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Titel |
An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe |
VerfasserIn |
V. S. Saba, M. A. M. Friedrichs, D. Antoine, R. A. Armstrong, I. Asanuma, M. J. Behrenfeld, A. M. Ciotti, M. Dowell, N. Hoepffner, K. J. W. Hyde, J. Ishizaka, T. Kameda, J. Marra, F. Mélin, A. Morel, J. O'Reilly, M. Scardi, W. O. Smith, T. J. Smyth, S. Tang, J. Uitz, K. Waters, T. K. Westberry |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1726-4170
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Digitales Dokument |
URL |
Erschienen |
In: Biogeosciences ; 8, no. 2 ; Nr. 8, no. 2 (2011-02-22), S.489-503 |
Datensatznummer |
250005454
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Publikation (Nr.) |
copernicus.org/bg-8-489-2011.pdf |
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Zusammenfassung |
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 14C 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. |
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