Articles | Volume 14, issue 11
https://doi.org/10.5194/essd-14-4935-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4935-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
08 Nov 2022
Data description paper |
| 08 Nov 2022
| 08 Nov 2022
The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters
Héloïse Lavigne
CORRESPONDING AUTHOR
Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Ana Dogliotti
Instistuto de Astronomía y FísicadelEspacio (IAFE),
CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina
David Doxaran
Laboratoire d'Océanographie de Villefranche, UMR7093 Sorbonne
Université /CNRS, Villefranche-sur-Mer, France
Fang Shen
State Key Laboratory of Estuarine and Coastal Research (SKLEC),
East China Normal University, Shanghai, China
Alexandre Castagna
Laboratory of Protistology and Aquatic Ecology, Ghent University,
Ghent, Belgium
Matthew Beck
Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Quinten Vanhellemont
Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Xuerong Sun
State Key Laboratory of Estuarine and Coastal Research (SKLEC),
East China Normal University, Shanghai, China
Juan Ignacio Gossn
Instistuto de Astronomía y FísicadelEspacio (IAFE),
CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina
European Organisation for the Exploitation of Meteorological
Satellites (EUMETSAT), Darmstadt, Germany
Pannimpullath Remanan Renosh
Laboratoire d'Océanographie de Villefranche, UMR7093 Sorbonne
Université /CNRS, Villefranche-sur-Mer, France
Koen Sabbe
Laboratory of Protistology and Aquatic Ecology, Ghent University,
Ghent, Belgium
Dieter Vansteenwegen
Flanders Marine Institute (VLIZ), Ostend, Belgium
Kevin Ruddick
Royal Belgian Institute of Natural Sciences, Brussels, Belgium
Data sets
The HYPERMAQ dataset Héloise Lavigne, Ana I Dogliotti, David Doxaran, Fang Shen, Alexandre Castagna, Matthew Beck, Quinten Vanhellemont, Xuerong Sun, Juan Ignacio Gossn, Renosh Pannimpullath, Koen Sabbe, Dieter Vansteenwegen, and Kevin Ruddick https://doi.org/10.1594/PANGAEA.944313
Short summary
Because of the large diversity of case 2 waters and the complexity of light transfer, retrieving main biogeochemical parameters in these waters is still challenging. By providing optical and biogeochemical parameters for 180 sampling stations with turbidity and chlorophyll-a concentration ranging from low to extreme values, the HYPERMAQ dataset will contribute to a better description of marine optics in optically complex water bodies and can help the scientific community to develop algorithms.
Because of the large diversity of case 2 waters and the complexity of light transfer, retrieving...
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