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Understanding the mercury cycle in the Arctic is important due to the harmful bioaccumulation of its toxic form, methylmercury, in wildlife and ultimately Arctic residents. Gaseous elemental mercury (Hg(0)) is relatively well-mixed across the northern hemisphere atmosphere due to its long atmospheric lifetime. Hg(0) can be oxidized, especially in the Arctic spring during halogen-driven depletion events. The resulting gaseous oxidized mercury (Hg(II)) is relatively quickly deposited onto snow, either directly or via condensing onto particles, forming particulate mercury (PHg). It is generally understood that a large fraction of the deposited Hg(II) and PHg is photoreduced to Hg(0) and re-emitted to the atmosphere. However, mercury remaining in the snowpack till melt can become bioavailable through entering the ocean.There is a severe lack of Hg(II) and PHg observations in the central Arctic, particularly over sea ice, limiting our understanding of the mercury cycle in that region and inhibiting us from quantifying mercury budgets in all environmental compartments and particularly where it unfolds its harmful neurotoxic effects. Moreover, most of the observational efforts aiming at creating process understanding focused on spring during mercury depletion events or the snow melt period, leaving large knowledge gaps for fall and winter.Here, we show atmospheric observations of PHg during MOSAiC, measured with an aerosol mass spectrometer in fall and spring over the central Arctic pack ice. In both seasons, PHg concentrations correlate strongly with wind speed and chloride, suggesting a mechanical (wind-driven) process behind atmospheric PHg related partly to blowing snow. In addition, there are significant differences between fall and spring observations (e.g. no atmospheric mercury depletion events in fall), suggesting that various processes are at play.This wind-driven process has hitherto not been reported and is different from observations at land-based stations as well as previous measurements over sea ice that ascribed the formation of PHg to adsorption of Hg(II) onto pre-existing aerosols or diamond dust rather than aerosolization from the snow pack. We hypothesize, based on snow chemical analyzes and literature, that the elevated halide content in snow on sea ice creates complexes of PHg, which are much harder to photoreduce than Hg(II), leading to a larger PHg content in snow. These processes of forming PHg and wind-driven aerosolization have implications for the mercury content of snow and the distances over which PHg is re-deposited after atmospheric transport given that the lifetime of PHg is about one order of magnitude larger than that of Hg(II) in the atmosphere.

The structure and evolution of the atmospheric boundary layer (ABL) under clear-sky fair weather conditions over mountainous terrain is dominated by the diurnal cycle of the surface energy balance and thus strongly depends on surface snow cover. We use data from three passive ground-based infrared spectrometers deployed in the East River Valley in Colorado’s Rocky Mountains to investigate the response of the thermal ABL structure to changes in surface energy balance during the seasonal transition from snow-free to snow-covered ground. Temperature profiles were retrieved from the infrared radiances using the optimal estimation physical retrieval TROPoe. A nocturnal surface inversion formed in the valley during clear-sky days, which was subsequently mixed out during daytime with the development of a convective boundary layer during snow-free periods. When the ground was snow covered, a very shallow convective boundary layer formed, above which the inversion persisted through the daytime hours. We compare these observations to NOAA’s operational High-Resolution-Rapid-Refresh (HRRR) model and find large warm biases on clear-sky days resulting from the model’s inability to form strong nocturnal inversions and to maintain the stable stratification in the valley during daytime when there was snow on the ground. A possible explanation for these model shortcomings is the influence of the model’s relatively coarse horizontal grid spacing (3 km) and its impact on the model’s ability to represent well-developed thermally driven flows, specifically nighttime drainage flows.

Dry deposition to the surface is one of the main removal pathways of tropospheric ozone (O3). We quantified for the first time the impact of O3 deposition to the Arctic sea ice on the planetary boundary layer (PBL) O3 concentration and budget using year-round flux and concentration observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign and simulations with a single-column atmospheric chemistry and meteorological model (SCM). Based on eddy-covariance O3 surface flux observations, we find a median surface resistance on the order of 20,000 s m−1, resulting in a dry deposition velocity of approximately 0.005 cm s−1. This surface resistance is up to an order of magnitude larger than traditionally used values in many atmospheric chemistry and transport models. The SCM is able to accurately represent the yearly cycle, with maxima above 40 ppb in the winter and minima around 15 ppb at the end of summer. However, the observed springtime ozone depletion events are not captured by the SCM. In winter, the modelled PBL O3 budget is governed by dry deposition at the surface mostly compensated by downward turbulent transport of O3 towards the surface. Advection, which is accounted for implicitly by nudging to reanalysis data, poses a substantial, mostly negative, contribution to the simulated PBL O3 budget in summer. During episodes with low wind speed (

Near-surface mercury and ozone depletion events occur in the lowest part of the atmosphere during Arctic spring. Mercury depletion is the first step in a process that transforms long-lived elemental mercury to more reactive forms within the Arctic that are deposited to the cryosphere, ocean, and other surfaces, which can ultimately get integrated into the Arctic food web. Depletion of both mercury and ozone occur due to the presence of reactive halogen radicals that are released from snow, ice, and aerosols. In this work, we added a detailed description of the Arctic atmospheric mercury cycle to our recently published version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem 4.3.3) that includes Arctic bromine and chlorine chemistry and activation/recycling on snow and aerosols. The major advantage of our modelling approach is the online calculation of bromine concentrations and emission/recycling that is required to simulate the hourly and daily variability of Arctic mercury depletion. We used this model to study coupling between reactive cycling of mercury, ozone, and bromine during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) spring season in 2020 and evaluated results compared to land-based, ship-based, and remote sensing observations. The model predicts that elemental mercury oxidation is driven largely by bromine chemistry and that particulate mercury is the major form of oxidized mercury. The model predicts that the majority (74%) of oxidized mercury deposited to land-based snow is re-emitted to the atmosphere as gaseous elemental mercury, while a minor fraction (4%) of oxidized mercury that is deposited to sea ice is re-emitted during spring. Our work demonstrates that hourly differences in bromine/ozone chemistry in the atmosphere must be considered to capture the springtime Arctic mercury cycle, including its integration into the cryosphere and ocean.

6 pags., 2 figs., Unlike bromine, the effect of iodine chemistry on the Arctic surface ozone budget is poorly constrained. We present ship-based measurements of halogen oxides in the high Arctic boundary layer from the sunlit period of March to October 2020 and show that iodine enhances springtime tropospheric ozone depletion. We find that chemical reactions between iodine and ozone are the second highest contributor to ozone loss over the study period, after ozone photolysis-initiated loss and ahead of bromine., This study received funding from the European Research Council Executive Agency under the European Union’s Horizon 2020 Research and Innovation Program (project ERC‐2016‐COG 726349 CLIMAHAL and ERC-2016-STG 714621 GASPARCON) and the European Commission via the EMME-CARE project and was supported by the Consejo Superior de Investigaciones Científicas of Spain. This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 856612 and the Academy of Finland (project no. 334514). The Indian Institute of Tropical Meteorology is funded by the Ministry of Earth Sciences, Government of India. Ozone, CO, CH4 and AMS measurements were funded by the Swiss National Science Foundation (grant 200021_188478), the Swiss Polar Institute and U.S. National Science Foundation grants 1914781 and 1807163. J.S. holds the Ingvar Kamprad chair for extreme environments research, sponsored by Ferring Pharmaceuticals. Data reported in this manuscript were produced as part of the international MOSAiC expedition with tag MOSAiC20192020, with activities supported by Polarstern expedition AWI-PS122_00. H.S. was funded by the European ERA-PLANET projects iGOSP and iCUPE (consortium agreement no. 689443 for both projects). We thank FORMAS and the Swedish Polar Research Secretariat for support. We gratefully acknowledge funding by the Deutsche Forschungsgemeinschaft (project no. 268020496 – TRR 172) within the Transregional Collaborative Research Center ‘ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3’ in subproject C03. We thank I. Bourgeois (NOAA/CIRES) for providing the ATom NOx data.

The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place from 7 January to 11 July 2020 in the tropical North Atlantic between the eastern edge of Barbados and 51∘ W, the longitude of the Northwest Tropical Atlantic Station (NTAS) mooring. Measurements were made to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Multiple platforms were deployed during ATOMIC including the NOAA RV Ronald H. Brown (RHB) (7 January to 13 February) and WP-3D Orion (P-3) aircraft (17 January to 10 February), the University of Colorado's Robust Autonomous Aerial Vehicle-Endurant Nimble (RAAVEN) uncrewed aerial system (UAS) (24 January to 15 February), NOAA- and NASA-sponsored Saildrones (12 January to 11 July), and Surface Velocity Program Salinity (SVPS) surface ocean drifters (23 January to 29 April). The RV Ronald H. Brown conducted in situ and remote sensing measurements of oceanic and atmospheric properties with an emphasis on mesoscale oceanic–atmospheric coupling and aerosol–cloud interactions. In addition, the ship served as a launching pad for Wave Gliders, Surface Wave Instrument Floats with Tracking (SWIFTs), and radiosondes. Details of measurements made from the RV Ronald H. Brown, ship-deployed assets, and other platforms closely coordinated with the ship during ATOMIC are provided here. These platforms include Saildrone 1064 and the RAAVEN UAS as well as the Barbados Cloud Observatory (BCO) and Barbados Atmospheric Chemistry Observatory (BACO). Inter-platform comparisons are presented to assess consistency in the data sets. Data sets from the RV Ronald H. Brown and deployed assets have been quality controlled and are publicly available at NOAA's National Centers for Environmental Information (NCEI) data archive (https://www.ncei.noaa.gov/archive/accession/ATOMIC-2020, last access: 2 April 2021). Point-of-contact information and links to individual data sets with digital object identifiers (DOIs) are provided herein.

International audience; With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place from January 7 to July 11, 2020 in the tropical North Atlantic between the eastern edge of Barbados and 51° W, the longitude of the Northwest Tropical Atlantic Station (NTAS) mooring. Measurements were made to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Multiple platforms were deployed during ATOMIC including the NOAA RV Ronald H. Brown (RHB) (Jan. 7 to Feb. 13) and WP-3D Orion (P-3) aircraft (Jan. 17 to Feb. 10), the University of Colorado's RAAVEN Uncrewed Aerial System (UAS) (Jan. 24 to Feb. 15), NOAA- and NASA-sponsored Saildrones (Jan. 12 to Jul. 11), and Surface Velocity Program Salinity (SVPS) surface ocean drifters (Jan. 23 to Apr. 29). The RV Ronald H. Brown conducted in situ and remote sensing measurements of oceanic and atmospheric properties with an emphasis on mesoscale oceanic-atmospheric coupling and aerosol-cloud interactions. In addition, the ship served as a launching pad for Wave Gliders, Surface Wave Instrument Floats with Tracking (SWIFTs), and radiosondes. Details of measurements made from the RV Ronald H. Brown, ship-deployed assets, and other platforms closely coordinated with the ship during ATOMIC are provided here. These platforms include Saildrone 1064 and the RAAVEN UAS as well as the Barbados Cloud Observatory (BCO) and Barbados Atmospheric Chemistry Observatory (BACO). Inter-platform comparisons are presented to assess consistency in the data sets. Data sets from the RV Ronald H. Brown and deployed assets have been quality controlled and are publicly available at the NOAA Physical Sciences Laboratory (PSL) ATOMIC ftp server (ftp://ftp2.psl.noaa.gov/Projects/ATOMIC/data/ (Quinn et al., 2020). In addition, the data have been submitted to NOAA's National Centers for Environmental Information (NCEI) data archive (https://www.ncei.noaa.gov/) for Digital Object Identifiers (DOIs). Point of contact information and links to individual data sets are provided herein.

The understanding of the sources, spatial distribution and temporal variability of turbulence in the atmospheric boundary layer (ABL) and improved simulation of its forcing processes require observations in a broad range of terrain types and atmospheric conditions. In this study, we estimate turbulence kinetic energy (TKE) dissipation rate using multiple techniques, including traditional in-situ measurements of sonic anemometers on meteorological towers, a hot-wire anemometer on a tethered lifting system (TLS), as well as remote-sensing retrievals from a vertically staring lidar and two lidars performing range-height indicator (RHI) scans. For the retrieval of ε from the lidar RHI scans, we introduce a modification of the Doppler Spectral Width (DSW) method. This method uses spatio-temporal averages of the variance of the line-of-sight (LOS) velocity and the turbulent broadening of the Doppler backscatter spectrum. We validate this method against the observations from the other instruments, also including uncertainty estimations for each method. The synthesis of the results from all instruments enables a detailed analysis of the spatial and temporal variability of ε across a valley between two parallel ridges at the Perdigão 2017 campaign. We find that the shear zones above and below nighttime low-level jets (LLJ) experience turbulence enhancements, as does the wake of a wind turbine (WT). We analyze in detail how ε varies in the early morning of 14 June 2017, when the turbulence in the valley, approximately eleven rotor diameters downstream of the WT, is still significantly enhanced by the WT wake.

A grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.

A fast response ozone analyzer based on the ozone-nitric oxide chemiluminescence method was integrated into the NOAA-ESRL flux system to achieve the first ship-borne, direct ozone flux measurements over the open ocean. Air was collected from an inlet at 18 m height over the ocean surface mounted to the bow-jackstaff and via a 30 m-long sampling line to the ozone instrument on the ship deck. A "puff" system was used for accurate and regular determination of the sample transport time (lag) between the inlet and the chemical analyzer. A Nafion-membrane dryer facilitated removal of fast water vapor fluctuations, which eliminated the need for quenching and density correction of the ozone signal. The sampling-analyzer system was found to have a ~0.25–0.40 s response time at a sensitivity of ~2800 counts s−1 per ppbv of ozone. Quality control and data filtering procedures for eliminating data that did not meet measurement requirements were critically evaluated. The new ozone flux system was deployed aboard the NOAA Ship Ronald H. Brown, and evaluated using results obtained during several research cruises off the coasts of the North and South America continents, yielding ozone deposition velocities (mean ± standard error) ranging from 0.009±0.001 cm s−1 to 0.24±0.020 cm s−1.

Dynamics of the Madden–Julian Oscillation (DYNAMO) and Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) observations and reanalysis-based surface flux products are used to test theories of atmosphere–ocean interaction that explain the Madden–Julian oscillation (MJO). Negative intraseasonal outgoing longwave radiation, indicating deep convective clouds, is in phase with increased surface wind stress, decreased solar heating, and increased surface turbulent heat flux—mostly evaporation—from the ocean to the atmosphere. Net heat flux cools the upper ocean in the convective phase. Sea surface temperature (SST) warms during the suppressed phase, reaching a maximum before the onset of MJO convection. The timing of convection, surface flux, and SST is consistent from the central Indian Ocean (70°E) to the western Pacific Ocean (160°E). Mean surface evaporation observed in TOGA COARE and DYNAMO (110 W m−2) accounts for about half of the moisture supply for the mean precipitation (210 W m−2 for DYNAMO). Precipitation maxima are an order of magnitude larger than evaporation anomalies, requiring moisture convergence in the mean, and on intraseasonal and daily time scales. Column-integrated moisture increases 2 cm before the convectively active phase over the Research Vessel (R/V) Roger Revelle in DYNAMO, in accordance with MJO moisture recharge theory. Local surface evaporation does not significantly recharge the column water budget before convection. As suggested in moisture mode theories, evaporation increases the moist static energy of the column during convection. Rather than simply discharging moisture from the column, the strongest daily precipitation anomalies in the convectively active phase accompany the increasing column moisture.

A variety of physical mechanisms are jointly responsible for facilitating air-sea gas transfer through turbulent processes at the atmosphere-ocean interface. The nature and relative importance of these mechanisms evolves with increasing wind speed. Theoretical and modeling approaches are advancing, but the limited quantity of observational data at high wind speeds hinders the assessment of these efforts. The HiWinGS project successfully measured gas transfer coefficients (k660) with coincident wave statistics under conditions with hourly mean wind speeds up to 24 m s−1 and significant wave heights to 8 m. Measurements of k660 for carbon dioxide (CO2) and dimethylsulfide (DMS) show an increasing trend with respect to 10-meter neutral wind speed (U10N), following a power-law relationship of the form: math formula and math formula. Among seven high wind speed events, CO2 transfer responded to the intensity of wave breaking, which depended on both wind speed and sea state in a complex manner, with k660 co2 increasing as the wind sea approaches full development. A similar response is not observed for DMS. These results confirm the importance of breaking waves and bubble injection mechanisms in facilitating CO2 transfer. A modified version of the Coupled Ocean-Atmosphere Response Experiment Gas transfer algorithm (COAREG ver. 3.5), incorporating a sea state-dependent calculation of bubble-mediated transfer, successfully reproduces the mean trend in observed k660 with wind speed for both gases. Significant suppression of gas transfer by large waves was not observed during HiWinGS, in contrast to results from two prior field programs.

The wake of a wind turbine is characterized by increased turbulence and decreased wind speed. Turbines are generally deployed in large groups in wind farms, and so the behaviour of an individual wake as it merges with other wakes and propagates downwind is critical in assessing wind-farm power production. This evolution depends on the rate of turbulence dissipation in the wind-turbine wake, which has not been previously quantified in field-scale measurements. In situ measurements of winds and turbulence dissipation from the wake region of a multi-MW turbine were collected using a tethered lifting system (TLS) carrying a payload of high-rate turbulence probes. Ambient flow measurements were provided from sonic anemometers on a meteorological tower located near the turbine. Good agreement between the tower measurements and the TLS measurements was established for a case without a wind-turbine wake. When an operating wind turbine is located between the tower and the TLS so that the wake propagates to the TLS, the TLS measures dissipation rates one to two orders of magnitude higher in the wake than outside of the wake. These data, collected between two and three rotor diameters \(D\) downwind of the turbine, document the significant enhancement of turbulent kinetic energy dissipation rate within the wind-turbine wake. These wake measurements suggest that it may be useful to pursue modelling approaches that account for enhanced dissipation. Comparisons of wake and non-wake dissipation rates to mean wind speed, wind-speed variance, and turbulence intensity are presented to facilitate the inclusion of these measurements in wake modelling schemes.

Obtaining accurate measurements of wave statistics from research vessels remains a challenge due to the platform motion. One principal correction is the removal of ship heave and Doppler effects from point measurements. Here, open-ocean wave measurements were collected using a laser altimeter, a Doppler radar microwave sensor, a radar-based system, and inertial measurement units. Multiple instruments were deployed to capture the low- and high-frequency sea surface displacements. Doppler and motion correction algorithms were applied to obtain a full 1D (0.035–1.3 ± 0.2 Hz) wave spectrum. The radar-based system combined with the laser altimeter provided the optimal low- and high-frequency combination, producing a frequency spectrum in the range from 0.035 to 1.2 Hz for cruising speeds ≤3 m s−1 with a spectral rolloff of f−4 Hz and noise floor of −20/−30 dB. While on station, the significant wave height estimates were comparable within 10%–15% among instrumentation. Discrepancies in the total energy and in the spectral shape between instruments arise when the ship is in motion. These differences can be quantified using the spectral behavior of the measurements, accounting for aliasing and Doppler corrections. The inertial sensors provided information on the amplitude of the ship’s modulation transfer function, which was estimated to be ~1.3 ± 0.2 while on station and increased while underway [2.1 at ship-over-ground (SOG) speed; 4.3 m s−1]. The correction scheme presented here is adequate for measurements collected at cruising speeds of 3 m s−1 or less. At speeds greater than 5 m s−1, the motion and Doppler corrections are not sufficient to correct the observed spectral degradation.

The spatial resolution of a sonic anemometer is limited by the distance between its transducers, and for studies of small-scale turbulence and theories of turbulence, it is desirable to increase this spatial resolution. We here consider resolution improvements obtainable by treating the sonic anemometer as a small tomography array, with application of appropriate inverse algorithms for the reconstruction of temperature and velocity. A particular modification of the sonic anemometer is considered when the number of its transducers is doubled and the time-dependent stochastic inversion algorithm is used for reconstruction. Numerical simulations of the sonic anemometer and its suggested modification are implemented with the temperature and velocity fields modelled as discrete eddies moving through the sonic’s volume. The tomographic approach is shown to provide better reconstructions of the temperature and velocity fields, with spatial resolution increased by as much as a factor of ten. The spatial resolution depends on the inverse algorithm and also improves by increasing the number of transducers.

Shallow precipitating cumuli within the easterly trades were investigated using shipboard measurements, scanning radar data, and visible satellite imagery from 2 weeks in January 2005 of the Rain in Cumulus over the Ocean (RICO) experiment. Shipboard rainfall rates of up to 2 mm h−1 were recorded almost daily, if only for 10–30 min typically, almost always from clouds within mesoscale arcs. The precipitating cumuli, capable of reaching above 4 km, cooled surface air by 1–2 K, in all cases lowered surface specific humidities by up to 1.5 g kg−1, reduced surface equivalent potential temperatures by up to 6 K, and were often associated with short-lived increases in wind speed. Upper-level downdrafts were inferred to explain double-lobed moisture and temperature sounding profiles, as well as multiple inversions in wind profiler data. In two cases investigated further, the precipitating convection propagated faster westward than the mean surface wind by about 2–3 m s−1, consistent with a density current of depth ~200 m. In their cold pool recovery zones, the surface air temperatures equilibrated with time to the sea surface temperatures, but the surface air specific humidities stayed relatively constant after initial quick recoveries. This suggested that entrainment of drier air from above fully compensated the moistening from surface latent heat fluxes. Recovery zone surface wind speeds and latent heat fluxes were not higher than environmental values. Nonprecipitating clouds developed after the surface buoyancy had recovered (barring encroachment of other convection). The mesoscale arcs favored atmospheres with higher water vapor paths. These observations differed from those of stratocumulus and deep tropical cumulus cold pools.

A ship-based eddy covariance ozone flux system was deployed to investigate the magnitude and variability of ozone surface fluxes over the open ocean. The flux experiments were conducted on five cruises on board the NOAA research vessel Ronald Brown during 2006-2008. The cruises covered the Gulf of Mexico, the southern as well as northern Atlantic, the Southern Ocean, and the persistent stratus cloud region off Chile in the eastern Pacific Ocean. These experiments resulted in the first ship-borne open-ocean ozone flux measurement records. The median of 10 min oceanic ozone deposition velocity (v(d)) results from a combined similar to 1700 h of observations ranged from 0.009 to 0.034 cm s(-1). For the Gulf of Mexico cruise (Texas Air Quality Study (TexAQS)) the median v(d) (interquartile range) was 0.034 (0.009-0.065) cm s(-1) (total number of 10 min measurement intervals, N-f = 1953). For the STRATUS cruise off the Chilean coast, the median v(d) was 0.009 (0.004-0.037) cm s(-1) (N-f = 1336). For the cruise from the Gulf of Mexico and up the eastern U. S. coast (Gulf of Mexico and East Coast Carbon cruise (GOMECC)) a combined value of 0.018 (0.006-0.045) cm s(-1) (N-f = 1784) was obtained (from 0.019 (-0.014-0.043) cm s(-1), N-f = 663 in the Gulf of Mexico, and 0.018 (-0.004-0.045) cm s(-1), N-f = 1121 in the North Atlantic region). The Southern Ocean Gas Exchange Experiment (GasEx) and African Monsoon Multidisciplinary Analysis (AMMA), the Southern Ocean and northeastern Atlantic cruises, respectively, resulted in median ozone v(d) of 0.009 (-0.005-0.026) cm s(-1) (N-f = 2745) and 0.020 (-0.003-0.044) cms(-1) (N-f = 1147). These directly measured ozone deposition values are at the lower end of previously reported data in the literature (0.01-0.12 cm s(-1)) for ocean water. Data illustrate a positive correlation (increase) of the oceanic ozone uptake rate with wind speed, albeit the behavior of the relationship appears to differ during these cruises. The encountered wide range of meteorological and ocean biogeochemical conditions is used to investigate fundamental drivers of oceanic O-3 deposition and for the evaluation of a recently developed global oceanic O-3 deposition modeling system.

[1] Direct measurements of air-sea heat, momentum, and mass (including CO2, DMS, and water vapor) fluxes using the direct covariance method were made over the open ocean from the NOAA R/V Ronald H. Brown during the Southern Ocean Gas Exchange (SO GasEx) program. Observations of fluxes and the physical processes associated with driving air-sea exchange are key components of SO GasEx. This paper focuses on the exchange of CO2 and the wind speed dependency of the transfer velocity, k, used to model the CO2 flux between the atmosphere and ocean. A quadratic dependence of k on wind speed based on dual tracer experiments is most frequently encountered in the literature. However, in recent years, bubble-mediated enhancement of k, which exhibits a cubic relationship with wind speed, has emerged as a key issue for flux parameterization in high-wind regions. Therefore, a major question addressed in SO GasEx is whether the transfer velocities obey a quadratic or cubic relationship with wind speed. After significant correction to the flux estimates (primarily due to moisture contamination), the direct covariance CO2 fluxes confirm a significant enhancement of the transfer velocity at high winds compared with previous quadratic formulations. Regression analysis suggests that a cubic relationship provides a more accurate parameterization over a wind speed range of 0 to 18 m s−1. The Southern Ocean results are in good agreement with the 1998 GasEx experiment in the North Atlantic and a recent separate field program in the North Sea.

[1] Updates for the Coupled Ocean-Atmosphere Response Experiment (COARE) physically based meteorological and gas transfer bulk flux algorithms are examined. The current versions are summarized and a generalization of the gas transfer codes to 79 gases is described. The current meteorological version COARE3.0 was compared with a collection of 26,700 covariance observations of drag and heat transfer coefficients (compiled from three independent research groups). The algorithm agreed on average to within 5% with observations for a wind speed range of 2 to 18 m s−1. Covariance observations of CO2 and dimethyl sulfide (DMS) gas transfer velocity k were normalized to Schmidt number 660 and compared to an ensemble of gas flux observations from six research groups and nine field programs. A reasonable fit of the mean k660 versus U10n values was obtained for both CO2 and DMS with a new version of the COARE gas transfer algorithm (designated COAREG3.1) using friction velocity associated with viscous (tangential) stress, u*ν, in the nonbubble term. In the wind speed range 5 to 16 m s−1, tracer-derived estimates of k660 are 10% to 20% lower than the CO2 covariance estimates presented here.

[1] Air-sea/land turbulent fluxes of momentum, sensible heat, water vapor, carbon dioxide, and ozone are discussed on the basis of eddy covariance measurements made aboard the NOAA R/V Ronald H. Brown during the Texas Air Quality Study (TexAQS) in August–September 2006. The TexAQS 2006 field campaign focused on air pollution meteorology associated primarily with ozone and aerosol transport in the Houston/Galveston region and the nearby coastal zone. The ship-based complement of instrumentation was used for the boundary layer measurements over water (the Gulf of Mexico and various harbors/bay areas) and “over land” (specifically, 80 km inside the Houston Ship Channel). In this study we focus on direct comparisons of TexAQS 2006 flux observations with the Coupled Ocean-Atmosphere Response Experiment (COARE) bulk flux algorithm to investigate possible coastal and urban area influences. It is found that the average neutral drag coefficient can be about an order of magnitude larger over very rough urban areas than over the sea surface. However, a similar effect was not observed for the scalar transfer; that is, the neutral Stanton and Dalton numbers do not change significantly over different footprint surfaces. Our data suggest that the TexAQS 2006 region was generally a sink for surface ozone whether over water or over land. The turbulent flux of carbon dioxide was mostly negative (uptake by the surface) for measurements over waters of the Gulf of Mexico and some bays, but the flux becomes positive (release to the air) for inland regions. Both ozone and carbon dioxide turbulent fluxes above land were larger in magnitude compared to the over water measurements.

[1] During summer 2006 eddy correlation CO2 fluxes were measured in the Greenland Sea using a novel system set‐up with two shrouded LICOR‐7500 detectors. One detector was used exclusively to determine, and allow the removal of, the bias on CO2 fluxes due to sensor motion. A recently published correction method for the CO2‐H2O cross‐correlation was applied to the data set. We show that even with shrouded sensors the data require significant correction due to this cross‐correlation. This correction adjusts the average CO2 flux by an order of magnitude from −6.7 × 10 −2 mol m −2 day −1 to −0.61 × 10 −2 mol m −2 day −1 , making the corrected fluxes comparable to those calculated using established parameterizations for transfer velocity. Citation: Lauvset, S. K., W. R. McGillis, L. Bariteau, C. W. Fairall, T. Johannessen, A. Olsen, and C. J. Zappa (2011), Direct measurements of CO2 flux in the Greenland Sea, Geophys. Res. Lett., 38, L12603, doi:10.1029/2011GL047722.

Funding was provided by the National Oceanic and Atmospheric Administration under Grant No. NA0900AR4320129

Funding was provided by the National Oceanic and Atmospheric Administration under Grant No. NA17RJ1223.

[1] In this paper, we examine observations of shallow, stable boundary layers in the cool waters of the Gulf of Maine between Cape Cod, Massachusetts, and Nova Scotia, obtained in the 2004 New England Air Quality Study (NEAQS-04), which was part of the International Consortium for Atmospheric Research into Transport and Transformation (ICARTT). The observations described herein were made from the NOAA Research Vessel Ronald H. Brown. The ship was instrumented for measurements of meteorological, gas-phase and aerosol atmospheric chemistry variables. Meteorological instrumentation included a Doppler lidar, a radar wind profiler, rawinsonde equipment, and a surface flux package. In this study, we focus on direct comparisons of the NEAQS-04 flux observations with the COARE bulk flux algorithm to investigate possible coastal influences on air-sea interactions. We found significant suppression of the transfer coefficients for momentum, sensible heat, and latent heat; the suppression was correlated with lighter winds, more stable surface layers, S-SE wind direction, and lower boundary layer heights. Analysis of the details shows the suppression is not a measurement, stability correction, or surface wave effect. The correlation with boundary layer height is consistent with an interpretation that our measurements at 18-m height do not realize the full surface flux in shallow boundary layers. We also find that a bulk Richardson number threshold of 0.1 gives a better estimate of boundary layer height than 0.25 or 0.5. Mean ozone deposition velocity is estimated as 0.44 mm s−1, corresponding to a boundary removal timescale of about 1 day.

Funding was provided by the National Oceanic and Atmospheric Administration under Grant No. NA17RJ1223 and the Cooperative Institute for Climate and Ocean Research (CICOR).

Eddy-correlation measurements of the oceanic $$\hbox {CO}_2$$ flux are useful for the development and validation of air–sea gas exchange models and for analysis of the marine carbon cycle. Results from more than a decade of published work and from two recent field programs illustrate the principal interferences from water vapour and motion, demonstrating experimental approaches for improving measurement precision and accuracy. Water vapour cross-sensitivity is the greatest source of error for $$\hbox {CO}_2$$ flux measurements using infrared gas analyzers, often leading to a ten-fold bias in the measured $$\hbox {CO}_2$$ flux. Much of this error is not related to optical contamination, as previously supposed. While various correction schemes have been demonstrated, the use of an air dryer and closed-path analyzer is the most effective way to eliminate this interference. This approach also obviates density corrections described by Webb et al. (Q J R Meteorol 106:85–100, 1980). Signal lag and frequency response are a concern with closed-path systems, but periodic gas pulses at the inlet tip provide for precise determination of lag time and frequency attenuation. Flux attenuation corrections are shown to be $$