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Determining the primary sources of uncertainty in the retrieval of marine remote sensing reflectance from satellite ocean color sensors II. Sentinel 3 OLCI sensors
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2023
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Source: Frontiers in Remote Sensing, 4
[PDF-4.97 MB]
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Journal Title:Frontiers in Remote Sensing
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Description:Uncertainties in remote sensing reflectance Rrs for the Ocean Color sensors strongly affect the quality of the retrieval of concentrations of chlorophyll-a and water properties. By comparison of data from SNPP VIIRS and several AERONET-OC stations and MOBY, it was recently shown that the main uncertainties come from the Rayleigh-type spectral component (Gilerson et al., 2022), which was associated with small variability in the Rayleigh optical thickness in the atmosphere and/or its calculation. In addition, water variability spectra proportional to Rrs were found to play a significant role in coastal waters, while other components including radiances from aerosols and glint were small. This work expands on the previous study, following a similar procedure and applying the same model for the characterization of uncertainties to the Sentinel-3A and B OLCI sensors. It is shown that the primary sources of uncertainties are the same as for VIIRS, i.e., dominated by the Rayleigh-type component, with the total uncertainties for OLCI sensors typically higher in coastal areas than for VIIRS.
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Source:Frontiers in Remote Sensing, 4
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ISSN:2673-6187
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Rights Information:CC BY
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