One area of attention is how extreme fires are currently represented by different fire models. Due to their stochastic nature, uncertainty in observations, and the challenge of representing local processes within global models, extreme fires and their impacts still present a challenge to coupled modelling. The big data science models and machine learning approaches show promise in representing extremes but are weak in coupling feedbacks to vegetation, soils and the wider Earth System.
We also welcome case studies of regional extreme wildfire events, their impacts, and prevention and mitigation strategy experiences worldwide. We encourage contributions from a wide range of disciplines, including global, regional, and landscape modelling, statistical and process-based modelling, observations and field studies, science and social science studies on all temporal scales. In this session, we aim to share knowledge across multiple disciplines, from science to decision-makers and practitioners, to help overcome the challenges that wildfires pose to our models and our society.
We aim to explore the significance and interactions of extreme wildfires and their impacts on society and the earth system and identify the current gaps in our understanding to help us prepare for and mitigate future extreme wildfire events.
How to cite: Jones, M.: Navigating the Era of Extreme Wildfires: Scientific Solutions and Future Directions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13652, https://doi.org/10.5194/egusphere-egu25-13652, 2025.
Wildfire influences the carbon cycle and impacts property, harvestable timber, and public health. The year 2023 saw a record area burned of 14.9 Mha in Canada, compared to an average of ~2 Mha between 1959 and 2015. Boreal wildfire is a critical process that is difficult to represent in land surface models. To enhance our understanding of historical and future wildfire regimes in Canada and their impact on carbon cycling we implement two methods of representing boreal wildfire in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC). These include a new dynamic wildfire model that represents fire weather and lightning ignitions as well as a fire model which is forced by historical observations of burned area. We find that in 2023 simulated wildfire emissions were eight times their 1985 - 2022 mean with consequences for the annual net carbon balance in Canada. Moving into the future we find that climate change below a 2°C global target (shared socioeconomic pathway [SSP] 126) yields burned area near modern (2004 - 2014) norms by end-century (2090 - 2100). However, under rapid climate change (SSP370/585), the end-century mean annual burned area increases 2 - 4 times, compared to present-day values, approaching the burned area seen in Canada in 2023. This work illustrates the historical implications of Canadian wildfires on the carbon cycle and the future implications of climate change for area burned in Canada.
How to cite: Curasi, S., Melton, J., Arora, V., Humphreys, E., and Whaley, C.: Canadian wildfire in a changing climate from the 2023 wildfire season to the 2100s, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13730, https://doi.org/10.5194/egusphere-egu25-13730, 2025.
The Brazilian Pantanal, renowned for its rich ecosystems and biodiversity, is under increasing threat from more frequent and intense fires. These wildfires endanger the region's ecology, wildlife, and critical role as a carbon sink. The catastrophic fires of 2020, which burned approximately 4 million hectares, highlighted the pressing need to better understand the Pantanal’s fire vulnerability and to develop effective strategies for protecting its ecosystems and carbon storage capacity.
Using the FLAME model, we evaluated the Pantanal’s fire susceptibility in the context of climate and land cover changes. Our analysis identified shifting precipitation patterns as a key driver of fire activity. Wetland cover emerged as a mitigating factor, with regions exhibiting a doubled wetland extent requiring half as much rainfall to avoid extreme burning levels. However, reducing wetland areas due to agricultural expansion and water management has significantly increased the region's fire vulnerability. The extreme fires of 2020 were linked to a critical threshold of reduced wetland extent and precipitation; without prior wetland degradation, the fires would likely have been less severe.
Our findings emphasize the necessity of integrating wetland cover dynamics and climate extremes into the Pantanal's fire management and conservation planning. This approach is vital for bolstering the region's resilience to fire and climate change, preserving its ecological integrity, and maintaining its carbon storage potential. The FLAME model facilitates the rapid assessment of burning scenarios, providing valuable insights for early preparedness and response strategies to protect this unique and irreplaceable ecosystem.
How to cite: Barbosa, M., Kelley, D., Burton, C., Libonati, R., Da Veiga, R., Ferreira, I., and Anderson, L.: Burning In Pantanal Driven By Wetland Degradation And Lower Precipitation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18657, https://doi.org/10.5194/egusphere-egu25-18657, 2025.
Haralamb Georgescu was a Romanian architect who fleed the communist rule and settled in the USA. After a brief period in the Eastern part, he settled in Los Angeles where not only did he build his most iconic buildings, but also was featured for futuristic utopic designs. Within the Romanian funded project "Future on the past" (featured at EGU 2023), which used digital humanities methods to develop innovative mapping techniques, including ontologies, for earthquake, flood and fire, also the buildings of Haralamb Georgescu were studied. This happened in conjunction with another Romanian sister project (both ended with the PNIII framework programme on the 31.12.2024) which focused on Romanian-American relationships in the interwar time in a publication of which first results were published. Haralamb Georgescu started his career in the interwar time in Romania. 2-7 January 2025 I visited Mangalia where is his last building built in Romania. Some others built in Bucharest were mapped before, and so were those in the USA, including Los Angeles. Materials on Los Angeles were available from two sources: the Getty archives and a book of drawings of building projects, catalogue of a past exhibition at the "Ion Mincu" University of Architecture and Urbanism, which was done after the rediscovery of Haralamb Georgescu following the restoration of the Pasinetti house, the most emblematic one, featured in a magazine of the time. The mapping in Google Maps of the buildings of Haralamb Georgescu was exported and imported in arcGIS online Living Atlas, the map on US current wildfires. This way three buildings of Haralamb Georgescu were identified (Bucharest restaurant next to the Eaton forest, Lark Arrow apartments in the same area, Rinaldi convalescent hospital) next to wildfires and one on a wildfire and this was the Pasinetti House in Beverly Hills. Unfortunately searching the news confirmed the mapping as the CBS reported dogs being rescued from the lost house of Pasinetti. Besides, during the project in frame of work for COST CA18135 - Fire in the Earth System: Science & Society (FIRElinks), as working group member of group 5 Socio-economic aspects of fire and fire risk management, an ontology of fire was developed and published. This contribution will test how the findings fit into this ontology. Current work is being done in the Climate change adaptation working group of ICOMOS ISCARSAH related to the structures of monuments which includes the effects of wildfire. The architecture of Haralamb Georgescu is Modernist architecture related in typology to that of the Cyclades, and the publication from the COST action also covered the relationship to fires in Greece, specifically Paros in 2022. Some more insights on this will be included after more site visits. This is in line with the research question of the project on how vernacular architecture may render Modernist buildings which include elements inspired by it more safe, through so-called local culture, extensively studied so far for seismic events and started for flood events, but scarcely so for wildfires. The ontology in computer science understanding helps this.
How to cite: Bostenaru Dan, M.: The impact of the January 2025 Southern California fires on the buildings of Haralamb Georgescu in Los Angeles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7664, https://doi.org/10.5194/egusphere-egu25-7664, 2025.
Firebrands, small pieces of burning vegetation, can be detached and transported far away from the main fire front during intense fires. The process of firebrand generation, transport and ignition of a fuel bed is known as spotting. Spotting can start new fires and plays an important role in wildfire spread, presenting critical challenges for containment strategies and risk management. This study utilizes a series of high-resolution simulations to evaluate the influence of wind speed, topographic features, fire intensity and atmospheric stability on firebrand transport and fuel ignition. By coupling a fire-atmosphere modeling with combustion and firebrand transport models, we analyze key processes affecting firebrand trajectories and ignition potential.
To obtain realistic conditions of an intense fire, we use the cloud resolving weather model MesoNH coupled with the fire propagation model ForeFire. Such coupled fire-atmosphere simulations are designed to have a computational domain of the same scale of large wildfires, here 80m resolution for 14 km wide, 28 km length and 16 km high. This coupled fire atmosphere model is run for 36 different conditions:
- Three reference wind speeds (5, 10 and 15m.s-1)
- Three head fire heat flux (40, 80 and 120 kW.m-2)
- Three topographies (a flat terrain, a hill and a canyon)
- Two atmospheric conditions: stable and unstable
Firebrands are modelled as point masses with three degrees of freedom (three translations), with a set of aerodynamic coefficients and a combustion model. By combining high-resolution LES simulations with detailed firebrand trajectory and combustion processes, we expect to obtain realistic firebrand trajectories.
The resulting different ground patterns distributions of potentially still burning firebrands show that high wind speeds significantly increase firebrand lofting and horizontal transport distances of up to several kilometers. The maximum spotting distance is increased when topographic elements, such as hills or canyons, are added to the simulation. Furthermore, atmospheric stability exerts a critical influence on firebrand behavior: unstable conditions encourage turbulent mixing, vortices, and upward lofting with increased maximum heights reached by the firebrands.
Our results also emphasize the interaction between fire intensity, terrain-driven wind patterns, and atmospheric conditions. This should allow to identify thresholds where long-range spotting becomes most likely. As a result, this research provides valuable insights into the mechanisms driving firebrand dynamics, advancing predictive wildfire modeling and improving hazard mitigation strategies.
These results contribute to the broader understanding of wildfire behavior and have practical implications for fire management, evacuation planning, and the development of tailored mitigation measures to address the growing threats posed by wildfires in a changing climate.
How to cite: Alonso Pinar, A., Filippi, J.-B., and Filkov, A.: Meteorological impacts on long-range spotting of firebrands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2126, https://doi.org/10.5194/egusphere-egu25-2126, 2025.
It is becoming increasingly important to understand how ecosystems will recover from wildfires, which are increasing in frequency, severity and size, especially in coniferous forests. Megafires—defined as wildfires burning exceptionally large areas—are thought to have more negative effects on ecosystems than smaller fires. However, the effects of megafires vary substantially, and one hypothesis is that intra-fire heterogeneity of burn patches can dictate the recovery of ecosystems. We evaluated the role of spatial configuration of burn patches within megafires using remote sensing data of fires and vegetation at 30x30 m resolution across 36 years and field-survey data of forest recovery in the western USA. Megafires contributed 62% of total burned area, with their frequency explaining 83% of the variation in the inter-annual burned area from 1984-2020. However, megafire size alone did not inherently result in severe ecosystem transitions, with megafires that experienced large contiguous patches of severely burned forest taking longer to recover. Field surveys illustrated delayed recovery resulted from a tree dispersal-limitation threshold of ca. 150 m, such that increasing distance from intact coniferous forest significantly delayed recovery. Machine learning image classification revealed that the rate of recovery in the severely burned areas has declined by ca. 50% from 1984-2020, with distance from seed source being more important than all climate variables analysed. Consequently, spatial configuration of high-severity burn patches within fires—which have become both larger and more compact through time—are key for assessing the effect of megafires on forest resilience.
How to cite: Pellegrini, A. and Schoenecker, J.: Spatial configuration of severely burned patches within megafires explains ecosystem resilience , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4739, https://doi.org/10.5194/egusphere-egu25-4739, 2025.
Climate warming has caused a widespread increase in extreme fire weather, making forest fires longer-lived and larger. The average forest fire size in Canada, the USA and Australia has doubled or even tripled in recent decades. In return, forest fires feed back to climate by modulating land–atmospheric carbon, nitrogen, aerosol, energy and water fluxes. However, the surface climate impacts of increasingly large fires and their implications for land management remain to be established. Here we use satellite observations to show that in temperate and boreal forests in the Northern Hemisphere, fire size persistently amplified decade-long postfire land surface warming in summer per unit burnt area. Both warming and its amplification with fire size were found to diminish with an increasing abundance of broadleaf trees, consistent with their lower fire vulnerability compared with coniferous species. Fire-size-enhanced warming may affect the success and composition of postfire stand regeneration as well as permafrost degradation, presenting previously overlooked, additional feedback effects to future climate and fire dynamics. Given the projected increase in fire size in northern forests, climate-smart forestry should aim to mitigate the climate risks of large fires, possibly by increasing the share of broadleaf trees, where appropriate, and avoiding active pyrophytes.
How to cite: Yue, C., Zhao, J., Wang, J., Hantson, S., Wang, X., He, B., Li, G., Wang, L., Zhao, H., and Luyssaert, S.: Forest fire size amplifies postfire land surface warming, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1986, https://doi.org/10.5194/egusphere-egu25-1986, 2025.
In recent years, newly available observations, and modelling systems as well as advancements in machine learning have transformed the capabilities of fire danger prediction systems. The European Centre for Medium-Range Weather Forecasts (ECMWF) has set out to forecast wildfire probability on a global scale up to a week in advance. A key milestone was the development of the SPARKY-Fuel Characteristics dataset, released in 2024, which provides the first long-term, high-resolution record of real-time fuel status.
This study evaluates ECMWF’s operational data-driven fire prediction system over its first year. Through analysis of major wildfire events, including the extensive fires in Canada in 2023 and the fires in Los Angeles in 2025, we demonstrate the potential of data-driven methods to outperform traditional fire danger metrics. The results highlight the role of dynamic, global fuel assessments and machine learning in improving the accuracy and timeliness of fire probability forecasts.
Our findings underscore the importance of integrating both innovative data-driven approaches and key variables into operational forecasting systems, providing critical support for fire management and mitigation efforts worldwide.
How to cite: McNorton, J.: Global Data-Driven Prediction of Fire Activity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17607, https://doi.org/10.5194/egusphere-egu25-17607, 2025.
The Fire Weather Index (FWI) is a widely used metric for assessing wildfire danger, relying on sub-daily meteorological data, typically recorded at local noon. However, most climate models and observational datasets only provide daily-aggregated variables, which can introduce biases in fire weather assessments under climate change. This study evaluates how approximating noon-specific calculations impacts the trends of extreme fire weather days (FWI95d), defined as the annual number of days exceeding the 95th percentile of daily FWI values (FWI95d).
Using global data from ERA5 for 1980–2023, we find that FWI95d have increased by 65% over 44 years, corresponding to an average of 11.66 additional extreme fire weather days per year. Daily approximations consistently overestimate this trend by 5–10%, with the largest differences observed in fire-prone regions such as the western United States, southern Africa, and parts of Asia. Among the tested proxies, the combination of daily mean values for air temperature, relative humidity, precipitation, and wind speed exhibits the lower biases, while proxies involving minimum relative humidity tend to overestimate trends more significantly.
Our findings emphasize the importance of sub-daily meteorological data for accurate wildfire risk projections. In its absence, we recommend prioritizing daily mean approximations over other proxies as the least-biased alternative in the absence of noon-specific data. These results underscore the potential for misrepresentation of future fire weather risks in climate models, particularly if systematic biases introduced by daily approximations are not addressed. Future climate model intercomparison projects should prioritize the inclusion of sub-daily meteorological outputs to enhance the reliability of fire weather assessments globally.
Acknowledgements
M.T. acknowledges funding by the Spanish Ministry of Science, Innovation and Universities through the Ramón y Cajal Grant Reference RYC2019-027115-I and through the project ONFIRE, Grant PID2021-123193OB-I00, funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This work was supported by the project ‘Climate and Wildfire Interface Study for Europe (CHASE)’ under the 6th Seed Funding Call by the European University for Well-Being (EUniWell).
How to cite: Moreno, A., Matteo, A., Herrera, S., Azorin-Molina, C., Bedia, J., Provenzale, A., Dunn, R. J. H., Garnés-Morales, G., Quilcaille, Y., Ángel Torres Vázquez, M., Di Giuseppe, F., and Turco, M.: Overestimating Fire Weather Trends: Challenges in Using Daily Climate Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6292, https://doi.org/10.5194/egusphere-egu25-6292, 2025.
In the United States, catastrophic wildfires have killed hundreds of people in recent years, including two high fatality events in the 2018 Camp Fire in California and the 2023 Lahaina Fire in Hawaii. These disasters were astounding not only because so many died so quickly, but also because they represent a shift in understanding of who dies in contemporary wildfires. For much of the 20th century, the primary lives lost in wildfires were the front line firefighters at the greatest risk. Over the last two decades, however, climate change has increased the extremity of wildfire behavior and resulted in numerous catastrophic wildfire events globally where dozens of civilians were killed. Here we evaluate both the biophysical drivers of fatal wildfires in the US and the social characteristics of wildfire fatalities. Downslope winds during drought conditions at the wildland-urban interface are the primary indicators of civilian fatalities, particularly in specific forest-shrubland interface Mediterranean fuel types and in complex terrain. Social vulnerability of the resident population was also a key driver of fatalities, as older populations with lower levels of mobility struggled to evacuate with no advanced notice. Fires that killed civilians stood in stark contrast to fires that killed firefighters, which occur primarily during peak fire season during extreme heat events and in rural, relatively forested areas. These differences highlight a critical gap in understanding how to mitigate civilian wildfire fatalities.
How to cite: Kolden, C. and Abatzoglou, J.: Who dies in wildfires? Common denominators of fatal wildfires in the US, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14597, https://doi.org/10.5194/egusphere-egu25-14597, 2025.
The 2023/24 fire season was marked by record-breaking burnt areas and carbon emissions in Canada, deadly blazes in Hawaii, extreme drought and smoke in the Amazon, burning in the Pantanal wetlands, and Europe's largest wildfire on record. These events exemplify extreme wildfires' growing prevalence and far-reaching impacts on societies, ecosystems, and global climate systems. Each year, the emergence of such events raises urgent questions from policymakers, fire management agencies, and the public:
- How much was climate to blame?
- Was it caused by humans?
- Who is affected?
- How does this year compare to previous years?
- Will we see more fires like this in the future?
- What can we do to prevent or prepare for them?
The inaugural State of Wildfires report addresses these questions by systematically analysing extreme fire events from the March 2023–February 2024 fire season. It links anomalies in burned area and emissions to drivers such as high fire weather and fuel abundance. Attribution analyses revealed that climate change amplified burned area by up to 40%, 18%, and 50% in Canada, Greece, and Amazonia, respectively. The report also projects an increasing risk of future extreme fires, even under ambitious emissions pathways aimed at limiting warming to 1.5–2°C. However, impacts at these emission levels are still projected to be less severe than those in higher warming scenarios. In Canada, for example, projections suggest that fires like those of 2023 could become 6–11 times more frequent by the end of the century under medium–high emissions scenarios.
Here, we present the main insights from the report, celebrate advances in fire science that are helping to meet the challenge of extreme fires, and invite feedback from the scientific community. We seek perspectives on missing analyses, overlooked impacts, and underexplored regions to enhance future reports.
How to cite: Kelley, D. I., Jones, M. W., Burton, C., and Di Giuseppe, F. and the State of Wildfires Report Co-authors: The State of Wildfires report: an annual review of fire activity and extreme events , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19519, https://doi.org/10.5194/egusphere-egu25-19519, 2025.
Tropical forests are at high risk of dieback due to human-induced disturbances including forest fires, agricultural expansion, and logging. These disturbances can degrade the ecosystems, slow forest recovery, and disrupt the global carbon cycle, leading to irreversible changes or ‘tipping point’ in the Earth’s climate system – the point at which disruption to the climate potentially becomes irreversible. Early warning signals of tipping points for the Amazon rainforest and Greenland ice sheet have already been detected. Monitoring these forest ecosystems is crucial to mitigate future long-term consequences. In order to analyse the response of vegetation to disturbances, we must first identify such disturbances, ideally across the entire tropics over a long period of time. We must also carefully consider what we mean by a “disturbance” and it is not necessarily just the largest fire event. It may be that a significant disturbance is a modest fire event but in a region that does not typically experience burning or a fire event outside of the typical fire season. In both of those instances, we might expect the vegetation response to have different characteristics to those from regular, large burns.
In this study, we applied Isolation Forest (IF) algorithm to detect Burned Area (BA) anomaly and apply it to ESA FireCCI51 dataset (2001-2020) over IPCC AR6 defined land regions, with Madagascar as a case study region. IF identifies anomalies by considering how easily they can be isolated from the main distribution and allows us to introduce features beyond just the burned area itself (e.g., time and location of the fire). Explainable AI (SHAP) analysis was also performed to further understand the predicted BA anomaly. A higher number of BA anomalies were mostly linked to larger values of BA over the Tropics and in Madagascar, however, anomalies in BA are also affected by temporal and geographical factors other than the magnitude of BA. IF detected a high number of anomalies (>20) in the northern region of Madagascar which comparatively had lower BA values which could indicate deviation from seasonal fire patterns. These results were further explained by SHAP analysis which showed that BA was the main factor influencing prediction of BA anomaly but that time and location could play a significant role in some anomaly detections. This suggests that deviation from the typical fire seasonality was another factor contributing to anomaly detection. The high number of anomalies in these specific areas highlights the need for targeted fire management strategies so that policymakers can anticipate the long-term effects of climate change and human activity on tropical forests, guiding sustainable land use, conservation, and climate adaptation efforts in vulnerable regions.
How to cite: Poudel, S., Parker, R., Balzter, H., Quaife, T., and Kelley, D.: Detecting Burned Area Anomalies with Isolation Forest in the Tropics: A Focus on Madagascar , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2854, https://doi.org/10.5194/egusphere-egu25-2854, 2025.
Wildfires are a critical component of natural ecosystems, contributing to biodiversity by shaping habitat structures and promoting species adaptation, but also posing significant risks to human life, infrastructure, and air quality. Wildfires can be characterized by both their impact and the drivers of their occurrence. Historical data exploration is essential for researchers to build data-driven models for wildfire risk assessment and also to capture the characteristics of extreme wildfire events (EWE). Such data may include fire perimeter records, weather observations, vegetation types, and topographic details, all of which contribute to understanding the conditions that lead to extreme fire behavior.
The first step toward achieving this goal involves establishing a comprehensive data-cube that integrates all relevant datasets for wildfire risk assessment. A data-cube framework simplifies data exploration and querying by organizing static and dynamic data (in terms of time varying) in a structured format. The data-cube stores multi-dimensional arrays, allowing for efficient analysis of spatial and temporal variations in complex datasets. Static data (e.g., digital elevation model) represent constant landscape features, while dynamic data (e.g., relative humidity or temperature) capture temporal variations. Cloud storage solutions are vital for managing the high memory requirements of data-cube structures, enabling cheaper storage and open-source availability.
The primary aim of this study is to utilize available data-cubes to identify the conditions that characterize EWE across historical records. By analyzing spatial and temporal dynamic data related to both wildfire occurrences and predisposing meteorological factors, we want to find patterns and signatures of extreme wildfires. Furthermore, additional datasets from various domains and resolutions will be structured into a similar data-cube format for broader analysis.
Focus will be on the Italian peninsula, leveraging on climatic data at a 3 km spatial resolution with hourly temporal intervals (Chapter Dataset, https://doi.org/10.25927/0ppk7-znk14) allowing for detailed capture of conditions surrounding extreme wildfire events. The outcomes of this study will contribute to the development of probabilistic risk assessment models, providing valuable insights for wildfire risk management and mitigation strategies.
Keywords: Extreme Wildfire Events, Probabilistic Wildfire Risk Assessment, Data-Cube, Meteorological indices in Wildfire Risk Assessment
How to cite: Ghasemiazma, F., Trucchia, A., Meschi, G., Perello, N., Tonini, M., Degli Esposti, S., and Fiorucci, P.: Probabilistic Analysis of Extreme Wildfire events in Italy Using Data-Cube Technology, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13787, https://doi.org/10.5194/egusphere-egu25-13787, 2025.
The frequency and severity of wildfires are projected to increase in the Mediterranean region. Greece currently lacks a developed standardized system for identifying and prioritizing burnt areas in relation to their restoration needs. Prioritization of areas for post-fire restoration efforts using geographic information system (GIS) and remote sensing (RS) can be useful in decision-making. However, this approach is often insufficient in effectively integrating perspectives from multiple stakeholders and socio-ecological criteria. Combining qualitative methods such as interviews with GIS and RS methods can enhance the understanding of nuances in a local context.
We designed an approach to identify high-priority areas for post-fire restoration. The identification was based on interviews with stakeholders and the application of GIS and RS. We conducted 15 interviews with stakeholders working on post-fire issues and selected criteria for the prioritization analysis based on their views. The expert interviews revealed perceptions regarding the necessity of vegetation restoration and rehabilitation efforts and helped to identify the key characteristics respondents consider essential for prioritizing burnt areas for restoration. These insights established an analysis using GIS and RS to select areas based on the identified characteristics.
We selected the areas for restoration based on fire history, slope, and designation as part of the protected areas. The outcomes of the analysis helped to highlight three areas that potentially need special attention. We propose a prioritization system that considers the natural regeneration potential of the Mediterranean and on-the-ground socio-ecological limitations, and can help government agencies, local foresters, private consultancies, and NGOs plan restoration actions and optimize the effectiveness of restoration programs in Greece.
How to cite: Palenova, E., Veraverbeke, S., Kontos, T., and Ebert, K.: Prioritizing Areas for Post-Fire Restoration in Greece Using Mixed-Methods Spatial Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1579, https://doi.org/10.5194/egusphere-egu25-1579, 2025.
In recent decades, surface air temperatures in the Arctic increased faster than average global temperatures. At the same time, weather conditions that favor wildfires became more frequent globally and will likely continue to do so in a warming climate. This might lead to an increase in fire activity in most areas of the world, but particularly in regions with moderate moisture supply that are rich in biomass, such as North American temperate forests and boreal forests.
Extreme wildfires potentially emit large quantities of smoke that can be elevated as high as to the stratosphere, thereby possibly leading to a long-lasting atmospheric perturbation. Smoke aerosol is mostly composed of black carbon (BC) and organic carbon (OC). While BC mainly impacts the climate by heating the atmosphere through absorption of solar radiation, OC particles are important as cloud condensation nuclei, affecting cloud and precipitation formation. In light of the rapid Arctic warming, it is crucial to understand the role of smoke aerosol from wildfires in the Arctic climate system.
Using multidecadal simulations with the global aerosol-climate model ECHAM6.3.0-HAM2.3., it is analyzed on which pathways BC and OC emitted during extreme boreal wildfire events are transported towards the Arctic and how their transport patterns differ from those of smoke particles originating from moderate boreal wildfires. The contribution from the wildfire aerosol to the total poleward aerosol flux is calculated, and it is quantified which fraction of boreal wildfire aerosol reaches the Arctic region in the course of extreme fires. Transport heights, the accurate representation of which still poses a challenge to current climate models, are compared to height-resolved measurements of smoke aerosol.
How to cite: Paul, S. and Heinold, B.: Poleward transport of smoke aerosol from extreme boreal wildfires, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18268, https://doi.org/10.5194/egusphere-egu25-18268, 2025.
The study of wildfires is crucial to understanding the Earth system, as severe wildfire events can lead to intense degradation of nature and property. The record-breaking 2023 Canadian wildfire event best represents this, with approximately 5% of the total forest area of Canada burned [1] [2], resulting in biomass burning (BB) emissions quantitatively comparable to the annual fossil fuel emissions of large nations [3], and with the highest Canadian carbon emissions on record [4]. Increased mean temperatures along with decreased humidity in the region due to climate change are considered responsible for this record series of wildfires [5], as increasing mean temperatures along with decreasing humidity in the region led to increased fire risk.
Large amounts of carbonaceous aerosols can exert substantial atmospheric radiative forcing, thus it is important to study the consequences of these emissions on large-scale atmospheric composition and meteorological behavior. In this work, global and local atmospheric impacts of this historic wildfire event are analyzed using the EC-Earth3 earth system model [6] in its standard AerChem configuration. BB emissions from the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS) were used as input in the model to produce two 10-member ensembles simulations, with and without the 2023 Canadian wildfire emissions. The results are analyzed, and the differences in various modelled atmospheric quantities between the two ensembles are spatially cross-correlated to determine connections between atmospheric anomalies and wildfire intrusions.
Modelled monthly changes in radiative effects, cloud cover, large-scale circulation, and temperature patterns throughout the North Hemisphere and Canada are found as a result of the 2023 BB emissions, and the mechanisms via which these can be caused are discussed and explained. These changes include the long-range transport of the BB pollutants in the troposphere and the stratosphere with marked impacts on cloud cover and on temperatures at low and high altitudes, differential cooling over the Canadian region due to a dual influence of direct and indirect effects of AOD increases, and even large-scale circulation anomalies which led to cooling as far as in Eastern Siberia. We find that the modelled temperature anomalies between the two ensembles caused by the wildfire-generated aerosols can be as intense as -5.44 °C locally, while the modelled average hemispheric temperature anomaly is equal to -0.91 °C.
[1] "Fire Statistics". Canadian Interagency Forest Fire Centre. Retrieved January 4, 2024.
[2] “The State of Canada’s Forests: Annual Report”. 2022. Canadian Minister of Natural Resources.
[3] Byrne, Brendan, et al. "Carbon emissions from the 2023 Canadian wildfires" Nature. 2024 835-839.
[4] “Copernicus: Emissions from Canadian wildfires the highest on record – smoke plume reaches Europe”. Atmosphere Monitoring Service, Copernicus. Retrieved January 4, 2024.
[5] Barnes, Clair, et al. "Climate change more than doubled the likelihood of extreme fire weather conditions in eastern Canada" 2023.
[6] Döscher, Ralf, et al. "The EC-earth3 Earth system model for the climate model intercomparison project 6." Geoscientific Model Development Discussions. 2021 1-90.
How to cite: Rosu, I.-A., Kasoar, M., Mourgela, R.-N., Boleti, E., Parrington, M., and Voulgarakis, A.: Large-scale impacts of the 2023 Canadian wildfires on the Northern Hemisphere atmosphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10833, https://doi.org/10.5194/egusphere-egu25-10833, 2025.
Wildfires can significantly alter the hydrological regime of a watershed until vegetation is reestablished and the hydrological cycle returns to its pre-disturbance state. These wildfire-induced changes can disrupt flow patterns by reducing rainfall interception and evapotranspiration due to vegetation loss. Additionally, wildfires can affect soil permeability, either through ash deposition or, in boreal regions, by facilitating permafrost thaw.
Land surface models play a critical role in understanding and predicting interactions between the Earth's surface the atmosphere. They enable detailed assessments of water, energy, and carbon cycling, which are essential for climate modeling, ecosystem management, and policy development.
In this study, we analyze surface runoff simulated by six fire-enabled ISIMIP3a land surface models for the period 1850–2019. We identify changes in the runoff coefficient between the most fire-active and least fire-active decades in the timeseries. To isolate the role of long-term climatic trends, we utilize counterfactual simulation outputs driven by detrended observational climate data, where the signal of global warming has been removed.
Our preliminary results reveal consistent patterns between the modeled results and observed runoff changes reported in other studies, though substantial variability exists among the different land surface models. This work aims to assess the ability of state-of-the-art land surface models to represent a complex interaction on the land surface, while also enhancing our understanding of the hydrological impacts of wildfires and contributing to improving the representation of fire-hydrology processes in modeling frameworks.
This work is supported by Leverhulme Centre for Wildfires, Environment, and Society through the Leverhulme Trust, grant number RC-2018-023.
How to cite: Grillakis, M. and Voulgarakis, A.: Hydrological impacts of wildfires on a global scale: An analysis based on the fire-enabled models of ISIMIP., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8889, https://doi.org/10.5194/egusphere-egu25-8889, 2025.
The Mediterranean region is one of Europe’s most fire-prone and vulnerable areas, facing compounding risks from urban expansion and wildfire activity. This study examines the evolution of human exposure to wildfires in Catalonia, northeastern Spain, over three decades (1992–2021). Using high-resolution geospatial data, including fire perimeters, nighttime light (NTL) intensity as a proxy for human activity, population data, and historical settlement patterns, we analyze trends in exposure per unit of burned area (BA). Results reveal a 77% increase in human exposure per unit BA, driven by population redistribution and urban expansion into fire-prone areas, despite a non-significant decrease in BA of −0.43 km²/year.
A novel aspect of this research is the integration of NTL data to capture dynamic changes in human activity and exposure, validated against population and settlement datasets. Exposure trends were assessed using counterfactual scenarios to isolate the impact of population dynamics. Findings underscore the critical need to account for human activity changes in wildfire risk assessments, highlighting the increasing vulnerability of expanding urban landscapes in Mediterranean regions. These insights are essential for developing adaptive and proactive wildfire management strategies to mitigate future risks.
This methodology provides a replicable framework for assessing wildfire exposure in diverse geographical contexts, emphasizing the value of integrating population dynamics with environmental datasets.
This work is currently in preparation.
Acknowledgements:
This work was supported by the project ‘Climate and Wildfire Interface Study for Europe (CHASE)’ under the 6th Seed Funding Call by the European University for Well-Being (EUniWell). M.T. acknowledges funding by the Spanish Ministry of Science, Innovation and Universities through the Ramón y Cajal Grant Reference RYC2019-027115-I. M.A.T-V and M.T acknowledge funding through the project ONFIRE, Grant PID2021-123193OB-I00, funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. AP acknowledges the support of the EU H2020 project “FirEUrisk”, Grant Agreement No. 101003890. The authors thank the Generalitat de Catalunya for access to fire perimeter data and Xavier Castro from the Forest Fire Prevention Service of the Generalitat de Catalunya for the helpful discussions on the matter.
How to cite: Torres-Vázquez, M. Á., Dalle Vaglie, M., Kettridge, N., Martellozzo, F., Miguez-Macho, G., Provenzale, A., Royé, D., Randelli, F., and Turco, M.: Human Exposure to Wildfires in Mediterranean Environments: A Case Study from Catalonia (1992–2021), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4358, https://doi.org/10.5194/egusphere-egu25-4358, 2025.
In recent years, the severe impact of wildfires has sharply increased due to rising temperatures and drought-like conditions. Therefore, in addition to continuous wildfire monitoring, a long-term understanding of the climate-wildfire relationship is warranted. This study has explored the climate-wildfire relationship in the southern Taiwan region over the past two millennia, focusing on the influence of climate and human activities on wildfire occurrences and their subsequent impact on lake. To achieve this, carbon, nitrogen, carbon isotopic composition of organic matter, charcoal, and diatom assemblages were analysed in the Dongyuan Lake core sediments. Wildfires occurring between 1850 and 1050 cal years BP were largely caused by drier climate conditions. However, wildfires occurring during 750-500 cal years BP and from 350 cal years BP to the present, intervals characterized by wet climate conditions, coincided with a significant number of archaeological sites near Dongyuan Lake, suggesting human-induced burning in the region. The observed wet interval during 1050-750 cal years BP in southern Taiwan attributed to the Medieval Warm Period (MWP), and dry interval during 500-350 cal years BP linked to Little Ice Age (LIA). The low carbon content in Dongyuan Lake sediments coincided with peaks of charcoal accumulation, indicating the loss of carbon due to wildfires and the dilution of sediments. The principal component analysis (PCA) of diatom data showed that PC1 and PC2 represented the lake's acidic conditions, suggesting an increase in pH from 750 to 150 cal years BP. This variation in pH appeared to be linked with wildfire intensity and frequency. PC1 and PC2 also showed strong acidic conditions during the last 150 years, plausibly due to the increase in acid rain conditions in the last century.
How to cite: Rahman, A. and Wang, L. C.: Climate-fire-human interactions and their impact on the limnology conditions of the Dongyuan Lake, Southern Taiwan during the last 1800 cal years BP, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-593, https://doi.org/10.5194/egusphere-egu25-593, 2025.
As an imprint of its rapid climatic transformation over the last two decades, the pan-Arctic region has experienced increasingly extreme fire events. However, a systematic and regionally comprehensive assessment of the recent extreme fire events in the pan-Arctic and the role played by human emissions is still pending. In this study, we employ an extreme event-attribution framework to assess the extent to which anthropogenic forcing affects the magnitude (Burned Area) and likelihood of favourable conditions of extreme fire events (Canadian Forest Fire Weather Index) in the pan-Arctic region throughout the 21st century. Therefore, we utilise large ensemble simulations conducted with the Community Earth System Model version 2 (CESM2), which are capable of isolating anthropogenic external climate forcings and observations from distinct remote sensing products as well as reanalysis data. Our results indicate that the presence of anthropogenic forcing throughout the 21st century was necessary to enable the observed extreme fire events in the pan-Arctic region. We find less than a 20% chance, that the extreme wildfire events occurred during recent fire seasons could have happened in the absence of human-induced external forcings. We can state that such wildfires have become 5 to 10 times more likely in comparison to pre-industrial climatic conditions. Furthermore, our findings indicate that the impact of anthropogenic forcings has significantly elevated the risk of high-latitudes experiencing severe fire-weather conditions by up to an order of magnitude. However, our study reveals the recent elevation in human-induced external forcings does not appear to be enough to explain the occurrence of observed extreme pan-Arctic wildfire events throughout the 21st century. We further explore the underlying mechanisms that drive changes in extreme fire-weather risk. We identify the relative contribution of maximum temperature, precipitation, relative humidity, and surface wind speed on the changes in extreme fire-weather risk.
How to cite: Fiedler, L., Barkhordarian, A., Brovkin, V., and Baehr, J.: Causal Attribution of Arctic Wildfire Events in the 21st Century to Anthropogenic Forcing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9817, https://doi.org/10.5194/egusphere-egu25-9817, 2025.
Wildfires occurring under warmer and drier conditions are likely to be destructive to infrastructure causing economic losses and affecting population. While climate, represented through fire weather, has been shown to be the dominant driver of wildfires there is still a lack of analyses exploring to what extent climate influences wildfire impacts. Here we examine the statistical relationship between fire weather conditions and wildfire impacts at an interannual scale across Mediterranean Europe. To do so, we combined Fire Weather Index (FWI) with burned area from the European Forest Fire Information System, as well as wildfire economic losses and affected population extracted from the EM-DAT disaster database over the period 2000–2023. Overall, most of the wildfire impacts were dominated by a few iconic events that have occurred during extreme fire seasons. Nearly 90% of the affected population and economic losses occurred when the FWI aggregated over the fire season exceeded 23 and 30 respectively. Additionally, the analysis highlighted the FWI as the main driver of burned area, showing strong positive correlations in all analyzed countries. FWI also showed moderate positive correlations with wildfire economic losses and population affected, yet these relationships varied by country. Countries more severely impacted by wildfires, such as Portugal, Spain, and Greece, exhibited stronger correlations than those less affected. These results emphasized the importance of climate variability in enabling wildfire activity and influencing impacts across Mediterranean countries.
How to cite: Galizia, L., Castet, C., and Rodrigues, M.: Assessing the influence of climate on wildfire impacts across Mediterranean Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19925, https://doi.org/10.5194/egusphere-egu25-19925, 2025.
Wildfires are an increasing environmental and societal threat across the Mediterranean region. While the widespread incidence of fires during recent summers has raised significant public concern, the impact of climate change on such events is challenging to quantify, and the evolving nature of extreme wildfires in general remains underexplored. Recent work has shed light on the link between extreme fire weather and climate change, particularly with respect to diagnosing uncertainties and sensitivities, but there are few studies directly linking individual wildfire events to the changing climate and its future implications.
This study employs an established statistical method applied to a large ensemble of climate model simulations as part of a seamless probabilistic approach to quantify how past, present and future risk in extreme fire weather has and will continue to change in the future. Using climate model projections to quantify the trends of likelihoods at different global warming levels offers great potential to support probabilistic assessment of future wildfire risks in a warmer world. Results reveal that fire weather conditions associated with the particularly damaging 2022 wildfires at ten independent locations across the Mediterranean regions of southern Europe and northern Africa have collectively become 80% more likely to occur compared to a century ago due to externally-forced warming temperatures. Further increases in likelihood of 60% and 80% are projected under +1.5°C and +2°C global warming levels, respectively, with the most pronounced increases observed in Spain and southern France. The findings emphasize the profound influence of climate change on the 2022-type wildfire events, manifesting the urgency of combining individual attribution studies further with future risk assessment to help enhance post-disaster resilience to the fire-prone regions.
How to cite: Liu, Z., Eden, J., Dieppois, B., Blackett, M., and Parker, R.: The Intensifying Threat of Wildfires in the Mediterranean: Quantifying the Role of Climate Change in Extreme Fire Weather Events from the Past, Present to the Future, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13777, https://doi.org/10.5194/egusphere-egu25-13777, 2025.
In recent years, fire activity at high latitudes has reached unprecedented levels, driven in part by global warming, which increases fire danger. Climate projections of fire risk rely on indices like the Canadian Forest Fire Weather Index (FWI), which are often derived from coarse-resolution climate models. Thus, there is the need for finer-scale fire weather projections to enable more effective planning and resource allocation as wildfire threats grow. High-resolution climate projections can be achieved through various methods, including dynamical and statistical downscaling, each potentially yielding different estimates of FWI and its future changes. We calculated the FWI based on HCLIM - Nordic Convection Permitting Climate Projections (NorCP) over Fennoscandia. The simulations include 12 x 12 km resolution models using HCLIM-ALADIN and convection-permitting simulation at 3 x 3 km resolution with HCLIM-AROME, covering both historical and future periods under the RCP8.5 scenario. Results were compared against FWI estimates from other climate datasets, such as CORDEX and statistically downscaled NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP).
As expected, all the simulations indicate that the annual and summer mean FWI indices will increase significantly in warmer future climates, along with an increase in days with moderate and high fire weather risk. However, the magnitude of the risk depends heavily on the climate dataset used. For instance, HCLIM-AROME simulations generally show higher FWI values in the historical period even when compared to the future projections of HCLIM-ALADIN, due to generally lower summer precipitation in the former model. Additionally, there are notable regional disparities between the HCLIM simulations, with the highest FWI values observed in coastal areas of southern Finland and Sweden. According to the HCLIM-AROME simulations under the RCP8.5 scenario, these regions experience a moderate fire risk (FWI > 11) on roughly one out of three summer days, whereas HCLIM-ALADIN simulations indicate an average of 7–20 days per summer with such risk. There are also differences in the magnitude and regional distribution of FWIs calculated from HCLIM, NEX-GDDP, and CORDEX simulations. However, all future FWI predictions consistently indicate that, without effective mitigation of global warming, conditions for forest fires will worsen in the future.
How to cite: Laakso, A., Palokangas, M., Park, T., Lipponen, A., Utriainen, L., and Mielonen, T.: Assessing the Impact of Climate Change on Forest Fire Weather Index Using Downscaled Climate Model Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12890, https://doi.org/10.5194/egusphere-egu25-12890, 2025.
The devastating fire events occurring during the intense fire season of 2023 have shown the importance of developing efficient fire detection methods capable of supporting the fire management activities. An enhanced configuration of the Normalized Hotspot Indices (NHI) algorithm has been developed in this direction to improve the fire mapping by satellite through near infrared (NIR) and short-wave infrared (SWIR) data (up to 20 m spatial resolution) from the Operational Land Imager (OLI/OLI2) and the Multispectral Instrument (MSI) aboard Landsat-8/9 (L8/9) and Sentinel-2 (S2) satellites, respectively. In this work, we show the results achieved by investigating the fire events occurring in California, Hawaii islands (USA), Yellowknife (Canada), Tenerife islands (Spain), Greece and Australia also through comparison with information from operational Landsat Fire and Thermal Anomaly (LFTA) product. Results of an extended validation analysis performed using information from well-established databases show that the enhanced NHI algorithm configuration enabled an accurate mapping of fire fronts with a very number of omission and commission errors. Moreover, the algorithm flagged up to 99% of fire pixels from the LFTA product over California and detected up to 70% of additional fire pixels, in night-time conditions, which better detailed the fire fronts and provided unique information about small-fire outbreaks. The effective integration of S2 (daytime) and L8/9 (daytime/night-time) observations, demonstrates that the enhanced NHI algorithm configuration may be used with success to analyse the dynamic evolution of flaming fronts by assessing/complementing information from satellite products at high-temporal/low-spatial resolution. The next implementation of the algorithm on from the Sea and Land Surface Temperature Radiometer (SLSTR) aboard Sentinel-3 satellite and the Flexible Combined Imager (FCI) of the Meteosat Third Generation (MTG) opens some interesting perspectives also regarding its usage for the near-real time monitoring of wildfires
How to cite: Mazzeo, G., Falconieri, A., Filizzola, C., Genzano, N., Pergola, N., and Marchese, F.: An enhanced NHI algorithm configuration for fire detection and mapping, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5629, https://doi.org/10.5194/egusphere-egu25-5629, 2025.
Posters virtual: Wed, 30 Apr, 14:00–15:45 | vPoster spot A
EGU25-18758 | Posters virtual | VPS4
Evaluating aerosol emissions from wildfires in the UK Earth System Model: What we have learnt from modelling the extreme wildfires in California during September 2020Wed, 30 Apr, 14:00–15:45 (CEST) | vPA.4
An accurate representation of biomass burning aerosol emissions is essential in climate and Earth System Models to capture aerosol properties and their interactions. The sources of regional smoke plumes include the widespread prevalence of numerous small fires, which are common across Savanahs, and larger more episodic wildfires, such as the extreme Californian wildfire event of September 2020. Capturing emissions from such a diverse range of fire activity is a major challenge and some atmospheric models, including the UK Earth System Model (UKESM) have scaled up aerosol emissions to ensure modelled AOD match observations. Past evaluations have struggled to provide a clear answer as to how to reconcile emissions and modelled aerosols, with contrasting outcomes for different regions and/or assessments of seasonal means versus individual smoke plumes. Our modelling study leverages observational data from the unprecedented wildfires in September 2020 to identify potential issues in capturing the aerosol from large / extreme wildfires in the global modelling system of UKESM. Running in nudged mode and with daily emissions from GFED4.1s emissions enables a realistic simulation of the thick smoke plumes that ensued across the continent and out into the Pacific, with little overall bias in AODs between UKESM and co-located observations (AERONET, VIRS, MAIAC). However, scaling emissions by a factor of 2 provides better agreement globally and across regions dominated by smaller fires. We therefore develop a means of differentiating between small and large fires based on the daily dry matter (fuel) consumption and apply this to enable scaling of emissions from small fires that seem to otherwise be underestimated in the model, whilst avoiding scaling those from large fires. Our results indicate a way forward to ensure a global simulation of biomass burning aerosol and fidelity in modelling extreme events.
How to cite: Johnson, B., Quaze, L., and Haywood, J.: Evaluating aerosol emissions from wildfires in the UK Earth System Model: What we have learnt from modelling the extreme wildfires in California during September 2020 , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18758, https://doi.org/10.5194/egusphere-egu25-18758, 2025.
