Scaling of an Atmospheric Model to Simulate Turbulence and Cloud Microphysics in the Pi Chamber

Abstract

The Pi Cloud Chamber offers a unique opportunity to study aerosol-cloud microphysics interactions in a steady-state, turbulent environment. In this work, an atmospheric large-eddy simulation (LES) model with spectral bin microphysics is scaled down to simulate these interactions, allowing comparison with experimental results. A simple scalar flux budget model is developed and used to explore the effect of sidewalls on the bulk mixing temperature, water vapor mixing ratio, and supersaturation. The scaled simulation and the simple scalar flux budget model produce comparable bulk mixing scalar values. The LES dynamics results are compared with particle image velocimetry measurements of turbulent kinetic energy, energy dissipation rates, and large-scale oscillation frequencies from the cloud chamber. These simulated results match quantitatively to experimental results. Finally, with the bin microphysics included the LES is able to simulate steady-state cloud conditions and broadening of the cloud droplet size distributions with decreasing droplet number concentration, as observed in the experiments. The results further suggest that collision-coalescence does not contribute significantly to this broadening. This opens a path for further detailed intercomparison of laboratory and simulation results for model validation and exploration of specific physical processes.

Light Scattering in a Turbulent Cloud: Simulations to Explore Cloud-Chamber Experiments

“…It is worth noting that the chosen approach of large eddy simulation captures the large-scale variability in scalar fields due to anisotropic forcing in Rayleigh-Bénard convection. The variability captured by the LES is consistent with observations in the Pi Chamber [15]. Because the dissipation scales are not resolved, other clustering effects, such as those due to droplet inertia, are not represented.…”

“…For simulating the aerosol-cloud interactions, the code has been coupled with HUJISBM, a spectral bin microphysics code [35]. To simulate the cloudy Rayleigh-Bénard convection within the Pi Chamber, SAM has been scaled down and the top and lateral boundary conditions have been modified and quantitatively verified against experiments [15]. For completeness, a brief description of the SAM model is provided below.…”

“…For the current study, we allowed the system to evolve and reach a steady supersaturation of 2.5%, measured as a planar average at the mean height in the chamber (excluding the grid points nearest the chamber sidewalls). Once the steady state supersaturation was reached [15], we injected cloud condensation nuclei (CCN) at the center of the chamber at a rate of 92,400 particles per cm 3 per second; all introduced CCN had a radius of 62.5 nm, representing a unimodal CCN distribution at the center of a bin ranging from 56 to 71 nm. The cloud reaches a steady state by striking a balance between activation and removal due to sedimentation.…”

“…In this work, a Large Eddy Simulation (LES) code is used to generate clouds with properties (such as optical thickness, particle size distribution function, and spatial correlation) realistic for a laboratory-generated mixing cloud in the Pi Chamber [15]. A MCRT code, capable of simulating scattering events with appropriate phase functions, propagates individual photons from a normally incident collimated beam through the LES-generated particle distribution, while tracking direct, diffuse forward and diffuse backward radiative fluxes.…”

Investigation of Light Transport and Scattering in Turbulent Clouds: Simulations and Laboratory Measurements

“…For simulating the aerosol -cloud interactions, the code has been coupled with HUJISBM, a spectral bin microphysics code (Khain et al, 2004). To simulate the cloudy Rayleigh-Bénard convection, SAM has been scaled down and the top and lateral boundary conditions have been modified and quantitatively verified against experiments (Thomas et al, 2019). For completeness, a brief description of the SAM model is provided below.…”