Abstract This study demonstrates the high‐resolution profiling of cloud microphysics in a laboratory chamber using Time‐Correlated Single Photon Counting (TCSPC) LiDAR. We present a novel retrieval method to derive vertical extinction (σ) profiles, constrained by in situ measurements, to diagnose responses to dry‐air entrainment. In clean clouds, the LiDAR signals and retrieved σ remain relatively uniform, with entrainment effects confined to the upper layer. In contrast, polluted clouds exhibit strong vertical variability and a transition to a water‐vapor‐limited state. Entrainment significantly enhances the haze number concentration Nh, particularly near the bottom, creating highly height‐dependent extinction profiles for polluted clouds. Our results highlight the capability of high‐resolution LiDAR in capturing fine‐scale vertical inhomogeneities. This approach provides a robust framework for quantifying how aerosol loading modulates entrainment sensitivity, offering new insights into the transition between buffered and water‐vapor‐limited regimes.

Understanding and quantifying the full chain of processes from aerosol activation to drizzle formation, and the associated feedbacks to the aerosol chemical and physical properties, all within a turbulent cloud are some of the toughest challenges in atmospheric chemistry and physics and are keys to the cloud-precipitation puzzle. This paper describes a concept for a new type of research facility consisting of a cloud chamber plus associated instrumentation and computational models, to explore aerosol-cloud interactions and processing, cloud optical properties, entrainment-cloud interactions, and quantitative assessment of drizzle onset. The envisioned design is for a 3 m & times; 3 m & times; 9 m chamber, such that the height is sufficient to achieve long lifetimes for aerosol processing and for significant drizzle growth by collision and coalescence. A suite of computational tools for simulating microphysical properties in the chamber provides a digital twin for designing the chamber and a range of example experiments. Theory and test results from novel remote sensing systems for exploring chemical and physical interactions and evolution of aerosols, cloud droplets, and drizzle within turbulent clouds are described. Testing of technology needed for the operation of a large-volume chamber, including aerosol generation methods and novel materials for water vapor boundary conditions, is described. Simulations suggest that spatially uniform turbulence and microphysical properties can be sustained in a steady state, with reasonable aerosol and water vapor fluxes, and that substantial drizzle can be produced through collision and coalescence of cloud droplets. Remaining challenges for more detailed engineering design and a discussion of possible first-light experiments are described. SIGNIFICANCE STATEMENT: Aconcept has been developed for an Aerosol-Cloud-Drizzle-Convection Chamber (ACDC2) with accompanying prototype instrumentation and computational modeling tools. Together, this envisioned facility would enable critical impacts in atmospheric science by addressing one of its toughest challenges: quantifying the links and feedbacks between aerosols, clouds, and precipitation. Existing gaps in our understanding of these interactions within turbulent clouds hinder accurate modeling of pollution, weather, and Earth system feedbacks. This novel, approximate to 10-m-tall chamber will create a controlled environment to explore the full chain of events from aerosol activation to drizzle onset with unprecedented measuring capabilities. It would serve as an ideal testbed for validating and improving atmospheric models, testing instrumentation, evaluating cloud-modification techniques, and untangling complex aerosol-cloud-precipitation processes.

Solar radiation modification (SRM) techniques such as mixed-phase cloud thinning (MCT), cirrus cloud thinning (CCT), and stratospheric aerosol injection (SAI) all include introducing foreign material into the troposphere and stratosphere, and can have unexpected effects on clouds spatially removed from the intended targets. It has been shown that mixed-phase clouds affect precipitation patterns over land, which in turn has tangible effects on agriculture. Mixed-phase clouds are generated at the Pi Chamber facility at Michigan Technological University by setting a temperature difference between the top and bottom plate of the chamber to create a convective cell, and then injecting aerosols or ice nucleating particles (INP). Using our own water isotope instruments and the cloud probes at the chamber, we will study the isotopic response of water vapor and condensate (H2O, HDO, H218O) in these mixed-phase clouds at varying glaciation fractions. We aim to better understand the growth and evolution of mixed-phase clouds in the presence of SRM material, in particular: the glaciation altitude of mixed-phase clouds, how processed SAI aerosols transported to the poles might affect mixed-phase clouds in that region, and the secondary effects of sedimenting particles used in CCT on mixed-phase clouds. We will also vary the amount and type of INP to study at what point precipitation might become suppressed. Ice deposition growth via the Wegner-Bergeron-Findeisen (WBF) process, which encourages the rapid growth and then sedimentation of ice crystals at the expense of liquid droplets, produces a strong isotopic signal that we will use to probe cloud microphysics and provide constraints on models. Early results from a bin-resolved microphysics model (BRIMM) show that our instruments are sensitive enough to see the expected isotopic signature from the WBF process. While only small modifications are needed to our previously field-tested flight and lab spectrometers to allow integration into the chamber (ChiWIS-airborne used in StratoClim and ACCLIP, and ChiWIS-lab used in IsoCloud), a method to best discriminate particles from vapor, without disturbing the cloud to be studied, is required. We explain design constraints and present early engineering test results.

The settling and deposition behavior of small particles significantly impacts many environmental and industrial processes. Although particle settling dynamics within turbulent environments have been extensively studied through theory and simulation, more experimental investigation is needed to test the idealized results against real-world turbulent flows. In this work, we infer the settling velocity of particles in Rayleigh-B & eacute;nard (RB) turbulence through the measurement of declines in particle concentration due to deposition within a 3.14 m(3) convection chamber. Oil droplets from 1 to 10 mu m and glass beads from 1 to 38 mu m were used as the particle material, yielding Kolmogorov-based particle Stokes numbers in the range of 3 & times;10(-5) to 0.1. Our measurements reveal a linear scaling with particle diameter, rather than the diameter-squared scaling expected for these Stokes numbers. Direct numerical simulations (DNS) designed to mirror the experimental configuration were also performed; these yielded the familiar diameter-squared scaling. We suggest that the discrepancy between the experimental results and the theoretical framework and DNS, which makes standard assumptions regarding lift and drag, may be due to unresolved physics near the domain boundary, which dictates overall removal rates. Future work employing more direct observational methods of particle settling within RB turbulence is required to better understand these near-wall removal processes. The departure from Stokes settling within this set of experiments brings to question the limits of the applicability of the "stirred settling" model commonly invoked for estimating particle removal rates, suggesting that adjustments to traditional assumptions may be required. Such corrections may prove especially important in the design of future cloud convection chambers.

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.

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.

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.

This study delves into the small-scale temperature structure inside the turbulent convection Pi Chamber under three temperature differences (10, 15, and 20 K) at Rayleigh number Ra similar to 109 and Prandtl number Pr approximate to 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 mu m 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 similar to-7/5), "transition range" (slopes of similar to-3), and "dissipative range", characterized by slopes of similar to-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.

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.

Changes in aerosol concentrations can modify cloud brightness, producing a strong but poorly constrained influence on Earth's energy balance. Because cloud reflectivity depends on the size distribution of cloud droplets, and aerosol size strongly governs activation into droplets, one might expect cloud properties to be sensitive to aerosol size distributions. Here we show, through a combination of cloud chamber experiments and high-resolution simulations, that cloud microphysical and optical properties are often insensitive to aerosol size. Detectable impacts on cloud optical properties occur only under weak convective forcing and high aerosol concentrations. These results indicate that, in most conditions, cloud reflectivity can be predicted from aerosol number alone without detailed knowledge of aerosol size distributions, providing new constraints on how aerosol perturbations affect climate.

Abstract Entrainment of subsaturated air into a cloud can influence its optical and microphysical properties in various ways, depending on the droplet evaporation and turbulent mixing time scales. Previous experiments in the Pi convection-cloud chamber have revealed that, given a fixed entrained air property, the mixing of entrained subsaturated air results in complete evaporation of some cloud droplets, with the rest remaining unchanged. This is a signature of inhomogeneous mixing. While comparing the results of entrainment with varying air properties, the mixing signature appears as if the subsaturated air is well mixed with the cloud to evenly reduce the droplets’ size. In other words, taken together, the experiments appear to have the signature of homogeneous mixing. To explore these results in a greater depth, we conduct large-eddy simulations combined with a bin microphysics scheme. Our results reproduce the similar signatures of inhomogeneous and homogeneous mixing, implying that LES can resolve the inhomogeneous mixing when the grid spacing is smaller than the entrained air parcel. Additionally, we observe that increasing the aerosol injection rate enhances the signature of inhomogeneous mixing, while coarser grid spacing diminishes it. Finally, the change in wall fluxes in response to various entrained air properties confirms that the homogeneous signature seen in the analysis of an ensemble of simulations is the result of various equilibrium states. This further strengthens the suggestion that the homogeneous mixing signature found in aircraft observations near the cloud top may result from combining entrainment events of different intensities, possibly caused by various-sized eddies. Significance Statement Large-eddy simulation and size-resolved microphysics can resolve time scales for turbulent mixing and evaporation and, therefore, are well suited for reproducing, extending, and interpreting the entrainment experiment in the Pi convection-cloud chamber. Our simulation results confirm (i) the inhomogeneous mixing signature for an individual entrainment event and (ii) the appearance of homogeneous mixing in an ensemble of entrainment episodes. Furthermore, we demonstrate that the inhomogeneous mixing signature is more pronounced in a polluted cloud, but coarser grid spacing in simulations may compromise the accuracy of this signature. Last, the homogeneous mixing signature results from various equilibrium states established for different entrainment intensities and adjusted wall fluxes, which are challenging to measure experimentally but can be easily analyzed in the simulations.

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.

Mixed-phase clouds affect precipitation and radiation differently from liquid and ice clouds, posing greater challenges to their representation in numerical simulations. Recent laboratory experiments using the Pi Cloud Chamber explored cloud glaciation conditions based on increased injection of ice-nucleating particles. In this study, we use two approaches to reproduce the results of the laboratory experiments: a bulk scalar mixing model and large-eddy simulation (LES) with bin microphysics. The first approach assumes a well-mixed domain to provide an efficient assessment of the mean cloud properties for a wide range of conditions. The second approach resolves the energy-carrying turbulence, the particle size distribution, and their spatial distribution to provide more details. These modeling approaches enable a separate and detailed examination of liquid and ice properties, which is challenging in the laboratory. Both approaches demonstrate that, with an increased ice number concentration, the flow and microphysical properties exhibit the same changes in trends. Additionally, both approaches show that the ice integral radius reaches the theoretical glaciation threshold when the cloud is subsaturated with respect to liquid water. The main difference between the results of the two approaches is that the bulk model allows for the complete glaciation of the cloud. However, LES reveals that, in a dynamic system, the cloud is not completely glaciated as liquid water droplets are continuously produced near the warm lower boundary and subsequently mixed into the chamber interior. These results highlight the importance of the ice mass fraction in distinguishing the mixed-phase clouds and ice clouds.

Entrainment of subsaturated air into a cloud can influence its optical and microphysical properties in various ways, depending on the droplet evaporation and turbulent mixing time scales. Previous experiments in the Pi convectioncloud chamber have revealed that, given a fixed entrained air property, the mixing of entrained subsaturated air results in complete evaporation of some cloud droplets, with the rest remaining unchanged. This is a signature of inhomogeneous mixing. While comparing the results of entrainment with varying air properties, the mixing signature appears as if the subsaturated air is well mixed with the cloud to evenly reduce the droplets' size. In other words, taken together, the experiments appear to have the signature of homogeneous mixing. To explore these results in a greater depth, we conduct large-eddy simulations combined with a bin microphysics scheme. Our results reproduce the similar signatures of inhomogeneous and homogeneous mixing, implying that LES can resolve the inhomogeneous mixing when the grid spacing is smaller than the entrained air parcel. Additionally, we observe that increasing the aerosol injection rate enhances the signature of inhomogeneous mixing, while coarser grid spacing diminishes it. Finally, the change in wall fluxes in response to various entrained air properties confirms that the homogeneous signature seen in the analysis of an ensemble of simulations is the result of various equilibrium states. This further strengthens the suggestion that the homogeneous mixing signature found in aircraft observations near the cloud top may result from combining entrainment events of different intensities, possibly caused by various-sized eddies.

Marine cloud brightening (MCB) is the deliberate injection of aerosol particles into shallow marine clouds to increase their reflection of solar radiation and reduce the amount of energy absorbed by the climate system. From the physical science perspective, the consensus of a broad international group of scientists is that the viability of MCB will ultimately depend on whether observations and models can robustly assess the scale-up of local-to-global brightening in today’s climate and identify strategies that will ensure an equitable geographical distribution of the benefits and risks associated with projected regional changes in temperature and precipitation. To address the physical science knowledge gaps required to assess the societal implications of MCB, we propose a substantial and targeted program of research—field and laboratory experiments, monitoring, and numerical modeling across a range of scales.

The subgrid-scale (SGS) scalar variance represents the " unmixedness " of the unresolved small scales in large -eddy simulations (LES) of turbulent fl ows. 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 fl uctuations in microphysics models. We present results from a priori tests of SGS scalar variance models using data collected in turbulent Rayleigh - B & eacute;nard convection in the Michigan Tech Pi chamber for Rayleigh numbers Ra 10 8 - 10 9 . Data from an array of 10 thermistors were spatially fi ltered and used to calculate the true SGS scalar variance, a scale -similarity model, and a gradient model for dimensionless fi lter widths of h / A = 25,14.3, and 10 (where h is the height of the chamber and A is the spatial fi lter width). The gradient model was found to have fairly low correlations ( p 0.2), with the most probable values departing signi fi cantly 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 ( p 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 and h / A. The similarity model, which only requires an additional test fi ltering operation, is therefore a promising approach for modeling the SGS scalar variance in LES of cloud turbulence and other related fl ows.