Data-based estimates of ocean carbon uptake biased high from neglect of submonthly atmospheric pressure variability

Abstract. Current estimates of the global ocean carbon sink based on measurements of CO₂ fugacity are inconsistent with those obtained from global ocean biogeochemistry models. Here we investigate how this gap might be partially closed by more fully accounting for submonthly variability in observation-based estimates. While these data-estimates compute the air-sea CO₂ flux based on hourly wind speed, other variables have only monthly resolution. Thus, they neglect high-frequency variability from short-term synoptic events such as storms for key variables such as atmospheric pressure. To evaluate this error, we compare data-based flux estimates from observational data sets having different temporal resolutions. We find that accounting for hourly variations in atmospheric pressure and daily variations in sea surface temperature in a data-based approach reduces the resulting estimate of global carbon uptake by 0.12 Pg C yr⁻¹, closing 25 % of the average gap between observation-based and model estimates. The cause is proper accounting of the covariance between wind speed and atmospheric pressure, particularly in the southern extratropics.