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dc.contributor.authorTorres, R
dc.contributor.authorArtioli, Y
dc.contributor.authorKitidis, V
dc.contributor.authorCiavatta, S
dc.contributor.authorRuiz-Villarreal, M
dc.contributor.authorShutler, J
dc.contributor.authorPolimene, L
dc.contributor.authorMartinez, V
dc.contributor.authorWiddicombe, C
dc.contributor.authorWoodward, EMS
dc.contributor.authorSmyth, T
dc.contributor.authorFishwick, J
dc.contributor.authorTilstone, GH
dc.date.accessioned2020-07-30T13:22:44Z
dc.date.issued2020-06-25
dc.description.abstractThis work evaluates the sensitivity of CO2 air–sea gas exchange in a coastal site to four different model system configurations of the 1D coupled hydrodynamic–ecosystem model GOTM–ERSEM, towards identifying critical dynamics of relevance when specifically addressing quantification of air–sea CO2 exchange. The European Sea Regional Ecosystem Model (ERSEM) is a biomass and functional group-based biogeochemical model that includes a comprehensive carbonate system and explicitly simulates the production of dissolved organic carbon, dissolved inorganic carbon and organic matter. The model was implemented at the coastal station L4 (4 nm south of Plymouth, 50°15.00’N, 4°13.02’W, depth of 51 m). The model performance was evaluated using more than 1500 hydrological and biochemical observations routinely collected at L4 through the Western Coastal Observatory activities of 2008–2009. In addition to a reference simulation (A), we ran three distinct experiments to investigate the sensitivity of the carbonate system and modeled air–sea fluxes to (B) the sea-surface temperature (SST) diurnal cycle and thus also the near-surface vertical gradients, (C) biological suppression of gas exchange and (D) data assimilation using satellite Earth observation data. The reference simulation captures well the physical environment (simulated SST has a correlation with observations equal to 0.94 with a p > 0.95). Overall, the model captures the seasonal signal in most biogeochemical variables including the air–sea flux of CO2 and primary production and can capture some of the intra-seasonal variability and short-lived blooms. The model correctly reproduces the seasonality of nutrients (correlation > 0.80 for silicate, nitrate and phosphate), surface chlorophyll-a (correlation > 0.43) and total biomass (correlation > 0.7) in a two year run for 2008–2009. The model simulates well the concentration of DIC, pH and in-water partial pressure of CO2 (pCO2) with correlations between 0.4–0.5. The model result suggest that L4 is a weak net source of CO2 (0.3–1.8 molCm−2 year−1). The results of the three sensitivity experiments indicate that both resolving the temperature profile near the surface and assimilation of surface chlorophyll-a significantly impact the skill of simulating the biogeochemistry at L4 and all of the carbonate chemistry related variables. These results indicate that our forecasting ability of CO2 air–sea flux in shelf seas environments and their impact in climate modeling should consider both model refinements as means of reducing uncertainties and errors in any future climate projections.en_GB
dc.description.sponsorshipEuropean Space Agencyen_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.description.sponsorshipUK National Centre for Earth Observationen_GB
dc.description.sponsorshipEuropean Unionen_GB
dc.identifier.citationVol. 12 (12), article 2038en_GB
dc.identifier.doi10.3390/rs12122038
dc.identifier.grantnumberBB/M019748/1en_GB
dc.identifier.grantnumber4000104762/11/I-AMen_GB
dc.identifier.grantnumber07-027-FR-ISECAen_GB
dc.identifier.urihttp://hdl.handle.net/10871/122254
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectdata assimilationen_GB
dc.subject1D ecosystem modelen_GB
dc.subjectCO2en_GB
dc.subjectair–sea gas exchangeen_GB
dc.titleSensitivity of Modeled CO2 Air–Sea Flux in a Coastal Environment to Surface Temperature Gradients, Surfactants, and Satellite Data Assimilationen_GB
dc.typeArticleen_GB
dc.date.available2020-07-30T13:22:44Z
dc.descriptionThis is the final version. Available on open access from MDPI via the DOI in this recorden_GB
dc.identifier.eissn2072-4292
dc.identifier.journalRemote Sensingen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-06-22
exeter.funder::European Space Agencyen_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-06-22
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-07-30T13:18:24Z
refterms.versionFCDVoR
refterms.dateFOA2020-07-30T13:22:54Z
refterms.panelCen_GB


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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).