Comprehensive global fire radiative power evaluation by minimizing detection bias with intercomparison and extended triple collocation analysis

Abstract

Satellite remote sensing has provided valuable information on fire radiative power (FRP), which is an important indicator for estimating biomass burning emissions and understanding fire dynamics. However, FRP evaluation faces challenges due to limited field measurements and the high variability of satellite sensor characteristics. Previous studies have tried to quantify the uncertainty of FRP by intercomparison, but they are limited to small numbers of cases and are not free from the detection capacity. To address this issue, we presented a comprehensive global evaluation of FRP from three satellite sensors-Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Sea and Land Surface Temperature Radiometer (SLSTR)-by integrating all possible fire clusters after minimizing differences in fire occurrence detection while preserving inherent differences in detection extent across sensors. Furthermore, we applied extended triple collocation analysis (ETC) to evaluate the consistency of FRP without relying on true reference data for the first time. Intercomparative results highlight robust consistency when the fire clusters overlap well across all three sensors, even under varying sample selection criteria. Notably, SLSTR and VIIRS have slightly higher FRP than MODIS, even after aligning detected fire events, due to the superiority of observing small or weak fires at the edge of fire clusters. ETC revealed high consistency in boreal forests, where large-scale, strong fire clusters are well matched. In contrast, uncertainties remain in South Africa because of highly variable fire dynamics in that area. This study contributes to understanding the regional characteristics of FRP and provides a robust framework for global-scale FRP assessments as new satellite datasets become available.