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Utilize este identificador para citar ou criar um link para este item: http://acervodigital.unesp.br/handle/11449/42386
Título: 
An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe
Autor(es): 
Instituição: 
  • Virginia Inst Marine Sci
  • CNRS
  • Univ Paris 06
  • SUNY Stony Brook
  • Tokyo Univ Informat Sci
  • Oregon State Univ
  • Universidade Estadual Paulista (UNESP)
  • European Commiss
  • NOAA
  • Nagoya Univ
  • Seikai Natl Fisheries Res Inst
  • CUNY
  • Univ Roma Tor Vergata
  • Plymouth Marine Lab
  • Fisheries & Oceans Canada
  • Univ Calif San Diego
ISSN: 
1726-4170
Financiador: 
National Aeronautics and Space Agency
Número do financiamento: 
NASA: NNG06GA03G
Resumo: 
Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models.
Data de publicação: 
1-Jan-2011
Citação: 
Biogeosciences. Gottingen: Copernicus Gesellschaft Mbh, v. 8, n. 2, p. 489-503, 2011.
Duração: 
489-503
Publicador: 
Copernicus Gesellschaft Mbh
Fonte: 
http://dx.doi.org/10.5194/bg-8-489-2011
Endereço permanente: 
Direitos de acesso: 
Acesso aberto
Tipo: 
outro
Fonte completa:
http://repositorio.unesp.br/handle/11449/42386
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