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Aerosol indirect effects are one of the leading contributors to cloud radiative properties relevant to climate. Aerosol particles become cloud droplets when the ambient relative humidity (saturation ratio) exceeds a critical value, which depends on the particle size and chemical composition. In the traditional formulation of this problem, only average, uniform saturation ratios are considered. Using experiments and theory, we examine the effects of fluctuations, produced by turbulence. Our measurements, from a multiphase, turbulent cloud chamber, show a clear transition from a regime in which the mean saturation ratio dominates to one in which the fluctuations determine cloud properties. The laboratory measurements demonstrate cloud formation in mean-subsaturated conditions (i.e., relative humidity <100%) in the fluctuation-dominant activation regime. The theoretical framework developed to interpret these measurements predicts a transition from a mean- to a fluctuation-dominated regime, based on the relative values of the mean and standard deviation of the environmental saturation ratio and the critical saturation ratio at which aerosol particles activate or become droplets. The theory is similar to the concept of stochastic condensation and can be used in the context of the atmosphere to explore the conditions under which droplet activation is driven by fluctuations as opposed to mean supersaturation. It provides a basis for future development of cloud droplet activation parameterizations that go beyond the internally homogeneous parcel calculations that have been used in the past.

Raindrop formation processes in warm clouds mainly consist of condensation and collision–coalescence of small cloud droplets. Once raindrops form, they can continue growing through collection of cloud droplets and self-collection. In this study, we develop novel emulators to represent raindrop formation as a function of various physical or background environmental conditions by using a sophisticated aerosol–cloud model containing 300 droplet size bins and machine learning methods. The emulators are then implemented in two microphysics schemes in the Weather Research and Forecasting Model and tested in two idealized cases. The simulations of shallow convection with the emulators show a clear enhancement of raindrop formation compared to the original simulations, regardless of the scheme in which they were embedded. On the other hand, the simulations of deep convection show a more complex response to the implementation of the emulators, in terms of the changes in the amount of rainfall, due to the larger number of microphysical processes involved in the cloud system (i.e., ice-phase processes). Our results suggest the potential of emulators to replace the conventional parameterizations, which may allow us to improve the representation of physical processes at an affordable computational expense.

Over the eastern North Atlantic (ENA) ocean, a total of 20 non-precipitating single-layer marine boundary layer (MBL) stratus and stratocumulus cloud cases are selected to investigate the impacts of the environmental variables on the aerosol–cloud interaction (ACIr) using the ground-based measurements from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the ENA site during 2016–2018. The ACIr represents the relative change in cloud droplet effective radius re with respect to the relative change in cloud condensation nuclei (CCN) number concentration at 0.2 % supersaturation (NCCN,0.2 %) in the stratified water vapor environment. The ACIr values vary from −0.01 to 0.22 with increasing sub-cloud boundary layer precipitable water vapor (PWVBL) conditions, indicating that re is more sensitive to the CCN loading under sufficient water vapor supply, owing to the combined effect of enhanced condensational growth and coalescence processes associated with higher Nc and PWVBL. The principal component analysis shows that the most pronounced pattern during the selected cases is the co-variations in the MBL conditions characterized by the vertical component of turbulence kinetic energy (TKEw), the decoupling index (Di), and PWVBL. The environmental effects on ACIr emerge after the data are stratified into different TKEw regimes. The ACIr values, under both lower and higher PWVBL conditions, more than double from the low-TKEw to high-TKEw regime. This can be explained by the fact that stronger boundary layer turbulence maintains a well-mixed MBL, strengthening the connection between cloud microphysical properties and the below-cloud CCN and moisture sources. With sufficient water vapor and low CCN loading, the active coalescence process broadens the cloud droplet size spectra and consequently results in an enlargement of re. The enhanced activation of CCN and the cloud droplet condensational growth induced by the higher below-cloud CCN loading can effectively decrease re, which jointly presents as the increased ACIr. This study examines the importance of environmental effects on the ACIr assessments and provides observational constraints to future model evaluations of aerosol–cloud interactions.

The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H1/3, consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H2/3. Temperature and other scalar fluctuations scale as H−3/7. Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers. Plain Language Summary In a convection–cloud chamber, turbulent convection is generated by heating the bottom surface and cooling the top surface. Water‐supersaturated conditions are achieved by maintaining the bottom and top surfaces wet. When aerosols are injected into the resulting turbulent, supersaturated flow, cloud droplets are formed and grow by vapor condensation, and possibly by collision and coalescence. The relative roles of condensation due to mean properties and fluctuating properties, as well as the role of collisional growth, depend on the time and velocity scales of the turbulence, all of which depend on the height of the chamber. In this work, turbulence and cloud properties in a convection–cloud chamber are simulated for several chamber heights. It is found that time and velocity scales increase with chamber height; cloud droplet size distributions can be approximately matched by appropriately increasing the aerosol injection rate; and the relevance of collisional growth increases with chamber height. These findings will help guide future computational and laboratory implementations of cloud formation in thermal, moist convection. Key Points Increasing the height of a convection‐cloud chamber leads to an increase in characteristic velocity and time scales Cloud droplet size distributions can be approximately matched by increasing the total aerosol injection rate as the square of the height Concentration of large cloud droplets due to collision and coalescence increases monotonically with increasing height

Cloud droplet size distributions (CDSDs), which are related to cloud albedo and rain formation, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a moving-size-grid cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, submicrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with early work. The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by numerous smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are as follows: (1) droplets form on aerosols of different sizes, and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in situ measurements and 3-D dynamic models.

A novel way to represent cloud condensation nuclei (CCN) activation and cloud droplet growth by the diffusion of water vapor is introduced. The key is to apply a phase space diagram that plots the radius of a liquid droplet (deliquesced CCN or cloud droplet) versus the difference between the ambient supersaturation and the equilibrium supersaturation corresponding to the droplet radius. The latter combines the droplet and environmental characteristics, and it determines whether a droplet grows or evaporates. The diagram can be used to depict (in a straightforward way) key microphysical processes of CCN activation and deactivation as well as haze or cloud droplet transition from growth to evaporation. To show its utility, the diagram is applied to an idealized simulation of CCN activation and cloud droplet growth inside a rising turbulent air parcel and to simulations of microphysical processes inside a laboratory apparatus, the Pi cloud chamber. The adiabatic parcel mimics microphysical processes near the base of a natural cumulus or stratocumulus cloud. The Pi chamber simulations represent microphysical transformations in moist turbulent Rayleigh–Bénard convection with CCN proceeding through cycles of activation, growth, evaporation, and deactivation. A more general version of the phase diagram that is independent of the CCN dry radius is also developed. The phase diagram allows simple interpretations of key microphysical processes and highlights differences between droplet formation in natural and laboratory clouds.

Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection–Cloud Chamber generates a turbulent cloud with a microphysical steady state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and collocated Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damköhler number (Da), under conditions corresponding to , i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such that is satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth.

Numerical simulations of turbulent moist Rayleigh–Bénard convection driving CCN activation and droplet growth in the laboratory Pi chamber are discussed. Supersaturation fluctuations come from isobaric mixing of warm and humid air rising from the lower boundary with colder air featuring lower water vapor concentrations descending from the upper boundary. Lagrangian particle–based microphysics is used to represent the growth of haze CCN and cloud droplets with kinetic, solute, and surface tension effects included. Dry CCN spectra in the range between 2- and 200-nm radii from field observations are considered. Increasing the total CCN concentration from pristine to polluted conditions results in an increase in the droplet concentration and reduction in the mean droplet radius and spectral width. These are in agreement with Pi chamber observations and numerical simulations, as well as with numerous past studies of CCN cloud-base activation in natural clouds. The key result is that a relatively small fraction of the available CCN is activated in the Pi chamber fluctuating supersaturations, from about a half in the pristine case to only a 10th in the polluted case. The activation fraction as a function of the dry CCN radius is similar in all simulations, close to zero at the CCN small end, increasing to a maximum at CCN radius around 50 nm, and decreasing to close to zero at the large CCN end. This is explained as too small supersaturations to activate small CCN as in natural clouds and insufficient time to allow large CCN reaching the critical radius.

This study investigates the evolution of temperature and lifetime of evaporating, supercooled cloud droplets considering initial droplet radius ( r 0 ) and temperature ( ), and environmental relative humidity (RH), temperature ( T ∞ ), and pressure ( P ). The time ( t ss ) required by droplets to reach a lower steady-state temperature ( T ss ) after sudden introduction into a new subsaturated environment, the magnitude of Δ T = T ∞ − T ss , and droplet survival time ( t st ) at T ss are calculated. The temperature difference (Δ T ) is found to increase with T ∞ , and decrease with RH and P . Δ T was typically 1–5 K lower than T ∞ , with highest values (∼10.3 K) for very low RH, low P , and T ∞ closer to 0°C. Results show that t ss is <0.5 s over the range of initial droplet and environmental conditions considered. Larger droplets ( r 0 = 30–50 μ m) can survive at T ss for about 5 s to over 10 min, depending on the subsaturation of the environment. For higher RH and larger droplets, droplet lifetimes can increase by more than 100 s compared to those with droplet cooling ignored. T ss of the evaporating droplets can be approximated by the environmental thermodynamic wet-bulb temperature. Radiation was found to play a minor role in influencing droplet temperatures, except for larger droplets in environments close to saturation. The implications for ice nucleation in cloud-top generating cells and near cloud edges are discussed. Using T ss instead of T ∞ in widely used parameterization schemes could lead to enhanced number concentrations of activated ice-nucleating particles (INPs), by a typical factor of 2–30, with the greatest increases (≥100) coincident with low RH, low P , and T ∞ closer to 0°C.

The formation and persistence of low-lying mixed-phase clouds (MPCs) in the Arctic depends on a multitude of processes, such as surface conditions, the environmental state, air mass advection, and the ambient aerosol concentration. In this study, we focus on the relative importance of different instantaneous aerosol perturbations (cloud condensation nuclei and ice-nucleating particles; CCN and INPs, respectively) on MPC properties in the European Arctic. To address this topic, we performed high-resolution large-eddy simulation (LES) experiments using the Consortium for Small-scale Modeling (COSMO) model and designed a case study for the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign in March 2013. Motivated by ongoing sea ice retreat, we performed all sensitivity studies over open ocean and sea ice to investigate the effect of changing surface conditions. We find that surface conditions highly impact cloud dynamics, consistent with the ACCACIA observations: over sea ice, a rather homogeneous, optically thin, mixed-phase stratus cloud forms. In contrast, the MPC over the open ocean has a stratocumulus-like cloud structure. With cumuli feeding moisture into the stratus layer, the cloud over the open ocean features a higher liquid (LWP) and ice water path (IWP) and has a lifted cloud base and cloud top compared to the cloud over sea ice. Furthermore, we analyzed the aerosol impact on the sea ice and open ocean cloud regime. Perturbation aerosol concentrations relevant for CCN activation were increased to a range between 100 and 1000 cm−3 and ice-nucleating particle perturbations were increased by 100 % and 300 % compared to the background concentration (at every grid point and at all levels). The perturbations are prognostic to allow for fully interactive aerosol–cloud interactions. Perturbations in the INP concentration increase IWP and decrease LWP consistently in both regimes. The cloud microphysical response to potential CCN perturbations occurs faster in the stratocumulus regime over the ocean, where the increased moisture flux favors rapid cloud droplet formation and growth, leading to an increase in LWP following the aerosol injection. In addition, IWP increases through new ice crystal formation by increased immersion freezing, cloud top rise, and subsequent growth by deposition. Over sea ice, the maximum response in LWP and IWP is delayed and weakened compared to the response over the open ocean surface. Additionally, we find the long-term response to aerosol perturbations to be highly dependent on the cloud regime. Over the open ocean, LWP perturbations are efficiently buffered after 18 h simulation time. Increased ice and precipitation formation relax the LWP back to its unperturbed range. On the contrary, over sea ice the cloud evolution remains substantially perturbed with CCN perturbations ranging from 200 to 1000 CCN cm−3.