期刊
APPLIED OPTICS
卷 61, 期 19, 页码 5735-5748出版社
Optica Publishing Group
DOI: 10.1364/AO.456216
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- Agence Nationale de la Recherche
- European Space Agency
- Centre National d'Etudes Spatiales
- Centre National de la Recherche Scientifique
- Institut national des sciences de l'Univers
- Conseil Regional Provence-Alpes-Cote d'Azur
- Sorbonne Universite, Institut de la Mer de Villefranche (IMEV)
The diel cycles of the optical backscattering coefficient of particulate matter in the ocean can generate measurable diel variability of the ocean reflectance. This provides a promising avenue for quantifying biogeochemical quantities, but current inversion algorithms have limitations in deriving diel changes.
Using in situ measurements of radiometric quantities and of the optical backscattering coefficient of particulate matter (b(bp)) at an oceanic site, we show that diel cycles of b(bp) are large enough to generate measurable diel variability of the ocean reflectance. This means that biogeochemical quantities such as net phytoplankton primary production, which are derivable from the diel b(bp) signal, can be potentially derived also from the diel variability of ocean color radiometry (OCR). This is a promising avenue for basin-scale quantification of such quantities because OCR is now performed from geostationary platforms that enable quantification of diel changes in the ocean reflectance over large ocean expanses. To assess the feasibility of this inversion, we applied three numerical inversion algorithms to derive b(bp) from measured reflectance data. The uncertainty in deriving b(bp) transfers to the retrieval of its diel cycle, making the performance of the inversion better in the green part of the spectrum(555 nm), with correlation coefficients >0.75 and a variability of 40% between the observed and derived b(bp) diel changes. While the results are encouraging, they also emphasize the inherent limitation of current inversion algorithms in deriving diel changes of b(bp), which essentially stems from the empirical parameterizations that such algorithms include. (C) 2022 Optica Publishing Group
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