Surface concentration of particulate organic carbon in the ocean estimated from remote sensing reflectances
Malgorzata
Stramska, CHORS, San Diego State University, mstramska@chors.sdsu.edu
(Presenting)
We have recently examined several approaches for estimating the surface concentration of particulate organic carbon, POC, from spectral remote sensing reflectance, Rrs(lambda), using historical (Stramski et al., in preparation) and our own field data collected in the north polar Atlantic (Stramska and Stramski, 2005) and tropical and subtropical waters of the eastern South Pacific and eastern Atlantic Oceans (Stramski et al., 2007). The POC algorithms based on the direct relationship between POC and Rrs(lambda)/Rrs(555) promise reasonably good performance in the vast areas of the open ocean covering different provinces. 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). We recommend that these algorithms (Stramski et al., 2007) be implemented for routine processing of ocean color satellite data to produce maps of surface POC with the status of an evaluation data product.
In this presentation we demonstrate how POC estimates from the ten years of SeaWiFS ocean color reveal patterns of regional, seasonal, and interannual variability. Patterns of interannual POC variability are intricate as they depend on the geographic location and particular time of year considered. By comparing the results averaged globally and over selected oceanic regions we demonstrate the interannual and regional trends. In the nearest future the POC estimates from satellite remote sensing of ocean color will be used for improved understanding of oceanic POC reservoir, its dynamics, and long-term trends in POC export.
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