Determination of biogeochemical properties in sea waters using the inversion of the three-stream irradiance model

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. Moreover, we provide a comprehensive sensitivity analysis of the model's skill by perturbing the parameters of the bio-optical properties and phytoplankton physiology. Analysis of the inversion indicates that the model is able to reconstruct the variability of the optical constituents. Results indicate that chlorophyll-a and coloured dissolved organic matter play a major role in light modulation. The sensitivity analysis shows that the parameterization of the ratio of chlorophyll-a to carbon is important for the performance of the inversion model. A coherent inversion model, as presented, can be used as an observational operator to assimilate remote sensing reflectance.

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Publication Details

Journal
Scientific Reports
Published
2024-09-27
DOI
https://doi.org/10.1038/s41598-024-71457-5
Citations
3
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
1.44

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article

Determination of biogeochemical properties in sea waters using the inversion of the three-stream irradiance model

Ilya Chernov, Vincenzo Vellucci, Eva Rodriguez Alvarez, Paolo Lazzari et al.
3 citations
Scientific Reports
Marine and coastal ecosystems
1.44
article

Determination of biogeochemical properties in sea waters using the inversion of the three-stream irradiance model

Ilya Chernov, Vincenzo Vellucci, Eva Rodriguez Alvarez, Paolo Lazzari, Mirna Gharbi Dit Kacem
article en
3 citations

Abstract

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. Moreover, we provide a comprehensive sensitivity analysis of the model's skill by perturbing the parameters of the bio-optical properties and phytoplankton physiology. Analysis of the inversion indicates that the model is able to reconstruct the variability of the optical constituents. Results indicate that chlorophyll-a and coloured dissolved organic matter play a major role in light modulation. The sensitivity analysis shows that the parameterization of the ratio of chlorophyll-a to carbon is important for the performance of the inversion model. A coherent inversion model, as presented, can be used as an observational operator to assimilate remote sensing reflectance.

Scientific ReportsVol. 14(1)
Centre National de la Recherche Scientifique (FR), Russian Academy of Sciences (RU), University of Trieste (IT), Sorbonne Université (FR), Karelian Research Centre (RU), Laboratoire de Biologie du Développement de Villefranche-sur-Mer (FR), Laboratoire d’Océanographie de Villefranche (FR), National Institute of Oceanography and Applied Geophysics (IT), Institut de la Mer de Villefranche (FR), Université Paris 1 Panthéon-Sorbonne (FR)
European Space Agency, European Commission, Centre National d’Etudes Spatiales, HORIZON EUROPE Framework Programme
Life below water
Openalex Percentile: Top 19%
Marine and coastal ecosystems
1.44
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