Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations
dc.contributor.author | Ciavatta, S | |
dc.contributor.author | Brewin, RJW | |
dc.contributor.author | Skákala, J | |
dc.contributor.author | Polimene, L | |
dc.contributor.author | de Mora, L | |
dc.contributor.author | Artioli, Y | |
dc.contributor.author | Allen, JI | |
dc.date.accessioned | 2019-08-07T10:05:43Z | |
dc.date.issued | 2018-01-19 | |
dc.description.abstract | We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998–2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO 2 , impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems. | en_GB |
dc.description.sponsorship | NERC | en_GB |
dc.description.sponsorship | National Centre for Earth Observation (NCEO) | en_GB |
dc.description.sponsorship | Modelling National Capability | en_GB |
dc.description.sponsorship | Atlantic BiogeoChemical (ABC) Fluxes Project of the RAPID‐AMOC Program | en_GB |
dc.description.sponsorship | EC H2020 project “TAPAS" | en_GB |
dc.identifier.citation | Vol. 123 (2), pp. 834 - 854 | en_GB |
dc.identifier.doi | 10.1002/2017JC013490 | |
dc.identifier.uri | http://hdl.handle.net/10871/38258 | |
dc.language.iso | en | en_GB |
dc.publisher | American Geophysical Union (AGU) | en_GB |
dc.rights | (c) 2018. The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. | en_GB |
dc.subject | carbon fluxes | en_GB |
dc.subject | emergent properties | en_GB |
dc.subject | data assimilation | en_GB |
dc.subject | ecosystem model | en_GB |
dc.subject | ocean color | en_GB |
dc.subject | plankton functional types | en_GB |
dc.title | Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-08-07T10:05:43Z | |
dc.identifier.issn | 2169-9275 | |
dc.description | This is the final version. Available from American Geophysical Union (AGU) via the DOI in this record. | en_GB |
dc.identifier.journal | Journal of Geophysical Research: Oceans | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_GB |
dcterms.dateAccepted | 2017-12-28 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2018-01-19 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-08-07T09:59:56Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2019-08-07T10:05:46Z | |
refterms.panel | C | en_GB |
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Except where otherwise noted, this item's licence is described as (c) 2018. The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs
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modifications or adaptations are made.