Inversion models, in the context of oceanography, relate the observed ocean color to the concentrations of the different biogeochemical components present in the water of the ocean. However, building accurate inversion models can be quite complex due to the many factors that can influence the observed ocean color, such as variations in the composition or the optical properties of biogeochemical products. Here we assess the feasibility of the inversion approach, by implementing the three-stream light inversion model in a one-dimensional water column configuration, represented at the BOUSSOLE site in the northwestern Mediterranean Sea.
View Article and Find Full Text PDFUsing in situ measurements of radiometric quantities and of the optical backscattering coefficient of particulate matter () at an oceanic site, we show that diel cycles of 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 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.
View Article and Find Full Text PDFLinear regression is widely used in applied sciences and, in particular, in satellite optical oceanography, to relate dependent to independent variables. It is often adopted to establish empirical algorithms based on a finite set of measurements, which are later applied to observations on a larger scale from platforms such as autonomous profiling floats equipped with optical instruments (e.g.
View Article and Find Full Text PDF