Uncertainty in Ocean-Color Estimates of Chlorophyll for Phytoplankton Groups

• Published in: Frontiers in Marine Science 2017-04, Vol.4
• Main Authors: Brewin, Robert J. W., Ciavatta, Stefano, Sathyendranath, Shubha, Jackson, Thomas, Tilstone, Gavin, Curran, Kieran, Airs, Ruth L., Cummings, Denise, Brotas, Vanda, Organelli, Emanuele, Dall'Olmo, Giorgio, Raitsos, Dionysios E.
• Format: Article
• Language: English
• Subjects: Biogeochemistry; Chlorophyll; Chlorophylls; Climate change; Color; Community structure; Data; Data assimilation; Data collection; Diatoms; Dinoflagellates; Ecosystem models; Ecosystems; Environmental changes; Estimates; Laboratories; Marine ecosystems; Ocean colour; Optical properties; Optical water types; Phytoplankton; Plankton; Products; Propagation; Remote sensing; Satellites; Sea surface; Sea surface temperature; Signatures; Taxonomy; Uncertainty; Water types
• ISSN: 2296-7745; 2296-7745
• DOI: 10.3389/fmars.2017.00104

Over the past decade, techniques have been presented to derive the community structure of phytoplankton at synoptic scales using satellite ocean-colour data. There is a growing demand from the ecosystem modelling community to use these products for model evaluation and data assimilation. Yet, from the perspective of an ecosystem modeller these products are of limited use unless: (i) the phytoplankton products provided by the remote-sensing community match those required by the ecosystem modellers; and (ii) information on per-pixel uncertainty is provided to evaluate data quality. Using a large dataset collected in the North Atlantic, we re-tune a method to estimate the chlorophyll concentration of three phytoplankton groups, partitioned according to size (pico- (20μm)). The method is modified to account for the influence of sea surface temperature, also available from satellite data, on model parameters and on the partitioning of microphytoplankton into diatoms and dinoflagellates, such that the phytoplankton groups provided match those simulated in a state of the art marine ecosystem model (the European Regional Seas Ecosystem Model, ERSEM). The method is validated using another dataset, independent of the data used to parameterise the method, of more than 800 satellite and in situ match-ups. Using fuzzy-logic techniques for deriving per-pixel uncertainty, developed within the ESA Ocean Colour Climate Change Initiative (OC-CCI), the match-up dataset is used to derive the root mean square error and the bias between in situ and satellite estimates of the chlorophyll for each phytoplankton group, for 14 different optical water types (OWT). These values are then used with satellite estimates of OWTs to map uncertainty in chlorophyll on a per pixel basis for each phytoplankton group. It is envisaged these satellite products will be useful for those working on the validation of, and assimilation of data into, marine ecosystem models that simulate different phytoplankton groups.