Stratification of the upper few meters of the ocean limits the penetration depth of wind mixing and the vertical distribution of atmospheric fluxes. Significant density stratification at depths ≤ 5 m was observed in 38% of a 2‐month data set from the central Indian Ocean collected during the DYNAMO experiment (Dynamics of the MJO, Madden‐Julian Oscillation). Diurnal warm layers (DWLs) formed by solar heating populated 30% of the data set and rain layers (RLs) populated 16%. Combined contributions from rain and insolation formed RL‐DWLs in 9% of the data set. RLs were detected at values of U10 up to 9.8 m s−1, while DWLs were only detected at U10 < 7.6 m s−1 (99th percentile values), symptomatic of the greater buoyancy flux provided by moderate to high rain rate compared to insolation. From the ocean friction velocity, u*w, and surface buoyancy flux, B, we derived estimates of htruêS, stable layer depth, and UtruêS, the maximum U10 for which stratification should persist at htruêS for fixed B. These estimates predicted (1) 36 out of 44 observed stratification events (88% success rate) and (2) the wind limits of these events, which are considered to be the 99th percentile values of U10). This suggests a means to determine the presence of ocean stable layers at depths ≤ 5 m from U10 and B. Near‐surface stratification varied throughout two Madden‐Julian Oscillation (MJO) cycles. In suppressed MJO periods, (U10 ≤ 8 m s−1 with strong insolation), RLs and RL‐DWLs were rare while DWLs occurred daily. During disturbed and active MJO periods, (U10 ≤ 8 m s−1 with increased rain and cloudiness), multiple RLs and RL‐DWLs formed per day and DWLs became less common. When westerly wind bursts occurred, (U10 = 7–17 m s−1 with steady rain), RLs formed infrequently and DWLs were not detected.

Low elevation aerosol spectra, ocean whitecap cover and 10m wind speeds measured during the 1978 JASIN experiment have been inter‐related and compared with previously published observations. The positive dependence of aerosol concentration upon whitecap cover was found to increase with droplet radius reflecting the expected higher correlation of the concentration of larger droplets, which have shorter effective residence time in the marine atmospheric boundary layer, with the immediate whitecap cover, which reflects the instantaneous rate of aerosol generation at the sea surface. The power‐law wind dependence, Uγ of the low elevation concentration of droplets larger than 8γm radius was determined to be similar to the wind dependence of whitecap cover, with γ values of 3.23 and 3.31 resulting from the respective application of the robust bi‐weight fitting technique. This observation is consonant with an aerosol generation model in which the instantaneous rate of production is simply proportional to the immediate whitecap cover. The large droplet end of the JASIN low elevation aerosol spectrum is seen to undergo a marked enhancement when the wind speed exceeds 10ms−1. This is a consequence of the onset at that speed of supplementary droplet production via the mechanical disruption of wave crests. The observed growth, with increasing wind speed, in the disparity in amplitude of near‐sea‐surface and near‐cloud‐base aerosol spectra is in part a consequence of the fact that the larger droplets, produced in relative abundance at the higher wind speeds, fall out before they can be mixed effectively through the boundary layer.

Abstract. The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.

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The air-sea gas transfer velocity (K660) is typically assessed as a function of the 10-m neutral wind speed (U10n), but there remains substantial uncertainty in this relationship. Here K660 of CO2 derived with the eddy covariance (EC) technique from eight datasets (11 research cruises) are reevaluated with consistent consideration of solubility and Schmidt number and inclusion of the ocean cool skin effect. K660 shows an approximately linear dependence with the friction velocity (u*) in moderate winds, with an overall relative standard deviation (relative standard error) of about 20% (7%). The largest relative uncertainty in K660 occurs at low wind speeds, while the largest absolute uncertainty in K660 occurs at high wind speeds. There is an apparent regional variation in the steepness of the K660-u* relationships: North Atlantic ≥ Southern Ocean &gt; other regions (Arctic, Tropics). Accounting for sea state helps to collapse some of this regional variability in K660 using the wave Reynolds number in very large seas and the mean squared slope of the waves in small to moderate seas. The grand average of EC-derived K660(−1.47 + 76.67u*+ 20.48u*2 or 0.36 + 1.203U10n+ 0.167U10n2) is similar at moderate to high winds to widely used dual tracer-based K660 parametrization, but consistently exceeds the dual tracer estimate in low winds, possibly in part due to the chemical enhancement in air-sea CO2 exchange. Combining the grand average of EC-derived K660 with the global distribution of wind speed yields a global average transfer velocity that is comparable with the global radiocarbon (14C) disequilibrium, but is ~20% higher than what is implied by dual tracer parametrizations. This analysis suggests that CO2 fluxes computed using a U10n2 dependence with zero intercept (e.g., dual tracer) are likely underestimated at relatively low wind speeds.