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dc.contributor.authorBrewin, RJW
dc.contributor.authorDall’Olmo, G
dc.contributor.authorGittings, J
dc.contributor.authorSun, X
dc.contributor.authorLange, PK
dc.contributor.authorRaitsos, DE
dc.contributor.authorBouman, HA
dc.contributor.authorHoteit, I
dc.contributor.authorAiken, J
dc.contributor.authorSathyendranath, S
dc.date.accessioned2022-04-13T06:30:08Z
dc.date.issued2022-03-18
dc.date.updated2022-04-12T20:25:17Z
dc.description.abstractWe describe an approach to partition a vertical profile of chlorophyll-a concentration into contributions from two communities of phytoplankton: one (community 1) that resides principally in the turbulent mixed-layer of the upper ocean and is observable through satellite visible radiometry; the other (community 2) residing below the mixed-layer, in a stably stratified environment, hidden from the eyes of the satellite. The approach is tuned to a time-series of profiles from a Biogeochemical-Argo float in the northern Red Sea, selected as its location transitions from a deep mixed layer in winter (characteristic of vertically well-mixed systems) to a shallow mixed layer in the summer with a deep chlorophyll-a maximum (characteristic of vertically stratified systems). The approach is extended to reproduce profiles of particle backscattering, by deriving the chlorophyll-specific backscattering coefficients of the two communities and a background coefficient assumed to be dominated by non-algal particles in the region. Analysis of the float data reveals contrasting phenology of the two communities, with community 1 blooming in winter and 2 in summer, community 1 negatively correlated with epipelagic stratification, and 2 positively correlated. We observe a dynamic chlorophyll-specific backscattering coefficient for community 1 (stable for community 2), positively correlated with light in the mixed-layer, suggesting seasonal changes in photoacclimation and/or taxonomic composition within community 1. The approach has the potential for monitoring vertical changes in epipelagic biogeography and for combining satellite and ocean robotic data to yield a three-dimensional view of phytoplankton distribution.en_GB
dc.description.sponsorshipMedical Research Council (MRC)en_GB
dc.description.sponsorshipSimons Foundation (SF)en_GB
dc.description.sponsorshipKing Abdullah University of Science and Technology (KAUST)en_GB
dc.description.sponsorshipEuropean Space Agency (ESA)en_GB
dc.description.sponsorshipEuropean Space Agency (ESA)en_GB
dc.identifier.citationVol. 127 (4), article e2021JC018195en_GB
dc.identifier.doihttps://doi.org/10.1029/2021jc018195
dc.identifier.grantnumberMR/V022792/1en_GB
dc.identifier.grantnumber549947,SSen_GB
dc.identifier.grantnumberREP/1/3268-01-01en_GB
dc.identifier.grantnumberBICEPen_GB
dc.identifier.grantnumberPOSEIDONen_GB
dc.identifier.urihttp://hdl.handle.net/10871/129369
dc.identifierORCID: 0000-0001-5134-8291 (Brewin, Robert JW)
dc.identifierScopusID: 35725269400 (Brewin, Robert JW)
dc.language.isoenen_GB
dc.publisherAmerican Geophysical Union / Wileyen_GB
dc.relation.urlhttps://github.com/rjbrewin/Two-community-phyto-modelen_GB
dc.rights© 2022. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_GB
dc.subjectphytoplanktonen_GB
dc.subjectcommunity structureen_GB
dc.subjectverticalen_GB
dc.subjectocean roboticsen_GB
dc.subjectsatelliteen_GB
dc.subjectBGC-Argoen_GB
dc.titleA conceptual approach to partitioning a vertical profile of phytoplankton biomass into contributions from two communitiesen_GB
dc.typeArticleen_GB
dc.date.available2022-04-13T06:30:08Z
dc.identifier.issn2169-9275
dc.descriptionThis is the final version. Available from American Geophysical Union / Wiley via the DOI in this record. en_GB
dc.descriptionThese data were collected and made freely available by the International Argo Program and the national programs that contribute to it (https://argo.ucsd.edu, https://www.ocean-ops.org). The Argo Program is part of the Global Ocean Observing System. All data and code used in the paper are provided openly on a GitHub page (https://github.com/rjbrewin/Two-community-phyto-model). This includes an example Jupyter Notebook Python Script, processing this BGC-Argo float and tuning the models. Details of how to run it without having to install software are provided as Supplementary Material to this manuscript.en_GB
dc.identifier.eissn2169-9291
dc.identifier.journalJournal of Geophysical Research: Oceansen_GB
dc.relation.ispartofJournal of Geophysical Research - Oceans
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-03-16
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-03-16
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-04-13T06:20:26Z
refterms.versionFCDVoR
refterms.dateFOA2022-04-13T06:30:10Z
refterms.panelCen_GB
refterms.dateFirstOnline2022-03-18


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© 2022. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's licence is described as © 2022. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.