Abstract:
This study addresses two key uncertainties in the fire radiative power (FRP) retrieval, which is essential for improving global top-down fire emission inventories. First,...Show MoreMetadata
Abstract:
This study addresses two key uncertainties in the fire radiative power (FRP) retrieval, which is essential for improving global top-down fire emission inventories. First, it proposes a novel FRP retrieval method by combining the ~4 and \sim 8.6~\mu m channels based on Monte Carlo simulation, which is verified using the Visible Infrared Imaging Radiometer Suite (VIIRS). The inclusion of the \sim 8.6~\mu m channel significantly improves the accuracy of FRP retrieval, especially for highly smoldering fires. Second, atmospheric correction is conducted using outputs from the state-of-the-art unified linearized vector radiative transfer model (UNL-VRTM). The importance of atmospheric correction is demonstrated through the single-channel ( \sim 4~\mu m) FRP retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire (AF), VIIRS AF, and VIIRS second-generation fire light detection algorithm (FILDA-2) products. Post-correction results show effective mitigation of nighttime FRP angular dependency, achieved by considering the enhanced atmospheric attenuation due to longer path length off-nadir. However, a residual daytime FRP angular dependency remains, likely due to the angular dependency of the thresholds used for daytime fire detection. Additionally, an enhanced agreement is observed between the VIIRS FILDA-2 FRP retrievals from the Suomi National Polar-orbiting Partnership (NPP) and National Oceanic and Atmospheric Administration (NOAA)-20 satellites after correction. Lastly, a global FRP increase is noted across all three products, with VIIRS AF and VIIRS FILDA-2 showing more significant increases (65.8% and 62.5%, respectively) than MODIS AF (20.8%). These advancements in FRP retrievals may enhance the downstream fire emission products, which will benefit the air pollution modeling community.
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 62)