Articles | Volume 14, issue 11
Data description paper
08 Nov 2022
Data description paper |  | 08 Nov 2022

The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters

Héloïse Lavigne, Ana Dogliotti, David Doxaran, Fang Shen, Alexandre Castagna, Matthew Beck, Quinten Vanhellemont, Xuerong Sun, Juan Ignacio Gossn, Pannimpullath Remanan Renosh, Koen Sabbe, Dieter Vansteenwegen, and Kevin Ruddick


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-189', Anonymous Referee #1, 23 Jul 2022
    • AC1: 'Reply on RC1', LAVIGNE Héloïse, 22 Sep 2022
  • RC2: 'Comment on essd-2022-189', Giorgio Dall'Olmo, 03 Aug 2022
    • AC2: 'Reply on RC2', LAVIGNE Héloïse, 22 Sep 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by LAVIGNE Héloïse on behalf of the Authors (22 Sep 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (28 Sep 2022) by François G. Schmitt
AR by LAVIGNE Héloïse on behalf of the Authors (07 Oct 2022)  Manuscript 
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.
Final-revised paper