With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in-situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from June 21 to July 20, 2017 and January 15 to February 18, 2018 in the Azores. The flights were designed to maximize the synergy between in-situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Finally, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.

Entrainment-mixing mechanisms significantly affect cloud droplet number concentration, radius, and spectral shape. Quantitative examination of entrainment-mixing effects on cloud droplet spectral width is lacking. This study examines the effects of entrainment-mixing processes on cloud microphysics by 12,218 different setups, each simulated 10 times using the Explicit Mixing Parcel Model (EMPM) driven by the observational data from the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) campaign. Parameterizations of entrainment-mixing mechanisms are developed by relating homogeneous mixing degree to transition scale number that depends on the dissipation rate and droplet evaporation time scale. The correlation between relative dispersion of cloud droplet size distribution and homogeneous mixing degree changes from negative to positive with the decreasing homogeneous mixing degree. The different relationships are closely related to the competition between complete and partial droplet evaporation and the number concentration of small droplets, which are quantitatively described by two newly introduced dimensionless numbers. The competition is significantly affected by relative humidity and mixing fraction of entrained air as well as turbulence dissipation rate, but not much by cloud droplet number concentration. Especially, when relative humidity and dissipation rate are high, there is only a negative correlation. This study sheds new light on generalizing the homogeneous/inhomogeneous concept by considering relative dispersion and also provides parameterizations of entrainment-mixing processes and relative dispersion for atmospheric models.

Cloud droplet spectral relative dispersion is critical to parameterizations of cloud radiative properties, warm-rain initiation, and aerosol-cloud interactions in models; however, there is no consistent relationship between relative dispersion and volume-mean radius in literature, which hinders improving relative dispersion parameterization and calls for physical explanation. Here we show, by analyzing aircraft observations of cumulus clouds during Routine AAF [Atmospheric Radiation Measurement (ARM) Aerial Facility] Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations, that the correlation between relative dispersion and volume-mean radius changes from positive to negative as volume-mean radius increases. With the new observation, we postulate that the sign of the correlation is determined by whether or not condensation (evaporation) occurs simultaneously with significant new activation (deactivation). The hypothesis is validated by simulations of both an adiabatic cloud parcel model and a parcel model accounting for entrainment-mixing. A new quantity, first bin strength, is introduced to quantify this new observation. Theoretical analysis of truncated gamma and modified gamma size distributions further supports the hypothesis and reconciles the contrasting relationships between relative dispersion and volume-mean radius, including the results in polluted fog observations. The results could shed new light on the so-called "twilight zone" between cloudy and cloud-free air, which in turn affects evaluation of aerosol-cloud interactions and retrieval of aerosol optical depth.Plain Language Summary The width of cloud droplet size distribution is critical to aerosol-cloud interactions and warm rain initiation. Relative dispersion represents the relative width of cloud droplet size distribution. Current parameterizations of relative dispersion often relate relative dispersion to volume-mean radius. Based on aircraft observations of cumulus clouds, it is found that relative dispersion is positively correlated with volume-mean radius when volume-mean radius is small, and the correlation becomes negative when volume-mean radius increases. A hypothesis is raised by relating the relationship between the two quantities to microphysical processes (activation, condensation, evaporation, and deactivation) and is substantiated with an adiabatic parcel model, a parcel model considering entrainment-mixing, and theoretical analysis. The results may promote the studies on the zone between cloudy and cloud-free air, which in turn affects evaluation of aerosol-cloud interactions.

The apparent turbulent entrainment-mixing mechanism between clouds and surrounding air is scale dependent; however, such scale dependence has been rarely studied, hindering development of scale-aware entrainment-mixing parameterizations. Here we extend our previous study on cumulus clouds to investigate scale dependence of entrainment-mixing processes in stratocumulus clouds during Aerosol and Cloud Experiments in Eastern North Atlantic and Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO). In contrast to previous studies, two opposite scale dependencies are found: Entrainment mixing can become more homogeneous or more inhomogeneous with increasing averaging scales, which is quantified by the difference between homogeneous mixing degree at the 100 and 10 m resolutions. A new heuristic model and two new quantities are introduced. The observations and model show that microphysical properties near and far away from droplet-free air and relative humidity of entrained air determine both the sign and strength of scale dependence, while droplet-free air fraction only affects the strength. The results shed new light on developing scale-aware parameterizations of entrainment-mixing mechanisms.Plain Language Summary Turbulent entrainment mixing between clouds and surrounding air significantly affects cloud microphysical properties over a wide range of scales, indicating that the apparent entrainment-mixing mechanism is scale dependent. Previous studies have shown that entrainment-mixing mechanisms tend to be more inhomogeneous when the sampling rate is lower. Surprisingly, the present study shows two opposite behaviors of scale dependence: The mechanisms can become more homogeneous or more inhomogeneous. To understand the physical mechanisms responsible for the scale dependence, a new heuristic model is established. Cloud microphysics and relative humidity of the entrained air determine both the sign and strength of scale dependence, while droplet-free air fraction only determines the strength. Two new quantities combining all the factors are defined, and they can better quantify the effects of the factors on scale dependence than each individual factor. This study finds a new phenomenon of scale dependence and improves our physical understanding of entrainment mixing.