and
Flannigan, D. M.: A review of machine learning applications in wildfire
science and management, Environ. Rev., 28, 478–505,
https://doi.org/10.1139/er-2020-0019, 2020.
Jauhiainen, J., Hooijer, A., and Page, S. E.: Carbon dioxide emissions from an Acacia plantation on peatland in Sumatra, Indonesia, Biogeosciences, 9, 617–630, https://doi.org/10.5194/bg-9-617-2012, 2012.
JASMIN Site: JASMIN The UK's data analysis facility for environmental science, https://jasmin.ac.uk/, last access: 26 October 2022.
Kim, S.: Particulate Matter and Ozone: Remote Sensing and Source Attribution, ProQuest Dissertations Publishing, https://dash.harvard.edu/handle/1/17467177 (last access: 21 April 2023), 2015.
Lasslop, G., Coppola, A. I., Voulgarakis, A., Yue, C., and Veraverbeke, S.:
Influence of Fire on the Carbon Cycle and Climate, Current Climate Change
Reports, 5, 112–123, https://doi.org/10.1007/s40641-019-00128-9, 2019.
Lawless, A. S., Gratton, S., and Nichols, N. K.: Approximate iterative method
for variational data assimilation, Int. J. Numer.
Meth. Fl., 1, 1129–1135, https://doi.org/10.1002/fld.851, 2005.
Lawrence, B. N. and Bennett, V. L. and Churchill, J. and Juckes, M. and Kershaw, P. and Pascoe, S. and Pepler, S. and Pritchard, M., and Stephens, A.: Storing and manipulating environmental big data with JASMIN, 2013 IEEE International Conference on Big Data, Silicon Valley, CA, USA, 6–9 October 2013, https://doi.org/10.1109/BigData.2013.6691556, 2013.
Li, H., Li, Y., Wang, Z., and Li, Z.: Remaining Useful Life Prediction of
Aero-Engine Based on PCA-LSTM, 2021 7th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO), IEEE, Guangzhou, China, 11–13 June 2021, 63–66,
https://doi.org/10.1109/CMMNO53328.2021.9467643, 2021.
Lorenc, C. A., Ballard, P. S., Bell, S. R., Ingleby, B. N., Andrews, F. L.
P., Barker, D. M., Bray, R. J., Clayton, M. A., Dalby, T., Li, D., Payne, J.
T., and Saunders, W. F.: The Met. Office global three-dimensional variational
data assimilation scheme, Royal Meteorological Society, 126, 2991–3012,
https://doi.org/10.1002/qj.49712657002, 2000.
Ma, X., Lu, X., Yu, Y., Zhu, J., and Chen, J.: Progress on hybrid
ensemble-variational data assimilation in numerical weather prediction,
J. Trop. Meteorol., 20, 1188–1195, 2014.
Mangeon, S., Voulgarakis, A., Gilham, R., Harper, A., Sitch, S., and Folberth, G.: INFERNO: a fire and emissions scheme for the UK Met Office's Unified Model, Geosci. Model Dev., 9, 2685–2700, https://doi.org/10.5194/gmd-9-2685-2016, 2016.
Marlier, E. M., DeFries, S. R., Kim, S. P., Koplitz, N. S., Jacob, J. D.,
Mickley, J. L., and Myers, S. S.: Fire emissions and regional air quality
impacts from fires in oil palm, timber, and logging concessions in
Indonesia, Environ. Res. Lett., 10, 85005,
https://doi.org/10.1088/1748-9326/10/8/085005, 2015.
Masci, J., Meier, V., Ciregan, D., and Schmidhuber, J.: Stacked convolutional auto-encoders for hierarchical feature extraction, International Conference on Artificial Neural Networks 2011, 6791, 52–59, https://doi.org/10.1007/978-3-642-21735-7_7, 2011.
Mohan, A. and Gaitonde, D.: A Deep Learning based Approach to Reduced Order
Modelling for Turbulent Flow Control using LSTM Neural Networks, arXiv [preprint], https://doi.org/10.48550/arXiv.1812.04951, 2018.
Nadeem, K., Taylor, S. W., Woolford, D., and Dean, C.: Mesoscale
spatiotemporal predictive models of daily human- and lightning-caused
wildland fire occurrence in British Columbia, Int. J.
Wildland Fire, 29, 11–27, https://doi.org/10.1071/WF19058, 2020.
Pais, C., Miranda, A., Carrasco, J., and Shen, Z. M.: Deep Fire Topology:
Understanding the role of landscape spatial patterns in wildfire
susceptibility, Environ. Modell. Softw., 143, 105–122,
https://doi.org/10.1016/j.envsoft.2021.105122, 2021.
Pechony, O. and Shindell, D. T.: Fire parameterization on a global scale,
J. Geophys. Res., 114, D16115, https://doi.org/10.1029/2009jd011927,
2009.
Peyron, M., Fillion, A., Gürol, S., Marchais, V., Gratton, S., Boudier,
P., and Goret, G.: Latent space data assimilation by using deep learning,
arXiv [preprint], https://doi.org/10.48550/arXiv.2104.00430, 2021.
Prentice, C. I. and Cowling, A. S.: Dynamic Global Vegetation Models,
Encyclopedia of Biodiversity, 2, 670–689,
https://doi.org/10.1016/B978-0-12-384719-5.00412-3, 2013.
Quilodrán-Casas, C., Silva, V., Arcucci, R., Heaney, C., Guo, Y., and
Pain, C.: Digital twins based on bidirectional LSTM and GAN for modelling
COVID-19, Neurocomputing, 470, 11–28,
https://doi.org/10.48550/arXiv.2102.02664, 2022.
Rabin, S. S., Melton, J. R., Lasslop, G., Bachelet, D., Forrest, M., Hantson, S., Kaplan, J. O., Li, F., Mangeon, S., Ward, D. S., Yue, C., Arora, V. K., Hickler, T., Kloster, S., Knorr, W., Nieradzik, L., Spessa, A., Folberth, G. A., Sheehan, T., Voulgarakis, A., Kelley, D. I., Prentice, I. C., Sitch, S., Harrison, S., and Arneth, A.: The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions, Geosci. Model Dev., 10, 1175–1197, https://doi.org/10.5194/gmd-10-1175-2017, 2017.
Teckentrup, L., Harrison, S. P., Hantson, S., Heil, A., Melton, J. R., Forrest, M., Li, F., Yue, C., Arneth, A., Hickler, T., Sitch, S., and Lasslop, G.: Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models, Biogeosciences, 16, 3883–3910, https://doi.org/10.5194/bg-16-3883-2019, 2019.
Vallino, J. J.: Improving marine ecosystem models: Use of data assimilation
and mesocosm experiments, J. Mar. Res., 58,
117–164, https://doi.org/10.1357/002224000321511223, 2000.
Ward, D. S., Kloster, S., Mahowald, N. M., Rogers, B. M., Randerson, J. T., and Hess, P. G.: The changing radiative forcing of fires: global model estimates for past, present and future, Atmos. Chem. Phys., 12, 10857–10886, https://doi.org/10.5194/acp-12-10857-2012, 2012.
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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