Significance: Fires burn an area comparable to Europe each year, emitting greenhouse gases and aerosols. We compared burned area (BA) based on 20-m resolution images with a BA derived from 500-m data. It represents an 80% increase in BA in sub-Saharan Africa, responsible for about 70% of global BA. This difference is predominately (87%) attributed to small fires (<100 ha), which account for 41% of total BA but only for 5% in coarse-resolution products. We found that African fires were responsible for emissions of 1.44 PgC, 31–101% higher than previous estimates and representing 14% of global CO ₂ emissions from fossil fuel burning. We conclude that small fires are critically important in characterizing the most important disturbance agent on a global scale.

Long-term records of burned area are needed to understand wildfire dynamics, assess fire impacts on ecosystems and air quality, and improve fire forecasts. Here, we fuse multiple streams of remote sensing data to create a 24 year (1997–2020) dataset of monthly burned area as a component of the fifth version of the Global Fire Emissions Database (GFED5). During 2001–2020, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned area product and adjust for the errors of commission and omission. Adjustment factors are estimated based on region, land cover, and tree cover fraction, using spatiotemporally aligned burned area from Landsat or Sentinel-2. Burned area in croplands, peatlands, and deforestation regions is estimated from MODIS active fire detections. Along-Track Scanning Radiometer (ATSR) and Visible and Infrared Scanner (VIRS) active fire data are used to extend the time series back to 1997. The global annual burned area during 2001–2020 is estimated to be 774 ± 63 Mha yr⁻¹ or 5.9 ± 0.5 % of ice-free land. Burned area declined by 1.21 ± 0.66 % yr⁻¹, a cumulative decrease of 24.2 ± 13.2 % over 20 years. The global reduction is primarily driven by a decrease in fires in savannas, grasslands, and croplands. Forest, peat, and deforestation fires did not exhibit significant long-term trends. The GFED5 global burned area is 93 % higher than MCD64A1, 61 % higher than GFED4s, and in closer agreement with products from higher-resolution satellite sensors. These data may reduce discrepancies between fire emission estimates from activity-based and atmospheric-based approaches, and improve our understanding of global fire impacts on the carbon cycle and climate system. The GFED5 global burned area product is freely accessible at https://doi.org/10.5281/zenodo.7668423 (Chen et al., 2023).

Climate change increases fire-favorable weather in forests, but fire trends are also affected by multiple other controlling factors that are difficult to untangle. We use machine learning to systematically group forest ecoregions into 12 global forest pyromes, with each showing distinct sensitivities to climatic, human, and vegetation controls. This delineation revealed that rapidly increasing forest fire emissions in extratropical pyromes, linked to climate change, offset declining emissions in tropical pyromes during 2001 to 2023. Annual emissions tripled in one extratropical pyrome due to increases in fire-favorable weather, compounded by increased forest cover and productivity. This contributed to a 60% increase in forest fire carbon emissions from forest ecoregions globally. Our results highlight the increasing vulnerability of forests and their carbon stocks to fire disturbance under climate change.

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land‐use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite‐derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire‐related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire‐related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire‐related forest loss, with larger contributions in small clearings in interior tropical forests and human‐dominated landscapes. Comparison to higher‐resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental‐scale estimates of fire‐related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire‐related and non‐fire‐related land‐use change emissions in forested ecosystems.

In fire emission models, the spatial resolution of both the modelling framework and the satellite data used to quantify burned area can have considerable impact on emission estimates. Consideration of this sensitivity is especially important in areas with heterogeneous land cover and fire regimes and when constraining model output with field measurements. We developed a global fire emissions model with a spatial resolution of 500 m using MODerate resolution Imaging Spectroradiometer (MODIS) data. To accommodate this spatial resolution, our model is based on a simplified version of the Global Fire Emissions Database (GFED) modelling framework. Tree mortality as a result of fire, i.e. fire-related forest loss, was modelled based on the overlap between 30 m forest loss data and MODIS burned area and active fire detections. Using this new 500 m model, we calculated global average carbon emissions from fire of 2.1±0.2 (±1σ interannual variability, IAV) Pg C yr⁻¹ during 2002–2020. Fire-related forest loss accounted for 2.6±0.7 % (uncertainty range =1.9 %–3.3 %) of global burned area and 24±6 % (uncertainty range =16 %–31 %) of emissions, indicating that fuel consumption in forest fires is an order of magnitude higher than the global average. Emissions from the combustion of soil organic carbon (SOC) in the boreal region and tropical peatlands accounted for 13±4 % of global emissions. Our global fire emissions estimate was higher than the 1.5 Pg C yr⁻¹ from GFED4 and similar to 2.1 Pg C yr⁻¹ from GFED4s. Even though GFED4s included more burned area by accounting for small fires undetected by the MODIS burned area mapping algorithm, our emissions were similar to GFED4s due to higher average fuel consumption. The global difference in fuel consumption could mainly be explained by higher SOC emissions from the boreal region as constrained by additional measurements. The higher resolution of the 500 m model also contributed to the difference by improving the simulation of landscape heterogeneity and reducing the scale mismatch in comparing field measurements to model grid cell averages during model calibration. Furthermore, the fire-related forest loss algorithm introduced in our model led to more accurate and widespread estimation of high-fuel-consumption burned area. Recent advances in burned area detection at resolutions of 30 m and finer show a substantial amount of burned area that remains undetected with 500 m sensors, suggesting that global carbon emissions from fire are likely higher than our 500 m estimates. The ability to model fire emissions at 500 m resolution provides a framework for further improvements with the development of new satellite-based estimates of fuels, burned area, and fire behaviour, for use in the next generation of GFED.