Comparison and validation of state-of-the-art fire emissions models for the Amazon

Amazon forest conservation is critical for reaching net-zero carbon emissions and protecting regional biodiversity but these efforts are at risk from deforestation, fire and drought. In particular, accurate quantification of carbon losses from forest and deforestation fires are required to understand long-term impacts of fire on the carbon cycle and inform management strategies. Recent developments in the detection of burned area, near-real time tracking of fire patch metrics, and higher-resolution fire emissions models allow for improved estimates of carbon losses from fire. Nevertheless, independent validation of these novel approaches often remains elusive, leading to large disagreement between different emissions inventories.

Here, we compare carbon emissions estimates from several state-of-the-art fire emissions models, including a 500-m resolution GFED version, GFAS, and the Sense4Fire project, in a case-study for the Amazon region. Where necessary, we have updated the models to extend to 2022 and to include the most recent version of model input data from MODIS (Collection 6.1). We analysed the added years of data to elucidate recent trends in fire-related carbon emissions across the Amazon and adjacent biomes. For validation, we ingested the CO emissions from the considered fire emissions models into an atmospheric transfer simulation (IFS-COMPO) and compared those to column CO observations from Sentinel-5P TROPOMI. Finally, we propose an optimization methodology for matching modelled CO concentrations to observations with the objective of constraining regional carbon losses from fire. Results provide novel insights into carbon losses from fire across different fire types and land use practices, and can be extended to global scale for improved estimates of global fire emissions.