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High resolution variability of the ocean carbon sink
  • Luke Gregor,
  • Jamie Shutler,
  • Nicolas Gruber
Luke Gregor
ETH Zurich

Corresponding Author:[email protected]

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Jamie Shutler
University of Exeter
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Nicolas Gruber
ETH Zürich
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Measurements of the surface ocean fugacity of carbon dioxide (fCO2) provide an important constraint on the global ocean carbon sink, yet the gap filling products developed so far to cope with the sparse observations are relatively coarse (1°x1° by 1 month). Here, we overcome this limitation by using the newly developed surface Ocean Carbon dioxide Neural Network (OceanCarbNN) method to estimate surface ocean fCO2 and the associated air sea CO2 fluxes (FCO2) at a resolution of 8-daily by 0.25°x0.25° (8D) over the period 1982 through 2022. The method reconstructs fCO2 with accuracy like that of low-resolution methods (~19 µatm) but improves it in the coastal ocean. Although global ocean CO2 uptake differs little, the 8D product captures 15\% more variance in FCO2. Most of this increase comes from the better-represented subseasonal scale variability, which is largely driven by the better resolved variability of the winds, but also contributed to by the better resolved fCO2. The high-resolution fCO2 is also able to capture the signal of short-lived regional events such as coastal upwelling and hurricanes. For example, the 8D product reveals that fCO2 was at least 25 µatm lower in the wake of Hurricane Maria (2017), the result of a complex interplay between the decrease in temperature, the entrainment of carbon-rich waters, and an increase in primary production. By providing new insights into the role of higher frequency variations of the ocean carbon sink and the underlying processes, the 8D product fills an important gap.
02 Feb 2024Submitted to ESS Open Archive
02 Feb 2024Published in ESS Open Archive