Preprints
https://doi.org/10.5194/essd-2022-294
https://doi.org/10.5194/essd-2022-294
 
02 Sep 2022
02 Sep 2022
Status: this preprint is currently under review for the journal ESSD.

OceanSODA-UNEXE: A multi-year gridded Amazon and Congo River outflow surface ocean carbonate system dataset

Richard Peter Sims1, Thomas Mitchell Holding2, Peter E. Land3, Jean-Francois Piolle4, Hannah Louise Green1,3, and Jamie D. Shutler1 Richard Peter Sims et al.
  • 1Centre for Geography and Environmental Science, College of Life and Environmental Sciences, University of Exeter, Penryn campus, United Kingdom
  • 2Department of Human Behaviour, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, 04103, Germany
  • 3Plymouth Marine Laboratory, Plymouth, PL13DH, United Kingdom
  • 4Laboratoire d'Océanographie Physique et Spatiale (LOPS), IFREMER, Université of Brest, CNRS, IRD, IUEM, Brest, France

Abstract. Large rivers play an important role in transferring water and all of its constituents including carbon in its various forms from the land to the ocean, but the seasonal and inter-annual variations in these riverine flows remain unclear. Satellite Earth observation datasets and reanalysis products can now be used to observe synoptic-scale spatial and temporal variations in the carbonate system within large river outflows. Here we present the OceanSODA-UNEXE time series, a dataset of the full carbonate system in the surface water outflows of the Amazon (2010–2020) and Congo Rivers (2002–2016). Optimal empirical approaches were used to generate gridded Total alkalinity (TA) and dissolved inorganic carbon (DIC) fields in the outflow regions. These combinations were determined by equitably evaluating all combinations of algorithms and inputs against a matchup database of in situ observations. Gridded TA and DIC along with gridded temperature and salinity data enable the calculation of the full carbonate system in the surface ocean. The algorithm evaluation constitutes a Type A uncertainty evaluation for TA and DIC where model, input and sampling uncertainties are considered. Total combined uncertainties for TA and DIC were propagated through the carbonate system calculation allowing all variables to be provided with an associated uncertainty estimate. In the Amazon outflow, the total combined uncertainty for TA was identified as 36 μmol kg−1 (weighted RMSD 35 μmol kgkg−1 and weighted bias 8 μmol kg−1 for n=82) and for DIC was 44 μmol kg−1 (weighted RMSD 44 μmol kg−1 and weighted bias −6 μmol kg−1 for n=70). The spatially averaged propagated uncertainties for the partial pressure of carbon dioxide (pCO2) and pH are 85 μatm and 0.08 respectively, where the pH uncertainty is relative to an average pH of 8.19. In the Congo outflow, the combined uncertainty for TA was identified as 29 μmol kg−1 (weighted RMSD 28 μmol kg−1and weighted bias 6 μmol kg−1 for n=102) and for DIC was 40 μmol kg−1 (weighted RMSD 37 μmol kg−1and weighted bias −16 μmol kg−1 for n=77). The spatially averaged propagated uncertainties for pCO2 and pH are 74 μatm and 0.08 respectively, where the pH uncertainty is relative to an average pH of 8.21. The combined uncertainties in TA and DIC in the Amazon and Congo outflows are lower than the natural variability their respective regions allowing the time varying regional variability to be evaluated. Potential uses of these data would be for assessing the spatial and temporal flow of carbon from the Amazon and Congo rivers into the Atlantic and for assessing the riverine driven carbonate system variations experienced by tropical reefs within the outflow regions.

Richard Peter Sims et al.

Status: open (until 28 Oct 2022)

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Richard Peter Sims et al.

Data sets

OceanSODA-UNEXE: Gridded surface ocean carbonate system datasets in the Amazon and Congo River outflows Sims, Richard P; Holding, Thomas; Land, Peter Edward; Piolle, Jean-Francois; Green, Hannah; Shutler, Jamie D https://doi.pangaea.de/10.1594/PANGAEA.946888

Model code and software

OceanSODA model code Richard Sims, Thomas Holding https://github.com/Richard-Sims/OceanSODA

Richard Peter Sims et al.

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Short summary
The flow of carbon between the land and ocean is poorly quantified with existing measurements. It is not clear how seasonality and long term variability impact this flow of carbon. Here we demonstrate how satellite observations can be used to create decadal timeseries of the inorganic carbonate system in the Amazon and Congo River outflows.