Estimating Particulate Inorganic Carbon Concentrations of the Global Ocean From Ocean Color Measurements Using a Reflectance Difference Approach

A new algorithm for estimating particulate inorganic carbon (PIC) concentrations from ocean color measurements is presented. PIC plays an important role in the global carbon cycle through the oceanic carbonate pump, therefore accurate estimations of PIC concentrations from satellite remote sensing are crucial for observing changes on a global scale. An extensive global data set was created from field and satellite observations for investigating the relationship between PIC concentrations and differences in the remote sensing reflectance ( R _rs ) at green, red, and near-infrared (NIR) wavebands. Three color indices were defined: two as the relative height of R _rs (667) above a baseline running between R _rs (547) and an R _rs in the NIR (either 748 or 869 nm), and one as the difference between R _rs (547) and R _rs (667). All three color indices were found to explain over 90% of the variance in field-measured PIC. But, due to the lack of availability of R _rs (NIR) in the standard ocean color data products, most of the further analysis presented here was done using the color index determined from only two bands. The new two-band color index algorithm was found to retrieve PIC concentrations more accurately than the current standard algorithm used in generating global PIC data products. Application of the new algorithm to satellite imagery showed patterns on the global scale as revealed from field measurements. The new algorithm was more resistant to atmospheric correction errors and residual errors in sun glint corrections, as seen by a reduction in the speckling and patchiness in the satellite-derived PIC images.