Gas transfer velocity in the presence of wave breaking

Ocean surface waves and wave breaking play a pivotal role in air-sea Carbon Dioxide (CO2) gas exchange by producing abundant turbulence and bubbles. Contemporary gas transfer models are generally implemented with wind speed, rather than wave parameters, to quantify CO2&#160;transfer velocity (KCO2). In our work, the direct relationship of KCO2&#160;and waves is explored through the combination of laboratory experiment, field observational data and estimation of global ocean uptake of CO2.In laboratory, the waves and CO2 transfer at water surface are forced for simultaneous measurements in a wind-wave flume. Three types of waves are exercised: mechanically generated monochromatic waves, pure wind waves with 10-meter wind speed ranging from 4.5 m/s to 15.5 m/s, and the coupling of monochromatic waves with superimposed wind force. The results show that KCO2 is well correlated with wave height and orbital velocity. In the connection of KCO2 with breakers, wave breaking probability (bT) should also be considered. The wind speed is competent too in describing KCO2 but may be inadequate for varied wave ages. A non-dimensional formula (hereafter the RHM model) is proposed in which gas transfer velocity is expressed as a main function of wave Reynolds number (RHM = UwHs/&#957;w, where Uw&#160;is wave orbital velocity, Hs&#160;is significant wave height, &#957;w is viscosity of water) while wind is accounted as an enhancement factor (1+&#219;, where &#219; is non-dimensional wind speed denoting the reverse of wave age). For wave breaking dominated gas exchange, second formula (hereafter the BT model) is developed by replacing components of RHM with breaker&#8217;s statistics and integrates an additional factor of bT.&#160;Utilizing campaign observations from open ocean, the RHM model can effectively reconcile the laboratory and field data sets. The BT model related with wave breaking, on the other hand, is adapted by including a complementary term of bubble-mediated gas transfer in which the bubble injection rate is parameterized with RHM. The updated BT model also performs well for the data. The conventional wind-based models show similar features as in laboratory experiments: the wind speed successfully captures the variation of gas transfer for respective observation yet is insufficient to neutralize the gaps among data sets.Our wave-based gas transfer models are applied for the estimation of net annual CO2&#160;fluxes of global ocean in the period of year 1985-2017. The results are in high agreement with previous studies. The wind-based gas transfer models might underestimate the CO2&#160;fluxes although the estimations still distribute within the range of uncertainty. Moreover, the models using wave parameters are found advantageous over the wind-based models in reducing the uncertainties of gas fluxes.

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Spatiotemporal variability of gas transfer velocity in a tropical high‐elevation stream using two independent methods

Ecosphere ◽

10.1002/ecs2.3647 ◽

2021 ◽

Vol 12 (7) ◽

Author(s):

Keridwen M. Whitmore ◽

Nehemiah Stewart ◽

Andrea C. Encalada ◽

Esteban Suárez ◽

Diego A. Riveros‐Iregui

Keyword(s):

High Elevation ◽

Spatiotemporal Variability ◽

Gas Transfer ◽

Transfer Velocity ◽

Gas Transfer Velocity

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Wind and fetch dependence of gas transfer velocity in an Arctic sea-ice lead determined from eddy covariance CO2 flux measurements

10.1002/essoar.10502449.1 ◽

2020 ◽

Author(s):

John Prytherch

Keyword(s):

Sea Ice ◽

Eddy Covariance ◽

Co2 Flux ◽

Arctic Sea Ice ◽

Gas Transfer ◽

Transfer Velocity ◽

Gas Transfer Velocity ◽

Arctic Sea ◽

Flux Measurements

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Sea-to-air and diapycnal nitrous oxide fluxes in the eastern tropical North Atlantic Ocean

Biogeosciences ◽

10.5194/bg-9-957-2012 ◽

2012 ◽

Vol 9 (3) ◽

pp. 957-964 ◽

Cited By ~ 26

Author(s):

A. Kock ◽

J. Schafstall ◽

M. Dengler ◽

P. Brandt ◽

H. W. Bange

Keyword(s):

Nitrous Oxide ◽

Gas Exchange ◽

Mixed Layer ◽

North Atlantic Ocean ◽

Gas Transfer ◽

Potential Contribution ◽

Transfer Velocity ◽

N2o Production ◽

Gas Transfer Velocity ◽

Upwelled Water

Abstract. Sea-to-air and diapycnal fluxes of nitrous oxide (N2O) into the mixed layer were determined during three cruises to the upwelling region off Mauritania. Sea-to-air fluxes as well as diapycnal fluxes were elevated close to the shelf break, but elevated sea-to-air fluxes reached further offshore as a result of the offshore transport of upwelled water masses. To calculate a mixed layer budget for N2O we compared the regionally averaged sea-to-air and diapycnal fluxes and estimated the potential contribution of other processes, such as vertical advection and biological N2O production in the mixed layer. Using common parameterizations for the gas transfer velocity, the comparison of the average sea-to-air and diapycnal N2O fluxes indicated that the mean sea-to-air flux is about three to four times larger than the diapycnal flux. Neither vertical and horizontal advection nor biological production were found sufficient to close the mixed layer budget. Instead, the sea-to-air flux, calculated using a parameterization that takes into account the attenuating effect of surfactants on gas exchange, is in the same range as the diapycnal flux. From our observations we conclude that common parameterizations for the gas transfer velocity likely overestimate the air-sea gas exchange within highly productive upwelling zones.

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Surfactant control of gas transfer velocity along an offshore coastal transect: results from a laboratory gas exchange tank

Biogeosciences ◽

10.5194/bg-13-3981-2016 ◽

2016 ◽

Vol 13 (13) ◽

pp. 3981-3989 ◽

Cited By ~ 19

Author(s):

R. Pereira ◽

K. Schneider-Zapp ◽

R. C. Upstill-Goddard

Keyword(s):

Organic Matter ◽

Gas Exchange ◽

Trace Gas ◽

Gas Transfer ◽

Transfer Velocity ◽

Chl A ◽

Gas Transfer Velocity ◽

Biogeochemical Models ◽

Sea Surface Microlayer ◽

Laboratory Water

Abstract. Understanding the physical and biogeochemical controls of air–sea gas exchange is necessary for establishing biogeochemical models for predicting regional- and global-scale trace gas fluxes and feedbacks. To this end we report the results of experiments designed to constrain the effect of surfactants in the sea surface microlayer (SML) on the gas transfer velocity (kw; cm h−1), seasonally (2012–2013) along a 20 km coastal transect (North East UK). We measured total surfactant activity (SA), chromophoric dissolved organic matter (CDOM) and chlorophyll a (Chl a) in the SML and in sub-surface water (SSW) and we evaluated corresponding kw values using a custom-designed air–sea gas exchange tank. Temporal SA variability exceeded its spatial variability. Overall, SA varied 5-fold between all samples (0.08 to 0.38 mg L−1 T-X-100), being highest in the SML during summer. SML SA enrichment factors (EFs) relative to SSW were ∼  1.0 to 1.9, except for two values (0.75; 0.89: February 2013). The range in corresponding k660 (kw for CO2 in seawater at 20 °C) was 6.8 to 22.0 cm h−1. The film factor R660 (the ratio of k660 for seawater to k660 for “clean”, i.e. surfactant-free, laboratory water) was strongly correlated with SML SA (r ≥ 0.70, p ≤ 0.002, each n = 16). High SML SA typically corresponded to k660 suppressions ∼  14 to 51 % relative to clean laboratory water, highlighting strong spatiotemporal gradients in gas exchange due to varying surfactant in these coastal waters. Such variability should be taken account of when evaluating marine trace gas sources and sinks. Total CDOM absorbance (250 to 450 nm), the CDOM spectral slope ratio (SR = S275 − 295∕S350 − 400), the 250 : 365 nm CDOM absorption ratio (E2 : E3), and Chl a all indicated spatial and temporal signals in the quantity and composition of organic matter in the SML and SSW. This prompts us to hypothesise that spatiotemporal variation in R660 and its relationship with SA is a consequence of compositional differences in the surfactant fraction of the SML DOM pool that warrants further investigation.

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Effect of gas-transfer-velocity parameterization choice on CO2 air–sea fluxes in the North Atlantic and European Arctic

Ocean Science Discussions ◽

10.5194/osd-12-2591-2015 ◽

2015 ◽

Vol 12 (6) ◽

pp. 2591-2616

Author(s):

I. Wróbel ◽

J. Piskozub

Keyword(s):

North Atlantic ◽

World Ocean ◽

Software Tool ◽

The Arctic ◽

Gas Transfer ◽

Transfer Velocity ◽

Gas Transfer Velocity ◽

The North ◽

European Arctic ◽

The North Atlantic

Abstract. The ocean sink is an important part of the anthropogenic CO2 budget. Because the terrestrial biosphere is usually treated as a residual, understanding the uncertainties the net flux into the ocean sink is crucial for understanding the global carbon cycle. One of the sources of uncertainty is the parameterization of CO2 gas transfer velocity. We used a recently developed software tool, FluxEngine, to calculate monthly net carbon air–sea flux for the extratropical North Atlantic, European Arctic as well as global values (or comparison) using several available parameterizations of gas transfer velocity of different dependence of wind speed, both quadratic and cubic. The aim of the study is to constrain the uncertainty caused by the choice of parameterization in the North Atlantic, a large sink of CO2 and a region with good measurement coverage, characterized by strong winds. We show that this uncertainty is smaller in the North Atlantic and in the Arctic than globally, within 5 % in the North Atlantic and 4 % in the European Arctic, comparing to 9 % for the World Ocean when restricted to functions with quadratic wind dependence and respectively 42, 40 and 67 % for all studied parameterizations. We propose an explanation of this smaller uncertainty due to the combination of higher than global average wind speeds in the North Atlantic and lack of seasonal changes in the flux direction in most of the region. We also compare the available pCO2 climatologies (Takahashi and SOCAT) pCO2 discrepancy in annual flux values of 8 % in the North Atlantic and 19 % in the European Arctic. The seasonal flux changes in the Arctic have inverse seasonal change in both climatologies, caused most probably by insufficient data coverage, especially in winter.

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