Douglas Stephen Hamilton

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 nearly doubled (likely synthesis range 0.33–44.9, median 1.85) the likelihood of extreme fire weather in this region and made the observed BA around 10 times more likely during July–August 2025. BA extent in the region is found to be 9 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 (virtually certain modelled range 0.14–657, median 3.63) 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 two times 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. However, comparison of SSP3-7.0 with SSP5-8.5 suggests that projected end-of-century extreme BA events in our focal regions are 4 %–23 % smaller than under the very high-emissions futures that were once considered plausible.. 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. Fifteen new and updated datasets created in this report are available from the State of Wildfires Project's Zenodo community (https://zenodo.org/communities/stateofwildfiresproject/, last access: 23 October 2026).

HTAP3-OPNS is a multi-model exercise designed to support the revision of the Gothenburg Protocol under the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). Using an ensemble of Chemical Transport Models (CTMs) and Chemistry-Climate Models (CCMs), this study investigates the long-range transport and impacts of ground-level ozone, particulate matter (PM), and nitrogen and sulphur deposition across different global regions. The project aims to assess the contributions of regional versus extra-regional emission sources, evaluate the suitability of current models, and project changes in air pollution under future emission scenarios and climate conditions. A series of perturbation simulations will enable the development of an ensemble emulator to explore and evaluate potential mitigation strategies efficiently. This paper outlines the scientific and policy questions motivating the study, describes the experimental design, including input datasets, model configurations, and required outputs, and discusses methodologies for data handling and analysis. The results will provide crucial insights for policy decisions aiming to improve air quality, protect human health, and protect ecosystems worldwide.

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m²/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m²/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.

Wildland fires are increasingly important drivers of ecosystem change, air quality degradation, and climate feedbacks, yet their emissions and plume rise are commonly prescribed in Earth system models. Here we introduce interactive fire aerosol emissions and a thermodynamical plume-height parameterization into CanESM5.1c. We evaluate simulated area burned, black carbon (BC) emissions, plume heights, and atmospheric BC distributions against multiple observation-based datasets for 2000--2023, and assess future changes under low- and moderate-warming scenarios. CanESM5.1c simulates global area burned between GFED4 and GFED5 estimates, while BC fire emissions are slightly high. Simulated mean plume heights are about 0.8 km lower than satellite-derived estimates but capture their broad spatial variability. Relative to fixed climatological injection heights, interactive plume height increases atmospheric BC above 850 hPa by 5--10% and decreases near-surface BC by 5--20%. Under moderate warming, end-of-century area burned and BC fire emissions increase by 23% and 53% in the Arctic and 33% and 37% in northern mid-latitudes, respectively, while globally dominant tropical area burned and emissions decrease by 24% and 22%. The frequency of fire plumes exceeding 8 km in height increase in several regions, including Australia/New Zealand, and the northern boreal forests. These changes are consistent with regional shifts in fuel availability, soil moisture, lightning, and atmospheric stability. Extreme fires contribute disproportionately to regional BC emissions and become more frequent in many extra-tropical regions. Under low warming, many fire characteristics remain closer to present-day conditions, emphasizing the benefits of climate change mitigation.

An improved understanding of how fire regimes changed from the pre-industrial to the present-day is required to reduce uncertainty in anthropogenic aerosol radiative forcing. Direct observations of pre-industrial fires are scarce so here we evaluate assumptions about historical fire regime change using black carbon data from polar and alpine ice core records and global climate model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Large Ensemble Community Project (LENS). Black carbon is a tracer of both natural and anthropogenic combustion, enabling comparison of fire and industrial combustion emission changes from the pre-industrial (1850 CE) to the present day (1980 CE). Polar ice core records indicate relatively modest increases in mean and median 1980 CE/1850 CE black carbon ratios of 1.27 and 1.15, compared with 2.89 and 2.64 in the CMIP6 ensemble, respectively. Alpine ice cores record larger increases (mean 2.31; median 1.93), compared with even larger increases simulated in CMIP6 in alpine regions (mean 3.59; median 2.50). We tested three possibilities to explain the difference between black carbon simulated by models and recorded in observations: (1) pre-industrial fire emissions are too low in models; (2) changes in aerosol transport over the Industrial Era using data from LENS; and (3) differences in modelled aerosol properties and deposition parameterizations using CESM2 data. Analysis of these different drivers revealed that the most effective method to reconcile the model-observation disparity is to increase pre-industrial fire emissions in the models and that transport or aerosol properties are of secondary consideration.

An improved understanding of how fire regimes changed from the pre-industrial to the present-day is required to reduce uncertainty in anthropogenic aerosol radiative forcing. Direct observations of pre-industrial fires are scarce so here we evaluate assumptions about historical fire regime change using black carbon data from polar and alpine ice core records and global climate model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Large Ensemble Community Project (LENS). Black carbon is a tracer of both natural and anthropogenic combustion, enabling comparison of fire and industrial combustion emission changes from the pre-industrial (1850 CE) to the present day (1980 CE). Polar ice core records indicate relatively modest increases in mean and median 1980 CE/1850 CE black carbon ratios of 1.27 and 1.15, compared with 2.89 and 2.64 in the CMIP6 ensemble, respectively. Alpine ice cores record larger increases (mean 2.31; median 1.93), compared with even larger increases simulated in CMIP6 in alpine regions (mean 3.59; median 2.50). We tested three possibilities to explain the difference between black carbon simulated by models and recorded in observations: (1) pre-industrial fire emissions are too low in models; (2) changes in aerosol transport over the Industrial Era using data from LENS; and (3) differences in modelled aerosol properties and deposition parameterizations using CESM2 data. Analysis of these different drivers revealed that the most effective method to reconcile the model-observation disparity is to increase pre-industrial fire emissions in the models and that transport or aerosol properties are of secondary consideration.

An improved understanding of how fire regimes changed from the pre-industrial to the present-day is required to reduce uncertainty in anthropogenic aerosol radiative forcing. Direct observations of pre-industrial fires are scarce so here we evaluate assumptions about historical fire regime change using black carbon data from polar and alpine ice core records and global climate model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Large Ensemble Community Project (LENS). Black carbon is a tracer of both natural and anthropogenic combustion, enabling comparison of fire and industrial combustion emission changes from the pre-industrial (1850 CE) to the present day (1980 CE). Polar ice core records indicate relatively modest increases in mean and median 1980 CE/1850 CE black carbon ratios of 1.27 and 1.15, compared with 2.89 and 2.64 in the CMIP6 ensemble, respectively. Alpine ice cores record larger increases (mean 2.31; median 1.93), compared with even larger increases simulated in CMIP6 in alpine regions (mean 3.59; median 2.50). We tested three possibilities to explain the difference between black carbon simulated by models and recorded in observations: (1) pre-industrial fire emissions are too low in models; (2) changes in aerosol transport over the Industrial Era using data from LENS; and (3) differences in modelled aerosol properties and deposition parameterizations using CESM2 data. Analysis of these different drivers revealed that the most effective method to reconcile the model-observation disparity is to increase pre-industrial fire emissions in the models and that transport or aerosol properties are of secondary consideration.

An improved understanding of how fire regimes changed from the pre-industrial to the present-day is required to reduce uncertainty in anthropogenic aerosol radiative forcing. Direct observations of pre-industrial fires are scarce so here we evaluate assumptions about historical fire regime change using black carbon data from polar and alpine ice core records and global climate model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Large Ensemble Community Project (LENS). Black carbon is a tracer of both natural and anthropogenic combustion, enabling comparison of fire and industrial combustion emission changes from the pre-industrial (1850 CE) to the present day (1980 CE). Polar ice core records indicate relatively modest increases in mean and median 1980 CE/1850 CE black carbon ratios of 1.27 and 1.15, compared with 2.89 and 2.64 in the CMIP6 ensemble, respectively. Alpine ice cores record larger increases (mean 2.31; median 1.93), compared with even larger increases simulated in CMIP6 in alpine regions (mean 3.59; median 2.50). We tested three possibilities to explain the difference between black carbon simulated by models and recorded in observations: (1) pre-industrial fire emissions are too low in models; (2) changes in aerosol transport over the Industrial Era using data from LENS; and (3) differences in modelled aerosol properties and deposition parameterizations using CESM2 data. Analysis of these different drivers revealed that the most effective method to reconcile the model-observation disparity is to increase pre-industrial fire emissions in the models and that transport or aerosol properties are of secondary consideration.

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m2/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.