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

Abstract

Abstract. The oceanic sink of carbon dioxide (CO 2 ) is an important part of the global carbon budget. Understanding uncertainties in the calculation of this net flux into the ocean is crucial for climate research. One of the sources of the uncertainty within this calculation is the parameterization chosen for the CO 2 gas-transfer velocity. We used a recently developed software toolbox, called the FluxEngine , to estimate the monthly air-sea CO 2 fluxes for the extratropical North Atlantic Ocean, including the European Arctic, and for the global ocean using several published quadratic and cubic wind speed parameterizations of the gastransfer velocity. The aim of the study is to constrain the uncertainty caused by the choice of parameterization in the North Atlantic Ocean. This region is a large oceanic sink of CO 2 , and it is also a region characterized by strong winds, especially in winter but with good in situ data coverage. We show that the uncertainty in the parameterization is smaller in the North Atlantic Ocean and the Arctic than in the global ocean. It is as little as 5 % in the North Atlantic and 4 % in the European Arctic, in comparison to 9 % for the global ocean when restricted to parameterizations with quadratic wind dependence. This uncertainty becomes 46, 44, and 65 %, respectively, when all parameterizations are considered. We suggest that this smaller uncertainty (5 and 4 %) is caused by a combination of higher than global average wind speeds in the North Atlantic (> 7 ms −1 ) and lack of any seasonal changes in the direction of the flux direction within most of the region. We also compare the impact of using two different in situ pCO 2 data sets (Takahashi et al. (2009) and Surface Ocean CO 2 Atlas (SOCAT) v1.5 and v2.0, for the flux calculation. The annual fluxes using the two data sets differ by 8 % in the North Atlantic and 19 % in the European Arctic. The seasonal fluxes in the Arctic computed from the two data sets disagree with each other possibly due to insufficient spatial and temporal data coverage, especially in winter.

Wave‐Related Reynolds Number Parameterizations of CO2 and DMS Transfer Velocities

“…Wind-only k parameterizations display significant disagreement between different studies (Garbe et al, 2014;Goddijn-Murphy et al, 2012;McGillis et al, 2001;Wanninkhof, 1992). While implementing different wind-only parameterizations for CO 2 may result in comparable globally averaged gas transfer velocities, the parameterization choice was shown to have significant impact on regional fluxes (Fangohr & Woolf, 2007;Wrobel & Piskozub, 2016). In light of current efforts to include wave processes in Earth System models (e.g., Li et al, 2016;Qiao et al, 2013), it is time to update the traditional wind-only gas transfer parameterizations to sea state-dependent ones and assess uncertainties linked to the choice of parameterization.…”

The FluxEngine air–sea gas flux toolbox: simplified interface and extensions for in situ analyses and multiple sparingly soluble gases

“…While it is common to estimate gas transfer using a polynomial relationship with wind speed, turbulence in the upper ocean is influenced by additional physical processes that are independent, or not solely dependent, on the wind. These include wave breaking, shear stress due to geostrophic currents, wind-wave-current interactions, bottom-generated turbulence, tidal forces, and precipitation (Villas Bôas et al, 2019;Zappa et al, 2007;Zhao et al, 2018).…”

“…In this case study we apply a gas transfer velocity parameterisation based on turbulent kinetic energy dissipation rate (ε), as developed by Zappa et al (2007), to quantify the impact of wind-and wave-driven turbulence on sea-to-air CO 2 . Zappa et al (2007) used direct measurements of k and ε in aquatic and shallow marine regions to derive the following relationship:…”

“…The additional input data were wind speed data from WAVEWATCH III reanalysis forcing field (WAVE-WATCH III development group, 2016), sea surface temperature from Reynolds Optimum Interpolation Sea Surface Temperature dataset (OISST; Reynolds et al, 2007), salinity data from the NOAA World Ocean Atlas (Zweng et al, 2018), xCO 2 from the GLOBALVIEW-CO2 dataset (GLOBALVIEW-CO2, 2013), and f CO 2 data from the SO-CAT derived sea-to-air CO 2 flux reference dataset for 2010 (Woolf et al, 2019). Since the Zappa et al (2007) relationship was parameterised in low to moderate wind speeds and in shallow marine environments, a mask was set in the configuration file to constrain the calculation to grid cells with wind speeds less than 10 m s −1 and shelf sea water depths between 20 and 200 m; then the analysis repeated with depths between 20 and 500 m. These depth ranges were chosen to be consistent with previous studies (e.g. Laruelle et al, 2018;Shutler et al, 2016), and the General Bathymetric Chart of the Oceans (GEBCO) Digital Atlas bathymetry was used for this masking (GEBCO, 2003).…”

“…Mean annual sea-to-air CO 2 flux of shelf seas in 2010 using theZappa et al (2007) gas transfer relationship for all regions and months with wind speeds 0 to 10 m s −1 . Shelf regions are defined as having depths between 20 and 200 m.…”