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\begin{document}

\title{High resolution variability of the ocean carbon sink}



\author[1]{Luke Gregor}%
\author[2]{Jamie Shutler}%
\author[3]{Nicolas Gruber}%
\affil[1]{ETH Zurich}%
\affil[2]{University of Exeter}%
\affil[3]{ETH Zürich}%


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  \date{May 24, 2024}


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\begin{abstract}
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\selectlanguage{ngerman}°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 (\textasciitilde{}19 \selectlanguage{greek}µ\selectlanguage{english}atm) but improves it in the coastal ocean.
Although global ocean CO2 uptake differs little, the 8D product captures
15\textbackslash{}\% 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 \selectlanguage{greek}µ\selectlanguage{english}atm 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.%
\end{abstract}%



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