Direct numerical simulation of turbulent mass transfer at the surface of an open channel flow

We present direct numerical simulation results of turbulent open channel flow at bulk Reynolds numbers up to 12 000, coupled with (passive) scalar transport at Schmidt numbers up to 200. Care is taken to capture the very large-scale motions which appear already for relatively modest Reynolds numbers. The transfer velocity at the flat, free surface is found to scale with the Schmidt number to the power ‘ $-1/2$ ’, in accordance with previous studies and theoretical predictions for uncontaminated surfaces. The scaling of the transfer velocity with Reynolds number is found to vary, depending on the Reynolds number definition used. To compare the present results with those obtained in other systems, we define a turbulent Reynolds number at the edge of the surface-influenced layer. This allows us to probe the two-regime model of Theofanous et al. (Intl J. Heat Mass Transfer, vol. 19, 1976, pp. 613–624), which is found to correctly predict that small-scale vortices significantly affect the mass transfer for turbulent Reynolds numbers larger than 500. It is further established that the root mean square of the surface divergence is, on average, proportional to the mean transfer velocity. However, the spatial correlation between instantaneous surface divergence and transfer velocity tends to decrease with increasing Schmidt number and increase with increasing Reynolds number. The latter is shown to be caused by an enhancement of the correlation in high-speed regions, which in turn is linked to the spatial distribution of surface-parallel vortices.

Accounting for surface waves improves gas flux estimation at high wind speed in a large lake

The gas transfer velocity (k) is a major source of uncertainty when assessing the magnitude of lake gas exchange with the atmosphere. For the diversity of existing empirical and process-based k models, the transfer velocity increases with the level of turbulence near the air–water interface. However, predictions for k can vary by a factor of 2 among different models. Near-surface turbulence results from the action of wind shear, surface waves, and buoyancy-driven convection. Wind shear has long been identified as a key driver, but recent lake studies have shifted the focus towards the role of convection, particularly in small lakes. In large lakes, wind fetch can, however, be long enough to generate surface waves and contribute to enhance gas transfer, as widely recognised in oceanographic studies. Here, field values for gas transfer velocity were computed in a large hard-water lake, Lake Geneva, from CO2 fluxes measured with an automated (forced diffusion) flux chamber and CO2 partial pressure measured with high-frequency sensors. k estimates were compared to a set of reference limnological and oceanic k models. Our analysis reveals that accounting for surface waves generated during windy events significantly improves the accuracy of k estimates in this large lake. The improved k model is then used to compute k over a 1-year time period. Results show that episodic extreme events with surface waves (6 % occurrence, significant wave height > 0.4 m) can generate more than 20 % of annual cumulative k and more than 25 % of annual net CO2 fluxes in Lake Geneva. We conclude that for lakes whose fetch can exceed 15 km, k models need to integrate the effect of surface waves.

Air–sea exchange of acetone, acetaldehyde, DMS and isoprene at a UK coastal site

Volatile organic compounds (VOCs) are ubiquitous in the atmosphere and are important for atmospheric chemistry. Large uncertainties remain in the role of the ocean in the atmospheric VOC budget because of poorly constrained marine sources and sinks. There are very few direct measurements of air–sea VOC fluxes near the coast, where natural marine emissions could influence coastal air quality (i.e. ozone, aerosols) and terrestrial gaseous emissions could be taken up by the coastal seas. To address this, we present air–sea flux measurements of acetone, acetaldehyde and dimethylsulfide (DMS) at the coastal Penlee Point Atmospheric Observatory (PPAO) in the south-west UK during the spring (April–May 2018). Fluxes of these gases were measured simultaneously by eddy covariance (EC) using a proton-transfer-reaction quadrupole mass spectrometer. Comparisons are made between two wind sectors representative of different air–water exchange regimes: the open-water sector facing the North Atlantic Ocean and the terrestrially influenced Plymouth Sound fed by two estuaries. Mean EC (± 1 standard error) fluxes of acetone, acetaldehyde and DMS from the open-water wind sector were −8.0 ± 0.8, −1.6 ± 1.4 and 4.7 ± 0.6 µmol m−2 d−1 respectively (“−” sign indicates net air-to-sea deposition). These measurements are generally comparable (same order of magnitude) to previous measurements in the eastern North Atlantic Ocean at the same latitude. In comparison, the Plymouth Sound wind sector showed respective fluxes of −12.9 ± 1.4, −4.5 ± 1.7 and 1.8 ± 0.8 µmol m−2 d−1. The greater deposition fluxes of acetone and acetaldehyde within the Plymouth Sound were likely to a large degree driven by higher atmospheric concentrations from the terrestrial wind sector. The reduced DMS emission from the Plymouth Sound was caused by a combination of lower wind speed and likely lower dissolved concentrations as a result of the estuarine influence (i.e. dilution). In addition, we measured the near-surface seawater concentrations of acetone, acetaldehyde, DMS and isoprene from a marine station 6 km offshore. Comparisons are made between EC fluxes from the open-water and bulk air–sea VOC fluxes calculated using air and water concentrations with a two-layer (TL) model of gas transfer. The calculated TL fluxes agree with the EC measurements with respect to the directions and magnitudes of fluxes, implying that any recently proposed surface emissions of acetone and acetaldehyde would be within the propagated uncertainty of 2.6 µmol m−2 d−1. The computed transfer velocities of DMS, acetone and acetaldehyde from the EC fluxes and air and water concentrations are largely consistent with previous transfer velocity estimates from the open ocean. This suggests that wind, rather than bottom-driven turbulence and current velocity, is the main driver for gas exchange within the open-water sector at PPAO (depth of ∼ 20 m).

Natural variability in air–sea gas transfer efficiency of CO2

The flux of CO2 between the atmosphere and the ocean is often estimated as the air–sea gas concentration difference multiplied by the gas transfer velocity (K660). The first order driver for K660 over the ocean is wind through its influence on near surface hydrodynamics. However, field observations have shown substantial variability in the wind speed dependencies of K660. In this study we measured K660 with the eddy covariance technique during a ~ 11,000 km long Southern Ocean transect. In parallel, we made a novel measurement of the gas transfer efficiency (GTE) based on partial equilibration of CO2 using a Segmented Flow Coil Equilibrator system. GTE varied by 20% during the transect, was distinct in different water masses, and related to K660. At a moderate wind speed of 7 m s−1, K660 associated with high GTE exceeded K660 with low GTE by 30% in the mean. The sensitivity of K660 towards GTE was stronger at lower wind speeds and weaker at higher wind speeds. Naturally-occurring organics in seawater, some of which are surface active, may be the cause of the variability in GTE and in K660. Neglecting these variations could result in biases in the computed air–sea CO2 fluxes.

Uncertainties in eddy covariance air–sea CO₂ flux measurements and implications for gas transfer velocity parameterisations

Air–sea carbon dioxide (CO2) flux is often indirectly estimated by the bulk method using the air–sea difference in CO2 fugacity (ΔfCO2) and a parameterisation of the gas transfer velocity (K). Direct flux measurements by eddy covariance (EC) provide an independent reference for bulk flux estimates and are often used to study processes that drive K. However, inherent uncertainties in EC air–sea CO2 flux measurements from ships have not been well quantified and may confound analyses of K. This paper evaluates the uncertainties in EC CO2 fluxes from four cruises. Fluxes were measured with two state-of-the-art closed-path CO2 analysers on two ships. The mean bias in the EC CO2 flux is low, but the random error is relatively large over short timescales. The uncertainty (1 standard deviation) in hourly averaged EC air–sea CO2 fluxes (cruise mean) ranges from 1.4 to 3.2 mmolm-2d-1. This corresponds to a relative uncertainty of ∼ 20 % during two Arctic cruises that observed large CO2 flux magnitude. The relative uncertainty was greater (∼ 50 %) when the CO2 flux magnitude was small during two Atlantic cruises. Random uncertainty in the EC CO2 flux is mostly caused by sampling error. Instrument noise is relatively unimportant. Random uncertainty in EC CO2 fluxes can be reduced by averaging for longer. However, averaging for too long will result in the inclusion of more natural variability. Auto-covariance analysis of CO2 fluxes suggests that the optimal timescale for averaging EC CO2 flux measurements ranges from 1 to 3 h, which increases the mean signal-to-noise ratio of the four cruises to higher than 3. Applying an appropriate averaging timescale and suitable ΔfCO2 threshold (20 µatm) to EC flux data enables an optimal analysis of K.

Oceanic eddy-induced modifications to air–sea heat and CO2 fluxes in the Brazil-Malvinas Confluence

Sea surface temperature (SST) anomalies caused by a warm core eddy (WCE) in the Southwestern Atlantic Ocean (SWA) rendered a crucial influence on modifying the marine atmospheric boundary layer (MABL). During the first cruise to support the Antarctic Modeling and Observation System (ATMOS) project, a WCE that was shed from the Brazil Current was sampled. Apart from traditional meteorological measurements, we used the Eddy Covariance method to directly measure the ocean–atmosphere sensible heat, latent heat, momentum, and carbon dioxide (CO2) fluxes. The mechanisms of pressure adjustment and vertical mixing that can make the MABL unstable were both identified. The WCE also acted to increase the surface winds and heat fluxes from the ocean to the atmosphere. Oceanic regions at middle and high latitudes are expected to absorb atmospheric CO2, and are thereby considered as sinks, due to their cold waters. Instead, the presence of this WCE in midlatitudes, surrounded by predominantly cold waters, caused the ocean to locally act as a CO2 source. The contribution to the atmosphere was estimated as 0.3 ± 0.04 mmol m−2 day−1, averaged over the sampling period. The CO2 transfer velocity coefficient (K) was determined using a quadratic fit and showed an adequate representation of ocean–atmosphere fluxes. The ocean–atmosphere CO2, momentum, and heat fluxes were each closely correlated with the SST. The increase of SST inside the WCE clearly resulted in larger magnitudes of all of the ocean–atmosphere fluxes studied here. This study adds to our understanding of how oceanic mesoscale structures, such as this WCE, affect the overlying atmosphere.