The project team have now released the large river flow dataset that was developed and evaluated within their previous work and project called OceanSODA. These data were optimally produced by evaluating all existing empirical algorithms (for estimating surface water alkalinity and dissolved inorganic carbon in large river plumes) in conjunction with all available satellite observations and re-analysis data products. Following their extensive evaluation, these optimal datasets can now be used to quantify the temporal and spatial mixing of the Amazon and Congo river outflows and they show how the pH of these waters changes through time and space.
This work (Sims et al., 2022) is now in peer review with the journal Earth System Science Data.
Figure 1:
Seasonally averaged DIC for the Amazon plume region in (a) January to March (b) April to June (c) July to September (d) October to December. Land outlines are shown in beige. Ocean regions out of bounds or where there was no algorithm output are left white. Algorithm data below 1600 μmolkg-1 at the river outflows is shown in mint green. The mouths of the Amazon, Orinoco and Maroni Rivers are labelled.
Reference
Sims, R. P., Holding, T. M., Land, P. E., Piolle, J.-F., Green, H. L., and Shutler, J. D.: OceanSODA-UNEXE (2022) A multi-year gridded Amazon and Congo River outflow surface ocean carbonate system dataset, Earth System Science Data Discussions. https://doi.org/10.5194/essd-2022-294, in review.