the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
State of Wildfires 2025–2026
Abstract. The global geography, behaviour, and impact of fires are shifting, as spatially varying human influences interact with a visibly changing climate. The State of Wildfires project systematically tracks global and regional fire activity, analyses the causes of prominent extreme wildfire events for three focal regions, and projects the likelihood of similar events under future climate scenarios. During the March 2025–February 2026 fire season, global burned area (BA) was 18 % below the 2002–2024 average and global fire carbon (C) emissions were also 20–31 % below average, making it one of the lowest years on record. Yet this globally low fire year still produced widespread regional impacts. Canada experienced a third consecutive extreme fire year, with national fire C emissions at nearly triple the average since 2002, 70,000 evacuations, and reported direct losses of USD 360 million. In the Midwestern Canadian Shield Forests, the epicentre of Canada’s anomalous season, we find that anthropogenic climate change has doubled the likelihood of extreme fire weather in this region and made the observed BA around 61 times more likely during July–August 2025, while BA extent in the region is 46 times greater. Many parts of Europe also experienced record or high-ranking BA and fire C emissions, including in Spain, Portugal, and the UK, and a record USD 4.11 billion of physical assets were exposed to fire across the continent. Direct fatalities occurred in Türkiye (17), Spain (8), Portugal (6), Cyprus (2), Greece (1) and France (1), and evacuations in Türkiye, Spain, and Greece totalled over 110,000. In the Northwest Iberian Peninsula, we find that extreme fire weather over August 2025 was around 3 times more likely due to climate change. Under a high-emissions scenario (SSP3-7.0), fires of the same return interval are likely to burn about 78 % more area by the end of the century, with some projections within the same scenario suggesting increases of around sevenfold. In Chile and northwest Argentina, January–February 2026 fires caused 23 fatalities, displaced 55,000 people and threatened a UNESCO World Heritage Site. In the Chilean Temperate Forests and Matorral, the epicentre, we find that BA was around 36 % larger due to anthropogenic climate change. Across all focal regions in this report, the conditions for extreme fire developed gradually through months of precipitation deficits, cumulative drying and, in the case of Northwest Iberia, antecedent fuel accumulation aided by preceding wet periods. Continued climate change is expected to intensify these hydroclimatic extremes, yet mitigation has already reduced projected end-of-century wildfire risk: under a high-end emissions pathway (SSP3-7.0), the extreme BA events in our focal regions are projected to be 4–23 % smaller than they would have been under a worst-case emissions scenario no longer considered credible (SSP5-8.5). Meeting the Paris targets (SSP1-2.6) would further reduce BA during these events by 5–36 % across our focal regions. By integrating expertise from across the wildfire community with state-of-the-art observations, data, and modelling, this annual report advances understanding of regional wildfire extremes and their drivers, providing evidence to inform policy, preparedness, mitigation, adaptation, and broader societal benefit. Seventeen new and updated datasets created in this report are available from the State of Wildfires Project's Zenodo community (https://zenodo.org/communities/stateofwildfiresproject/).
Competing interests: Sander Veraverbeke is a member of the editorial board of Earth System Science Data. Niels Andela and Dave van Wees are employees of BeZero Carbon Ltd., a carbon credit ratings agency for the voluntary carbon market.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 09 Sep 2026)
Data sets
Regional Summaries of Burned Area, Fire Emissions, and Individual Fire Characteristics for National, Administrative and Biogeographical Regions M. W. Jones et al. https://doi.org/10.5281/zenodo.21262381
Updates to the Global Fire Atlas of individual fire size, duration, speed and direction N. Andela and M. W. Jones https://doi.org/10.5281/zenodo.21262381
Population Exposure to Wildfire data S. Teymoor Seydi et al. https://doi.org/10.5281/zenodo.20787866
Physical Asset Exposure to Wildfire data are available at Steinmann C. B. Steinmann et al. https://doi.org/10.5281/zenodo.21332621
Daily mean PM2.5 surface concentrations aggregated by Continent, Biome, Country, and Administrative Region data E. Di Tomaso et al. https://doi.org/10.5281/zenodo.21277053
Protected Areas Exposure to Fire data À. Cunill Camprubí et al. https://doi.org/10.5281/zenodo.20764120
Forest Carbon Project Exposure to Fire data N. Andela et al. https://doi.org/10.5281/zenodo.21430353
Anomalies in Extreme Fire Weather Days by Continent, Biome, Country, and Administrative Region M. Turco et al. https://doi.org/10.5281/zenodo.20757872
Data for "Large-scale modelled impacts of the 2025 Canadian wildfires" by Rosu et al. I.-A. Rosu et al. https://doi.org/10.5281/zenodo.20523005
ERA5-Land hourly data from 1950 to present J. Muñoz Sabater https://doi.org/10.24381/cds.e2161bac
Observation and ERA5-Land derived 9 km global daily fire fuel characteristics since 2003 European Centre for Medium-Range Weather Forecasts (ECMWF) https://doi.org/10.24381/378d1497
FWI calculated from HadGEM3-A and Present-Day Attribution using HadGEM3-A large ensemble data A. Hartley et al. https://doi.org/10.5281/zenodo.21379381
State of Wildfires 2025-26: Present-Day Attribution and Future Projections of Focal Events Using FWI7X Z. Liu and J. Eden https://doi.org/10.5281/zenodo.20827512
HadGEM3-A historical data Met Office http://catalogue.ceda.ac.uk/uuid/99b29b4bfeae470599fb96243e90cde3
WWA Attribution and Future Projection of Focal Events Using FWI95 data T. Keeping https://doi.org/10.5281/zenodo.21374687
State of Wildfires 2025-26: Midwestern Canadian Shield Forests Burned Area Attribution and Projections D. Kelley et al. https://doi.org/10.5281/zenodo.21468717
State of Wildfires 2025-26: Northwest Iberia Burned Area Attribution and Projections D. Kelley et al. https://doi.org/10.5281/zenodo.21458571
State of Wildfires 2025-26: Chilean Temperate Forests and Matorral Burned Area Attribution and Projections D. Kelley et al. https://doi.org/10.5281/zenodo.21459106
JULES-ES bias adjustment data J. Wessel and F. Spuler https://doi.org/10.5281/zenodo.21397548
BuRNN: A Data-Driven Fire Model S. Lampe https://doi.org/10.5281/zenodo.17778519
BuRNN (v1.0): a data-driven fire model S. Lampe et al. https://doi.org/10.5194/gmd-19-955-2026
Wildfires on a changing planet O. Haas et al. https://doi.org/10.1038/s41467-025-68176-4
Model code and software
State of Wildfires 2025-26: Present-Day Attribution and Future Projections of Focal Events Using FWI7X Z. Liu and J. Eden https://doi.org/10.5281/zenodo.20827512
State of Wildfires 2025-26: WWA Attribution and Future Projection of Focal Events Using FWI95 T. Keeping https://doi.org/10.5281/zenodo.21374687
douglask3/State_of_Wildfires_report: State of Wildfires 2025-26: FWI attribution model (Versions Sow2526_v0.1) C. Burton et al. https://doi.org/10.5281/zenodo.21499355
Data for "Large-scale modelled impacts of the 2025 Canadian wildfires" by Rosu et al. I.-A. Rosu et al. https://doi.org/10.5281/zenodo.20523005
State-of-Wildfires_CLIMADA Carmen B. Steinmann https://doi.org/10.5281/zenodo.21393395
State of Wildfires 2025-26: ConFLAME (Versions SoW2526_v0.1) D. Kelley et al. https://doi.org/10.5281/zenodo.21473591
VUB-HYDR/BuRNN: Version 1.1 (Version v1.1) S. Lampe https://doi.org/10.5281/zenodo.17834206
BuRNN (v1.0): a data-driven fire model S. Lampe et al. https://doi.org/10.5194/gmd-19-955-2026
Wildfires on a changing planet O. Haas et al. https://doi.org/10.1038/s41467-025-68176-4
Set up the models O. Haas https://doi.org/10.6084/m9.figshare.24764583
Run models O. Haas https://doi.org/10.6084/m9.figshare.24764577
Results scripts O. Haas https://doi.org/10.6084/m9.figshare.24764571