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dc.contributor.authorEvers-King, Hayley
dc.contributor.authorMartinez-Vicente, Victor
dc.contributor.authorBrewin, Robert J. W.
dc.contributor.authorDall’Olmo, Giorgio
dc.contributor.authorHickman, Anna E.
dc.contributor.authorJackson, Thomas
dc.contributor.authorKostadinov, Tihomir S.
dc.contributor.authorKrasemann, Hajo
dc.contributor.authorLoisel, Hubert
dc.contributor.authorRöttgers, Rüdiger
dc.contributor.authorRoy, Shovonlal
dc.contributor.authorStramski, Dariusz
dc.contributor.authorThomalla, Sandy
dc.contributor.authorPlatt, Trevor
dc.contributor.authorSathyendranath, Shubha
dc.date.accessioned2020-11-02T20:09:28Z
dc.date.available2020-11-02T20:09:28Z
dc.date.issued2017
dc.identifier.citationEvers-King, H,; Martinez-Vicente, V.; Brewin, R.J.W. et al (2017) Validation and Intercomparison of Ocean Color Algorithms for Estimating Particulate Organc Carbon in the Oceans. Frontiers in Marine Science, 4:251, 20pp. DOI: 10.3389/fmars.2017.00251en_US
dc.identifier.urihttp://hdl.handle.net/11329/1438
dc.identifier.urihttp://dx.doi.org/10.25607/OBP-941
dc.description.abstractParticulate Organic Carbon (POC) plays a vital role in the ocean carbon cycle. Though relatively small compared with other carbon pools, the POC pool is responsible for large fluxes and is linked to many important ocean biogeochemical processes. The satellite ocean-color signal is influenced by particle composition, size, and concentration and provides a way to observe variability in the POC pool at a range of temporal and spatial scales. To provide accurate estimates of POC concentration from satellite ocean color data requires algorithms that are well validated, with uncertainties characterized. Here, a number of algorithms to derive POC using different optical variables are applied to merged satellite ocean color data provided by the Ocean Color Climate Change Initiative (OC-CCI) and validated against the largest database of in situ POC measurements currently available. The results of this validation exercise indicate satisfactory levels of performance from several algorithms (highest performance was observed from the algorithms of Loisel et al., 2002; Stramski et al., 2008) and uncertainties that are within the requirements of the user community. Estimates of the standing stock of the POC can be made by applying these algorithms, and yield an estimated mixed-layer integrated global stock of POC between 0.77 and 1.3 Pg C of carbon. Performance of the algorithms vary regionally, suggesting that blending of region-specific algorithms may provide the best way forward for generating global POC products.en_US
dc.language.isoenen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.otherSatellite ocean colouren_US
dc.subject.otherParticulate organic carbonen_US
dc.subject.otherAlgorithmsen_US
dc.subject.otherBio-optical algorithmsen_US
dc.subject.otherEssential climate variables (ECV)en_US
dc.titleValidation and Intercomparison of Ocean Color Algorithms for Estimating Particulate Organic Carbon in the Oceans.en_US
dc.typeJournal Contributionen_US
dc.description.refereedRefereeden_US
dc.format.pagerange20pp.en_US
dc.identifier.doi10.3389/fmars.2017.00251
dc.subject.parameterDisciplineParameter Discipline::Biological oceanography::Phytoplanktonen_US
dc.subject.dmProcessesData Management Practices::Data acquisitionen_US
dc.bibliographicCitation.titleFrontiers in Marine Scienceen_US
dc.bibliographicCitation.volume4en_US
dc.bibliographicCitation.issueArticle 251en_US
dc.description.sdg14.Aen_US
dc.description.eovPhytoplankton biomass and diversityen_US
dc.description.eovParticulate matteren_US
dc.description.eovOcean colouren_US
dc.description.maturitylevelTRL 8 Actual system completed and "mission qualified" through test and demonstration in an operational environment (ground or space)en_US
dc.description.bptypeManual (incl. handbook, guide, cookbook etc)en_US
obps.contact.contactnameHayley Evers-King
obps.contact.contactemailhek@pml.ac.uk
obps.resourceurl.publisherhttps://www.frontiersin.org/articles/10.3389/fmars.2017.00251/fullen_US


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International