A key area is how extreme fires are represented in fire models. Their stochastic behaviour, uncertainties in observations, and the difficulty of capturing local processes within global frameworks make simulating extremes and their impacts a persistent challenge for coupled models. Emerging big data and machine learning approaches show promise in capturing such events but remain limited in their ability to represent feedback to vegetation, soils, and the broader Earth system.
This session also invites case studies of regional extreme wildfire events, their impacts, and experiences with prevention and mitigation strategies from around the world. We welcome contributions from a wide range of disciplines, including global, regional, and landscape-scale modelling; statistical and process-based modelling; observational and field studies; and social science research on all time scales. Our goal is to foster knowledge exchange across disciplines and between scientists, decision-makers, and practitioners, to advance our collective ability to understand, model, and respond to the challenges posed by present and future extreme wildfires.
Orals: Tue, 5 May, 16:15–18:00 | Room N1
Extreme wildfires are occurring more frequently in many (although not all) flammable ecosystems. However, what exactly is meant by extreme depends on the context, as fires may be increasing in extent, size, intensity, rate of spread, severity, and/or infrastructural and economic damage, and these different meanings of extreme fire are often conflated. Here, we explore what is meant by extreme wildfire and discuss some of the analytical challenges to understanding extreme fire behaviors. We also examine some examples of analyses that have appropriately differentiated extreme fires from other wildfires to better understand the drivers of extreme wildfires in the context of climate and global change.
How to cite: Staver, C.: What makes a wildfire extreme?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15952, https://doi.org/10.5194/egusphere-egu26-15952, 2026.
The 2024–2025 fire season saw extreme wildfires across the Americas, with events in the Amazon, Pantanal, and Los Angeles emerging from the tails of historical distributions and burning substantially larger areas than would have occurred without human-induced climate change. These amplified fire extents translated into severe impacts on carbon emissions, air quality, and communities. These are the key findings in the latest State of Wildfires report: an annual, community-led synthesis developed in response to the increasing prevalence of high-impact wildfire events worldwide.
Globally over this period, wildfires burned approximately 3.7 million km², exposed around 100 million people and over USD 200 billion of infrastructure, and generated more than eight billion tonnes of CO₂ emissions, which was around 10 % above the long-term average, driven largely by intense forest fires in South America and Canada. Impacts were particularly severe in the Amazon and Pantanal, where large-scale forest and wetland fires caused extreme smoke exposure and major economic losses, and in Los Angeles, where January 2025 fires resulted in mass evacuations and substantial damage.
In several regions, climate change substantially increased burned area, with fires approximately four times larger in Amazonia, 35 times larger in the Pantanal–Chiquitano, 25 times larger in Southern California, and nearly three times larger in the Congo Basin compared to a world without human-induced climate change. In these regions, we found anomalous weather created conditions for extreme fires, with prolonged drought dominating in tropical systems, and compound heat, wind, and fuel build-up shaping fires in California. Projections indicate that events of comparable scale will become markedly more frequent in tropical regions under continued warming, while strong mitigation can substantially limit, but not eliminate, the additional risk.
The State of Wildfires report (https://stateofwildfires.com/latest-report/) snapshot of globally extreme wildfire impacts and drivers, providing an evolving evidence base to support preparedness, mitigation, and adaptation as wildfire risk intensifies. Looking ahead, the 2025–2026 edition will expand coverage to emerging hotspots, and we welcome contributions that help capture the next generation of assessments of high-impact wildfire events.
How to cite: Kelley, D. I., Burton, C., Di Giuseppe, F., and Jones, M. and the State of Wildfires report 2024-2025 co authors: State of Wildfires 2024-2025, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19953, https://doi.org/10.5194/egusphere-egu26-19953, 2026.
As part of the ESA Climate Change Initiative (CCI), two projects – FireCCI and XFires – have developed during the past year several datasets that will significantly contribute to the understanding of the fire phenomenon and the analysis of extreme fires and their climatic consequences.
In FireCCI, we have developed the first global Sentinel-2 burned area (BA) dataset at 20-m spatial resolution (FireCCIS2.v1), achieving a level of detection of small fire patches not possible with coarse resolution sensors, and thus increasing the BA detection to more than 8 Mkm2 for the year 2023. This means more than double the BA detected by other existing global products such as MCD64A1 and VNP64A1, and >60% more than the Sentinel-3 based dataset FireCCIS311. This new generation of medium resolution datasets is expected to significantly improve the calculation of fire emissions, and contribute to fire ecology, land use change, and other fire related research.
Complementary, we have also produced a harmonised global burned area dataset that extends the ESA FireCCI record from 2003 to 2024 (to be extended to the future), with monthly temporal resolution on a 0.25° grid. The product, named FireCCI60, ensures continuity between the historical FireCCI51 product (based on MODIS) and the more recent FireCCIS311 product (based on Sentinel-3), addressing the challenge posed by the forthcoming end of the MODIS mission for long-term fire monitoring and its climate-related applications. This dataset harmonises de FireCCI51 BA detections to resemble as close as possible FireCCIS311, which has a better detection capability, in order to obtain a dataset that is consistent through the time series and can be directly used for time series analysis and extreme fire research. This harmonisation adds around of 1 Mkm2 of BA per year to the FireCCI51 detection, with mean yearly BA values of ~5.6 Mkm2.
Finally, as part of the XFires project, we have developed an extreme fire events (EFE) dataset, based on FireCCI51 BA and MODIS active fires products, and identified both extreme and non-extreme fire events over the past two decades on a 0.25° grid. The identification of EFEs is performed using a statistical approach on a per-region basis that aims to tackle the fact that different parts of the world present different typical patterns of fire – one of the main challenges to defining EFEs globally. This dataset is currently being updated to integrate the harmonised FireCCI60 one, to obtain a consistent EFE database spanning to the present that can be used to explore trends, causes and consquences of extreme fire occurrence during the past decades.
How to cite: Pettinari, M. L., Segura-García, C., Solano-Romero, E., Torres-Vázquez, M. Á., Khaïroun, A., Ramo-Sánchez, R., Storm, T., Boettcher, M., Neuschmidt, H., Brockmann, C., Albergel, C., Sitch, S., and Chuvieco, E.: CCI Fire advances: global Sentinel-2 burned area product, harmonised MODIS - Sentinel-3 dataset, and extreme fires events database, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16760, https://doi.org/10.5194/egusphere-egu26-16760, 2026.
Fire weather waves (FWWs), episodes of persistent extreme fire weather akin to heat waves, sustaining favorable burning conditions over multiple consecutive days. Here, we examine the relationship between FWWs and fire activity, as well as the patterns and trends of FWWs across global terrestrial ecoregions. Accounting for only 4% of days during 2002–2024 in forested ecoregions, FWWs coincided with 26% of the area burned, and half of the top 1% of energetic fires ignited on FWW days. Compared with grassland and shrubland fires, forest fires exhibit a larger and more persistent increase in daily burned area in response to FWWs, particularly in Mediterranean forests. FWWs intensify fire activity by sustaining warmer, drier, and windier conditions compared to non-FWW periods – facilitating chronic periods of favorable fire weather that promote fire spread. FWWs have become, and are projected to become, more frequent, persistent, and severe, with a twofold increase in FWW days projected for 2076–2100 compared to 1979–2024. These findings underscore forecasted FWWs as an important component of early warning systems to strengthen preparedness for extreme forest fires.
How to cite: Abatzoglou, J., Yin, C., Jain, P., Sadegh, M., Flannigan, M., and Jones, M.: Fire weather waves drive extreme fires globally, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14889, https://doi.org/10.5194/egusphere-egu26-14889, 2026.
Fire plays an important role in the Earth system, affecting atmospheric composition and climate, vegetation, soil and societal resources. Extreme fires are particularly important, as they entail the most severe damages, both in terms of social and ecological values. According to the European Commission, within Europe “most damage caused by fires is due to extreme fire events, which only account for about 2% of the total number of fires”. Their occurrence and impacts are closely linked to climate change, and are related to a wide range of climatic and environmental state variables, such as soil and vegetation moisture content, biomass, temperature, etc. Fires have a powerful impact on the atmosphere and thus aerosol, greenhouse gases, and ozone concentrations, while the indirect effects of fire-related particles affect also water bodies and ice sheets.
Here we summarize progress on the XFires project, which aims to research and quantify all of the above interactions to gain a holistic understanding of extreme fires, including understanding drivers of extreme fire events, modelling their occurrence and their impact in the Earth system. A particular focus of this project lies in gaining an improved theoretical and quantitative understanding of what the medium-term net effects of fire are on global carbon and radiative forcing budgets. This is important because at a global scale, little is known regarding how extreme fires impact vegetation and soil recovery timescales with respect to the time until the same system next experiences fire. Extreme fires are of particular interest because of how different biomes might hypothetically respond to, and recover from, different extreme fire characteristics, which have significant potential bearing on the global carbon cycle. To address these questions, we first use a cross-Essential Climate Variable (ECVs) approach to define and characterise extreme fires. Results show almost 20k extreme fire events over the period 2003 to 2022. We then explore trends in extreme fire events across biomes and associated greenhouse gas emissions. We will then develop and apply machine-learning approaches to model extreme fires and generate new emissions datasets to be used as input into an Earth System Model, to quantify impacts on atmospheric composition and climate. Finally, we will explore the wider impact of extreme fires on human health, lakes, and via black carbon affecting melt-rates on the Greenland ice-sheet.
How to cite: Sitch, S., Albergel, C., Ciais, P., Bowring, S., Chuvieco, E., Defourny, P., Dorigo, W., Eames, T., Ghent, D., Pettinari, M. L., Haywood, J., Hubert, D., Johnson, B., Kildegaard Rose, S., Lamarche, C., Langsdale, M. F., Segura García, C., Solano Romero, E. C., Vernooij, R., and van der Werf, G. and the XFires Team: Modelling multidimensional causes and impacts of extreme fires in the climate system through X-ECV analysis (XFires), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13422, https://doi.org/10.5194/egusphere-egu26-13422, 2026.
Extreme forest fires are escalating globally, causing extensive forest loss and prolonged recovery time, which raises the risk of forests transitioning from carbon sinks to sources. However, most studies define extreme fires solely by burned area, neglecting interactions among fire characteristics and potentially underestimating their impacts on post-fire recovery. Here we constructed a global multidimensional forest fire dataset (2001–2021) comprising >300,000 events with burned area, intensity, duration, spread rate, and severity. After around 2010, fire characteristics intensified, especially in extratropical forests, with burned area and duration often triggering cascading amplifications of intensity, spread rate, and severity. While extreme large‑area fires frequently coincided with fast spread and long duration, they seldom reached extremes in both intensity and severity. Notably, the 244 forest fires that were extreme across all five dimensions simultaneously increased significantly, yet 75% occurred after 2011. Forests affected by these synchronized extremes required 1.2 years longer to recover than the global mean and also 0.4–1.0 years longer than fires extreme in any single dimension. We further identified that the interaction between fire intensity and severity as the primary driver of prolonged recovery across nearly all biogeographic pyromes. These results demonstrate that conventionally defined extreme large-area fires do not necessarily represent the most ecologically damaging events. Despite increasing global fire-suppression investment, current strategies may primarily remove low-intensity, small fires while failing to mitigate the catastrophic consequences of climate-amplified extreme wildfires, escalating threat poses profound challenges to global forest recovery and carbon-cycle stability.
How to cite: Lv, Q. and Peng, J.: Synchronized Extremes in Forest Wildfires: Amplified Recovery Delays from Coupled Intensity and Severity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6152, https://doi.org/10.5194/egusphere-egu26-6152, 2026.
The 2025 European fire season was characterised by record-breaking burned area and multiple extreme wildfire events across the continent. Increasing wildfire extremes in Europe and globally has intensified interest in how climate and land-use changes are altering European fire regimes. Extreme event attribution of antecedent and concurrent fire weather conditions is used here to assess the changing likelihood and intensity of recent events both relative to preindustrial conditions and under projected climate change.
We analyse five regions that experienced extreme wildfire activity in 2025: northwestern Iberia, upland Britain, southwestern Mediterranean France, the eastern Adriatic/Ionian, and northern and western Türkiye. For each region, we attribute changes in the likelihood of short-term fire-weather extremes around peak wildfire activity, using 7-day maxima of vapour pressure deficit (VPD), surface wind speed, and a composite index of VPD and wind, in addition to spring and summer effective precipitation to characterise seasonal drought and fuel accumulation conditions. In addition to weather-related drivers, we assess trends in spring and summer vegetation cover using the leaf area index (LAI) and in land abandonment or reclamation using the changing fraction of managed and unmanaged land.
Climate change strongly increased vapour pressure deficit and the composite VPD/wind index for all southern European regions, with the likelihood of drought conditions at least as strong as 2025 also increasing by over a factor of three relative to in the preindustrial climate. Short-term fire weather or summer drought exhibited a weak positive and negative trend with warming respectively, though an increasing likelihood of spring drought conditions, a key driver of 2025’s wildfires, was identified. Spring vegetation significantly increased across Europe, implying higher fuel loads and a potential for more intense wildfires. Land management trends were mixed, with long-term land abandonment in southwestern France and northern and western Türkiye and a recent, rapid land abandonment signal in the eastern Adriatic/Ionian.
The record-breaking 2025 European fire season occurred in the context of a climate change driven intensification of the fire weather extremes and drought conditions associated with each of the five wildfire events examined. Combined with increasing growth-season vegetation cover and ongoing land abandonment, these factors suggest increases in European wildfire extremes will continue.
How to cite: Keeping, T., Zachariah, M., Barnes, C., Haas, O., Grillakis, E., Pinto, I., Clarke, B., Kimutai, J., Philip, S., Kew, S., and Otto, F.: How Climate and Land Cover Change Shaped Europe's Record Breaking 2025 Fire Season, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19805, https://doi.org/10.5194/egusphere-egu26-19805, 2026.
In February 2024, the Las Tablas wildfire killed at least 135 people near the coastal city of Valparaíso, Chile, making it the deadliest wildfire disaster since the 2009 Black Saturday bushfires in Australia. Amid increased focus on global wildfire disasters, the economic impacts of wildfires often overshadow fatalities, presenting a gap in analysis and understanding of why some fires are more deadly than others. Here, we reconstruct the 2024 Las Tablas Fire and use a mixed methods approach to examine the factors contributing to the record fatalities. We further assess how this fire aligns with other recent global wildfire disasters that produced mass fatalities. The Las Tablas Fire occurred during a record heat wave and with an offshore wind, known locally as a puelche wind. Satellite data and burn severity patterns show it exhibited high rates of spread burning through highly flammable, non-native forests and complex topography in the wildland-urban interface. Most fatalities occurred in neighborhoods of informal, unregulated housing not connected to city services and home to some of the most vulnerable residents of the region. Both the biophysical and social factors present in the Las Tablas Fire are consistent with many recent fatal wildfire disasters globally, particularly in Mediterranean climates. These common denominators point to the potential for increasing frequency of fatal wildfire disasters with climate change, land use change, and social disparities. They also highlight the complexity of mitigating fatal wildfires.
How to cite: Kolden, C.: Why was the 2024 Las Tablas Fire in Chile so deadly? Common socioecological drivers of global wildfire disasters, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5690, https://doi.org/10.5194/egusphere-egu26-5690, 2026.
Wildfires are natural components of fire-prone settings. Yet, their severity, intensity, frequency and duration have escalated to damaging levels in recent decades, predominantly due to climate change. The rise of extreme fire weather conditions has amplified the impacts of wildfires, calling for prevention mechanisms to become more prominent and broadly implemented. In this context, Integrated Fire Management (IFM) emerges as a mitigation strategy worldwide, in which prescribed burning (PB) is a common activity. In Brazil, after the prevalence of fire exclusion policies, the Integrated Fire Management National Policy (PNMIF, in Portuguese) was approved in 2024, positioning IFM as a strategy to reduce the intensity and severity of wildfires, while encouraging a comprehensive understanding of the ecological, economic and sociocultural aspects of fire. In light of the recently approved National Policy, documentation of existing results is extremely important, as current IFM projects can inform the implementation of fire management activities at a national level. In this study, we assess over two decades (2001-2021) of remote sensing data to evaluate fire regime in protected areas in Brazil before and after the implementation of PB, through the analysis of burned area and fire intensity in the late dry season. We use MODIS MCD64A1 product to estimate burned area and Fire Radiative Power (FRP) derived from MCD14DL active fire product to estimate fire intensity. We evaluate 31 Protected Areas in Brazil, including Indigenous Lands, Conservation Units and Quilombola Territory, spread across Amazonia, Cerrado, Mata Atlantica and Pantanal biomes. We separate them into four groups, based on the year when PB started: 2015, 2016, 2017 or 2018. We compare the Kernel Probability Density Function for 11 different percentiles, from p50 to p99, of burned area and FRP for the periods before and after the implementation of PB of each group. We emphasize extreme events using the percentiles above p90 (p90, p95 and p99). Our results indicate that PB effectively reduces burned area and FRP, but its effectiveness decreases during extreme events, as shown by the prevalence of smaller reductions at higher percentiles. We hypothesize that extreme events are predominantly driven by climatic variables, which limits the effectiveness of PB in such conditions. This becomes increasingly relevant under a changing climate. Our results also indicate that PB does not yield immediate outcomes. For burned area, groups with the shortest PB history are ineffective at p99 in 2017 and from p85 onward in 2018, evidenced by higher values after PB implementation relative to the pre-implementation period. For FRP, 2018 is also dominated by the ineffectiveness of PB. This research is ongoing, and our preliminary results highlight the role of PB in managing burned area and fire intensity, as well as the influence of climatic factors in driving extreme fire events. Thus, the implementation of PNMIF and the management of wildfires require strategic planning and continuous monitoring, with adaptation and mitigation mechanisms as key components.
How to cite: Veiga, R., Rodrigues, J., Sena, C., Peres, L., Moura, L., Boock, J., Gajardo, O., Silva, D., Schmidt, I., and Libonati, R.: Prescribed burning reduces wildfire impacts in Brazil, but extreme events are climate-driven, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-897, https://doi.org/10.5194/egusphere-egu26-897, 2026.
Mountains create their own weather through topographic modification of the prevailing synoptic meteorology. As a result, wildfires in mountainous terrain may exhibit erratic and extreme behaviour as ridges and valleys modify the prevailing winds. Here we present a case study analysis of a wildfire that occurred in mountainous terrain in subtropical eastern Australia. The wildfire was observed to transition between a wind-driven and plume-driven wildfire on at least three occasions with a periodicity of around 60 minutes. The Weather Research and Forecasting (WRF) model was used to investigate the surface windfield and vertical thermodynamic properties of the atmosphere. Results from the WRF simulations aligned with observational data indicating that topographic lifting caused by only moderate changes in terrain may have contributed to the coupling of the wildfire plume to an elevated layer of humidity leading to rapid pyrocumulus (pyroCu) development. Strong horizontal wind shear caused the pyroCu to detach from the wildfire on at least three occasions with a subsequent return to wind-driven wildfire behaviour. Our results highlight the importance of understanding the influence of what may be perceived as only subtle to moderate changes in terrain on local meteorological conditions and wildfire behaviour.
How to cite: McGowan, H., Guyot, A., Sturman, A., Seifried, V., and Dale, T.: Wind to plume driven wildfire cycles caused by topographically forced wildfire – atmosphere coupling, Southeast Queensland, Australia., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-583, https://doi.org/10.5194/egusphere-egu26-583, 2026.
Anomalies in sea surface temperature of the tropical Pacific Ocean, are associated with changes in precipitation and humidity patterns in the Amazon region. Temperature increases (El Niño) causes abnormal dry seasons, making the forest more susceptible to wildfires. The decrease (La Niña) in ocean temperatures implies abnormal increases in rainfall, especially in the northern region of Amazon. Between 2019 and 2024, the municipality of Santarém (Pará, Brazil), eastern Amazon, was affected by an increase in forest fires, leading the local government to declare an environmental emergency state in 2024. The objective of this study was to characterize burned areas and changes in land cover in Santarém during the recent ENSO period (2019 to 2024). Annual data on Land Use and Land Cover (LULC) from MapBiomas (Collection 10), and monthly data of burned area from MapBiomas Fogo (Collection 4) were used. National Oceanic and Atmospheric Administration's (NOAAs) Weather Prediction Center data was used to define El Niño (EN), La Niña (LN) and “no anomalies” months (Regular - Rg). LULC was analyzed in small properties (SMp > 300 hectares (ha)), medium-sized (MS, 300 to 1125 ha), large properties (LP >1125 ha), and smallholdings (SMs < 300 ha), as well as indigenous lands (ILs), quilombola areas (Qa), and conservation units (Cs). These data were extracted from SICAR (National Rural Environmental Registry System). For EN periods, 19 months between 2019 and 2024 were analyzed, with 62,962.56 ha of burned areas. For LN (28 months), 15,799.59 ha were burned. During Rg (25 months), 60,109.20 ha of burned area were detected. During EN and Rg periods, Forest Formation (FF) was the most affected coverage, with 36,016.92 ha (EN, 57%) and 39,183.03 (Rg, 65%). For LN, the highest burned coverage was Pasture (Pt), with 8,537.94 ha burned. Mostly small properties (SMp) were affected, with 1,249.29 ha (EN) and 1,124.82 ha (Rg) of FF scorched (1.87%). Pt areas were also affected in SMp (2.07%), accounting for 4.84% of the total. For the protected areas, Cs had 5.63% of the total burned area, with 3,913.47 ha (EN), 2,574.09 ha (Rg) and 1,330.56 ha (LN), mostly in FF. ILs had 1.04% of the total, mostly during EN, with 1,287.27 ha. Other classes (MS, LP, SMs and Qa) accounted for only 1.06% of the burned area. Areas without SICAR classification had the largest burned area (87.43% of the total). These patterns raise concern, given that burning persists in forest areas that remain unprotected and unmonitored. The occurrence of climatic phenomena that induce drier vegetation and less precipitation in the Amazon enable increases in burned area associated with anthropic activities. Implementing fire-prevention measures in vulnerable areas is crucial, and it is equally important to account for these climatic periods. Investment in public policies for environmental education and fire mitigation are essential for transforming these scenarios, in order to mitigate the effects of climate change.
How to cite: Freitas, S., Dutra, D., Haddad, I., Mataveli, G., Escada, M. I., and Aragão, L.: Fires during recent El Niño and La Niña periods in Eastern Amazon, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1269, https://doi.org/10.5194/egusphere-egu26-1269, 2026.
In recent years, California has experienced increasingly severe wildfire events, leading to substantial socio-economic losses and ecological degradation. Against this backdrop, this study aims to identify key indicators influencing forest fire occurrence, assess forest fire vulnerability, and examine vegetation cover changes in Butte County, California. First, we analyze and visualize 14 wildfire-relevant environmental and anthropogenic factors, capturing climatic, topographic, and land-use characteristics of the study area. To address multicollinearity among variables, the Variance Inflation Factor (VIF) is employed, resulting in the selection of 11 non-collinear indicators. Based on these selected variables, a Boosted Regression Tree (BRT) model is applied to evaluate spatial patterns of wildfire vulnerability in Butte County. Finally, we employ Vegetation Fractional Cover (VFC) to quantify post-fire vegetation cover changes, enabling an assessment of wildfire impacts on vegetation dynamics. The results indicate that rainfall, land use, and topographic conditions exert significant influences on wildfire vulnerability in Butte County. Moreover, VFC analysis reveals a notable decline in vegetation cover surrounding fire locations between July 2024 and September 2024, highlighting the short-term ecological impacts of recent wildfire events.
How to cite: Tong, C.: Wildfire Vulnerability Modeling and Vegetation Cover Change in Butte: An Analysis Based on Boosted Regression Tree, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4145, https://doi.org/10.5194/egusphere-egu26-4145, 2026.
Extreme wildfires are one of the most destructive natural phenomena in our world. Modeling of these fires is challenging due to large uncertainties in model parameters as well as initial and boundary conditions. High-resolution observations of fire behavior can be used to reduce modeling uncertainties. However, adequate observational systems and methods are scarce.
We will present airborne based mid-wave infrared (MWIR) and long-wave infrared (LWIR) imagery with high spatial and temporal resolution of extreme fires that occurred in California around September 2022. This data was captured using the SJSU Wildfire Imaging Suite during the California Fire Dynamics Experiment (CalFiDE) campaign together with meteorological data both from ground-based and airborne instruments.
We will show a comparison of our airborne observations with the infrared spectral imagery captured by the spaceborne MODIS and VIIRS instruments during the campaign. The cross-platform comparison will address the spatial extent of the fire as well as the differences in the registered radiance values.
This rich dataset, including more than 400 overpasses over multiple days and multiple extreme fires, provides a unique detailed view of the active wildfire behavior during these fire events.
Acknowledgements: This work was supported by the U.S. National Science Foundation under award number 2053619, the U.S. National Oceanic and Atmospheric Administration during the CalFiDE campaign, and the EU COST Action NERO (CA22164).
How to cite: Stockmans, T., Klofas, A., Clements, C. B., Giesige, C. C., Goldbeck-Dimon, E., Manoj Santhi, S., Olivera Prieto, P., and Valero, M. M.: Airborne infrared observations of extreme wildfires in California 2022, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6694, https://doi.org/10.5194/egusphere-egu26-6694, 2026.
Extreme wildfires present an increasing environmental and socio-economic concern across Europe. However, the absence of comprehensive observational datasets of fire behaviour restricts the capacity to analyse, model, and manage extreme wildfire events effectively. This work aims to develop a unified and standardized dataset of extreme wildfire events in Europe based on reliable official sources, thus contributing to a consistent reference for research and management applications.
Fire event information was gathered from European fire management agencies. The data has been filtered and organized to capture the most relevant variables for extreme fire behaviour analysis, such as the temporal evolution of the burned area and the fire perimeter. Data processing and validation was performed in QGIS and outputs were exported in GeoJSON format to ensure easy integration in any geographic information system. The produced dataset allows the temporal and spatial reconstruction of fire progression. The overarching goal is to develop a comprehensive dataset of extreme wildfire events across Europe to support research and modelling efforts through shared, high-quality and standardized data resources.
Acknowledgements: This research initiative is based upon work from COST Action NERO, CA22164, supported by COST (European Cooperation in Science and Technology).
How to cite: Olivera Prieto, P., Fernández Anez, N., Berčák, R., Stockmans, T., Manoj Santhi, S., Giannaros, T. M., and Valero, M. M.: Building a Unified Framework for Extreme Wildfire Data in Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6760, https://doi.org/10.5194/egusphere-egu26-6760, 2026.
Extreme wildfires have become more frequent in many regions worldwide in recent years. Compared with moderate events, the most intense wildfires, especially those that generate pyrocumulonimbus (pyroCb) clouds, exert disproportionately large impacts on the Earth system and cause substantial socioeconomic losses. High‑fidelity modeling is a critical tool for studying wildfire behavior, identifying key drivers, and quantifying their impacts. Here, we improve the pyroCb representation in the global Energy Exascale Earth System Model (E3SM) by leveraging its kilometer-scale regionally refined model (RRM) capability, integrating satellite-based high-resolution (hourly, 500 m) fire emissions, and incorporating fire-related parameterizations. Compared with conventional global simulations at coarse resolution (approximately 100 km), the kilometer-scale grid spacing over the fire source region substantially improves the simulation by explicitly resolving more fire-related dynamic and thermodynamic processes. In the meanwhile, the RRM configuration enables seamless smoke transport and interactions between the fine and coarse meshes and allows efficient simulation of downstream fire aerosol spatiotemporal distributions in regions where high resolution is less critical. The simulations capture essential pyroCb features, e.g., cloud height, spatiotemporal evolution, and convective intensity, as observed by satellite and ground measurements for different cases occurred in California. Sensitivity experiments suggest that pyroCb formation in our simulations is not controlled by a single dominant factor, but instead emerges from the coupled interactions of multiple fire-atmosphere processes. Furthermore, we use the global RRM to investigate the mechanisms of stratospheric aerosol injection and examine implications for seasonal and longer predictability. Because these simulations include interactive chemistry and aerosol schemes, we also evaluate the impacts of wildfires on surface air quality.
How to cite: Tang, Q., Ke, Z., Zhang, J., Chen, Y., Ding, X., Randerson, J., Zhang, Y., and Chen, G.: Extreme wildfire simulations using kilometer-scale regionally refined E3SM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8792, https://doi.org/10.5194/egusphere-egu26-8792, 2026.
Large wildfires are a major source of atmopsheric aerosol. The lifetime of the smoke aerosol in the atmosphere, and thus their impact on the climate, is strongly controlled by the altitude in which the smoke is injected into the atmopshere. While most fires release their smoke in the lower troposphere, so called pyrocumulunimbus (PyroCb) events have the potential to transport smoke aerosol upwards deep into the troposphere and even into the lower stratosphere, extending the lifetime of the smoke by several orders of magnitude. These PyroCbs are thunderstorms that are triggered by extreme heat release and occasionally form above particularly intense wildfires.
For example, during the extreme PyroCb event now often referred to as the “Australian New Year’s Eve Event” of 2019/2020, deep pyro-convective plumes generated by record-breaking wildfires injected vast quantities of smoke into the tropopause region that are comparable to those of a major volcanic eruption. It is therefore crucial to understand which fires produce deep PyroCbs and why. In this study, we investigate the critical heat emission threshold at which shallow wildfire smoke plumes transition into pyroCbs that penetrate deep into the tropopause region. We further examine the sensitivity of the pyroCbs to further changes in the total amount of heat released by the fire and analyze how changes in the sensible heat emissions and water vapor release impact plume dynamics.
To do that, using case studies of extreme fires such as the Australian New Years Eve PyroCb event, we perform semi-idealized simulations with a regional high-resolution atmospheric model. Based on the so simulated plumes, we uncover a pronounced bimodal behavior of the fire-induced convection with an abrupt onset of pyroCb formation when the sensible heat flux emissions by the fire exceeds 50kW m-2. We show, that whenever cloud formation is present within the plume, the plume top height is mainly controlled by the sum of the sensible and latent heat flux by the fire, while the ratio between the two plays a subordinate role. Increasing either heat flux will simultanously raise both the plume water content and temperature anomaly within the cloud. These results show the importance of accurate estimates of heat and moisture released by fires for predicting pyroCb development. Encouragingly, these results suggest that a reliable estimate of the total heat flux might be sufficient to characterize the behavior of pyroCbs, reducing the need for detailed partitioning of sensible and latent heat.
How to cite: Müller, J., Senf, F., and Tegen, I.: How Sensible Heat Release and Water Vapor Emissions from Fires Impact the Characteristics of Pyro-convective Plumes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10023, https://doi.org/10.5194/egusphere-egu26-10023, 2026.
Extreme fire weather conditions are becoming increasingly unprecedented worldwide, yet the full range of potentially high-impact extreme wildfires remains difficult to assess. Here we generate a large ensemble of wildfire simulations by forcing the process-based model LPJmL-SPITFIRE with a 40-member bias-adjusted and statistically downscaled climate model (ACCESS-ESM1-5). This enables robust sampling of extreme wildfire events and allows comparison against single realizations (using forcing from climate reanalysis GSWP3-W5E and from an individual climate model ensemble member, r1i1p1f1). We show that wildfire ensemble maxima typically exceed single realizations maxima, suggesting that using a single climate forcing misses a substantial portion of the plausible extreme wildfire events due to internal climate variability. Extreme fire impacts (carbon emissions and burned area) respond more strongly to internal climate variability than fire weather conditions, suggesting a strong vegetation-fire feedback sensitivity to the climate forcing. Additionally, the large ensemble simulations capture climate driver-fire relationships not captured by single realizations, where maximum impacts occur without maximum fire danger, and vice-versa, highlighting the critical role of other factors beyond weather conditions that contribute to whether fires become extreme. These findings demonstrate that modelling a large range of possible wildfire events using the full distribution of climate realizations can help identify the mechanisms leading to the most extreme events.
How to cite: Ribeiro, A., Thonicke, K., Billing, M., von Bloh, W., Wessel, J., Undorf, S., Forkel, M., and Zscheischler, J.: Sampling extreme wildfire events from LPJmL-SPITFIRE large ensemble simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10291, https://doi.org/10.5194/egusphere-egu26-10291, 2026.
As the frequency and intensity of megafires continue to increase, projecting and managing future wildfire occurrence is becoming increasingly important. Wildfires damage forests as major carbon sinks, thereby posing substantial uncertainties to carbon uptake. Furthermore, climate change is expected to intensify wildfire spread, leading to greater overall damage. Therefore, future wildfire management requires assessments that incorporate wildfire spread patterns under changing climate conditions. However, most existing studies have focused primarily on estimating wildfire ignition locations, with limited consideration of wildfire spread under climate change. In this study, we trained wildfire spread patterns within wildfire events using a combination of remote sensing data and field survey observations. Based on these patterns, we estimated future wildfire occurrence and subsequent spread using a dynamic Bayesian network framework. We further analyzed changes in forest carbon uptake resulting from wildfire occurrence and spread. Our results indicate that simulations accounting for both wildfire occurrence and spread result in greater total burned area by 2050 compared to simulations considering wildfire occurrence alone. In particular, repeated wildfire occurrences and their spatial propagation expanded the cumulative damaged areas. When wildfire spread was included, forest carbon uptake declined more sharply, with some regions projected to shift from net carbon sinks to net carbon sources. These findings demonstrate that excluding wildfire spread leads to an underestimation of wildfire damage and associated carbon sequestration.
How to cite: Kim, S. and Park, C.: Impact of future wildfire spread on forest carbon seqeustrartion: A case study of South Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21274, https://doi.org/10.5194/egusphere-egu26-21274, 2026.
Wildfires have become much more frequent in recent decades and are posing an increasing threat to human health and the surrounding environment. Beside generating aerosol particles predominantly in the accumulation mode, wildfires also emit giant aerosol particles (> 20 µm) and pyrometeors (> 2 mm), whose occurrence and transport in the atmosphere are not yet fully understood. This knowledge gap must be addressed in order to improve our understanding of the possible effects of these particles on the climate and to advance the early detection and tracking of wildfires using weather radar.
The NOAA/NASA joint aircraft field campaign FIREX-AQ of 2019 conducted systematic measurements of trace gases and aerosol particles in wildfire smoke plumes. During the project, we observed smoke particles up to a nominal diameter of 6.2 mm with state-of-the-art open-path instruments (Cloud, Aerosol, and Precipitation Spectrometer and Precipitation Imaging Probe; both manufactured by Droplet Measurement Technologies, Longmont, CO, USA) aboard the NASA DC-8 research aircraft at various distances from the wildfire. In total, 194 smoke plume encounters (“transects”) were investigated from nine different wildfires with some measured on multiple days. In this study we discuss the shape, occurrence, and transport of particles larger than 0.1 mm emitted by western US wildfires in the near- to mid-field from the source.
Giant aerosol particles and pyrometeors were found in the vast majority of the transects examined, with younger smoke containing more of the very massive particles than 4-hour old smoke. In only 4% of cases where the smoke age was less than 2 hours particles larger than 0.1 mm were absent. The largest particles, measuring up to over 4 mm, were observed during transects in which the Modified Combustion Efficiency (MCE) indicates flaming combustion conditions. All observed particles larger than 0.1 mm were analyzed based on their shape. The results show that the larger the particles are, the more elongated their shape is with median aspect ratios (ratio of major to minor axis length) of 5.2 for particles larger than 2.6 mm. Furthermore, a case study was considered in which we attempt to reconstruct the observed settling of pyrometeors with a size of about 3.5 mm with theoretical calculations.
How to cite: Schöberl, M., Tatsii, D., Dollner, M., Gattringer, A., Kupc, A., Schwarz, J. P., Holmes, C. D., Halliday, H. S., Hair, J. W., Fenn, M. A., Bui, P. T., Stohl, A., and Weinzierl, B.: Giant aerosol particles and pyrometeors emitted by western US wildfires: shape, occurrence, and transport, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21215, https://doi.org/10.5194/egusphere-egu26-21215, 2026.
Wildfires are becoming more frequent and severe in many fire-prone regions, with disproportionate impacts on carbon emissions, ecosystems, and society. However, existing fire and Earth system models still struggle to represent the highly localized and stochastic nature of extreme fire ignitions and to quantify their short-term impacts at fine spatial scales.
In this work, we develop a data-driven framework for next day active fire forecasting at sub-kilometre resolution by combining reanalysis meteorology with satellite fire observations. Our approach builds on recent advances in spatio-temporal deep learning from the AI community, in particular Earth system transformers and denoising diffusion probabilistic models. We use multi-year ERA5 meteorological fields together with static variables (topography, land cover, fuel proxies) as training data, and VIIRS active fire detections and pixel-level brightness/fire radiative power as targets.
The model consists of a deterministic spatio-temporal backbone that encodes the joint evolution of weather and surface conditions, coupled to a diffusion-based probabilistic head that predicts the distribution of future ignition locations and associated fire intensity. This design allows us to explicitly represent uncertainty in rare, extreme events while retaining high spatial resolution. We evaluate the system on multiple fire-prone regions and held-out seasons containing documented extreme fire episodes. Preliminary results show improved skill in localizing ignitions and capturing extreme-tail intensity compared to baseline statistical and convolutional models, particularly in top-k precision metrics relevant for operational targeting.
We plan to couple the predicted intensity fields with standard emission factors to estimate event-scale CO₂ emissions and explore the relative importance of meteorological and surface drivers using feature attribution techniques using causality discovery methods. Our findings illustrate the potential of modern probabilistic deep learning to bridge between high-resolution fire observations and Earth system applications, and to support the assessment and management of future extreme fires.
How to cite: Bai, Y., Athanasiou, G., Antonopoulos, D., Papoutsis, I., and Carvalhais, N.: Probabilistic forecasting of wildfire ignitions and intensity at sub-kilometre scale using diffusion models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18849, https://doi.org/10.5194/egusphere-egu26-18849, 2026.
Extreme wildfires and megafires in Mediterranean Europe generate disproportionate ecological, social, and economic impacts, yet the processes that govern transitions from large fires to the most extreme events remain insufficiently constrained. In particular, it is unclear whether the emergence of megafires is primarily controlled by short-term atmospheric fire-weather anomalies, antecedent drought-driven fuel preconditioning, or their compound interaction. Clarifying these mechanisms is critical for improving impact-oriented wildfire risk assessment and early warning.
Here, we analyse 11,403 summer wildfires (≥30 ha) that occurred across Mediterranean Europe between 2008 and 2022, including 44 megafires (≥10,000 ha). Fires are classified into four size categories (30–100 ha, 100–1,000 ha, 1,000–10,000 ha, and ≥10,000 ha) to explicitly examine transitions across wildfire size classes. Official fire perimeters from EFFIS are combined with the MESOGEOS environmental–fire datacube (daily, 1 km), integrating meteorological variables, drought indicators, and land-surface conditions.
Fast-reacting atmospheric drivers (air and land-surface temperature, relative humidity, precipitation, and wind speed) are characterized over a ±1-day window around the reported ignition date and aggregated as a 3-day mean to account for start-date uncertainty. Slow-reacting environmental controls are represented using multi-month antecedent drought indicators, including the Standardized Precipitation–Evapotranspiration Index (SPEI), capturing longer-term fuel moisture and stress conditions.
Across increasing fire-size classes, we observe a systematic intensification of hot, dry, and windy conditions near ignition, alongside progressively drier antecedent conditions. Drought indicators show marked stepwise deterioration from medium to very large fires, supporting a strong role of fuel preconditioning driven by prolonged moisture deficits. However, the transition from very large fires to megafires is distinguished less by further increases in drought severity and more by exceptional short-term fire-weather anomalies, particularly strong winds and anomalously high night-time land-surface temperatures.
Using Random Forest classification models with permutation-based feature importance and repeated cross-validation to address class imbalance, we identify a compact and interpretable set of predictors that consistently discriminate transitions toward extreme fire sizes. Night-time land-surface temperature and wind speed emerge as dominant drivers of megafire occurrence, while multi-month drought indicators play a secondary role at the uppermost tail. Complementary logistic regression analyses confirm coherent directions of effect and demonstrate meaningful predictive skill for rare extreme events.
Overall, our results support a compound but non-uniform mechanism: antecedent drought and fuel stress set the stage for very large fires, whereas megafires arise when this preconditioning coincides with extreme short-term fire-weather conditions, particularly persistent nocturnal heat and strong winds. These findings provide actionable insights for extreme-event-focused wildfire early warning and highlight the need to jointly address fuel management and short-term atmospheric extremes under a warming Mediterranean climate.
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How to cite: Ghasemiazma, F., Tonini, M., Fiorucci, P., and Turco, M.: Why some wildfires become megafires: compound short-term fire weather and antecedent drought controls in Mediterranean Europe., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12505, https://doi.org/10.5194/egusphere-egu26-12505, 2026.
