An eddy covariance system to measure fluxes of momentum, sensible heat, latent heat, and CO2 was installed on a 10 m tower located on the northwest side of Qikirtaarjuk Island, a low-lying island (500×200 m) in Dease Strait, roughly 35 km west of Cambridge Bay, Nunavut (Fig. 1). Qikirtaarjuk Island is the southernmost island in a chain that extends across Dease Strait, creating active tidal straits that produce polynyas in the fall and early spring (Fig. 1). Except for the islands north of the tower, the closest being Unihitak Island 3.5 km away, the tower has unimpeded fetch on the order or 50 km from large-angled swaths to the east and west. This ensures that much of the flux footprint represents only water and not a mix of water and land.

The tower was configured with an array of instruments (Fig. 2) to measure mean meteorological variables (logged as 1 min averages on a Campbell Scientific CR1000 data logger) and high-frequency flux variables (10 Hz; CR3000 data logger). Mean wind speed and direction were measured using a 2-D propeller vane anemometer (RM Young; Marine Wind Monitor) mounted at 7.8 m above ground level (a.g.l.). Three temperature and relative humidity probes (Campbell Scientific HMP45C) were mounted at 9.6 m, 5 m, and 2.2 m a.g.l. A net radiometer (Kipp & Zonen; CNR4) was mounted 2.8 m a.g.l.

Fluxes of momentum (τ, N m-2), sensible heat (HS, W m-2), latent heat (HL, W m-2), and CO2 (FCO2, mmol m-2 d-1) were calculated for 20 min intervals as τ=ρa‾u′w′‾2+v′w′‾2,HS=ρa‾cpw′T′‾,HL=ρa‾Lvw′q′‾,FCO2=ρa‾w′c′‾, where u,v, and w (m s-1) are the along-wind, cross-wind, and vertical wind components, respectively, ρa‾ (mol m-3) is the mean dry air density, cp (J kg-1 K-1) is the specific heat capacity of air, T (K) is the dry air temperature, Lv (J kg-1) is the latent heat of vaporization, q (kg kg-1) is the specific humidity, c is the CO2 mixing ratio (µmolmol-1), primes indicate fluctuations about the mean, and the overbar corresponds to the time average. The dry air temperature was calculated from the sonic temperature after correction for the effect of water vapor on air density and speed of sound (Schotanus et al., 1983).

The mean wind speed from the sonic anemometer was adjusted to neutral stability at 10 m height using a semilogarithmic wind profile and assuming a constant flux layer according to U10n=(u∗/κ)ln(10/z0), where u∗=(τ/ρ)1/2 is the friction velocity (m s-1) measured by CSAT3, κ is the von Karman constant of 0.4, z is the measurement height, and z0 is the roughness length (m) calculated as z0=zexp-κU‾zu∗-ψmzL, where ψm represents the stability function of Paulson (1970) for unstable stratification and Grachev et al. (2007) for stable stratification, both functions of z/L, where z is the measurement height and L is the Obukhov length, calculated as L=Tκgu∗3w′T′‾+0.61T1+0.61Qw′q′‾, where g is the acceleration due to gravity, T is the air temperature, Q is the specific humidity, and w′T′‾ and w′q′‾ are the turbulent fluxes of temperature and water vapor (Andreas et al., 2010).

Quality control criteria were used to select intervals that passed the underlying assumptions of eddy covariance. First, intervals were selected that exhibited stationarity, following RNcov=(w′x′‾)5‾-(w′x′‾)20(w′x′‾)20≤0.3, where (w′x′‾)5‾ represents the mean of the four 5 min turbulent flux subintervals and (w′x′‾)20 represents the turbulent flux of the whole 20 min interval (Blomquist et al., 2014). The purpose of this criterion is to identify and remove intervals in which large-scale phenomena (e.g., mesoscale motions), outside the frequency range of turbulent fluxes, are contributing to the measured flux.

A second quality control criterion selected for wind directions of -150 to 150∘ (relative to the anemometer) to eliminate winds from aft that were affected by flow distortion from the instruments and tower frame. The size and shape of the island (0.2 km wide and extending 0.5 km behind the tower) meant the remaining wind directions from the back hemisphere had some degree of island contributing to their flux footprint. To estimate the impact of the island on the flux measurements, we ran the flux footprint model of Kljun et al. (2015). Using the mean meteorological conditions from each 5∘ wind sector it was found that on average the island accounted for 5 % of the footprint for wind directions from the front hemisphere (-90 to 90∘). From the back wind sectors (-150 to -90∘ and 90 to 150∘) 44 % of the flux footprint was represented by the island. However, because extent of the footprint varied with meteorological conditions, there were many periods during which these wind directions saw minimal influence from the island. The island is bare rock, which means that it should not act as either a source or a sink for CO2. This means that the magnitudes of CO2 fluxes from these back sectors are somewhat underestimated, by a factor that most likely scales with the portion of the footprint that falls on the island. Future work is planned to collect field data (i.e., coincident upwind pCO2w data for varying wind directions) to determine if a linear scaling factor could be used to correct flux magnitudes for these wind sectors.

The period reported in this study ranges from 4 May to 1 September 2017, encompassing the transition from full ice coverage to fully open water. From 4 May through 25 May the study area was characterized by snow-covered sea ice. With air temperatures well below 0 ∘C, this period represents winter ice conditions. From 25 May to 25 June melt ponds began to form. Comparing the AMSR2 SIC product to the in situ photographs (which show no open water) suggests that the melt ponds during this period ranged from 0 to 50 % of the surface area. Following this period there was an ice breakup period (25 June to 7 July) which exhibited both ice and open water. This breakup initially occurred directly in front (north) of the tower, creating a polynya that was probably caused by tidal currents in the strait funneled between the islands (Fig. 1). By the end of the breakup period the area was ice-free for the remainder of the summer season.

The meteorology of the study area through the study period shows the strong seasonal shift. The temperature over this period rose from its minimum of -24 ∘C on 5 May, to its maximum of 18 ∘C on 13 August, with over half of the time in between being within ±5∘ of 0 ∘C (Fig. 6b). Incoming solar radiation exhibited strong diurnal trends, with over 75 % of days experiencing peak daytime values greater than 500 W m-2, and nighttime minimum values near zero (Fig. 6a). These oscillations did not result in large diurnal temperature swings. Due to the low temperatures, the relative humidity was typically high, with a mean of 86 % (Fig. 6c). Actual water vapor content of the air was lowest in May, with a mean of 3.3 parts per thousand (ppt), followed by a mean of 7.7 ppt from June to September (Fig. 6h). The CO2 mixing ratio was roughly 410 ppm at the start of May and decreased to 403 ppm by the end of August, indicative of the seasonal trend that occurs when plant biomass consumes atmospheric CO2 in the boreal growing season (Fig. 6g). Wind speed was moderate, ranging between 0 and 16.4 m s-1 with a mean of 5.6±2.7 m s-1. The winds exhibited no distinct change in magnitude over the course of the season (Fig. 6e), and were most commonly from the southeast (105 to 135∘) and the west southwest (235 to 275∘) (Figs. 6f, 7). These directions were generally advantageous due to the large fetch in the east and west directions, the only caveat being the very small island 1.5 km southeast of the tower.

Time series of τ, HS, HL, and FCO2 over the course of this study are shown in Fig. 8. The τ ranged from 0 to 0.41 N m-2, with a mean of 0.05±0.05 N m-2 (Fig. 8a). The range in τ was similar through all different surface conditions, being most strongly influenced by wind speed. The HS showed a diurnal trend (increasing during the day, decreasing at night) throughout much of the study period. The sea surface type also played a role in mean HS, with the flux during full ice cover generally upward, then, during ice breakup and early summer downward, and in the open water at the end of the summer upward again. HL acted similarly to HS, with upward fluxes early in the season (full ice and melt ponds), transitioning to downward fluxes during ice breakup, and upward fluxes under full open water conditions.

FCO2 measured by the dried, closed-path system was low during periods with sea ice cover. During full ice cover FCO2 hovered around zero, with a mean of -0.03±1.21 mmol m-2 d-1. During melt season FCO2 was slightly negative (i.e., downward), with a mean of -0.34±2.04 mmol m-2 d-1. During ice breakup, when the surface was mixed ice and water, FCO2 was downward (mean of -2.9±4.9 mmol m-2 d-1). By the full open water period in August, FCO2 had switched direction and the water was outgassing CO2 to the atmosphere (mean of 3.8±4.7 mmol m-2 d-1).

FCO2 values calculated from the different IRGAs are shown in Fig. 9. Both open-path IRGAs yielded flux values with magnitudes much larger than those from the dried LI-7200, sometimes orders of magnitude larger. For example, during full ice conditions, when the dried LI-7200 measured near-zero FCO2, the LI-7500 and EC150 had means of -22±58 and -32±103 mmol m-2 d-1, respectively.

Because comparisons of FCO2 from different gas analyzers do not have a dependent variable, we used Pearson's correlation coefficient (r) to describe the linear correlations between the two variables (Goodrich et al., 2016). Comparisons of FCO2 from the closed-path LI-7200 against FCO2 from the two open-path IRGAs showed no correlation (Fig. 10a, b), with r=0.04 and r=0.15 for the LI-7500 and EC150, respectively. An orthogonal regression of FCO2 (LI-7500) against FCO2 (EC150) yielded a fit closer to 1 : 1 (Fig. 10c), but with more scatter and an r=0.44. On the other hand, the regression for HL (LI-7500) against HL (EC150) showed a distinct 1 : 1 relationship (Fig. 10d). The correlation coefficient for this case was 0.93, thus showing a strong linear relationship. This suggests that the open-path IRGAs are better suited to measuring HL than FCO2 in this environment.

FCO2 values from all three IRGAs were also compared against heat fluxes, HL and HS (Fig. 11). Negative relationships were found between FCO2 from the open-path IRGAs and heat fluxes. FCO2 from the dried, closed-path IRGA showed no relationship with HL or HS.

During the spring season prior to ice breakup, the dried, closed-path EC system measured FCO2 of -0.25±1.75 mmol m-2 d-1. When only considering sea ice conditions prior to melt pond formation, FCO2 was -0.03±1.21 mmol m-2 d-1. These measurements are within the range measured by previous enclosure measurements, which taken together span from -5.4 to 2.2 mmol m-2 d-1 (Table 1; Delille, 2006; Nomura et al., 2010, 2013; Sejr et al., 2011; Geilfus et al., 2012, 2014, 2015; Delille et al., 2014; Sievers et al., 2015). The measurements also exhibit a sharp divergence from previous open-path EC FCO2 measurements, which at tens to hundreds of mmol m-2 d-1 are several orders of magnitude larger (Semiletov et al., 2004; Zemmelink et al., 2006; Else et al., 2011; Miller et al., 2011; Papakyriakou and Miller, 2011). Unlike the dried, closed-path system, our open-path systems installed at our site did measure FCO2 with similar magnitudes to these previous open-path EC studies, with mean values of -22±58 (LI-7500) and -32±103 (EC150) mmol m-2 d-1.

This disagreement between simultaneous open-path and dried, closed-path systems at our site suggests that the reason for discrepancies between previous chamber and open-path EC measurements was not the result of different scales of measurement, but was rather problems with the ability of open-path EC to resolve fluxes. This is further demonstrated by the poor agreement between the two open-path FCO2 results (Fig. 10c).

Previous undried EC studies over the open ocean have found relationships between heat fluxes (HS and HL) and FCO2 (Landwehr et al., 2014; Sievers et al., 2015). However, in these instances the magnitude of measured FCO2 at high latent heat fluxes exceeds values calculated from bulk FCO2 formula. In their comparison of dried and undried closed-path EC systems, Landwehr et al. (2014) concluded that such relationships represented bias, and did not result from real physical phenomena. They also found that the degree of bias was different for each individual IRGA instrument. While our OP IRGAs found a relationship between heat fluxes and FCO2 our dried, closed-path system did not (Fig. 11). This supports the finding that these relationships represent bias, further evidence that open-path IRGAs do not fully remove the effects of HS and HL in the density correction and/or the instruments' built-in water vapor corrections.

To the best of our knowledge, this study is the first published test of the EC150 against the LI7500 in a marine environment. The two instruments produced similar HL (Fig. 10d), showing that both are capable instruments for measuring water vapor flux. When it came to FCO2, the EC150 values diverged from the dried, closed-path system to a similar degree as the LI-7500 (Fig. 10b). Like the LI-7500, the EC150 also showed a strong negative relationship between FCO2 and both HS and HL (Fig. 11). These findings suggest that the EC150 is affected by the same problems that affect the LI-7500.

However, FCO2 comparison between the EC150 and LI-7500 did not show strong agreement (Fig. 10c). It is possible that the disagreement between the two stems from differences in their design (e.g., the EC150 is not necessarily affected by the same instrument-induced HS as the LI-7500 (Burba et al., 2008) and presumably has a different set of equations accounting for water vapor cross sensitivity). But the overall spurious, high magnitudes for FCO2 appear to stem from problems inherent to the open-path design. The EC150, like the LI-7500, appears to be more appropriate for use in regions with larger magnitude FCO2.

While measuring FCO2 in the same range as chamber measurements shows that the method ameliorates problems associated with open-path systems, it alone is not a full accounting of measurement quality. To further assess the performance of the flux system, we compared our open water results against those from previous studies. To do this we calculated gas transfer velocity, a coefficient which describes the efficiency of gas transport across the air–sea interface. Gas transfer velocity is a more effective comparison than FCO2 because it provides more context. It was calculated by setting our measured flux equal to the bulk CO2 flux formula (FCO2 =ks[pCO2w-pCO2atm]) and rearranging the equation to form k=FCO2s(pCO2w-pCO2atm), where k is the gas transfer velocity, s is the solubility of CO2 in seawater, and pCO2w and pCO2atm are the partial pressure of CO2 in water and the atmosphere, respectively (Wanninkhof and McGillis, 1999). While FCO2 and pCO2atm were continuously measured by the EC system, s and pCO2w were not. They were however, measured aboard the research vessel (RV) Martin Bergmann, which made several courses past the island in August 2017. For the flux intervals that aligned temporally with these passes (all fully open water), we calculated k660 (k adjusted to a Schmidt number (Sc) of 660). The k660 values plotted against U10n (Fig. 12) showed good agreement with previous parameterizations of k660 (Wanninkhof, 1992, 2014). Because the (RV) Martin Bergmann data showed that pCO2w had high temporal and spatial variability in this region, and because we only have three data points, this result should not be interpreted as a new functional form to the k vs. U10n relationship. What it does indicate is that the dried, closed-path flux system is able to resolve FCO2 within an expected range, based on previous results. Conversely, k660 values from the open-path IRGAs were not similar to previous findings. For these three intervals, the mean k660 was 247 cm h-1 for the EC150 and -28 cm h-1 for the LI-7500 (where negative represents counter-gradient flux). This provides additional evidence that the open-path IRGAs are not capable of resolving CO2 fluxes in this environment.

The quality of the flux measurement was also assessed by comparing previous years' measurements of pCO2w to estimated pCO2w (using FCO2) from our study period. Measurements of pCO2w were collected aboard the Canadian Coast Guard (CCGS) Ice Breaker Amundsen near Qikirtaarjuk Island during five previous summers (2010, 2011, 2014, 2015, 2016). August measurements of pCO2w (collected within a 10 km radius of the tower) ranged from 360 to 469 µatm, with a mean of 407±34 µatm. Estimates of pCO2w from our study period were calculated by rearranging Eq. (9) so that pCO2w = FCO2 k-1 s-1 + pCO2atm. As stated above, pCO2atm and FCO2 were measured by the tower. Gas transfer velocity was obtained using the Wanninkhof (2014) parameterization with measured U10n, plus the mean Schmidt number (Sc) from the RV Martin Bergmann dataset (Sc = 1150). Solubility was also estimated as the mean value from the RV Martin Bergmann data (s=48 mol m-3 atm-1).

Using FCO2 from the dried, closed-path IRGA yielded pCO2w estimates ranging from 347 to 481 µatm (10th to 90th percentile) and a median value of 407 µatm, over the course of summer 2017. This matched reasonably well with the range identified by the CCGS Amundsen measurements. Comparatively, the pCO2w values from the open-path IRGAs were not as tightly clustered around a central value (Fig. 13). The fluxes from the LI-7500 and EC150 led to pCO2w estimates ranging from -1255 to 1101 µatm and -1252 to 906 µatm, respectively. These values are far beyond the magnitude observed in this region (and with no physical basis in the case of negative values), further evidence that the open-path IRGAs are not capable of providing accurate FCO2 measurements in the relatively low ΔpCO2 conditions typically found in the marine environment.

The drying system worked as desired, drying the sample air to dew point temperatures of -27.5±7.6 ∘C, compared to the LI-7500 which measured average ambient dew point temperatures of 6.0±7.6 ∘C. Perhaps more importantly it reduced fluctuations in water vapor, reducing the standard deviation in H2O mixing ratio by over an order of magnitude from 0.1±0.2 mmol mol-1 to 0.007±0.008 mmol mol-1. This resulted in reducing the standard deviation of the CO2 mixing ratio from 0.7±1.8 to 0.1±0.1 µmolmol-1. This matches the LI-7200's specification for root mean square noise at a sampling rate of 10 Hz, showing that preconditioning the sample air completely removed the influence of other variables on the CO2 measurement.

As the comparisons between the LI-7200 and LI-7500/EC150 show, drying the air did seem helpful in producing FCO2 that are more in line with expected values. Interestingly, however, there were two occasions when the desiccant's capacity ran out and the closed-path IRGA was receiving sample air with near-ambient water vapor content (Fig. 6h). During those periods of time, the LI-7200 still experienced standard deviations in H2O mixing ratio 3.5 times lower than the open-path LI-7500. Additionally, there was no increase in the variance of FCO2 from the LI-7200 during these periods, and FCO2 magnitudes did not increase to open-path levels. This suggests that even without a dry counterflow, the Nafion drier still improves FCO2 measurements to an acceptable level by reducing fluctuations in water vapor. This makes sense because spikes of moister or drier air will still exchange H2O with a counterflow that is at mean ambient humidity. Without a parallel, undried LI7200 it impossible to quantify how much of the smoothing is from the Nafion compared to the natural “stickiness” of H2O on tube walls. However, the impact of H2O smoothing from tube walls alone was tested in Butterworth and Miller (2016b) with an undried LI7200. It was found that tubing did not fully remove the influence of water vapor on the CO2 flux, and instead showed up as a spurious low-frequency contribution to the flux, which was visible in the flux cospectra. In this study, when the desiccant was exhausted, the cospectra did not indicate interference from water vapor, suggesting that the Nafion played a critical role. This finding may have important implications for the design of future systems (i.e., a system could be designed that uses a Nafion and counterflow, but without a dry air source), and should be investigated further.

In April 2018 as part of the Polar Knowledge Canada-funded CAT-TRAIN project in collaboration with the Arctic Research Foundation, a mobile power station/research lab was installed at the site. This new infrastructure will be used to increase the functionality of the system. Specific additions that are being considered are incorporating waterside pCO2w measurements, to be used to calculate gas transfer velocity continuously through an annual cycle. This would be particularly useful considering the pCO2w measurements from the CCGS Amundsen and the RV Martin Bergmann, which showed that this region often has ΔpCO2 of sufficient magnitude to measure accurate gas transfer velocities.

Additionally, for data redundancy we plan to install a second closed-path greenhouse gas analyzer (CRDS) capable of measuring CO2, H2O, and methane (GGA-FGGA, Los Gatos Research), which we which have only deployed on ships due to the large power consumption. Next spring a planned intercomparison study taking place in Cambridge Bay will add simultaneous enclosure measurements to verify agreement between the two methods. Lastly, the system will be used (in forthcoming papers) to investigate annual gas exchange cycles and process-level questions, including the processes affecting FCO2 during spring melt and autumn freeze-up.