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dc.contributor.authorFriedrichs, Marjorie A. M.-
dc.contributor.authorCarr, Mary-Elena-
dc.contributor.authorBarber, Richard T.-
dc.contributor.authorScardi, Michele-
dc.contributor.authorAntoine, David-
dc.contributor.authorArmstrong, Robert A.-
dc.contributor.authorAsanuma, Ichio-
dc.contributor.authorBehrenfeld, Michael J.-
dc.contributor.authorBuitenhuis, Erik T.-
dc.contributor.authorChai, Fei-
dc.contributor.authorChristian, James R.-
dc.contributor.authorCiotti, Aurea M.-
dc.contributor.authorDoney, Scott C.-
dc.contributor.authorDowell, Mark-
dc.contributor.authorDunne, John-
dc.contributor.authorGentili, Bernard-
dc.contributor.authorGregg, Watson-
dc.contributor.authorHoepffner, Nicolas-
dc.contributor.authorIshizaka, Joji-
dc.contributor.authorKameda, Takahiko-
dc.contributor.authorLima, Ivan-
dc.contributor.authorMarra, John-
dc.contributor.authorMelin, Frederic-
dc.contributor.authorMoore, J. Keith-
dc.contributor.authorMorel, Andre-
dc.contributor.authorO'Malley, Robert T.-
dc.contributor.authorO'Reilly, Jay-
dc.contributor.authorSaba, Vincent S.-
dc.contributor.authorSchmeltz, Marjorie-
dc.contributor.authorSmyth, Tim J.-
dc.contributor.authorTjiputra, Jerry-
dc.contributor.authorWaters, Kirk-
dc.contributor.authorWestberry, Toby K.-
dc.contributor.authorWinguth, Arne-
dc.date.accessioned2014-05-20T15:32:26Z-
dc.date.accessioned2016-10-25T18:08:40Z-
dc.date.available2014-05-20T15:32:26Z-
dc.date.available2016-10-25T18:08:40Z-
dc.date.issued2009-02-20-
dc.identifierhttp://dx.doi.org/10.1016/j.jmarsys.2008.05.010-
dc.identifier.citationJournal of Marine Systems. Amsterdam: Elsevier B.V., v. 76, n. 1-2, p. 113-133, 2009.-
dc.identifier.issn0924-7963-
dc.identifier.urihttp://hdl.handle.net/11449/41342-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/41342-
dc.description.abstractDepth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BCGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of similar to 1000 C-14 measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PR specifically yielding too few low PP (< 0.2 g Cm-2 d(-1)) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomassnormalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140 degrees W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill. (C) 2008 Elsevier BY. All rights reserved.en
dc.format.extent113-133-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.sourceWeb of Science-
dc.subjectPrimary productionen
dc.subjectModelingen
dc.subjectRemote sensingen
dc.subjectSatellite ocean coloren
dc.subjectStatistical analysisen
dc.subjectTropical Pacific Ocean (15 degrees N to 15 degrees S and 125 degrees Een
dc.subjectto 95 degrees W)en
dc.titleAssessing the uncertainties of model estimates of primary productivity in the tropical Pacific Oceanen
dc.typeoutro-
dc.contributor.institutionVirginia Inst Marine Sci-
dc.contributor.institutionCALTECH-
dc.contributor.institutionDuke Univ-
dc.contributor.institutionUniv Roma Tor Vergata-
dc.contributor.institutionUniv Paris 06-
dc.contributor.institutionCNRS-
dc.contributor.institutionSUNY Stony Brook-
dc.contributor.institutionTokyo Univ Informat Sci-
dc.contributor.institutionOregon State Univ-
dc.contributor.institutionUniv E Anglia-
dc.contributor.institutionUniv Maine-
dc.contributor.institutionFisheries & Oceans Canada-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionWoods Hole Oceanog Inst-
dc.contributor.institutionCommiss European Communities-
dc.contributor.institutionGeophys Fluid Dynam Lab-
dc.contributor.institutionNASA-
dc.contributor.institutionNagasaki Univ-
dc.contributor.institutionNatl Res Inst Far Seas Fisheries-
dc.contributor.institutionCUNY Brooklyn Coll-
dc.contributor.institutionUniv Calif Irvine-
dc.contributor.institutionNOAA NMFS Narragansett Lab-
dc.contributor.institutionPlymouth Marine Lab-
dc.contributor.institutionBjerknes Ctr Climate Res-
dc.contributor.institutionNOAA Coastal Serv Ctr-
dc.contributor.institutionUniv Texas Arlington-
dc.description.affiliationVirginia Inst Marine Sci, Coll William & Mary, Gloucester Point, VA 23062 USA-
dc.description.affiliationCALTECH, Jet Prop Lab, Pasadena, CA 91101 USA-
dc.description.affiliationDuke Univ, Marine Lab, Beaufort, NC 28516 USA-
dc.description.affiliationUniv Roma Tor Vergata, Dept Biol, I-00133 Rome, Italy-
dc.description.affiliationUniv Paris 06, Paris 6, France-
dc.description.affiliationCNRS, Lab Oceanog Villefranche, Paris, France-
dc.description.affiliationSUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA-
dc.description.affiliationTokyo Univ Informat Sci, Wakaba Ku, Chiba 2658501, Japan-
dc.description.affiliationOregon State Univ, Dept Bot & Plant Pathol, Corvallis, OR 97331 USA-
dc.description.affiliationUniv E Anglia, Lab Global Marine & Atmospher Chem, Sch Environm Sci, Norwich NR4 7TJ, Norfolk, England-
dc.description.affiliationUniv Maine, Sch Marine Sci, Orono, ME 04469 USA-
dc.description.affiliationFisheries & Oceans Canada, Sidney, BC V8L 4B2, Canada-
dc.description.affiliationUniv Estadual Paulista, BR-11330900 São Paulo, Brazil-
dc.description.affiliationWoods Hole Oceanog Inst, Dept Marine Chem & Geochem, Woods Hole, MA 02543 USA-
dc.description.affiliationCommiss European Communities, Joint Res Ctr, I-21020 Ispra, Italy-
dc.description.affiliationGeophys Fluid Dynam Lab, Princeton, NJ 08540 USA-
dc.description.affiliationNASA, Goddard Space Flight Ctr, Global Modeling & Assimilat Off, Greenbelt, MD 20771 USA-
dc.description.affiliationNagasaki Univ, Fac Fisheries, Nagasaki 8528521, Japan-
dc.description.affiliationNatl Res Inst Far Seas Fisheries, Grp Oceanog, Shizuoka 4248633, Japan-
dc.description.affiliationCUNY Brooklyn Coll, Dept Geol, Brooklyn, NY 11210 USA-
dc.description.affiliationUniv Calif Irvine, Dept Earth Syst Sci, Irvine, CA 92697 USA-
dc.description.affiliationNOAA NMFS Narragansett Lab, Narragansett, RI 02887 USA-
dc.description.affiliationPlymouth Marine Lab, Plymouth PL1 3DH, Devon, England-
dc.description.affiliationBjerknes Ctr Climate Res, N-5007 Bergen, Norway-
dc.description.affiliationNOAA Coastal Serv Ctr, Charleston, SC 29405 USA-
dc.description.affiliationUniv Texas Arlington, Dept Earth & Environm Sci, Arlington, TX 76019 USA-
dc.description.affiliationUnespUniv Estadual Paulista, BR-11330900 São Paulo, Brazil-
dc.identifier.doi10.1016/j.jmarsys.2008.05.010-
dc.identifier.wosWOS:000263851000009-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofJournal of Marine Systems-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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