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Winter data of surface ocean temperature (SST), salinity (SSS) and CO2 fugacity (fCO(2)) collected on the VOS M/V Nuka Arctica in the subpolar North Atlantic between 2004 and 2017 are used to establish trends, drivers, and interannual variability. Over the period, waters cooled and freshened, and the fCO(2) increased at a rate similar to the atmospheric CO2 growth rate. When accounting for the freshening, the inferred increase in dissolved inorganic carbon (DIC) was found to be approximately twice that expected from atmospheric CO2 alone. This is attributed to the cooling. In the Irminger Sea, fCO(2) exhibited additional interannual variations driven by atmospheric forcing through winter mixing. As winter fCO(2) in the region is close to the atmospheric, the subpolar North Atlantic has varied between being slightly supersaturated and slightly undersaturated over the investigated period.

Plain Language Summary The global oceans take up roughly a quarter of carbon dioxide (CO2) from fossil fuels and industry per year. As the emissions of CO2 increase, the amount of CO2 taken up by the oceans should increase in proportion; however, the ability of the ocean to remove CO2 from the atmosphere varies on interannual to decadal time scales. Here we assess processes that drive short-term variability and long-term trends of the subpolar North Atlantic carbon sink based on observational data obtained during winters between 2004 and 2017. We find that the subpolar North Atlantic has indeed kept pace with rising emissions over the entire period of time, which was mainly attributed to solubility-driven uptake of CO2. Year-to-year changes of the surface ocean partial pressure of CO2 can be linked to the depth of the winter mixed layer as well as atmospheric forcing. In general, the North Atlantic has shifted between a small source and a small sink of atmospheric CO2 during wintertime. Our results underline the need to maintain long-term physical, chemical, and biological observations in order monitor the ocean CO2 sink and understand the processes driving variability.