Biogeosciences www.biogeosciences.net 1726-4170 1726-4189 5 1 2008 10.5194/bg-5-171-2008 http://www.biogeosciences.net/5/171/2008/ http://www.biogeosciences.net/5/171/2008/bg-5-171-2008.html http://www.biogeosciences.net/5/171/2008/bg-5-171-2008.pdf 171 201 2008-02-14 Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans D. Stramski dstramski@ucsd.edu R. A. Reynolds M. Babin S. Kaczmarek M. R. Lewis R. Röttgers A. Sciandra M. Stramska M. S. Twardowski B. A. Franz H. Claustre Marine Physical Lab., Scripps Institution of Oceanography, Univ. of California at San Diego, La Jolla, CA 92093-0238, USA CNRS, UMR 7093, Laboratoire d'Océanographie de Villefranche (LOV), 06230 Villefranche-sur-mer, France Université Pierre et Marie Curie-Paris6, UMR 7093, LOV, 06230 Villefranche-sur-mer, France Institute of Oceanology, Polish Academy of Sciences, Powstanców Warszawy 55, 81-712 Sopot, Poland Department of Oceanography, Dalhousie University, Halifax, NS, BH3 4J1, Canada Institute for Coastal Research, GKSS Research Center, Geesthacht, Max-Planck-Str., 21502 Geesthacht, Germany Center for Hydro-Optics & Remote Sensing, San Diego State Univ., 6505 Alvarado Rd., San Diego, CA 92120, USA Department of Research, WET Labs, Inc., 165 Dean Knauss Dr., Narragansett, RI 02882, USA Science Applications International Corporation, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA 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. 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