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A comprehensive analysis of air-sea CO2 flux uncertainties constructed from surface ocean data products
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  • Daniel J Ford,
  • Josh Blannin,
  • Jennifer Watts,
  • Andrew Watson,
  • Peter Landschützer,
  • Annika Jersild,
  • Jamie Shutler
Daniel J Ford
University of Exeter

Corresponding Author:[email protected]

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Josh Blannin
Met Office
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Jennifer Watts
University of Exeter Cornwall Campus
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Andrew Watson
University of Exeter
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Peter Landschützer
Flanders Marine Institute
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Annika Jersild
Max Planck Institute for Meteorology
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Jamie Shutler
University of Exeter
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Increasing anthropogenic CO2 emissions to the atmosphere are partially sequestered into the global oceans through the air-sea exchange of CO2 and its subsequent movement to depth, and this collective large-scale absorption is commonly referred to as the global ocean carbon sink. Quantifying this ocean carbon sink provides a key component for closing the global carbon budget which is used to inform and guide policy decisions. These estimates are typically accompanied by an uncertainty budget built by selecting what are perceived as critical uncertainty components based on selective experimentation. However, there is a growing realisation that these budgets are incomplete and may be underestimated, which limits their power as a constraint within global budgets. In this study, we present a methodology for quantifying spatially and temporally varying uncertainties in the air-sea CO2 flux calculations and data that allows an exhaustive assessment of all known sources of uncertainties, including decorrelation length scales between gridded measurements, and the approach follows standard uncertainty propagation methodologies. The resulting standard uncertainties are higher than previously suggested budgets, but the components are consistent with previous work, and they identify how the significance and importance of key uncertainty components change in space and time. For an exemplar method (the UEP-FNN-U method) the work identifies that we can currently estimate the annual ocean carbon sink to an accuracy of ±0.72PgCyr-1 (1 standard deviation uncertainty). Due to this method having been built on established uncertainty propagation and approaches, it appears applicable to all data-product assessments of the ocean carbon sink.
30 Mar 2024Submitted to ESS Open Archive
01 Apr 2024Published in ESS Open Archive