OSOcean ScienceOSOcean Sci.1812-0792Copernicus PublicationsGöttingen, Germany10.5194/os-12-1091-2016Effect of gas-transfer velocity parameterization choice on air–sea CO2
fluxes in the North Atlantic Ocean and the European ArcticWrobelIwonahttps://orcid.org/0000-0003-1315-5231PiskozubJacekhttps://orcid.org/0000-0003-3386-6604Institute of Oceanology, Polish Academy of Sciences, Sopot, PolandIwona Wróbel (iwrobel@iopan.gda.pl)30September20161251091110322September20153November20152September201614September2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://os.copernicus.org/articles/12/1091/2016/os-12-1091-2016.htmlThe full text article is available as a PDF file from https://os.copernicus.org/articles/12/1091/2016/os-12-1091-2016.pdf
The oceanic sink of carbon dioxide (CO2) 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 CO2 gas-transfer velocity. We used a recently developed
software toolbox, called the FluxEngine (Shutler et al., 2016), to estimate
the monthly air–sea CO2 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 gas-transfer 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 CO2, 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 pCO2 data sets (Takahashi et
al. (2009) and Surface Ocean CO2 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.
Introduction
The region of extratropical North Atlantic Ocean, including the European
Arctic, is a region responsible for the formation of deep ocean waters (see
Talley, 2013, for a recent review). This process, part of the global
overturning circulation, makes the area a large sink of atmospheric carbon dioxide (CO2)
(Takahashi et al., 2002, 2009; Landschützer et al.,
2014; Le Quéré et al., 2015; Orr et al., 2001). Therefore, there is a widespread
interest in tracking the changes in the North Atlantic net CO2
fluxes, especially as models appear to predict a decrease in the sink volume
later this century (Halloran et al., 2015).
Seasonal and annual mean air–sea fluxes of CO2 (mg C m-2 day-1)
in the North Atlantic, using Nightingale et al. (2000). k parameterization and Takahashi et al. (2009) climatology: (a) annual, (b) DJF
(winter), (c) MAM (spring), (d) JJA (summer), and (e) SON (autumn). The gaps (white
areas) are due to missing data, land, and ice masks.
The trend and variations in the North Atlantic CO2 sinks has been
intensively studied since observations have shown it appeared to be
decreasing (Lefèvre et al., 2004). This decrease on interannual timescales has been confirmed by further studies (Schuster and Watson, 2007) and
this trend has continued in recent years north of 40∘ N
(Landschützer et al., 2013). It is not certain how many of these changes
are the result of long-term changes, decadal changes in atmospheric forcing –
namely the North Atlantic Oscillation (González-Dávila et al., 2007;
Thomas et al., 2008; Gruber, 2009; Watson et al., 2009), or changes in
meridional overturning circulations (Pérez et al., 2013). Recent
assessments of the Atlantic and the Arctic net sea-air CO2 fluxes
(Schuster et al., 2013) and the global ocean net carbon uptake (Wanninkhof
et al., 2013) show that the cause is still unknown.
Annual air–sea CO2 fluxes (in Pg) using different k parameterizations. The values in parentheses are fluxes normalized to
Nightingale et al. (2000; as in Fig. 7).
Some relevant surface ocean currents in the North Atlantic Ocean and
the European Arctic against the background of the annual mean air–sea
CO2 fluxes (mg C m-2 day-1) as in Fig. 1. The North
Atlantic Drift continues as the Norwegian–Atlantic Current in the Nordic
Seas.
To study the rate of the ocean CO2 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 CO2 fluxes can be about
60 % due to differences in pCO2 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 CO2
(fCO2), the method used for normalization of fugacity data to a
reference year in a world of ever increasing atmospheric CO2, 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.), and some which are not
usually included in the calculations but most probably influence the flux
values (sea state parameters, air bubble void fraction, surfactant effects,
etc.) as well as the choice of the gas-transfer velocity k parameterization
formula (Landschützer et al., 2014). 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. The North Atlantic is
one of the regions of the world ocean best covered by CO2 fugacity
measurements (Watson et al., 2011), the coverage of the Arctic seas is much poorer,
especially in winter (Schuster et al., 2013).
Seasonal and annual pCO2 values (µatm) in surface
waters of the North Atlantic, estimated using the Takahashi et al. (2009)
climatology: (a) annual, (b) DJF (winter), (c) MAM (spring), (d) JJA
(summer), and
(e) SON (autumn). The gaps (white areas) are due to missing data, land and ice
masks.
In the literature there are many different parameterizations to choose from
and most depend on a cubic or quadratic wind speed relationship. The choice
of the appropriate parameterization is not trivial as indicated by the name
of an international meeting, which focused on this topic (“k conundrum”
workshop, COST-735 Action organized meeting in Norwich, February 2008). The
conclusions from this meeting have been incorporated into a recent review
book chapter (Garbe et al., 2014). This paper concentrates on quantifying
the uncertainty caused by the choice of the gas-transfer velocity
parameterization in the North Atlantic and the European Arctic. These
regions were chosen as they are the areas for which many of the
parameterizations were originally derived. They are also regions with wind
fields skewed towards higher winds (in comparison to the global average)
enabling the effect of stronger winds on the net flux calculations to be
investigated by using published gas-transfer velocity formulas.
MethodsData sets
We calculated net air–sea CO2 fluxes using a set of software processing
tools called the “FluxEngine” (Shutler et al., 2016), which was created as
part of European Space Agency funded OceanFlux Greenhouse Gases (GHGs)
project (http://www.oceanflux-ghg.org). The tools were developed to
provide the community with a verified and consistent toolbox and to encourage
the use of satellite Earth observation (EO) data for studying air–sea
fluxes. The toolbox source code can be downloaded or alternatively there is a
version that can be run through a web interface. Within the online web
interface, a suite of re-analysis data products, in situ and model data are
available as input to the toolbox. The FluxEngine allows the users to select
several different air–sea flux parameterizations producing monthly global
gridded net air–sea fluxes products with 1∘× 1∘
spatial resolution. The output consists of twelve NetCDF files (one file per
month). One monthly composite file includes the mean (first-order moment),
median, standard deviation, and the second-, third-, and fourth-order
moments. There is also information (metadata) about origin of data inputs.
For example, the monthly EO input data include rain intensity, wind speed and
direction, % of sea ice cover from monthly model data, ECMWF (European
Centre for Medium-Range Weather Forecast) air pressure, whitecapping
(Goddijn-Murphy et al., 2011), two options for monthly data sets of
pCO2, sea surface temperature (SST), and salinity. The user then needs
to choose the different components and structure of the net air–sea gas flux
calculation and choose the transfer velocity parameterization.
For the calculations, we used pCO2 and salinity values from Takahashi
et al. (2009) climatology, which was based on more than 3 million
measurements of surface water pCO2 in open-ocean environments during
non-El Niño conditions. For some calculations, we used, as an
alternative, Surface Ocean CO2 Atlas (SOCAT) v1.5 and v2.0 (Sabine et
al., 2013; Pfeil et al., 2013; Bakker et al., 2014) pCO2, and
associated SST data. SOCAT is a community-driven data set containing 6.3 and
10.1 million surface water CO2 fugacity values for v1.5 and v2.0,
respectively, with a global coverage. The SOCAT databases have been
re-analysed and then converted to climatologies using the methodology
described in Goddijn-Murphy et al. (2015). All the climatologies were
calculated for year 2010 with the FluxEngine toolset. The SSTskin (defined
within Group for High Resolution SST (GHRSST) as temperature of the surface
measured by an infrared radiometer operating at the depth of
∼ 10–20 µm) values were taken from the Advance Along Track
Scanning Radiometer (ESA/ARC/(A)ATSR) Global Monthly Sea Surface data set
(Merchant et al., 2012) in the case of both data sets, and have been
preprocessed in the same way for use with the FluxEngine (Shutler et al.,
2016).
We used EO wind speed and sea roughness (σ0
– altimeter backscatter signal in Ku-band from GlobWave L2P products) data
obtained from the European Space Agency (ESA). The GlobWave satellite
products give a “uniform” set of along track satellite wave data from all
available Altimeters (spanning multiple space agencies) and from ESA
Synthetic Aperture Radar (SAR) data and are publicity available at the
Ifremer/CERSAT cloud (http://globwave.ifremer.fr/products/data-access). Wave
data are collected from six altimeter missions (Topex/POSEIDON, Jason-1/22,
CryoSAT, GEOSAT, and GEOSAT Follow On) and from ESA SAR missions, namely ERS-1/2 and ENVISAT. All data come in netCDF-3
format.
Wind speed distribution U10 (ms-1) in the North Atlantic
used to determine the relationship between gas-transfer velocity and air–sea
CO2 fluxes: (a) annual, (b) DJF (winter), (c) MAM (spring), (d) JJA
(summer), and (e) SON (autumn). The gaps (white areas) are due to missing data,
land, and ice masks.
All analyses were performed using global data contained in the FluxEngine
software. From the gridded product (1∘× 1∘) we extracted data from the extratropical North Atlantic Ocean (north of
30∘ N), and its subset, the European Arctic (north of
64∘ N). For comparison, we also calculated fluxes in the
Southern Ocean (south of 40∘ S). Hereafter, we follow the
convention of that sources of CO2 (upward ocean-to-atmosphere gas
fluxes) are positive and sinks (downward atmosphere-to-ocean gas fluxes) are
negative. We give all results of net CO2 fluxes in the SI unit of Pg
(Pg is 1015 g, which is numerically identical to Gt).
Difference maps for the air–sea CO2 fluxes (mg C m-2 day-1) in the North Atlantic, between a cubed and a squared
parameterization (Wanninkhof and McGillis, 1999 and Wanninkhof, 2014):
(a) annual, (b) DJF (winter), (c) MAM (spring), (d) JJA (summer) and (e) SON (autumn).
The gaps (white areas) are due to missing data, land, and ice masks.
k parameterizations
The flux of CO2 at the interface of air and the sea is controlled by
wind speed, sea state, SST, and other factors. We
estimate the net air–sea flux of CO2 (F, mg C m-2 day-1) as the product of gas-transfer velocity (k,
ms-1) and the difference in CO2 concentration
(gm-3) in the sea water and its interface with the air
(Land et al., 2013). The concentration of CO2 in sea water is the
product of its solubility (α, gm-3µatm-1) and its fugacity (fCO2, µatm).
Solubility is, in turn, a
function of salinity and temperature. Hence F is defined as
F=k(αWfCO2W-αSfCO2A),
where the subscripts denote values in water (W) and the air–sea interface
(S) and in the air (A). We can exchange fugacity with the partial pressure
(their values differ by < 0.5 % over the temperature range
considered; McGillis et al., 2001). So Eq. (1) now becomes
F=k(αWpCO2W-αSpCO2A).
One can also ignore the differences between the two solubilites, and just
use the waterside solubility αW. Equation (2) will then become
F=kαW(pCO2W-pCO2A).
This formulation is often referred to as the “bulk parameterization”.
In this study we chose to analyse the air–sea gas fluxes using five
different gas-transfer parameterizations (k). All of them are wind speed
parameterizations, but differ in the formula used:
k=√(660.0/Scskin)⋅(0.212U102+0.318U10)(Nightingale et al., 2000),k=√(660.0/Scskin)⋅0.254U102(Ho et al., 2006),k=√(660.0/Scskin)⋅0.0283U103(Wanninkhof and McGillis, 1999),k=√(660.0/Scskin)⋅0.251U102(Wanninkhof, 2014),k=√(660.0/Scskin)⋅(3.3+0.026U103)(McGillis et al., 2001),
where Scskin stands for the Schmidt numbers at the skin surface, a
function of SST ([= (kinematic viscosity of water)/(diffusion coefficient
of CO2 in water)]), 660.0 is the Schmidt number corresponding to values
of CO2 at 20 ∘C in seawater, and U10 is
the wind speed 10 m above the sea surface.
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). Its purpose is to enable a separate evaluation of the effect
of the two processes on air–sea gas fluxes and it is an algorithm that has
yet to be calibrated. We used two versions of this parameterization: wind-driven direct transfer (using the U10 wind fields) and radar backscatter-driven direct transfer (using mean wave square slope) as described in
Goddijn-Murphy et al. (2012).
Monthly values of CO2 air–sea fluxes (Pg month-1) for
the five parameterizations (Eqs. 4–8); (a) the North Atlantic, (b) the European
Arctic.
Results
Using the FluxEngine software, we have produced global gridded monthly net
CO2 air–sea fluxes and from these we have extracted the values for the
two study regions, the extratropical North Atlantic Ocean and separately for
its subset – the European Arctic seas. Figure 1 shows maps of the monthly
mean air–sea CO2 fluxes for the North Atlantic, calculated with
Nightingale et al. (2000; hereafter called N2000) k parameterization and the
Takahashi et al. (2009) climatology for the whole year and for each season.
The area, as a whole, is a sink of CO2 but some regions close to North
Atlantic Drift and East Greenland Current (Fig. 2) are net sources. At the
seasonal maps one can see more variability caused by physical process (with
temperature changes causing maximum oceanic pCO2 in summer) or
biological activity (with phytoplankton blooms causing summer values to be
lowest in the annual cycle). For example, the areas close to the North
Atlantic Drift and East Greenland Current are sinks of CO2 in the
summer (likely due to the growth of phytoplankton) while the southern most
areas of the region become CO2 sources in summer and autumn (which is
likely to be due to the effect of sea-water temperature changes). Much of
this variability is caused by changes in the surface water pCO2 values,
shown in Fig. 3 for the whole year and for each season (and variability in
atmospheric CO2 partial pressure, not shown). However, the flux is
proportional to the product of ΔpCO2 and k. In most
parameterizations k is a function of wind speed (Eqs. 4–8). The mean wind
speed U10 for the whole year and each season are shown in Fig. 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). This effect is especially visible
between formulas with different powers of U10. Figure 5 shows the
difference in the air–sea CO2 fluxes calculated using two example
parameterizations: one proportional to U103 (Eq. 6) and one to
U102 (Eq. 7), namely Wanninkhof and McGillis (1999; hereafter
called WMcG1999) and Wanninkhof (2014; hereafter called W2014). It can be
seen that the “cubic” function results in higher absolute air–sea flux
values when compared to the “quadratic” function in the regions of high
winds, and lower absolute air–sea flux values in weaker winds.
Annual air–sea fluxes of CO2 for the five (Eqs. 4–8)
parameterizations as well as for backscatter (default) and wind-driven
OceanFlux GHG parameterizations normalized to flux values of Nightingale et
al. (2000) k parameterization (see text): (a) globally, (b) the North
Atlantic, (c) the European Arctic, and (d) the Southern Ocean. Average values for
all parameterization and standard deviations are marked as vertical grey
lines.
Comparison of monthly air–sea CO2 fluxes calculated with
different pCO2 data sets (Takahashi et al., 2009; SOCAT v1.5 and v2.0)
using the same k parameterization (Nightingale et al., 2000); (a) the North
Atlantic, (b) the European Arctic.
Figure 6 shows the monthly values of air–sea CO2 fluxes for the five
parameterizations (Eqs. 4–8) for the North Atlantic and the European Arctic.
The regions are sinks of CO2 in every month, although August is close
to neutral for the North Atlantic. The results using cubic parameterizations
(Eqs. 6 and 8) are higher in absolute values, by up to 30 % for WMcG1999
and 55 % for McGillis et al. (2001; hereafter called McG2001), in comparison to
the “quadratic” of N2000 (Eq. 4). The other two “quadratic”
parameterizations W2014 and Ho et al. (2006; hereafter called H2006; Eqs. 5 and 7) resulted in fluxes within 5 % of N2000. In addition to the five
parameterizations, Fig. 7 presents results for both of the OceanFlux GHG
Evolution formulas (using wind and radar backscatter data). The mean and
standard deviations of the parameterization ensemble are shown as grey
vertical lines. The standard deviation in global fluxes is similar to
previous estimates (Sweeney et al., 2007; Landschützer et al., 2014) but
they cannot be directly compared due to different parameterization choices
and methodologies. Annual net fluxes for the North Atlantic, Southern and
global oceans, as well as for the European Arctic, are shown in Table 1. The
results show that the annual North Atlantic net air–sea CO2 sink,
depending on the formula used, varies from -0.38 for N2000 to
-0.56 Pg C for McG2001. In the case of global net air–sea CO2 sink the values
are -1.30 and -2.15 Pg C, respectively. Table 1 as well as Fig. 7
shows the same data “normalized” to the N2000 data (divided by value),
which allows us to visualize the relative differences (in Table 1 values in
parentheses). In the case of the North Atlantic, using the “quadratic”
W2014 and H2006 parameterizations results in net air–sea fluxes that are
4 and 5 % higher in absolute values, respectively, than the equivalent
N2000 result, while the “cubic” WMcG1999 and McG2000 result in values
that are 28 and 44 % higher, respectively, than the N2000 results for
this regions. The respective values for the Arctic are 3 % for W2014 and
4 % for H2006, as well as 28 % for WMcG1999 and 44 % for McG2001 than
N2000. In the case of global net air–sea CO2 fluxes the equivalent
values are 8 % (W2014) and 9 % (H2006) higher than the N2000 result for
the quadratic functions as well as 33 % (WMcG1999) and 65 % (McG2001)
for cubic ones. The OceanFlux GHG parameterization for the backscatter and
wind-driven versions, results in net air–sea CO2 fluxes higher for
North Atlantic Ocean than the N2000, that are 38 and 47 %,
respectively, and in the global case the values, for those two versions,
were 44 and 52 % higher, respectively, than N2000 values. The spread
of the Arctic values was lower than that of the Atlantic values (see Table 1).
On the other hand, the values for the Southern Ocean were slightly higher
than for the North Atlantic but lower than the global values, with the
exception of the OceanFlux GHG parameterizations.
All the above results were obtained with the Takahashi et al. (2009)
pCO2 climatology and for comparison, we have also calculated the air–sea
CO2 fluxes using the re-analysed SOCAT v1.5 and v2.0 data (which
were converted to climatologies using methodology described in
Goddijn-Murphy et al., 2015). Figure 8 shows the results using the N2000 k parameterization for all three of the data sets (Takahashi et al., 2009 and
both SOCAT versions). In the case of the North Atlantic Ocean study area,
although the monthly values show large differences (using both SOCAT
data sets results in a larger sink in summer and smaller in winter compare to
Takahashi et al., 2009), the annual values are similar: -0.38 Pg C for both
Takahashi et al. (2009) and SOCAT v1.5 and -0.41 Pg C for SOCAT v2.0. In the
case of the European Arctic, the situation is very different, with Takahashi
et al. (2009) and SOCAT data set-derived climatologies resulting in inverse
seasonal variability but with annual net air–sea CO2 fluxes results
that are similar: -0.102 Pg C for Takahashi et al. (2009), -0.085 Pg C for
SOCAT v1.5, and -0.088 Pg C for SOCAT v2.0.
Discussion
Our results show that the three “quadratic” parameterization (Nightingale
et al., 2000; Ho et al., 2006 and Wanninkhof, 2014) air–sea fluxes are
within 5 % of each other in the case of the North Atlantic (Table 1,
values in parentheses). This discrepancy is smaller than the 9 %
difference identified for the global case (Table 1 and Fig. 7). This
confirms that at present, these different parameterizations are
interchangeable for the North Atlantic as this range is within the
experimental uncertainty (Nightingale, 2015). The three parameterizations
were derived using different methods and data from different regions, namely
passive tracers and dual-trace experiments in the North Sea in the case of
Nightingale et al. (2000), dual tracers in the Southern Ocean in the case of
Ho et al. (2006), and global ocean 14C inventories in the case of
Wanninkhof (2014). The differences between the quadratic and cubic
parameterization are large, and instead of the quadratic functions that are
supported by several lines of evidence (see Garbe et al., 2014 for
discussion), the cubic function are not completely refuted by the available
observation. Therefore, it is important to notice that a choice of one of
the available cubic functions may lead to net air–sea CO2 fluxes that
are considerably larger in absolute values, by up to 33 % in the North
Atlantic Ocean and more than 50 % in the global ocean.
The above results imply smaller relative differences between the
parameterizations in the North Atlantic Ocean than in the global ocean. This
is interesting because the North Atlantic is the region of strong winds and
over most of its area there are no seasonal changes in the air–sea flux
direction (Fig. 1). For example in the South Atlantic, the annual mean wind
speed is 8.5 m s-1, which is lower than in the North Atlantic (9 m s-1), and the range of seasonal changes in the air–sea CO2 fluxes
are from -0.05 to +0.05 Pg C yr-1 with the difference between
parameterizations being lower than in the North Atlantic (Le Quéré et al.,
2007; Takahashi et al., 2009). Takahashi et al. (2009) also indicate that
the air–sea CO2 flux difference in the Southern Ocean is strongly
dependent on the choice of the gas-transfer parameterizations and wind
speed. Smaller differences in the North Atlantic Ocean than in the global
ocean are surprising, given that at least some of the older
parameterizations (e.g. W2009 or WMcG1999) were developed using a smaller
range of winds than what occurs in the North Atlantic. There may be two
reasons for this. First, when comparing quadratic and cubic
parameterizations (Fig. 9), the cubic parameterization implies higher
air–sea fluxes for high winds, whereas the quadratic ones lead to higher
fluxes for weaker winds. This difference can be presented in arithmetic
terms. Let us assume two functions of wind speed U, F1(U) quadratic and
F2(U) cubic:
F1(U)=aU2,F2(U)=bU3.
The difference between the two functions ΔF is equal to
ΔF=F2-F1=bU3-aU2=bU2(U-ab-1)=bU2(U-Ux),
where Ux=ab-1. The difference is positive for wind speeds
greater than Ux and negative for winds less than Ux. Ux is the
value of wind speed for which the two functions intersect. In the case of
Eqs. (6) and (7), where a= 0.251 and b= 0.0283, they imply that
Ux= 8.87 m s-1. In fact all of the functions presented in Fig. 9
produce very similar values for Ux, all of which are close to 9 m s-1. This value is very close to average wind speed in the North
Atlantic (Fig. 4). This is one of the reasons for the small relative
difference in net air–sea fluxes. The spread of flux values for the Southern
Ocean seems to support this conclusion, being larger than that in the North
Atlantic. The Southern Ocean has on average stronger winds than the North
Atlantic (including also the Arctic seas), which seems to have the smallest
spread of flux values for different parameterizations. The other reason of
smaller relative differences between the parameterizations in the North
Atlantic than in the global ocean is the lack of seasonal variation in the
sign of the air–sea flux. In the case of seasonal changes in the air–sea
flux direction (caused by seasonal changes in water temperature or primary
productivity), with winds stronger than Ux in some seasons and weaker in
others (usually strong winds in winter and weak in summer), the fluxes
partly cancel each other. The difference between cubic and quadratic
parameterizations adds to each other due to simultaneous changes in the sign
of both fluxes itself and the U-Ux term. This effect of seasonal
variation has been suggested to us based on available observations (A.
Watson, University of Exeter, personal communication, 2015) but we are unaware of
any paper investigating it or even describing it explicitly.
Different k660 parameterizations as a function of wind speed.
In addition to the five parameterizations described above, we calculated the
air–sea fluxes using the OceanFlux GHG Evolution combined formula, which is
based on knowledge that air–sea exchange is enhanced by air-entraining wave
breaking and bubble-mediated transfer, especially for the less soluble gases
than CO2. Goddijn-Murphy et al. (2016) assume a linear wind
relationship for dimethyl sulphide (DMS) and an additional bubble-mediated
term for less soluble gases, parameterized with whitecap coverage. 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.
Using both Takahashi et al. (2009) climatology and SOCAT data sets (Fig. 8)
results in similar annual net air–sea CO2 fluxes in the North Atlantic;
however it should be noted that they show different seasonal variations.
This may have been caused by slightly different time periods of the data
sets,
as the SOCAT-based data set contains more recent data. It should be noted
that a significant part of the data from Takahashi et al. (2009) are
included in SOCAT; therefore, the differences in the European Arctic may be due to
the sparse data coverage and possible interpolation artefacts
(Goddijn-Murphy et al., 2015) or to processing of the data through the
FluxEngine. A recent paper (Couldrey et al., 2016) using even more high
latitude data than were available in the SOCAT v1.5 and v2.0, which
we used, shows a similar seasonal pattern to SOCAT. Still, this discrepancy
makes us treat the net air–sea CO2 fluxes results from the Arctic with
much less confidence than the values for the whole North Atlantic. It is
impossible to decide in this study which data set is more accurate as only
new data can settle this. However, new data, not included in the SOCAT
versions we used, have been available due to the recent analysis by Yasunaka et
al. (2016). The observed pCO2 data (Fig. 4 in Yasunaka et al., 2016),
especially since 2005, have clearly shown an annual cycle compatible with the
SOCAT seasonal flux variability.
Conclusions
In this paper we have studied the effect of the choice of gas-transfer
velocity parameterization on the net CO2 air–sea gas fluxes in the
North Atlantic and the European Arctic using the recently developed
FluxEngine software. The results show that the uncertainty caused by the
choice of the k formula is smaller in the North Atlantic and in the Arctic
than it is globally. The difference in the annual net air–sea CO2
fluxes caused by the choice of the parameterization is 5 % in the North
Atlantic and 4 % in the European Arctic, compared to 9 % globally for
the studied functions with quadratic wind dependence. It is up to 46 %
different for the North Atlantic, 36 % for the Arctic and 65 % globally
when comparing cubic and quadratic functions. In both cases the uncertainty
in the North Atlantic and the Arctic regions are smaller than the global
case. We explain the smaller North Atlantic variability to be a combination
of, first, higher than global average wind speeds in the North Atlantic,
close to 9 m s-1, which is the wind speed at which most k parameterization have similar values, and, second, the all-season CO2
sink conditions in most North Atlantic areas. We repeated the analysis using
Takahashi et al. (2009) and SOCAT pCO2-derived climatology and find that
although the seasonal variability in the North Atlantic is different the
annual net air–sea CO2 fluxes are within 8 % in the North Atlantic
and 19 % in the European Arctic. The seasonal flux calculated from the two
pCO2 data sets in the Arctic have inverse seasonal variations, indicating
possible under sampling (aliasing) of the pCO2 in this polar region and
therefore highlighting the need to collect more polar pCO2 observations
in all months and seasons.
Data availability
Several relevant data sets have been collected from various sources for the
OceanFlux project. They have been processed in order to provide consistent
and homogeneous composite files, on the same grid and temporal resolution, as
well as multi-year climatologies. All these input and processed data sets are
available in the OceanFlux FTP repository at ftp://eftp.ifremer.fr. Some of
these data sets are at present restricted to project partners for reasons
related to the original provider distribution policy. Therefore the access to
the FTP site is protected: any user interested in the data sets should send a
request to the CERSAT help desk (fpaf@infremer.fr) in order to get a login
and password.
Acknowledgements
The publication has been financed from the funds of the Leading National
Research Centre (KNOW) received by the Centre for Polar Studies for the
period 2014–2018; OceanFlux Greenhouse Gases Evolution, a project funded by
the European Space Agency, ESRIN contract no. 4000112091/14/I-LG; and GAME
“Growing of Marine Arctic Ecosystem”, funded by Narodowe Centrum Nauki grant
DEC-2012/04/A/NZ8/00661. We would also like to thank Jamie Shutler for
important advice on the FluxEngine and for correcting the manuscript for
English language. The authors are very grateful to those who have produced
and made freely available the LDEO Flux Climatology base, FluxEngine
software funded by European Space Agency, Surface Ocean CO2 Atlas
(SOCAT), GlobWave Project funded by European Space Agency, as well as Centre
de Recherché et d'Exploitation Satellitaire (CERSAT) at IFREMER.
Edited by: M. Hoppema
Reviewed by: three anonymous referees
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