Direct Estimation of Wildfire Emissions at High Latitudes from Combined Polar Orbiter FRP and Sentinel-5P CO Data
Abstract. High Latitude (HL) landscape fires are an important source of greenhouse gases and aerosols, with growing significance under rapid anthropogenic climate change-induced warming. Current fire emission inventories are mostly ‘bottom-up’ in nature; combining, or relying on linear regressions between, satellite remote sensing data and process-based model outputs. However, these methods rely on uncertainties surrounding fuel load and combustion completeness. Here, we adapt the ‘top-down’ Fire Radiative Energy Emission (FREM) approach for HL fires (HLFREM), linking Fire Radiative Energy (FRE) directly to emissions via coefficients derived solely from satellite observations. We derive biome-specific emission coefficients by combining Fire Radiative Power (FRP) from GFAS v1.4 with TROPOMI Total Column Carbon Monoxide plume observations, for the HL’s four most fire-prone biomes; Deciduous and Evergreen Needleleaf Forests, Grasslands, and Shrublands. By applying these coefficients to daily GFAS v1.2 FRE totals (2003–2024), we estimate CO and total carbon emissions across the HL using HLFREM. HLFREM-derived CO emissions generally agree with other widely used inventories (GFAS v1.2, FEERv1.0-GFASv1.2, and GFEDv4.1s) in forested biomes, with annual average differences of -32 % to -43 % for Deciduous Needleleaf Forests, and -28 % to -43 % for Evergreen Needleleaf forests. For Shrublands and Grassland biomes, HLFREM estimates are 31–43 % and 61–80 % lower respectively. Total carbon emissions, using Emission Factors, were found to show consistent patterns with CO across all biomes. Our results represent the first HL fire emissions dataset based only on satellite data of a major carbon containing gas (CO) emitted by fires and the rate of fire radiative energy release.
This manuscript presents a methodologically innovative and scientifically significant advancement in the assessment of high-latitude wildfires (≥ 60° N), achieved through a robust integration of multiple satellite-derived data sources within a well-conceptualized methodological framework. The study is well aligned with the scope of Biogeosciences and represents a genuine advance over existing wildfire emission inventories.
I recommend minor revisions, not due to flaws in the core methodology, but because several conceptual, statistical, and reproducibility aspects should be strengthened.
The manuscript would benefit from explicitly stated research questions and testable hypotheses in the Introduction. This would improve conceptual clarity and narrative structure.
The manual digitization of matchup fires may introduce subjectivity and selection bias. A quantitative comparison between matchup fires and the full fire population is recommended.
Biome-specific emission coefficients are derived using zero-intercept OLS regression. The physical justification for this assumption should be clarified, and sensitivity analyses or alternative regression approaches should be considered.
The framework does not explicitly distinguish soil carbon combustion, which may lead to underestimation in peat-rich regions. This limitation should be clearly discussed.
Uncertainties are not fully propagated into long-term emission totals. A clearer description of uncertainty propagation is encouraged.