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Improved winter data coverage of the Southern Ocean CO2 sink from extrapolation of summertime observations
Mackay, N.; Watson, A.J.; Suntharalingam, P.; Chen, Z.; Landschützer, P. (2022). Improved winter data coverage of the Southern Ocean CO2 sink from extrapolation of summertime observations. Commun. Earth Environ. 3(1): 265. https://dx.doi.org/10.1038/s43247-022-00592-6
In: Communications Earth & Environment. Springer Nature: London. e-ISSN 2662-4435
Related to:
Mackay, N.; Watson, J.; Suntharalingam, P.; Chen, H.; Landschutzer, P. (2022). Author Correction: Improved winter data coverage of the Southern Ocean CO2 sink from extrapolation of summertime observations. Commun. Earth Environ. 3(1): 317. https://dx.doi.org/10.1038/s43247-022-00637-w, more
Peer reviewed article  
Available in  Authors 
    Vlaams Instituut voor de Zee: Open access 384757 [ download pdf ]
Keyword
    Marine/Coastal
Authors  Top 
  • Mackay, N.
  • Watson, A.J.
  • Suntharalingam, P.
  • Chen, Z.
  • Landschützer, P.
Abstract
    The Southern Ocean is an important sink of anthropogenic CO2, but it is among the least well-observed ocean basins, and consequentially substantial uncertainties in the CO2 flux reconstruction exist. A recent attempt to address historically sparse wintertime sampling produced ‘pseudo’ wintertime observations of surface pCO2 using subsurface summertime observations south of the Antarctic Polar Front. Here, we present an estimate of the Southern Ocean CO2 sink that combines a machine learning-based mapping method with an updated set of pseudo observations that increases regional wintertime data coverage by 68% compared with the historical dataset. Our results confirm the suggestion that improved winter coverage has a modest impact on the reconstruction, slightly strengthening the uptake trend in the 2000s. After also adjusting for surface boundary layer temperature effects, we find a 2004-2018 mean sink of −0.16 ± 0.07 PgC yr−1 south of the Polar Front and −1.27 ± 0.23 PgC yr−1 south of 35°S, consistent with independent estimates from atmospheric data.
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