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dc.contributor.authorSun, X
dc.contributor.authorBrewin, RJW
dc.contributor.authorSathyendranath, S
dc.contributor.authorDall’Olmo, G
dc.contributor.authorAntoine, D
dc.contributor.authorBarlow, R
dc.contributor.authorBracher, A
dc.contributor.authorKheireddine, M
dc.contributor.authorLi, M
dc.contributor.authorRaitsos, DE
dc.contributor.authorShen, F
dc.contributor.authorTilstone, GH
dc.contributor.authorVellucci, V
dc.date.accessioned2024-11-18T12:55:48Z
dc.date.issued2024-11-15
dc.date.updated2024-11-18T10:55:22Z
dc.description.abstractAbstract. In the first part of this paper series (Sun et al., 2023), we developed an ecological model that partitions the total chlorophyll-a concentration (Chl-a) into three phytoplankton size classes (PSCs), pico-, nano-, and microplankton. The parameters of this model are controlled by sea surface temperature (SST), intended to capture shifts in phytoplankton size structure independently of variations in total Chl-a. In this second part of the series, we present an Ocean Colour Modelling Framework (OCMF), building on the classical Case-1 assumption, that explicitly incorporates our ecological model. The OCMF assumes the presence of the three PSCs and the existence of an independent background of non-algal particles. The framework assumes each phytoplankton group resides in a distinct optical environment, assigning chlorophyll-specific inherent optical properties to each group, both directly (phytoplankton) and indirectly (non-algal particulate and dissolved substances). The OCMF is parameterised, validated, and assessed using a large global dataset of inherent and apparent optical properties. We use the OCMF to explore the influence of variations in temperature and Chl-a on phytoplankton size structure and its resulting effects on ocean colour. We also discuss applications of the OCMF, such as its potential for inverse modelling and phytoplankton climate trend detection, which will be explored further in subsequent papers.en_GB
dc.description.sponsorshipUKRIen_GB
dc.description.sponsorshipUK National Centre for Earth Observation (NCEO)en_GB
dc.description.sponsorshipSimons Foundation Project Collaboration on Computational Biogeochemical Modeling of Marine Ecosystemsen_GB
dc.description.sponsorshipRoyal Societyen_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.description.sponsorshipDeutsche Forschungsgemeinschaften_GB
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_GB
dc.format.extent114487-114487
dc.identifier.citationVol. 316, article 114487en_GB
dc.identifier.doihttps://doi.org/10.1016/j.rse.2024.114487
dc.identifier.grantnumberMR/V022792/1en_GB
dc.identifier.grantnumber549947en_GB
dc.identifier.grantnumberIEC NSFC 211058en_GB
dc.identifier.grantnumberNE/Y005589/1en_GB
dc.identifier.grantnumber268020496–TRR 172en_GB
dc.identifier.grantnumber42076187en_GB
dc.identifier.grantnumber42271348en_GB
dc.identifier.urihttp://hdl.handle.net/10871/138673
dc.identifierORCID: 0000-0003-4855-6692 (Sun, Xuerong)
dc.identifierScopusID: 57197781816 (Sun, Xuerong)
dc.identifierORCID: 0000-0001-5134-8291 (Brewin, Robert JW)
dc.identifierScopusID: 35725269400 (Brewin, Robert JW)
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights© 2024 The Authors. Published by Elsevier Inc. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.en_GB
dc.subjectOcean colour modelling frameworken_GB
dc.subjectForward modellingen_GB
dc.subjectInherent and apparent optical propertiesen_GB
dc.subjectPhytoplankton size classesen_GB
dc.subjectOcean-colour remote sensingen_GB
dc.subjectClimate changeen_GB
dc.titleCoupling ecological concepts with an ocean-colour model: Parameterisation and forward modellingen_GB
dc.typeArticleen_GB
dc.date.available2024-11-18T12:55:48Z
dc.identifier.issn0034-4257
exeter.article-number114487
dc.descriptionThis is the final version. Available from Elsevier via the DOI in this record. en_GB
dc.descriptionData availability. Data will be made available on request.en_GB
dc.identifier.eissn1879-0704
dc.identifier.journalRemote Sensing of Environmenten_GB
dc.relation.ispartofRemote Sensing of Environment, 316
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2024-10-23
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2024-11-15
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2024-11-18T12:43:47Z
refterms.versionFCDVoR
refterms.dateFOA2024-11-18T13:00:55Z
refterms.panelBen_GB
exeter.rights-retention-statementNo.


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© 2024 The Authors. Published by Elsevier Inc. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
You are not required to obtain permission to reuse this article.
Except where otherwise noted, this item's licence is described as © 2024 The Authors. Published by Elsevier Inc. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.