A Color-Index-Based Empirical Algorithm for Determining Particulate Organic Carbon Concentration in The Ocean From Satellite Observations

An empirical algorithm for estimating particulate organic carbon (POC) concentration in the surface ocean from satellite observations is formulated and validated using in situ POC data and remote-sensing reflectance ( R _rs ) data obtained from match-up satellite ocean color measurements. The algorithm builds upon the band-difference algorithm concept, which was originally developed for estimating chlorophyll-a concentration in clear waters. This algorithm utilizes three spectral bands centered approximately at 490, 550, and 670 nm to determine a color index (CI _POC ), from which POC can be estimated from satellite measurements. For comparison, the blue-green band-ratio algorithm is also formulated using the same data set of in situ POC and satellite-derived R _rs . Results show that the statistical parameters characterizing the differences between the satellite-derived POC and matchup in situ POC are similar when the CI _POC and band ratio algorithms are applied to open ocean waters where the values of CI _POC are relatively low. In coastal waters where the values of CI _POC are generally higher, the statistical parameters of algorithm performance are better for the CI _POC algorithm. In addition, because the CI _POC algorithm is less sensitive to errors and noise in the satellite-derived R _rs , the image quality obtained with this algorithm can be improved for both open-ocean and coastal waters.