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Inversion of spectral absorption coefficients to infer phytoplankton size classes, chlorophyll concentration, and detrital matter

Authors :
Xiaodong Zhang
Annick Bricaud
Heidi M. Sosik
Yannick Huot
China Agricultural University (CAU)
Département de géomatique appliquée [Sherbrooke] (UdeS)
Université de Sherbrooke (UdeS)
Laboratoire d'océanographie de Villefranche (LOV)
Observatoire océanologique de Villefranche-sur-mer (OOVM)
Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)
Woods Hole Oceanographic Institution (WHOI)
Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Source :
Applied Optics, Applied Optics, 2015, 54 (18), pp.5805-5816. ⟨10.1364/AO.54.005805⟩
Publication Year :
2015
Publisher :
HAL CCSD, 2015.

Abstract

Measured spectral absorption coefficients were inverted to infer phytoplankton concentration in three size classes (picoplankton, nanoplankton, and microplankton), chlorophyll concentration[Chl], and both magnitude and spectral shape of absorption by colored detrital matter (CDM). Our algorithm allowed us to solve for the nonlinear factor of CDM absorption slope separately from the other linear factors, thus fully utilizing the additive characteristic inherent in absorption coefficients. We validated the inversion with three datasets: two spatially distributed global datasets, the Laboratoire d'Oceanographie de Villefranche dataset and the NASA bio-Optical Marine Algorithm Dataset, and a time series coastal dataset, the Martha's Vineyard Coastal Observatory dataset. Comparison with high performance liquid chromatography analyses showed that the phytoplankton size classes can be retrieved with correlation coefficients (r)> 0.7, root mean square errors of 0.2, and median relative errors of 20% in oceanic waters and with similar performance in coastal waters. Much improved agreement was found for the entire phytoplankton population, with r > 0.90 for[Chl] and absorption coefficients (a(ph)) for all three datasets. The inferred a(CDM) (400) and CDM spectral slope agree within +/- 4% of measurements in both oceanic and coastal waters. The results indicate that the chlorophyll-a specific absorption spectra used as an inversion kernel represent well the global mean states for each of the three phytoplankton size classes. The method can be applied to either bulk or particulate absorption data and is spectrally flexible. (C) 2015 Optical Society of America

Details

Language :
English
Database :
OpenAIRE
Journal :
Applied Optics, Applied Optics, 2015, 54 (18), pp.5805-5816. ⟨10.1364/AO.54.005805⟩
Accession number :
edsair.doi.dedup.....682b88c95252fc95d4d0fec553960c84
Full Text :
https://doi.org/10.1364/AO.54.005805⟩