This global dissolved organic carbon (DOC) dataset contains monthly DOC concentrations between 2010-2018 at 9km resolution. By using in-situ data set from Hansell et al. 2021 a random forest regression model for near surface ocean DOC is trained. The model uses Ocean colour Earth observation reflectance, primary production, SST, salinity and geographical information as predictors. The model has been used to produce monthly global marine DOC for years 2010-2019 using global monthly version of the predictors, namely Ocean Colour CCI , PP, Salinity CCI and SST. The work has been done as a part of ESA funded BICEP project (2020-2023).

The ESA Ocean Colour CCI project has produced global, level 3, binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies. This dataset contains their Version 5.0 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites) covering the period 1997 - 2020. Note, the chlorophyll-a data are also included in the 'All Products' dataset. This data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)