Changement climatique - Recherche française (avec laboratoires CNRS) - 2010-2015


The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms

Publication Year


  • Brewin, Robert J. W.
  • Sathyendranath, Shubha
  • Mueller, Dagmar
  • Brockrnann, Carsten
  • Deschamps, Pierre-Yves
  • Devred, Emmanuel
  • Doerffer, Roland
  • Fomferra, Norman
  • Franz, Bryan
  • Grant, Mike
  • Groom, Steve
  • Horseman, Andrew
  • Hu, Chuanmin
  • Krasemann, Hajo
  • Lee, ZhongPing
  • Maritorena, Stephane
  • Melin, Frederic
  • Peters, Marco
  • Platt, Trevor
  • Regner, Peter
  • Smyth, Tim
  • Steinmetz, Francois
  • Swinton, John
  • Werdell, Jeremy
  • White, George N., III
REMOTE SENSING OF ENVIRONMENT Volume: 162 Pages: 271-294 Published: 2015
0034-4257 eISSN: 1879-0704

Satellite-derived remote-sensing reflectance (R-rs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ Rrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in R data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model: We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies. (C) 2013 Elsevier Inc All rights reserved.

Author Keyword(s)
  • Phytoplankton
  • Ocean colour
  • Inherent Optical Properties
  • Remote sensing
  • Chlorophyll-a
KeyWord(s) Plus
ESI Discipline(s)
  • Computer Science
  • Engineering
  • Environment/Ecology
  • Geosciences
  • Physics
Web of Science Category(ies)
  • Environmental Sciences
  • Remote Sensing
  • Imaging Science & Photographic Technology

[Brewin, Robert J. W.; Sathyendranath, Shubha; Grant, Mike; Groom, Steve; Horseman, Andrew; Platt, Trevor; Smyth, Tim] Plymouth Marine Lab, Plymouth PL1 3DH, Devon, England; [Brewin, Robert J. W.; Sathyendranath, Shubha] Plymouth Marine Lab, Natl Ctr Earth Observat, Plymouth PL1 3DH, Devon, England; [Mueller, Dagmar; Doerffer, Roland; Krasemann, Hajo] Helmholtz Zentrum Geesthacht, D-21502 Geesthacht, Germany; [Brockrnann, Carsten; Fomferra, Norman; Peters, Marco] Brockmann Consult, D-21502 Geesthacht, Germany; [Deschamps, Pierre-Yves; Steinmetz, Francois] HYGEOS, F-59000 Lille, France; [Devred, Emmanuel] Univ Laval, Quebec City, PQ G1V 0A6, Canada; [Franz, Bryan; Werdell, Jeremy] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA; [Hu, Chuanmin] Univ S Florida, Coll Marine Sci, St Petersburg, FL 33701 USA; [Lee, ZhongPing] Univ Massachusetts, Coll Sci & Math, Boston, MA 02125 USA; [Maritorena, Stephane] Univ Calif Santa Barbara, Earth Res Inst, Santa Barbara, CA 93106 USA; [Melin, Frederic] European Commiss, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, Italy; [Regner, Peter] European Space Agcy, ESRIN, I-00044 Frascati, Italy; [Swinton, John] Telespazio VEGA UK Ltd, Luton LU1 3LU, Beds, England; [White, George N., III] Bedford Inst Oceanog, Ocean Sci Div, Dartmouth, NS B2Y 4A2, Canada

Reprint Adress

Brewin, RJW (reprint author), Plymouth Marine Lab, Prospect Pl, Plymouth PL1 3DH, Devon, England.

  • Canada
  • France
  • Germany
  • Italy
  • United Kingdom
  • United States
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