Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT

Página do item simplificado
dc.contributor.authorSaba, Vincent S.
dc.contributor.authorFriedrichs, Marjorie A. M.
dc.contributor.authorCarr, Mary-Elena
dc.contributor.authorAntoine, David
dc.contributor.authorArmstrong, Robert A.
dc.contributor.authorAsanuma, Ichio
dc.contributor.authorAumont, Olivier
dc.contributor.authorBates, Nicholas R.
dc.contributor.authorBehrenfeld, Michael J.
dc.contributor.authorBennington, Val
dc.contributor.authorBopp, Laurent
dc.contributor.authorBruggeman, Jorn
dc.contributor.authorBuitenhuis, Erik T.
dc.contributor.authorChurch, Matthew J.
dc.contributor.authorCiotti, Aurea M. [UNESP]
dc.contributor.authorDoney, Scott C.
dc.contributor.authorDowell, Mark
dc.contributor.authorDunne, John
dc.contributor.authorDutkiewicz, Stephanie
dc.contributor.authorGregg, Watson
dc.contributor.authorHoepffner, Nicolas
dc.contributor.authorHyde, Kimberly J. W.
dc.contributor.authorIshizaka, Joji
dc.contributor.authorKameda, Takahiko
dc.contributor.authorKarl, David M.
dc.contributor.authorLima, Ivan
dc.contributor.authorLomas, Michael W.
dc.contributor.authorMarra, John
dc.contributor.authorMcKinley, Galen A.
dc.contributor.authorMelin, Frederic
dc.contributor.authorMoore, J. Keith
dc.contributor.authorMorel, Andre
dc.contributor.authorO'Reilly, John
dc.contributor.authorSalihoglu, Baris
dc.contributor.authorScardi, Michele
dc.contributor.authorSmyth, Tim J.
dc.contributor.authorTang, Shilin
dc.contributor.authorTjiputra, Jerry
dc.contributor.authorUitz, Julia
dc.contributor.authorVichi, Marcello
dc.contributor.authorWaters, Kirk
dc.contributor.authorWestberry, Toby K.
dc.contributor.authorYool, Andrew
dc.contributor.institutionUniv Paris 06
dc.contributor.institutionSUNY Stony Brook
dc.contributor.institutionTokyo Univ Informat Sci
dc.contributor.institutionUPMC
dc.contributor.institutionBermuda Inst Ocean Sci
dc.contributor.institutionOregon State Univ
dc.contributor.institutionUniv Wisconsin
dc.contributor.institutionUVSQ
dc.contributor.institutionVrije Univ Amsterdam
dc.contributor.institutionUniv E Anglia
dc.contributor.institutionColumbia University
dc.contributor.institutionUniv Hawaii Manoa
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionWoods Hole Oceanog Inst
dc.contributor.institutionCommiss European Communities
dc.contributor.institutionNOAA
dc.contributor.institutionMIT
dc.contributor.institutionVirginia Inst Marine Sci
dc.contributor.institutionNASA
dc.contributor.institutionNagoya Univ
dc.contributor.institutionNatl Res Inst Far Seas Fisheries
dc.contributor.institutionCUNY Brooklyn Coll
dc.contributor.institutionUniv Calif Irvine
dc.contributor.institutionMiddle E Tech Univ
dc.contributor.institutionUniv Roma Tor Vergata
dc.contributor.institutionPlymouth Marine Lab
dc.contributor.institutionFisheries & Oceans Canada
dc.contributor.institutionUniv Bergen
dc.contributor.institutionUniv Calif San Diego
dc.contributor.institutionCtr Euro Mediterraneo & Cambiamenti Climatici
dc.contributor.institutionNatl Oceanog Ctr
dc.date.accessioned2014-05-20T15:33:19Z
dc.date.available2014-05-20T15:33:19Z
dc.date.issued2010-09-15
dc.description.abstractThe performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ (14)C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-alpha was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-alpha time series were available.en
dc.description.affiliationUniv Paris 06, Lab Oceanog Villefranche, UMR 7093, CNRS, F-06238 Villefranche Sur Mer, France
dc.description.affiliationSUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA
dc.description.affiliationTokyo Univ Informat Sci, Chiba 2658501, Japan
dc.description.affiliationUPMC, Lab Oceanog Experimentat & Approche Numer, IPSL, IRD,CNRS,Ctr IRD Bretagne, F-29280 Plouzane, France
dc.description.affiliationBermuda Inst Ocean Sci, St Georges GE01, Bermuda
dc.description.affiliationOregon State Univ, Dept Bot & Plant Pathol, Corvallis, OR 97331 USA
dc.description.affiliationUniv Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI 53706 USA
dc.description.affiliationUVSQ, Lab Sci Climat & Environm, IPSL, CEA,CNRS,CEN Saclay, F-91191 Gif Sur Yvette, France
dc.description.affiliationVrije Univ Amsterdam, Dept Theoret Biol, Fac Earth & Life Sci, NL-1081 HV Amsterdam, Netherlands
dc.description.affiliationUniv E Anglia, Lab Global Marine & Atmospher Chem, Sch Environm Sci, Norwich NR4 7TJ, Norfolk, England
dc.description.affiliationColumbia Univ, Columbia Climate Ctr, Earth Inst, New York, NY 10027 USA
dc.description.affiliationUniv Hawaii Manoa, Dept Oceanog, Sch Ocean & Earth Sci & Technol, Honolulu, HI 96822 USA
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.affiliationNOAA, Geophys Fluid Dynam Lab, Princeton, NJ 08540 USA
dc.description.affiliationMIT, Cambridge, MA 02139 USA
dc.description.affiliationVirginia Inst Marine Sci, Coll William & Mary, Gloucester Point, VA 23062 USA
dc.description.affiliationNASA, Global Modeling & Assimilat Off, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
dc.description.affiliationNOAA, Natl Marine Fisheries Serv, Narragansett Lab, Narragansett, RI 02882 USA
dc.description.affiliationNagoya Univ, Hydrospher Atmospher Res Ctr, Chikusa Ku, Nagoya, Aichi 4648601, 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.affiliationMiddle E Tech Univ, Inst Marine Sci, TR-33731 Erdemli Mersin, Turkey
dc.description.affiliationUniv Roma Tor Vergata, Dept Biol, I-00133 Rome, Italy
dc.description.affiliationPlymouth Marine Lab, Plymouth PL1 3DH, Devon, England
dc.description.affiliationFisheries & Oceans Canada, Inst Freshwater, Winnipeg, MB R3T 2N6, Canada
dc.description.affiliationUniv Bergen, Inst Geophys, N-5007 Bergen, Norway
dc.description.affiliationUniv Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92093 USA
dc.description.affiliationCtr Euro Mediterraneo & Cambiamenti Climatici, Ist Nazl Geofis & Vulcanol, I-40127 Bologna, Italy
dc.description.affiliationNOAA, Coastal Serv Ctr, Charleston, SC 29405 USA
dc.description.affiliationNatl Oceanog Ctr, Southampton SO14 3ZH, Hants, England
dc.description.affiliationUnespUniv Estadual Paulista, BR-11330900 São Paulo, Brazil
dc.description.sponsorshipNational Aeronautics and Space Agency
dc.description.sponsorshipIdNASA: NNG06GA03G
dc.format.extent21
dc.identifierhttp://dx.doi.org/10.1029/2009GB003655
dc.identifier.citationGlobal Biogeochemical Cycles. Washington: Amer Geophysical Union, v. 24, p. 21, 2010.
dc.identifier.doi10.1029/2009GB003655
dc.identifier.issn0886-6236
dc.identifier.urihttp://hdl.handle.net/11449/41985
dc.identifier.wosWOS:000282010300001
dc.language.isoeng
dc.publisherAmer Geophysical Union
dc.relation.ispartofGlobal Biogeochemical Cycles
dc.relation.ispartofjcr4.457
dc.relation.ispartofsjr3,217
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.titleChallenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOTen
dc.typeResumo
dcterms.licensehttp://informahealthcare.com/page/resources/authors
dcterms.rightsHolderAmer Geophysical Union

Arquivos

Licença do Pacote
Agora exibindo 1 - 2 de 2
Nenhuma Miniatura disponível
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição:
Nenhuma Miniatura disponível
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição:

Coleções

Artigos