Eddy covariance measurements show gas transfer velocity suppression at medium to high wind speed. A
wind–wave interaction described by the transformed Reynolds number is used to
characterize environmental conditions favoring this suppression. We take the transformed
Reynolds number parameterization to review the two most cited wind speed gas transfer
velocity parameterizations:

Gas flux

In contrast to commonly accepted gas transfer velocity parameterizations,
parameterizations based on direct flux measurements by eddy covariance systems have shown
a decrease or flattening of

A flux measurement at values of

It is noteworthy that, so far, only gas transfer velocities deduced by eddy covariance
have shown a gas transfer suppression. This may be due to the spatial (1 km) and
temporal (30 min) resolution of eddy covariance measurements, or to the types of gases
measured (e.g.,

There are two main goals of this study: (1) develop and use a simplistic algorithm to
adjust for gas transfer suppression; (2) illustrate that gas transfer suppression is
ubiquitous, showing up in our most used gas transfer parameterizations. To address
goal 1, we develop a gas transfer suppression model and apply it to two DMS eddy
covariance data sets. To address goal 2, we investigate the two most commonly used gas
parameterizations (both cited more than 1000 times each) for the occurrence of gas
transfer suppression. The

In addition, we use wind and wave data for the year 2014, calculate

We use wave data from the WWIII model hindcast run by the
Marine Modeling and Analysis Branch of the Environmental Modeling Center of the National
Centers for Environmental Prediction (NCEP;

Surface air temperature

Air–sea partial pressure difference (

DMS water concentrations were taken from the Lana DMS climatology

We linearly interpolated all data sets to the grid and times of the WWIII model.

The kinematic viscosity

The Reynolds number describes the balance of inertial forces and viscous forces. It is
the ratio of the typical length and velocity scale over the kinematic viscosity. The
transformed Reynolds number, in Eq. (

Below

Work flow of the gas transfer suppression model. In the case of suppressed gas
transfer, the output is the adjusted wind speed

Given a set wave field (constant

A change in the parameters of the wave field is, in our opinion, not feasible as the wave field is influenced to a certain extent by swell that is externally prescribed. Swell travels long distances and does not necessarily have a direct relation to the wind conditions at the location of the gas transfer and measurement. Therefore, we change the wind speed only.

Adjustments to the SO234-2/235 DMS

The difference between

We test the adjustment of

Figures

Adjustments to the Knorr11 DMS

Figure

Mean differences between the reference fits (column one) and the
adjusted and unadjusted

Linear fits to the adjusted and unadjusted data sets of Knorr11 and SO234-2/235. The error estimates correspond to a 95 % confidence interval.

Figure

Table

The slopes for the two altered data sets show a good agreement. However, we
do not account for the suppression entirely. The adjusted slopes are both in
the range of the linear function ZA18

The N00 parameterization is a quadratic wind-speed-dependent parameterization of

We analyzed each individual measurement that was used in the parameterization to assess
the amount of gas transfer suppressing instances that are within the
N00 parameterization. The single measurements, which are used for fitting the quadratic
function of the N00 parametrization, are shown together with N00 in
Fig.

Individual dual-tracer measurements that contribute to the N00 (solid line)
parameterization

We expect a negative correlation between the suppression index and the relation of the
individual measurement vs. the N00 parameterization. The higher the suppression index,
the higher the gas transfer suppression and the lower the gas transfer velocity

Figure

Adjusted individual measurements, comprising the N00 parameterization, resulting
from the algorithm described in Sect.

A new quadratic fit was applied to the adjusted datapoints (Eq.

The calculation of the unsuppressed N00 parameterization is an example application for
this adjustment algorithm. We advise using the unsuppressed parameterization
(N00

The W14 parameterization estimates the gas transfer velocity using the natural
disequilibrium between ocean and atmosphere of

Wind speed distributions for the year 2014

The quadratic coefficient,

A comparison of W14, N00 and the unsuppressed parameterizations is shown in
Fig.

We used the native global grid (0.5

Figure

The global probability of experiencing gas transfer suppression during the respective month (2014). The percentage is the number of gas transfer suppressed occurrences with respect to the total datapoints with a 3 h resolution.

The global reduction of the

The probability of experiencing gas transfer suppression during the respective month (2014) divided into ocean basins and hemispheres. The Southern Ocean was added to the southern part of the respective ocean basin. The percentage is the number of gas transfer suppressed instances with respect to the total datapoints with a 3 h resolution.

The absolute change of

The absolute values of DMS flux reduction (Fig.

2014 DMS flux in teragrams.

The absolute change of DMS gas transfer due to suppression for each
month of 2014. The shown magnitudes denote the reduction by gas transfer
suppression. The change is calculated using the bulk flux formula
(Eq.

The DMS emissions from the ocean to the atmosphere are shown in Table

We provide a first approach to adjust

We investigated the individual measurements leading to the N00 gas transfer
parameterization for the influence of gas transfer suppression. We think that the overall
parameterization is heavily influenced by gas transfer suppression, but the suppression
is likely masked by bubble-mediated gas transfer, due to the solubility of the
dual-tracer measurement gases. We show a significant negative correlation between the
occurrence of gas transfer suppression and the ratio of the individual measurements to
the N00 parameterization. We applied an adjustment due to gas transfer suppression and
fitted a new quadratic function to the adjusted data set. The new parameterization is on
average 22 % higher than the original N00 parameterization. This leads to the
conclusion that gas transfer suppression influences gas transfer parameterizations, even
if it is not directly visible, via a smaller slope.

For the W14 parameterization we used a global wind speed climatology for the year 2014
and applied the gas transfer suppression model

We think that gas transfer suppression has a global influence on air–sea gas exchange of 10 %–11 %. These numbers are supported by the adjustment of the W14 parametrization as well as a global DMS gas transfer calculation. Local conditions may lead to much higher influences. Gas transfer velocity parameterizations from regional data sets might be heavily influenced by gas transfer suppression. We have shown this for the N00 parameterization. This should be considered with their use.

Using the

The wave data are available at the website of the NOAA Environmental Modeling Center. The ERA-Interim data are available at the website of the ECMWF. The data are stored at the data portal of GEOMAR Kiel.

Figure

Wind at an angle of

The streamlined shape of a wave (cylindrical half sphere) that experiences wind
flowing over it from various angles

A shift on the

Illustration of the gas transfer suppression adjustments either along the wind speed or gas transfer velocity axis.

The adjustments of the two DMS data sets (SO234-2/235 and Knorr11) are done by
shifting

AZ developed the model. AZ and CAM provided and collected the data. AZ prepared the manuscript with contributions from CAM.

The authors declare that they have no conflict of interest.

The authors thank Kirstin Krüger, the chief scientist of the R/V ^{®} data. We thank the European Centre for
Medium-Range Weather Forecasts for providing the ERA-Interim data. This work was carried
out under the Helmholtz Young Investigator Group of Christa A. Marandino,
TRASE-EC (VH-NG-819), from the Helmholtz Association. The cruise 234-2/235 was financed
by the BMBF, 03G0235A. Edited by: Martin Heimann
Reviewed by: Christopher Fairall and Mingxi Yang