# Enhanced Air–Sea Exchange of Heat and Carbon Dioxide Over a High Arctic Fjord During Unstable Very-Close-to-Neutral Conditions

## Abstract

Eddy-covariance measurements made in the marine atmospheric boundary layer above a high Arctic fjord (Adventfjorden, Svalbard) are analyzed. When conditions are unstable, but close to neutral −0.1 < *z/L* < 0, where *z* is the height, and *L* is the Obukhov length, the exchange coefficient for sensible heat *C*_{H} is significantly enhanced compared with that expected from classical surface-layer theory. Cospectra of the vertical velocity component (*w*) and temperature (*T*) reveal that a high-frequency peak develops at *f* ≈ 1 Hz for *z/L* > − 0.15. A quadrant analysis reveals that the contribution from downdrafts to the vertical heat flux increases as conditions become close to neutral. These findings are the signature of the evolving unstable very-close-to-neutral (UVCN) regime previously shown to enhance the magnitude of sensible and latent heat fluxes in the marine surface layer over the Baltic Sea. Our data reveal the significance of the UVCN regime for the vertical flux of the carbon dioxide (CO_{2}) concentration (*C*). The cospectrum of *w* and *C* clearly shows how the high-frequency peak grows in magnitude for *z/L* > − 0.15, while the high-frequency peak dominates for *z/L* > − 0.02. As found for the heat flux, the quadrant analysis of the CO_{2} flux shows a connection between the additional small-scale turbulence and downdrafts from above. In contrast to the vertical fluxes of sensible and latent heat, which are primarily enhanced by the very different properties of the air from aloft (colder and drier) during UVCN conditions, the increase in the air–sea transfer of CO_{2} is possibly a result of the additional small-scale turbulence causing an increase in the water-side turbulence. The data indicate an increase in the gas-transfer velocity for CO_{2} for *z/L* > − 0.15 but with a large scatter. During the nearly 2 months of continuous measurements (March–April 2013), as much as 36% of all data are associated with the stability range −0.15 < *z/L* < 0, suggesting that the UVCN regime is of significance in the wintertime Arctic for the air–sea transfer of heat and possibly also CO_{2}.

## Keywords

Air–sea exchange Arctic CO_{2}Gas-transfer velocity Unstable very-close-to-neutral

## 1 Introduction

_{2}) into the atmosphere, causing ocean acidification (Le Quéré et al. 2015), while limiting the climate impact. For accurate estimates of the global carbon budget, the net uptake of CO

_{2}and its variation with time is crucial to quantify. High-latitude seas and marine polar waters are regions of climatic importance since they constitute a major net sink of atmospheric CO

_{2}. In order to understand the ocean response to the increasing emissions of CO

_{2}into the atmosphere, a correct description of the air–sea gas transfer at these latitudes is crucial. Studies of air–sea gas exchange in the high Arctic environment are, however, few and a detailed description of the processes controlling the transfer efficiency in these areas is lacking. The gas flux of a non-reactive gas such as CO

_{2}can be computed using the bulk flux equation,

*k*

_{c}is the gas-transfer velocity for CO

_{2},

*K*

_{0}is a gas-specific solubility constant,

*p*

_{cw}is the partial pressure of CO

_{2}in the surface seawater, and

*p*

_{ca}is the partial pressure of CO

_{2}in the atmosphere. Despite the simplicity of Eq. 1, the physical complexity in describing air–sea gas transfer is contained within the parametrization of the gas-transfer velocity, which essentially describes the efficiency of the transfer across the air–sea interface, and is controlled by several processes, such as molecular diffusion, bubble mediated transfer, and surface renewal. In the presence of turbulence, the molecular diffusion layer separating air and water deforms, which in turn enhances the air–sea gas-transfer velocity, thus an increase in turbulence results in higher values of

*k*

_{c}and, thus, a larger air–sea CO

_{2}flux. For a gas of low solubility, such as CO

_{2}, the interfacial gas transfer is almost exclusively driven by the magnitude of turbulence in the surface water. Water-side turbulence is in turn caused by a variety of processes, such as wind stress on the water surface (Liss and Merlivat 1986; Wanninkhof 1992; Wanninkhof et al. 2009), breaking waves and bubbles (Woolf 1993, 1997; Asher and Wanninkhof 1998; Bell et al. 2017), water-side convection (MacIntyre et al. 2002; Rutgersson and Smedman 2010; Rutgersson et al. 2011; Andersson et al. 2017), and rain (Ho et al. 1997, 2004; Zappa et al. 2009; Drushka et al. 2016).

_{2}during unstable, but near-neutral conditions. Former studies over land and the open sea during unstable very-close-to-neutral (UVCN) conditions in combination with relatively high wind speeds have shown an enhancement of the vertical fluxes of temperature (

*T)*and humidity (Smedman et al. 2007a, b; Sahlée et al. 2008a, b). The larger fluxes are associated with downdrafts of cold and dry air by detached eddies originating from the mixed layer, manifest as additional small-scale turbulence in the cospectra of

*w*and

*T*. Our focus is on the possible importance of the UVCN regime for the air–sea transfer of heat and CO

_{2}in the wintertime marine Arctic using eddy-covariance data taken at Adventfjorden, Svalbard (Fig. 1). We present data indicating a possible impact of the additional turbulence (found for unstable, but near-neutral conditions) related to the UVCN regime on the air–sea gas-transfer velocity for CO

_{2}.

## 2 Theory

### 2.1 Formation of the Convective Boundary Layer

*h*

_{b}of the CBL increases with the distance

*x*from the upwind land/ice edge, for which Garratt (1992) provides the expression

*h*

_{b}with

*x*. Here,

*z*

_{02}is the roughness length of the smooth surface, and the dimensionless constant

*A*≈ 1. Within the CBL, the generally accepted model is that the wind stress acting on the surface, and due to the mean wind speed and/or surface convection, generates small eddies formed at the surface, which increase in size with height.

### 2.2 Gas-Transfer Velocity

*F*

_{c}and the difference in partial pressure of CO

_{2}(Δ

*p*

_{c}) between the surface water and at the measurement height are known, the transfer velocity

*k*

_{c}follows from Eq. 1 as

*k*

_{c}are corrected for changes in molecular diffusivity and viscosity and scaled to the corresponding counterpart for CO

_{2}at 20 °C in seawater (

*k*

_{660}) through the Schmidt number

*Sc*= 660,

*Sc*is obtained using the parametrization of Wanninkhof (1992). In a review article by Wanninkhof et al. (2009), a parametrization of the gas-transfer velocity was presented relating the value of

*k*

_{C}to the wind speed at 10-m height above sea level

*U*

_{10}. This is the state-of-the-art parametrization, since it is based on both theoretical concepts and measurements, and includes the effects from both low and high wind-speed regimes through

*k*

_{660}was investigated using eddy-covariance measurements from a Svalbard fjord (Adventfjorden). After scaling the measured values of

*k*

_{660}to represent open-sea conditions, and removing the impact of the wind speed on

*k*

_{660}according to Eq. 5, Andersson et al. (2017) found a relation between the gas-transfer velocity for CO

_{2}(

*k*

_{wsc}=

*k*

_{660}−

*k*

_{W09}) and the water-side convection

*w*

_{*w}as

*w*

_{*w}is determined using the expression from Jeffery et al. (2007),

Here, *B* is the buoyancy flux at the sea surface, and *z*_{ml} denotes the mixed-layer depth in water. We follow the scaling concept presented in Andersson et al. (2017), and use Eqs. 6 and 7 to calculate the contribution from water-side convection to the value of *k*_{660.}

### 2.3 Transfer Coefficient

*C*

_{H}) can be obtained through the bulk relation

*U*

_{w}is the wind speed at the sea surface,

*θ*

_{10}is the potential temperature (K) at 10-m height, and

*θ*

_{w}is the temperature at

*z*=

*z*

_{T}, where

*z*

_{T}is the scalar roughness length for temperature, and

*θ*

_{w}is approximated by the sea-surface temperature. Here, the value of

*C*

_{H}is determined from measurements of the potential temperature

*θ*

_{4}and wind speed

*U*

_{4}taken at 4-m height. Within the surface layer, the turbulent fluxes are assumed to be approximately constant, and, provided Monin–Obukhov similarity theory (MOST) is valid, the non-dimensional profiles of

*U*and

*θ*over a horizontally-homogenous surface can be expressed as

*g*is the acceleration due to gravity, and

*T*

_{0}is the mean temperature of the surface layer. After vertical integration of Eq. 9, the surface-layer profile

*U*(

*z*) is

*z*

_{0}is the roughness length, and

*U*

_{w}is the wind speed at the sea surface (here,

*U*

_{w}is set to zero), with the small term

*ψ*(

*z*

_{0}/

*L*) neglected. During unstable conditions, we base the function

*ϕ*

_{m}on (Högström 1996)

### 2.4 Spectral Analysis

*n*) to the energy of, for example, the specified quantities

*U*or

*C*. Following Kolmogorov theory, and by applying the Taylor hypothesis, the energy spectrum

*S(n)*in the inertial subrange for the longitudinal velocity component can be expressed as

*ɛ*is the dissipation rate of turbulent kinetic energy, and

*α*

_{k}is the Kolmogorov constant. For the wind speed

*U*,

*α*

_{k}= 0.52, although studies have shown a dependence on the wave age (Sjöblom and Smedman 2004),

*α*

_{k}≈ 0.8 for temperature, but 0.68 ≤

*α*

_{k}≤ 0.89 for CO

_{2}(see, e.g., Othaki 1982; Verma and Anderson 1984; Norman et al. 2012). Within the inertial subrange, the value of

*nS*

_{u}(

*n*) should follow a −2/3 slope when plotted against the logarithm of frequency

*n*. As shown in several studies, Kolmogorov theory also applies for the quantities

*v*(transverse velocity component),

*w*,

*T*(Kaimal et al. 1972),

*q*(specific humidity) and

*C*(Ohtaki and Matsui 1982; Anderson and Verma 1985; Sahlée et al. 2008c), and probably also for the oxygen concentration (Andersson et al. 2014). For the investigation of the turbulent flux, the cospectrum (

*C*

_{wx}) is preferably studied, where the eddy size is shown as a function of the frequency, and the scalar flux

*F*

_{x}is computed as the integral of the cospectrum (

*C*

_{wx}),

### 2.5 The Unstable Very-Close-to-Neutral Regime

During moderate instability, the boundary layer is characterized by organized longitudinal eddies of roll-type structure (e.g. Mason and Sykes 1982), giving a normalized spectral peak located at *f* ≈ 10^{−2} Hz, and the MOST approach is valid. As the boundary layer becomes closer to neutral (−*L* > 150 m) due to an increase in wind speed or a decrease in the air–sea temperature difference (Δ*T*), the small-scale turbulence dominates the spectrum of temperature (see Smedman et al. 2007a, b). This new regime is denoted as the unstable very-close-to-neutral (UVCN) regime, and is characterized by a development of a secondary peak at higher frequencies in the spectrum of *T* and in the cospectrum of *wT*. Simultaneously, the value of *C*_{H} increases with increasing wind speed, and MOST becomes no longer valid. From a quadrant analysis of the value of *wT*, the additional small-scale turbulence coincides with an increase in the contribution to the heat flux from downdrafts of cold air from layers aloft. In the transition between the more unstable branch characterized by large-eddy structures and the UVCN regime, an intermediate range is found at the intersection of these two regimes characterized by “camel-shaped” spectra and cospectra with two distinct maxima: a large-scale maximum in the energy-containing range related to local production, and a maximum at higher frequency related to the UVCN regime. Smedman et al. (2007a) argued that this small-scale turbulence is explained by detached eddies created by shear in the upper part of the boundary layer. The concept of detached eddies for high Reynolds numbers, which was explained in Hunt and Morrison (2000) and Hunt and Carlotti (2001), and later confirmed by measurements (Högström et al. 2002), says that, as detached eddies move downwards, they are deformed due to blocking and stretching by the surface-layer wind shear. While the UVCN regime is found to occur for approximately −*L* > 150 m, Smedman et al. (2007a) speculated that the value of *h/L*, with *h* the boundary-layer height, would be the controlling parameter, but did not possess any measurements of *h*. In Sahlée et al. (2008a), the additional turbulence typical of the transition regime was found to significantly increase the vertical turbulent flux of humidity.

## 3 Site and Measurements

### 3.1 The Adventpynten Site

During the period from 7 March to 22 April 2013, a field campaign was conducted in the area of Adventfjorden close to Longyearbyen, Svalbard in Norway (Fig. 1). Adventfjorden is a typical, high Arctic fjord where the valley opens out into the water, giving a fjord surrounded by steep mountains. However, the terrain at the Adventpynten site (see Fig. 1a) is relatively flat, resulting in a smooth transition from land to water. As a side fjord to the larger Isfjorden, Adventfjorden is about 7 km long, and the distance across the fjord from Adventpynten to the other side of the fjord is about 3.5 km. The site contains (Fig. 1b) one tower equipped with an eddy-covariance system installed at 3-m height above mean sea level, and a second tower equipped with slow-response instruments measuring the wind speed, temperature, and humidity at two heights (0.5 m and 4 m above ground). The eddy-covariance system consists of one CSAT3 sonic anemometer (Campbell Scientific, North Logan, Utah, USA) measuring the three velocity components and temperature, and a LICOR-7500A gas analyzer (LI-COR Inc., Lincoln, Nebraska, USA) measuring the humidity, CO_{2} concentration, and pressure. On five occasions during the period 14–25 March, measurements from a boat were taken within the flux footprint. A net radiometer (CNR-1, Kipp & Zonen, Delft, The Netherlands) installed on a boom at the front of the boat measured the net radiation over water. Measurements of the sea-surface temperature, partial pressure of CO_{2}, and the water salinity were also recorded, and vertical profiles of water temperature were taken every 15 min using a conductivity, temperature, and depth sensor (CTD, SeaBird SBE 19plus V2 SeaCat, Seabird Electronics Inc., Bellevue, Washington, USA).

### 3.2 Data Analysis

Based on a footprint analysis and spectral/cospectral evaluations (Andersson et al. 2017), data not associated with a wind direction in the range of 080°–150° were discarded to minimize the influence of land. A double rotation was performed on the eddy-covariance velocity data, with vectors first rotated into the mean wind direction and then tilt corrected to yield a zero mean vertical velocity component, giving a velocity vector aligned with the mean wind direction. The gas-analyzer data were screened with a filter using the mean concentrations of humidity and CO_{2} to exclude data with icing on the device. Data were then despiked and divided into 30-min blocks, with data not fulfilling the skewness and flatness criteria of Vickers and Mahrt (1997) discarded. Every individual block of data was linearly detrended and corrected for time lags caused by the separation distance between the sonic anemometer and the gas analyzer. Corrections for density fluctuations due to heat and moisture fluxes were made based on Webb et al. (1980). For the spectral and cospectral analysis of CO_{2}, the density correction was performed directly on the raw signal following the method presented in Sahlée et al. (2008c), where the output signal was transformed into a mixing ratio to avoid the influence from temperature and humidity variations on the shape of the *wC* cospectrum. Here, cospectra consist of 21 points, with each point representing a normalized mean cospectral estimate for the respective frequency. The data and site are described in detail in Andersson et al. (2017).

## 4 Results

### 4.1 Heat Transfer

^{−1}) and air temperatures consistently below zero characterized the weather conditions during the field campaign (Fig. 2a, b). The prevailing wind direction was from the south-east, corresponding to flow from the Advent valley out over the fjord. Flow from the northern sector (into the fjord) was rarely observed. At the beginning of the field campaign, a period with ice formation in the Adventfjord (black bars, Fig. 2d) occurred, and by 9 March a major part of the fjord upstream from the tower was covered with ice but with patches of open water. The heat fluxes drastically decreased and the atmospheric stability (Fig. 2c) altered between unstable and stable conditions, typically with −2 <

*z/L*< 0.1. On 11 March, a cold-air outbreak occurred with wind speeds at 3-m height as high as 12 m s

^{−1}in combination with air temperatures < − 18 °C. The ice quickly disappeared, the sensible heat flux increased up to 400 W m

^{−2}, and latent heat fluxes were > 150 W m

^{−2}(not shown). Several periods with high wind speeds, large heat fluxes, and unstable, but near-neutral, conditions could be distinguished. The atmospheric stability (Fig. 2c) generally varied from unstable during more calm conditions to unstable, but near-neutral, conditions in the range −0.2 <

*z/L*< − 0.03 during higher wind-speed conditions (34% of the time). The large air–sea gradient in temperature also set an upper limit for the stability, and only 5% of the data were found in the stability range −0.03 <

*z/L*< 0. The combination of cold, humid air and relatively high wind speeds during the first half of the field campaign caused severe icing on the instruments. The gas analyzer and hence the CO

_{2}signal was found to be sensitive to icing, causing large false positive fluxes of CO

_{2}, which can be observed frequently during the first three weeks of the campaign (Fig. 2e). Useful data during this period were reduced to some hours just after the daily maintenance of the instruments. After the first three weeks, the flux

*F*

_{c}(Fig. 2e) was directed downwards as expected given the direction of the air–sea concentration difference of CO

_{2}, which is consistent with the fjord acting as a sink of atmospheric CO

_{2}. The variability of the flux

*F*

_{c}observed during this field campaign reflects the expected development of the concentration of CO

_{2}in the fjord. At the turn of the month from February to March, the biological activity in the water is generally low, and the CO

_{2}concentration in the water often reaches its annual maximum value. Approaching the middle of March, the number of sunlight hours drastically increases, and the net result of photosynthesis and respiration leads to a decreasing partial pressure of CO

_{2}in the water. During the short period from 14 to 19 March, the measured air–sea difference of

*pCO*

_{2}increased from 118 µatm to 135 µatm. From late March, the flux

*F*

_{c}was consistently directed downwards.

*C*

_{H}as a function of

*z/L*associated with the wind-direction sector of 090°–140°, where each mark (grey) denotes a 30-min value calculated from Eq. 8, and the black curve is the interpolated function based on the bin averages (black, filled circles). For

*z/L*< − 0.15, the data scatter around

*C*

_{H}= 0.0015, which is a somewhat larger heat exchange than that normally found over the open ocean, but agrees well with other studies in the same area (Kilpeläinen and Sjöblom 2010), as well as studies over water bodies with limited fetch (e.g., Andreas and Cash 1999). For

*z/L*> − 0.2, the value of

*C*

_{H}increases slightly, and, when the stability becomes closer to neutral for

*z/L*> − 0.1, the value of

*C*

_{H}increases significantly. For −0.075 <

*z/L*< 0 corresponding to

*L*< − 40 m,

*C*

_{H}= 0.0018 on average.

*C*

_{H}is plotted against the wind speed

*U*(Fig. 4). As in Fig. 3, the bin-averaged values of

*C*

_{H}are found to increase with increasing values of

*U*in Fig. 4, but with a larger scatter in the

*C*

_{H}values. For the data presented in Figs. 3 and 4, the difference

*θ*

_{w}−

*θ*

_{4}varies over the broad range of 0.7 − 19.9 °C, which could explain why a large variation in

*θ*

_{w}−

*θ*

_{4}values for a specific value of

*U*obscures the expected relation between

*C*

_{H}and

*U*. Nonetheless, as much as 86% of the

*C*

_{H}data have values

*C*

_{H}> 0.0015 for

*U*> 9 m s

^{−1}.

### 4.2 Spectral Analysis

*wT*are shown in Fig. 5 for five different atmospheric stabilities from

*L*= − 5 m (red curve) to

*L*= 600 m (blue curve). Here, the mean

*wT*cospectrum is shown in a linear–logarithmic representation, so that the area below the curve is directly proportional to the vertical turbulent flux of temperature. The two black curves are related to the transition regime with

*L*= − 20 m (black dashed curve) and

*L*= − 100 m (black solid curve). The green curve is a mean cospectrum for

*wT*during UVCN conditions with

*L*= − 300 m. For the moderately unstable case (red curve), the cospectrum takes an expected shape with one peak at

*n*= 0.08 Hz. As the thermal forcing weakens, this peak decreases in magnitude, and a second peak in the cospectrum of

*wT*develops as the Obukhov length changes from

*L*= − 20 m to

*L*= − 300 m. For

*L*= − 100 m, the low-frequency peak is reduced and the cospectrum of

*wT*shows a plateau, but for

*L*= − 300 m, the cospectrum of

*wT*is dominated by the high-frequency maxima, which is the signature of the UVCN regime. As a consequence of the large air–sea difference in temperature, high wind-speed events are generally associated with large heat fluxes, so that conditions for

*L*< − 200 m are rarely observed.

*wT*are, therefore, shown in Fig. 6 for cases with shorter fetch (upwind distance to land of 1500–2000 m), of height

*h*

_{b}= 120 m, and with

*L*= − 100 m (black solid curve),

*L*= − 20 m (dashed black curve) and

*L*= − 5 m (red curve), which represent conditions with mountains located upstream of the fjord of different roughness and boundary-layer height. As the cospectral characteristics of Fig. 6 are qualitatively consistent with the shape of the normalized spectra

*nC*

_{wt}in Fig. 5, the topography is not likely to be responsible for the change of the turbulent characteristics when approaching UVCN conditions. As the atmospheric conditions approach neutrality from the unstable side, a high-frequency peak appears at

*L*= − 20 m, where, similar to the long-fetch case during more unstable conditions (Fig. 5, red curve), the small-scale turbulence is not observed for

*L*= –5 m (red curve, Fig. 6). For

*L*= − 100 m (black solid curve, Fig. 6), the influence from the low-frequency peak almost vanishes, and the normalized cospectrum of

*wT*is dominated by the peak at

*f*≈ 0.5 Hz.

### 4.3 Quadrant Analysis

*x*and

*y*are presented in an

*x*–

*y*plane numbered according to quadrant I (

*x*> 0 and

*y*> 0), quadrant II (

*x*< 0 and

*y*> 0), quadrant III (

*x*< 0 and

*y*< 0), and quadrant IV (

*x*> 0,

*y*< 0), with

*x*=

*T*and

*y*=

*w*in Fig. 7, and

*x*=

*C*and

*y*=

*w*in Fig. 8. Quadrants I and III (II and IV) give a positive (negative) contribution to the upwards heat flux. The hyperbolic hole of size

*H*introduced by Willmarth and Lu (1974) and defined as

*x*ˈ,

*y*ˈ) lies on a hyperbolic function bounding the whole region in the

*x*–

*y*plane for each quadrant. By varying the value of

*H*from zero to 10, the flux fraction from the different quadrants can be studied for flux events of magnitude one to 10 times that of the average flux. Using the method from Raupach (1981), the flux fraction

*S*

_{iH}is determined from

*i*refers to the quadrant number, and the brackets indicate a conditional average, which is formally defined from the conditioning function

*I*

_{iH}defined as

*I*

_{iH}= 1 within the

*i*th quadrant, and \( \left| {x'y'} \right| \ge H\left| {\overline{x'y'} } \right| = 0 \) otherwise, giving

Figure 7 shows a quadrant plot for a moderately unstable case with *L* = − 5 m (red) and a UVCN situation with *L* = − 300 m (black), which is also shown in Fig. 5 (green). For the moderately unstable case, the majority of the flux is constrained to quadrant I, implying that the flux originates from an upwards transfer of warm air. The case related to *L* = − 300 m displays a different behaviour, with a large part of the positive contribution to the heat flux originating from quadrant III, corresponding to a downwards transfer of cold air from above. A closer inspection of the case related to *L* = − 300 m shows that for *H* = 4, the sum of the flux fraction is 0.66 and *S*_{3,4} = 0.25, meaning that 66% of the flux occurs in events where the flux is more than four times the average value, and where the flux fraction from quadrant III is 25%. For the more unstable case related to *L* = − 5 m with *H* = 4, the sum of the flux fractions is 0.49, and the flux fraction from quadrant III is below 3%.

### 4.4 Implications for the Air–Sea Gas Transfer of CO_{2}

Section 4.2 shows that the vertical turbulent flux of temperature is enhanced as conditions become neutral from the unstable side. As mentioned earlier, the enhanced fluxes of temperature and humidity during UVCN conditions reported in Smedman et al. (2007a, b) and Sahlée et al. (2008a, b) are the result of the different properties (colder and drier) of the air aloft, which is transported downwards by detached eddies. The quadrant analysis of the heat flux presented in Fig. 7 also shows an enhanced contribution from downdrafts of cold air for the UVCN regime, which possibly enhance the magnitude of the flux *wT*, and cause the increase in the value of *C*_{H} for this regime. For CO_{2}, while we do not expect as large differences in concentration between the upper and lower part of the atmospheric surface layer as for temperature, it is possible that the imprints of the additional small-scale turbulence increase the magnitude of the water-side turbulence, and thereby the transfer velocity of the air–sea transfer of CO_{2}. In Fig. 8, a quadrant analysis is presented for three cases with *L* ≈ − 6 m (red dot), *L* ≈ − 30 m (black stars) and *L* = − 150 m (black dots), with the positive contributions to the measured downwards flux *F*_{c} from quadrants II and IV. Similar to the quadrant analysis of the cospectrum *wT* (Fig. 7), the increasing significance of downdrafts when approaching the UVCN regime are also observed for the flux *F*_{c} (here quadrant IV) when *L* = − 150 m.

*wC*for the cases

*L*= − 150 m (green),

*L*= − 100 m (black solid),

*L*= − 50 m (black dashed) and

*L*= − 5 m (red) are shown, and present a behaviour qualitatively similar to the

*wT*cospectra (Fig. 5). For

*L*= − 5 m, the cospectrum of

*wC*shows a maximum at 0.03 Hz, but a second peak near 1 Hz is present in the high-frequency part of the cospectrum for

*L*= − 50 m, which grows in magnitude as conditions become closer to neutral, with the cospectrum for

*L*= − 100 m displaying a plateau shape. For

*L*= − 150 m representing the UVCN regime (the same case as in Fig. 8), the low-frequency peak has almost vanished, and instead the maximum at 1 Hz is very distinct.

*k*

_{660}is revealed (Fig. 10). Here, data are separated by wind speed, with

*U*> 6.5 m s

^{−1}denoted by red dots, and

*U*< 6.5 m s

^{−1}by grey dots. During more unstable conditions, the gas-transfer velocities are well described by the sum of

*k*

_{wsc}and

*k*

_{W09}, so that the mean value of

*k*

_{660}− (

*k*

_{wsc}+

*k*

_{W09}) scatters around zero. For data closer to neutral conditions corresponding to −0.2 <

*z/L*< − 0.1, the mean value of

*k*

_{660}− (

*k*

_{wsc}+

*k*

_{W09}) increases with

*z/L*, but a larger scatter can be observed, where the case

*L*≈ − 30 m has similar flux characteristics as the moderately unstable data (black stars, Fig. 8), and is associated with a low value of

*k*

_{660}− (

*k*

_{wsc}+

*k*

_{W09}) (black circle, Fig. 10).

As conditions became more neutral and *z/L* > − 0.1 (see the black dashed line in Fig. 10), a different behaviour is also observed for the gas-transfer velocities of CO_{2}; the scatter decreases and as much as 80% of the data attain values *k*_{660} − (*k*_{wsc} +* k*_{W09}) > 10 cm h^{−1}. The data within this regime are characterized by larger values of *u*_{*}, resulting in enhanced water-side turbulence, and an enhanced contribution of the CO_{2} flux from downdrafts of air with higher concentrations of CO_{2}, such as the case *L* = − 150 m (green circle), which is also presented in Fig. 8 (black dots) and Fig. 9 (green curve).

## 5 Summary and Conclusions

In winter, a CBL develops over the high Arctic fjord where the height of the boundary layer increases with increasing distance from land. The combination of a large air–sea temperature gradient and relatively high wind speed results in a well-mixed boundary layer with stability −1 < *z/L* < − 0.03. During conditions with stability −0.2 < *z/L* < 0, measurements show enhanced vertical fluxes of heat not associated with the local gradient. From being relatively constant for *z*/*L* < − 0.15, the bulk transfer coefficient increases from a typical mean value of *C*_{H} = 0.0015 to *C*_{H} = 0.0018 for *z/L* = − 0.075. The increase of the bulk transfer as a function of wind speed is not as prominent, which is probably a result of the large variation in temperature gradient. The cospectra of *wT* show that the enhanced heat transfer is associated with small-scale turbulence with a peak at around *f* = 1 Hz, which gradually grows in magnitude as conditions became more neutral, and the relative contribution from the low-frequency peak at *f* = 0.003 Hz decreases in magnitude. For *L* = − 300 m, the high-frequency maximum dominates the normalized cospectrum of *wT*. Simultaneously, the contribution from downdrafts to the total heat flux increases from 3% for *L* = − 5 m to 25% of the flux for *L* = − 300 m. This is the signature of the UVCN regime presented in a series of papers.

Small-scale turbulence, which is potentially caused by detached eddies, also affects the air–sea exchange of CO_{2}. A quadrant analysis of the CO_{2} flux shows that, as conditions approach neutral and the Obukhov length decreases from *L* = − 30 m to *L* = − 150 m, the contribution to the CO_{2} flux from downdrafts of air with higher concentrations of CO_{2} increases. Similar to the flux *wT*, the increased contribution from downdrafts to the air–sea CO_{2} flux is found to coincide with the formation and increase in a high-frequency peak in the cospectra for *wC*. After removing the effect from the two dominant processes affecting the gas-transfer velocity using published parametrizations of water-side convection (*k*_{wsc}) and shear-induced turbulence from the mean wind speed (*k*_{W09}), the gas-transfer velocity was examined, showing the values of *k*_{660} − (*k*_{W09} + *k*_{wsc}) scattered around zero for moderately unstable conditions. However, when approaching the UVCN regime (*z/L* > − 0.1 and *U* > 6.5 m s^{−1}), the values of *k*_{660} − (*k*_{W09} + *k*_{wsc}) are found to increase, where as much as 80% of the data take values *k*_{660} − (*k*_{W09} + *k*_{wsc}) > 0.1 m h^{−1}. These results are somewhat surprising since one does not expect the vertical gradient of CO_{2} in the atmosphere to be as large as the vertical gradient for temperature. We speculate that a part of the enhanced CO_{2} flux is due to imprints on the water surface by the additional small-scale turbulence resulting in increased levels of water-side turbulence.

In summary, we show the possible importance of the UVCN regime for the air–sea exchange of heat in the Arctic during winter, and that the UVCN regime affects the air–sea exchange of CO_{2}, becoming significant for stabilities *z/L* ≥ –0.1. During the nearly 2 months of continuous measurements, as much as 30% of the data were associated with conditions −0.1 ≤ *z/L* < 0. We believe that a larger dataset of gas-transfer velocities would emphasize the relevance of the UVCN regime for air–sea gas exchange.

## Notes

### Acknowledgements

The authors wish to thank Tor de Lange at the Geophysical Institute, University of Bergen, Norway for his useful support and technical assistance during the fieldwork. Data supporting the results will be provided upon request.

## References

- Anderson DE, Verma SB (1985) Turbulence spectra of CO
_{2}, water vapour temperature and wind velocity fluctuations over a crop surface. Boundary-Layer Meteorol 33:1–14CrossRefGoogle Scholar - Andersson A, Rutgersson A, Sahlée E (2014) Using a high-frequency fluorescent oxygen probe in atmospheric eddy covariance applications. J Atmos Ocean Technol 31:2498–2511. https://doi.org/10.1175/JTECH-D-13-00249.1 CrossRefGoogle Scholar
- Andersson A, Falck E, Sjöblom A, Kljun N, Sahlée E, Omar AM, Rutgersson A (2017) Air–sea gas transfer in high Arctic fjords. J Geophys Lett. https://doi.org/10.1002/2016gl072373
- Andreas EL, Cash BA (1999) Convective heat transfer over wintertime leads and polynyas. J Geophys Res Oceans 104(C11):25721–25734CrossRefGoogle Scholar
- Andreas EL, Murphy B (1986) Bulk transfer coefficients for heat and momentum over leads and polynyas. J Phys Oceanogr 16:1875–1883CrossRefGoogle Scholar
- Asher WE, Wanninkhof R (1998) The effect of bubble-mediated gas transfer on purposeful dual-gaseous tracer experiments. J Geophys Res 103:10555–10560CrossRefGoogle Scholar
- Bell TG, Landwehr S, Miller SD, de Bruyn WJ, Callaghan AH, Scanlon B, Ward B, Yang M, Saltzman ES (2017) Estimation of bubble-mediated air–sea gas exchange from concurrent DMS and CO
_{2}transfer velocities at intermediate–high wind speeds. Atmos Chem Phys 17:9019–9033. https://doi.org/10.5194/acp-17-9019-2017 CrossRefGoogle Scholar - Drushka K, Asher WE, Ward B, Walesby K (2016) Understanding the formation and evolution of rain-formed fresh lenses at the ocean surface. J Geophys Res Oceans 121:2673–2689. https://doi.org/10.1002/2015JC011527 CrossRefGoogle Scholar
- Else BGT, Papakyriakou TN, Galley RJ, Drennan WM, Miller LA, Thomas H (2011) Wintertime CO
_{2}fluxes in an Arctic polynya using eddy covariance: Evidence for enhanced air–sea gas transfer during ice formation. J Geophys Res Oceans 116(C9)Google Scholar - Garratt JR (1992) The atmospheric boundary layer. Cambridge University Press, CambridgeGoogle Scholar
- Ho DT, Bliven LF, Wanninkhof R, Schlosser P (1997) The effect of rain on air–water gas exchange. Tellus B 49:149–158CrossRefGoogle Scholar
- Ho DT, Zappa CJ, McGillis WR, Bliven LF, Ward B, Dacey JWH, Schlosser P, Hendriks MB (2004) Influence of rain on air–sea gas exchange: lessons from a model ocean. J Geophys Res 109:C08S18CrossRefGoogle Scholar
- Högström U (1996) Review of some basic characteristic of the atmospheric surface layer. Boundary-Layer Meteorol 78:215–246CrossRefGoogle Scholar
- Högström U, Hunt JCR, Smedman A (2002) Theory and measurements for turbulence spectra and variances in the atmospheric neutral surface layer. Boundary-Layer Meteorol 103(1):101–124CrossRefGoogle Scholar
- Hunt JCR, Carlotti P (2001) Statistical structure at the wall of the high Reynolds number turbulent boundary layer. Flow Turbul Combust 66:453–475CrossRefGoogle Scholar
- Hunt JC, Morrison JF (2000) Eddy structure in turbulent boundary layers. Eur J Mech B/Fluids 19(5):673–694CrossRefGoogle Scholar
- Jeffery C, Woolf D, Robinson I, Donolon C (2007) One-dimensional modelling of convective CO
_{2}exchange in the tropical Atlantic. Ocean Modell 19(3–4):161–182CrossRefGoogle Scholar - Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface layer turbulence. Q J Roy Meteorol Soc 98:563–589CrossRefGoogle Scholar
- Katul G, Kuhn G, Schieldge J, Hsieh C-I (1997) The ejection-sweep character of scalar fluxes in the unstable surface layer. Boundary-Layer Meteorol 83:1–26CrossRefGoogle Scholar
- Kilpeläinen T, Sjöblom A (2010) Momentum and sensible heat exchange in an ice-free Arctic fjord. Boundary-Layer Meteorol 134(1):109–130CrossRefGoogle Scholar
- Le Quéré C, Moriarty R, Andrew RM, Peters GP, Ciais P, Friedlingstein P, Jones SD, Sitch S, Tans P, Arneth A, Boden TA, Bopp L, Bozec Y, Canadell JG, Chini LP, Chevallier F, Cosca CE, Harris I, Hoppema M, Houghton RA, House JI, Jain AK, Johannessen T, Kato E, Keeling RF, Kitidis V, Klein-Goldewijk K, Koven C, Landa CS, Landschützer P, Lenton A, Lima ID, Marland G, Mathis JT, Metzl N, Nojiri Y, Olsen A, Ono T, Peng S, Peters W, Pfeil B, Poulter B, Raupach MR, Regnier P, Rödenbeck C, Saito S, Salisbury JE, Schuster U, Schwinger J, Séférian R, Segschneider J, Steinhoff T, Stocker BD, Sutton AJ, Takahashi T, Tilbrook B, van der Werf GR, Viovy N, Wang Y-P, Wanninkhof R, Wiltshire A, Zeng N (2015) Global carbon budget 2014. Earth Syst Sci Data 7(1):47–85. https://doi.org/10.5194/essd-7-47-2015 CrossRefGoogle Scholar
- Liss PS, Merlivat L (1986) Air–sea gas exchange rates: introduction and synthesis. In: Buat-Menard P (ed) The Role of Air-Sea Exchange in Geochemical Cycling. Reidel, Dordrecht, pp 113–127CrossRefGoogle Scholar
- Lu SS, Willmarth WW (1973) Measurements of the structure of the Reynolds stress in a turbulent boundary layer. J Fluid Mech 60:481–511CrossRefGoogle Scholar
- MacIntyre S, Eugster W, Kling GW (2002) The critical importance of buoyancy flux for gas flux across the air–water interface, in: Donelan MA, Drennan WM, Saltzman ES, Wanninkhof R (eds) Gas Transfer at Water Surfaces, Geophysical Monograph, American Geophysical Union, Washington DC, vol 127, pp 13–28Google Scholar
- Mason PJ, Sykes RI (1982) A two-dimensional numerical study of horizontal roll vortices in an inversion capped planetary boundary layer. Q J R Meteorol Soc 108:801–823CrossRefGoogle Scholar
- Norman M, Rutgersson A, Sörensen LL, Sahlée E (2012) Methods for estimating air–sea fluxes of CO
_{2}using high frequency measurements. Boundary-Layer Meteorol 144:379–400. https://doi.org/10.1007/s10546-012-9730-9 CrossRefGoogle Scholar - Ohtaki E, Matsui T (1982) Infrared device for simultaneous measurement of fluctuations of atmospheric carbon dioxide and water vapor. Boundary-Layer Meteorol 24:109–119CrossRefGoogle Scholar
- Othaki E (1982) Kolmogorov constant for carbon dioxide in the atmospheric surface layer over a paddy field. Boundary-Layer Meteorol 23(2):153–159CrossRefGoogle Scholar
- Raupach MR (1981) Conditional statistics of Reynolds stress in roughwall and smooth-wall turbulent boundary layers. J Fluid Mech 108:363–382CrossRefGoogle Scholar
- Rutgersson A, Smedman A (2010) Enhanced air–sea CO
_{2}transfer due to water-side convection. J Mar Syst 80(1):125–134CrossRefGoogle Scholar - Rutgersson A, Smedman A, Sahlée E (2011) Oceanic convective mixing and the impact on air–sea gas transfer velocity. Geophys Res Lett 38(2):L02602. https://doi.org/10.1029/2010GL045581 CrossRefGoogle Scholar
- Sahlée E, Smedman A, Högström U, Rutgersson A (2008a) Reevaluation of the bulk exchange coefficient for humidity at sea during unstable and neutral conditions. J Phys Oceangr 38(1):257–272CrossRefGoogle Scholar
- Sahlée E, Smedman A, Högström U, Rutgersson A (2008b) Spectra of CO2 and water wapour in the marine atmospheric surface layer. Boundary-Layer Meteorol 126(2):279–295CrossRefGoogle Scholar
- Sahlée E, Smedman A, Rutgersson A, Högström U (2008c) Influence of a new turbulence regime on the global air–sea heat fluxes. J Clim 21(22):5925–5941CrossRefGoogle Scholar
- Sahlée E, Rutgersson A, Podgrajsek E, Bergström H (2014) Influence from surrounding land on the turbulence measurements above a lake. Boundary-Layer Meteorol 150(2):235–258CrossRefGoogle Scholar
- Sjöblom A, Smedman A (2004) Comparison between eddy-correlation and inertial dissipation methods in the marine atmospheric surface layer. Boundary-layer Meteorol 110(2):141–164CrossRefGoogle Scholar
- Smedman A, Högström U, Hunt JCR, Sahlée E (2007a) Heat/mass transfer in the slightly unstable atmospheric surface layer. Q J R Meteorol Soc 133:37–51CrossRefGoogle Scholar
- Smedman A, Högström U, Sahlée E, Johansson C (2007b) Critical reevaluation of the bulk transfer coefficient for sensible and latent heat over the ocean during unstable and neutral conditions. Q J R Meteorol Soc 1:227–250Google Scholar
- Tetzlaff A, Lüpkes C, Hartmann J (2015) Aircraft-based observations of atmospheric boundary-layer modification over Arctic leads. Q J R Meteorol Soc 141:2839–2856. https://doi.org/10.1002/qj.2568 CrossRefGoogle Scholar
- Verma S, Anderson D (1984) Kolmogorov constants for CO
_{2}, wind velocity, air temperature, and humidity fluctuations over a crop surface. Boundary-Layer Meteorol 28:161–167. https://doi.org/10.1007/BF00119461 CrossRefGoogle Scholar - Vickers D, Mahrt L (1997) Quality control and flux sampling problems for tower and aircraft data. J Atmos Ocean Technol 14:512–526CrossRefGoogle Scholar
- Wanninkhof R (1992) Relationship between wind speed and gas exchange over the ocean. J Geophys Res 97:7373–7382CrossRefGoogle Scholar
- Wanninkhof R, Asher WE, Ho DT, Sweeney C, McGillis WR (2009) Advances in quantifying air–sea gas exchange and environmental forcing. Annu Rev Mar Sci 1:213–244CrossRefGoogle Scholar
- Webb EK, Pearman GI, Leuning R (1980) Correction of flux measurements for density effects due to heat water vapor transport. Q J R Meteorol Soc 106:85–100CrossRefGoogle Scholar
- Willmarth WW, Lu SS (1974) Structure of the Reynolds stress and the occurrence of bursts in the turbulent boundary layer. Adv Geophys 18A:287–314Google Scholar
- Woolf DK (1993) Bubbles and the air–sea transfer velocity of gases. Atmos-Ocean 31(4):517–540CrossRefGoogle Scholar
- Woolf DK (1997) Bubbles and their role in air–sea gas exchange. In: Liss P, Duce R (eds) The Sea Surface and Global Change. Cambridge University Press, New York, pp 173–205CrossRefGoogle Scholar
- Zappa C, Ho D, McGillis WR, Banner M, Dacey J, Bliven L, Ma B, Nystuen J (2009) Rain-induced turbulence and air–sea gas transfer. J Geophys Res 114:C07009. https://doi.org/10.1029/2008JC005008 CrossRefGoogle Scholar

## Copyright information

**Open Access**This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.