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Diel changes of the optical backscattering coefficient of oceanic particulate matter determined from diel changes in apparent optical properties: a case study in the Mediterranean Sea (BOUSSOLE site).
Appl Opt ; 61(19): 5735-5748, 2022 Jul 01.
Article em En | MEDLINE | ID: mdl-36255807
ABSTRACT
Using in situ measurements of radiometric quantities and of the optical backscattering coefficient of particulate matter (bbp) at an oceanic site, we show that diel cycles of bbp 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 bbp 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 bbp from measured reflectance data. The uncertainty in deriving bbp 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 bbp diel changes. While the results are encouraging, they also emphasize the inherent limitation of current inversion algorithms in deriving diel changes of bbp, which essentially stems from the empirical parameterizations that such algorithms include.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Material Particulado Idioma: En Revista: Appl Opt Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Material Particulado Idioma: En Revista: Appl Opt Ano de publicação: 2022 Tipo de documento: Article