Improved winter data coverage of the Southern Ocean CO2 sink from extrapolation of summertime observations

Uncertainties in the CO2 flux in the Southern Ocean, produced by a lack of direct wintertime observations, can be addressed by a combination of pseudo observations and neural network machine learning-based mapping. 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 pCO(2) 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 degrees S, consistent with independent estimates from atmospheric data.