International Journal of Digital Earth · 2024 · 17 citations · 62 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceRemote SensingSatellite MeteorologyAerosol Remote SensingAtmospheric CorrectionAtmospheric OpticsRemote Sensing Image AnalysisSatellite Image InterpretationSatellite SensorsAerosol Optical Depth RetrievalAerosol Optical Depth ValidationOptical DepthPassive Sensor Aerosol RetrievalsRetrievalSpectral RetrievalsSurface ReflectanceSurface Reflectance Retrieval
The Medium Resolution Spectral Image (MERSI) is a MODIS-like sensor aboard Fengyun-3 satellite. The first version of MERSI aerosol algorithm has been developed based on MODIS dark target (DT) algorithm, with modified models for estimating surface reflectance and an adjusted inland water masking method to release haze aerosols. This study applies MERSI DT algorithm to the global observations from the upgraded MERSI sensor (MERSI-II) on Fengyun-3D. And then, the Aerosol Optical Depth (AOD) results from the year of 2019–2020 are validated against the Aerosol Robotic Network (AERONET) data. In addition, analyses of the spatial distribution and error characteristics of MODIS and MERSI-II retrievals are presented. The overall validation demonstrates that MERSI-II retrievals perform well globally, with a correlation coefficient of 0.877 and 67.1% of matchups within the Expected Error envelope of ± (0.05 + 0.2τ), which are close to the statistic metrics of MODIS products. In addition, MERSI-II and MODIS AODs exhibit similar error trends and error dependence. Moreover, the similar global distribution characteristics of the two AODs are revealed in the retrieval performance at site and regional scales, as well as in the analysis of monthly averages. These findings indicate the success of the ported MERSI algorithm.
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