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

Abstract

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 change by more fully accounting for submonthly variability in observation-based estimates, a step closer to the roughly hourly frequencies used in models. While these data-based estimates use hourly to 6-hourly wind speeds to compute the air-sea CO2 flux, other input variables are available only at monthly resolution. Thus, they neglect high-frequency variability in key variables such as atmospheric pressure associated with synoptic events such as storms. To evaluate this error, we compare flux estimates from observational data sets with different temporal resolutions. Accounting for hourly variations in atmospheric pressure and daily variations in sea surface temperature, a data-based approach reduces the estimated global carbon uptake by 0.12 Pg C yr−1, closing 25 % of the average gap between observation-based and model estimates. This reduction results from proper accounting of the covariance between wind speed and atmospheric pressure, particularly in the southern extratropics.