A new method to estimate the dissolved organic carbon concentration from remote sensing in the global open ocean

The Dissolved Organic Carbon (DOC) represents the largest organic carbon reservoir in ocean. Therefore, describing its spatio-temporal distribution is crucial for better understanding global cycle. Recent studies have demonstrated possibility to determine DOC coastal waters from ocean color radiometry (OCR) based on strong correlation with absorption coefficient of Colored Matter (acdom(λ)). However, open ocean, CDOM relationship highly variable as they present different sources, sinks, and kinetics. Here we a new approach estimating over an Artificial Neural Network (ANN) algorithm. This model accounts i) Optical Water Classes (OWC) ii) sea surface temperature (SST), mixed layer depth (MLD), acdom(443), chlorophyll-a (Chl-a) concentration, iii) time lags depending input parameter. satellite estimated this good agreement situ measurements (MAPD = 7.04%), while spatial patterns follow former observations outputs. A sensitivity analysis has shown that main descriptors assess at given oligotrophic mesotrophic are SST one week before, acdom(443) two weeks before; Chl-a before additional parameter more productive waters. study allows first assessment contribution particulate (POC) total (TOC) POC/TOC ratio value varies between 1.31% 9.07%, mean about 4.57 ± 1.87%.