Effects of the Large-Scale Circulation on Temperature and Water Vapor Distributions in the Π Chamber

Microphysical processes are important for the development of clouds and thus Earth\u27s climate. For example, turbulent fluctuations in the water vapor concentration, r, and temperature, T, cause fluctuations in the saturation ratio, S. Because S is the driving factor in the condensational growth of droplets, fluctuations may broaden the cloud droplet size distribution due to individual droplets experiencing different growth rates. The small scale turbulent fluctuations in the atmosphere that are relevant to cloud droplets are difficult to quantify through field measurements. We investigate these processes in the laboratory, using Michigan Tech\u27s Π Chamber. The Π Chamber utilizes Rayleigh-Benard convection (RBC) to create the turbulent conditions inherent in clouds. In RBC it is common for a large scale circulation (LSC) to form. As a consequence of the LSC, the temperature field of the chamber is not spatially uniform. In this paper, we characterize the LSC in the Π chamber and show how it affects the shape of the distributions of r, T and S. The LSC was found to follow a single roll with an updraft and downdraft along opposing walls of the chamber. Near the updraft (downdraft), the distributions of T and r were positively (negatively) skewed. S consistently had a negatively skewed distribution, with the downdraft being the most negative

Light scattering in a turbulent cloud: Simulations to explore cloud-chamber experiments

Radiative transfer through clouds can be impacted by variations in particle number size distribution, but also in particle spatial distribution. Due to turbulent mixing and inertial effects, spatial correlations often exist, even on scales reaching the cloud droplet separation distance. The resulting clusters and voids within the droplet field can lead to deviations from exponential extinction. Prior work has numerically investigated these departures from exponential attenuation in absorptive and scattering media; this work takes a step towards determining the feasibility of detecting departures from exponential behavior due to spatial correlation in turbulent clouds generated in a laboratory setting. Large Eddy Simulation (LES) is used to mimic turbulent mixing clouds generated in a laboratory convection cloud chamber. Light propagation through the resulting polydisperse and spatially correlated particle fields is explored via Monte Carlo ray tracing simulations. The key finding is that both mean radiative flux and standard deviation about the mean differ when correlations exist, suggesting that an experiment using a laboratory convection cloud chamber could be designed to investigate non-exponential behavior. Total forward flux is largely unchanged (due to scattering being highly forward-dominant for the size parameters considered), allowing it to be used for conditional sampling based on optical thickness. Direct and diffuse forward flux means are modified by approximately one standard deviation. Standard deviations of diffuse forward and backward fluxes are strongly enhanced, suggesting that fluctuations in the scattered light are a more sensitive metric to consider. The results also suggest the possibility that measurements of radiative transfer could be used to infer the strength and scales of correlations in a turbulent cloud, indicating entrainment and mixing effects

Direct numerical simulation of turbulence and microphysics in the Pi Chamber

The Pi Chamber is a cloud chamber at Michigan Technological University that utilizes moist turbulent Rayleigh-Bénard flow between two temperature-controlled, saturated plates to create cloud conditions in a controlled laboratory setting. This experimental apparatus has been the source of numerous scientific studies but also offers an advantageous platform with which to test numerical modeling approaches. In this study, the primary goal is to use direct numerical simulation (DNS) with Lagrangian aerosol/droplet microphysics to recreate, as realistically as possible, the conditions inside the Pi Chamber. The biggest discrepancies between the DNS and laboratory setups are the Rayleigh number (Ra=7.9×106 in the DNS) and the use of periodic lateral boundary conditions. Nonetheless, numerical experiments are conducted for two published Pi Chamber cases: steady aerosol injection and the resulting statistically steady-state cloud and transient conditions when aerosol injection is shut off. Generally speaking, the DNS is able to capture many of the salient features observed in the Pi Chamber experiments, both qualitatively and quantitatively, including microphysical details and influences on the fluctuating ambient saturation in the chamber. From the DNS, Lagrangian statistics are interrogated which are otherwise inaccessible from the experimental view. In particular, the supersaturation fluctuations seen by droplets are observed to deviate from a Gaussian distribution - a common assumption in stochastic modeling - and the probability distribution of droplet lifetime does not adhere to the expected behavior assuming solid particles settling in a quiescent medium

Sources of Stochasticity in the Growth of Cloud Droplets: Supersaturation Fluctuations versus Turbulent Transport

The role played by fluctuations of supersaturation in the growth of cloud droplets is examined in this study. The stochastic condensation framework and the three regimes of activation of cloud droplets— namely, mean dominant, fluctuation influenced, and fluctuation dominant—are used for analyzing the data from high-resolution large-eddy simulations of the Pi convection-cloud chamber. Based on a detailed budget analysis the significance of all the terms in the evolution of the droplet size distribution equation is evaluated in all three regimes. The analysis indicates that the mean-growth rate is a dominant process in shaping the droplet size distribution in all three regimes. Turbulence introduces two sources of stochasticity, turbulent transport and particle lifetime, and supersaturation fluctuations. The transport of cloud droplets plays an important role in all three regimes, whereas the direct effect of supersaturation fluctuations is primarily related to the activation and growth of the small droplets in the fluctuation-influenced and fluctuation-dominant regimes. We compare our results against the previous studies (experimental and theory) of the Pi chamber, and discuss the limitations of the existing models based on the stochastic condensation framework. Furthermore, we extend the discussion of our results to atmospheric clouds, and in particular focus on recent adiabatic turbulent cloud parcel simulations based on the stochastic condensation framework, and emphasize the importance of entrainment/mixing and turbulent transport in shaping the droplet size distribution

Is Contact Nucleation Caused by Pressure Perturbation?

The reason why ice nucleation is more efficient by contact nucleation than by immersion nucleation has been elusive for over half a century. Six proposed mechanisms are summarized in this study. Among them, the pressure perturbation hypothesis, which arose from recent experiments, can qualitatively explain nearly all existing results relevant to contact nucleation. To explore the plausibility of this hypothesis in a more quantitative fashion and to guide future investigations, this study assessed the magnitude of pressure perturbation needed to cause contact nucleation and the associated spatial scales. The pressure perturbations needed were estimated using measured contact nucleation efficiencies for illite and kaolinite, obtained from previous experiments, and immersion freezing temperatures, obtained from well-established parameterizations. Pressure perturbations were obtained by assuming a constant pressure perturbation or a Gaussian distribution of the pressure perturbation. The magnitudes of the pressure perturbations needed were found to be physically reasonable, being achievable through possible mechanisms, including bubble formation and breakup, Laplace pressure arising from the distorted contact line, and shear. The pressure perturbation hypothesis provides a physically based and experimentally constrainable foundation for parameterizing contact nucleation that may be useful in future cloud-resolving models

Measurement of optical blurring in a turbulent cloud chamber

© 2016 SPIE. Earth\u27s atmosphere can significantly impact the propagation of electromagnetic radiation, degrading the performance of imaging systems. Deleterious effects of the atmosphere include turbulence, absorption and scattering by particulates. Turbulence leads to blurring, while absorption attenuates the energy that reaches imaging sensors. The optical properties of aerosols and clouds also impact radiation propagation via scattering, resulting in decorrelation from unscattered light. Models have been proposed for calculating a point spread function (PSF) for aerosol scattering, providing a method for simulating the contrast and spatial detail expected when imaging through atmospheres with significant aerosol optical depth. However, these synthetic images and their predicating theory would benefit from comparison with measurements in a controlled environment. Recently, Michigan Technological University (MTU) has designed a novel laboratory cloud chamber. This multiphase, turbulent Pi Chamber is capable of pressures down to 100 hPa and temperatures from -55 to +55°C. Additionally, humidity and aerosol concentrations are controllable. These boundary conditions can be combined to form and sustain clouds in an instrumented laboratory setting for measuring the impact of clouds on radiation propagation. This paper describes an experiment to generate mixing and expansion clouds in supersaturated conditions with salt aerosols, and an example of measured imagery viewed through the generated cloud is shown. Aerosol and cloud droplet distributions measured during the experiment are used to predict scattering PSF and MTF curves, and a methodology for validating existing theory is detailed. Measured atmospheric inputs will be used to simulate aerosol-induced image degradation for comparison with measured imagery taken through actual cloud conditions. The aerosol MTF will be experimentally calculated and compared to theoretical expressions. The key result of this study is the proposal of a closure experiment for verification of theoretical aerosol effects using actual clouds in a controlled laboratory setting

Aerosol Composition, Mixing State, and Phase State of Free Tropospheric Particles and Their Role in Ice Cloud Formation

The prediction of ice cloud formation in the atmosphere remains challenging. Free tropospheric aerosols can act as ice nucleating particles, affecting cloud properties and precipitation. The physicochemical properties of free tropospheric particles are modified upon long-range transport by different atmospheric processes. These modifications affect the ice formation potential of individual particles. We investigated the physicochemical properties of free tropospheric particles collected at the remote Pico Mountain Observatory at 2225 m a.s.l. in the North Atlantic Ocean using multimodal micro-spectroscopy and chemical imaging techniques. We probed their ice nucleation (IN) activity using an IN stage interfaced with an environmental scanning electron microscope. Retroplume analysis, chemical imaging, and micro-spectroscopy analysis indicated that the size-resolved chemical composition, mixing state, and phase state of the particles with similar aging times but different transport patterns were substantially different. Relative humidity-dependent glass-transition temperatures estimated from meteorological conditions were consistent with the observed organic component of the particles\u27 phase. More viscous (solid and semi-solid-like) particles are more ice active in the deposition mode at temperatures ranging from 205 to 220 K than less viscous particles. This study provides a better understanding of the phase and mixing state of long-range transported free tropospheric aerosols and their role in ice cloud formation