Estimating and Monitoring Dissolved Organic Carbon (DOC) Concentrations from Space across the Global Ocean

Effective monitoring of Dissolved Organic Carbon (DOC) from space is crucial for tracking carbon stocks and understanding fluctuations in both coastal and open ocean environments. As part of the OCROC project, founded by the Copernicus Marine Service, we have enhanced the existing Ocean and Land Color Instrument (OLCI) DOC algorithm, designed to leverage data from both historical and current ocean color sensors. This algorithm initially used four key inputs: the absorption coefficient of Colored Dissolved Organic Matter (a_cdom), chlorophyll-a concentration, Sea Surface Temperature (SST), and Mixed Layer Depth (MLD), each at varied time lags to account for water mass dynamics.

Our updated version introduces two optimized Artificial Neural Network models, a specialized approach for coastal areas affected by terrestrial influences, and reanalysis data for SST and MLD from COPERNICUS. We also assess the algorithm's adaptability for MODIS and VIIRS missions, requiring wavelength adjustments to ensure accurate a_cdom estimation—a process undergoing further calibration. By incorporating MODIS and VIIRS data, we aim to expand our dataset significantly, creating a new baseline for the algorithm.

The final weekly DOC product, spanning from 1998 to 2022 with a 4 km resolution, is available for community evaluation and feedback. This dataset supports in-depth studies of DOC variations, the identification of significant spatial and temporal patterns, and long-term time series analyses and tendencies, thereby advancing our understanding of carbon dynamics in coastal and open ocean waters.