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| Titel |
Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans |
| VerfasserIn |
D. Stramski, R. A. Reynolds, M. Babin, S. Kaczmarek, M. R. Lewis, R. Röttgers, A. Sciandra, M. Stramska, M. S. Twardowski, B. A. Franz, H. Claustre |
| 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 ; 5, no. 1 ; Nr. 5, no. 1 (2008-02-14), S.171-201 |
| Datensatznummer |
250002236
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| Publikation (Nr.) |
 copernicus.org/bg-5-171-2008.pdf |
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| Zusammenfassung |
| We have examined several approaches for estimating the surface concentration
of particulate organic carbon, POC, from optical measurements of spectral
remote-sensing reflectance, Rrs(λ), using field data
collected in tropical and subtropical waters of the eastern South Pacific and
eastern Atlantic Oceans. These approaches include a direct empirical
relationship between POC and the blue-to-green band ratio of reflectance,
Rrs(λB)/Rrs(555), and two-step algorithms
that consist of relationships linking reflectance to an inherent optical
property IOP (beam attenuation or backscattering coefficient) and POC to the
IOP. We considered two-step empirical algorithms that exclusively include
pairs of empirical relationships and two-step hybrid algorithms that consist
of semianalytical models and empirical relationships. The surface POC in our
data set ranges from about 10 mg m−3 within the South Pacific
Subtropical Gyre to 270 mg m−3 in the Chilean upwelling area, and
ancillary data suggest a considerable variation in the characteristics of
particulate assemblages in the investigated waters. The POC algorithm based
on the direct relationship between POC and
Rrs(λB)/Rrs(555) promises reasonably good
performance in the vast areas of the open ocean covering different provinces
from hyperoligotrophic and oligotrophic waters within subtropical gyres to
eutrophic coastal upwelling regimes characteristic of eastern ocean
boundaries. The best error statistics were found for power function fits to
the data of POC vs. Rrs(443)/Rrs(555) and POC
vs. Rrs(490)/Rrs(555). For our data set that
includes over 50 data pairs, these relationships are characterized by the
mean normalized bias of about 2% and the normalized root mean square error
of about 20%. We recommend that these algorithms be implemented for routine
processing of ocean color satellite data to produce maps of surface POC with
the status of an evaluation data product for continued work on algorithm
development and refinements. The two-step algorithms also deserve further
attention because they can utilize various models for estimating IOPs from
reflectance, offer advantages for developing an understanding of bio-optical
variability underlying the algorithms, and provide flexibility for regional
or seasonal parameterizations of the algorithms. |
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