On which timescales do gas transfer velocities control North Atlantic CO₂ flux variability?

Abstract

The North Atlantic is an important basin for the global ocean's uptake of anthropogenic and natural carbon dioxide (CO2), but the mechanisms controlling this carbon flux are not fully understood. The air‐sea flux of CO2, F, is the product of a gas transfer velocity, k, the air‐sea CO2 concentration gradient, ΔpCO2, and the temperature‐ and salinity‐dependent solubility coefficient, α. k is difficult to constrain, representing the dominant uncertainty in F on short (instantaneous to interannual) timescales. Previous work shows that in the North Atlantic, ΔpCO2 and k both contribute significantly to interannual F variability but that k is unimportant for multidecadal variability. On some timescale between interannual and multidecadal, gas transfer velocity variability and its associated uncertainty become negligible. Here we quantify this critical timescale for the first time. Using an ocean model, we determine the importance of k, ΔpCO2, and α on a range of timescales. On interannual and shorter timescales, both ΔpCO2 and k are important controls on F. In contrast, pentadal to multidecadal North Atlantic flux variability is driven almost entirely by ΔpCO2; k contributes less than 25%. Finally, we explore how accurately one can estimate North Atlantic F without a knowledge of nonseasonal k variability, finding it possible for interannual and longer timescales. These findings suggest that continued efforts to better constrain gas transfer velocities are necessary to quantify interannual variability in the North Atlantic carbon sink. However, uncertainty in k variability is unlikely to limit the accuracy of estimates of longer‐term flux variability.

Effect of gas-transfer velocity parameterization choice on air–sea CO<sub>2</sub> fluxes in the North Atlantic Ocean and the European Arctic

“…4. The wind speeds in the North Atlantic are higher than the mean value in the world ocean (which is 7 m s −1 ; Couldrey et al, 2016), with mean values higher than 10 m s −1 in many regions of the study area in all seasons except for the summer (with the highest values in winter). This is important because the air-sea flux depends not only on average wind speed but also on its distribution (see Discussion below).…”

“…The resulting air-sea fluxes are higher in absolute terms, than all of the quadratic functions considered in this study, and are closer in value to cubic parameterization. This may mean that the bubble-mediated term of Fangohr and Woolf (2007) is overestimating the bubble component, implying the need for a dedicated calibration effort. This question will be the subject of further studies in the OceanFlux GHG Evolution project.…”

“…(7) , In addition to the purely wind-driven parameterizations, we have used the combined Goddijn-Murphy et al (2012) and Fangohr and Woolf (2007) parameterization, which was developed as a test algorithm within of OceanFlux GHG Evolution project. This parameterization separates contributions from direct-and bubble-mediated gas transfer as suggested by Woolf (2005).…”

“…To study the rate of the ocean CO 2 sink and especially its long-term trend, one needs to first constrain the uncertainty in the flux calculation. The global interannual variability in air-sea CO 2 fluxes can be about 60 % due to differences in pCO 2 and 35 % by gas-transfer velocity k parameterization (Couldrey et al, 2016). Sources of uncertainty include sampling coverage, the method of data interpolation, data quality of the fugacity of CO 2 (f CO 2 ), the method used for normalization of fugacity data to a reference year in a world of ever increasing atmospheric CO 2 , the measurement uncertainty in all the parameters used to calculate the fluxes (partial pressure in water and air, bulk and skin water temperatures, air temperatures, wind speed, etc.…”

“…as well as the choice of the gastransfer velocity k parameterization formula . It has also been identified that the choice of the wind data product provides an additional source of uncertainty in gas-transfer velocity, even by 10-40 %, and the choice of the wind speed parameterization may cause variability in k by as much as about 50 % (Gregg et al, 2014;Couldrey et al, 2016). In this work we have analysed solely the effects of the choice between various published empirical wind-driven gas-transfer parameterizations.…”