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Abstract Atmospheric aerosol particles that contain water‐soluble components can absorb water vapor in humid environments and form either haze particles or cloud droplets, depending on supersaturation conditions. Laboratory and in situ measurements have shown that haze particles and cloud droplets often coexist and compete for available water vapor in shallow clouds and fogs, especially under polluted conditions. It is expected that more aerosol particles can form more haze particles and cloud droplets, so that the haze and cloud number concentrations are positively correlated. However, recent large‐eddy simulations show that haze and cloud number concentration can be negatively correlated under extremely polluted conditions. Haze–cloud interactions across different environmental settings remain poorly understood. In this study, experiments in a convection cloud chamber with the same aerosol injection rate show that, as supersaturation forcing increases (i.e., changing from polluted to clean conditions), the covariance between haze and cloud droplet number concentration changes from negative to positive and finally to zero. Large‐eddy simulations (LES) of the cloud chamber with a fixed supersaturation forcing but varying aerosol injection rates show a similar result for the haze–cloud correlation: near zero in clean, mean‐supersaturation‐dominated activation conditions; positive in moderate, supersaturation‐fluctuation‐influenced activation conditions; and negative in polluted, supersaturation‐fluctuation‐dominated activation conditions. A theoretical covariance framework was developed to interpret this behavior based on the relative magnitude and signs of the correlations between supersaturation and the populations of haze and cloud droplets. Significantly, experiments, LES, and theory all yield the same three‐regime behavior for the sign of the haze–cloud covariance. Our results show that the haze–cloud covariance remains robust and easily measurable, thereby providing a useful metric for regime identification in the atmosphere, improving regime‐aware parameterizations, and informing aerosol interventions such as fog dispersion, rainfall enhancement, and albedo modification. 

Abstract Experiments in the Pi Convection‐Cloud Chamber conducted by systematically changing the diameter of injected dry aerosol particles while holding the temperature difference constant demonstrate that dry diameter strongly influences the onset of haze‐dominated conditions. Two factors contribute: the system becomes water‐limited, resulting in reduction of supersaturation by growing aerosol particles to the activation diameter; and the activation process becomes kinetically limited. Dry aerosol diameter exerts a strong influence on activation time, with a power‐law exponent of . Kinetically limited activation occurs when the ratio of the activation and droplet residence times is greater than unity. The findings demonstrate that a haze‐dominated state, where cloud formation is suppressed, can be achieved not only with weak supersaturation forcing and high aerosol concentration but also with large, hygroscopic aerosol particles. These results have implications for cloud formation in polluted environments, fog development near the ocean, and hygroscopic cloud seeding. 

Abstract This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties. 

Abstract Cloud formation in the Pi Convection–Cloud Chamber is achieved via ionization in humid conditions, without the injection of aerosol particles to serve as cloud condensation nuclei (CCN). Abundant ions, turbulence, and supersaturated water vapor combine to produce new particles, which grow to become CCN sized and eventually are activated to form clouds. Coupling between the new particle formation and cloud droplets causes predator-prey type oscillations in aerosol and droplet concentrations under turbulent conditions. Leading terms are identified in the budgets for Aitken and accumulation mode aerosols and for cloud droplets. The cloud coupling is proposed to be a result of cloud-induced runaway CCN production through aerosol scavenging. The experiments suggest potential applications to marine cloud brightening, in which ions rather than sea-salt aerosols are generated. 

Abstract The subgrid-scale (SGS) scalar variance represents the “unmixedness” of the unresolved small scales in large-eddy simulations (LES) of turbulent flows. Supersaturation variance can play an important role in the activation, growth, and evaporation of cloud droplets in a turbulent environment, and therefore efforts are being made to include SGS supersaturation fluctuations in microphysics models. We present results from a priori tests of SGS scalar variance models using data collected in turbulent Rayleigh–Bénard convection in the Michigan Tech Pi chamber for Rayleigh numbers Ra ∼ 10⁸–10⁹. Data from an array of 10 thermistors were spatially filtered and used to calculate the true SGS scalar variance, a scale-similarity model, and a gradient model for dimensionless filter widths ofh/Δ = 25, 14.3, and 10 (wherehis the height of the chamber and Δ is the spatial filter width). The gradient model was found to have fairly low correlations (ρ∼ 0.2), with the most probable values departing significantly from the one-to-one line in joint probability density functions (JPDFs). However, the scale-similarity model was found to have good behavior in JPDFs and was highly correlated (ρ∼ 0.8) with the true SGS variance. Results of the a priori tests were robust across the parameter space considered, with little dependence on Ra andh/Δ. The similarity model, which only requires an additional test filtering operation, is therefore a promising approach for modeling the SGS scalar variance in LES of cloud turbulence and other related flows. 

Abstract. This study delves into the small-scale temperature structure inside the turbulent convection Π Chamber under three temperature differences (10, 15, and 20 K) at Rayleigh number Ra∼109 and Prandtl number Pr≈0.7. We performed high-frequency measurements (2 kHz) with the UltraFast Thermometer (UFT) at selected points along the vertical axis. The miniaturized design of the sensor with a resistive platinum-coated tungsten wire, 2.5 µm thick and 3 mm long, mounted on a miniature wire probe, allowed for vertically undisturbed temperature profiling through the chamber's depth spanning from 8 cm above the bottom to 5 cm below the top. The collected data, consisting of 19 and 3 min time series, were used to investigate the variability of the temperature field within the chamber, aiming to better address scientific questions related to its primary objective: understanding small-scale aerosol–cloud interactions. The analyses reveal substantial variability in both variance and skewness of temperature distributions near the top and bottom plates and in the bulk (central) region, which were linked to local thermal plume dynamics. We also identified three spectral regimes termed “inertial range” (slopes of ∼-7/5), “transition range” (slopes of ∼-3), and “dissipative range”, characterized by slopes of ∼-7. Furthermore, the analysis showed a power law relationship between the periodicity of large-scale circulation (LSC) and the temperature difference. Notably, the experimental results are in good agreement with direct numerical simulation (DNS) conducted under similar thermodynamic conditions, illustrating a comparative analysis of this nature. 

Impacts of aerosol particles on clouds, precipitation, and climate remain one of the significant uncertainties in climate change. Aerosol particles entrained at cloud top and edge can affect cloud microphysical and macrophysical properties, but the process is still poorly understood. Here we investigate the cloud microphysical responses to the entrainment of aerosol-laden air in the Pi convection-cloud chamber. Results show that cloud droplet number concentration increases and mean radius of droplets decreases, which leads to narrower droplet size distribution and smaller relative dispersion. These behaviors are generally consistent with the scenario expected from the first aerosol-cloud indirect effect for a constant liquid water content (L). However, L increases significantly in these experiments. Such enhancement of L can be understood as suppression of droplet sedimentation removal due to small droplets. Further, an increase in aerosol concentration from entrainment reduces the effective radius and ultimately increases cloud optical thickness and cloud albedo, making the clouds brighter. These findings are of relevance to the entrainment interface at stratocumulus cloud top, where modeling studies have suggested sedimentation plays a strong role in regulating L. Therefore, the results provide insights into the impacts of entrainment of aerosol-laden air on cloud, precipitation, and climate.