Retrieving Supersaturation in a Convective Cloud Chamber through Droplet Size Distribution.

Laboratory convection cloud chambers (like the Pi Chamber at Michigan Technological University) produce supersaturation by turbulent mixing of saturated air parcels with different temperatures. A cloud forms in the chamber by continuously injecting aerosols into the supersaturated air. A steady state is reached when the source of supersaturation and injected aerosols are balanced by condensation, growth of cloud droplets, and their sedimentation.

Measurements of water vapor in the Pi Chamber have been made by an infrared hygrometer. Anderson et al. (2021, 2024) combined these with temperature measurements to calculate the mean and fluctuations of supersaturation. However, Anderson et al. (2024) noted limitations in the ability to measure the magnitude of supersaturation, which motivated us to investigate methods for inferring the mean supersaturation with alternative methods.

One approach relies on measured particle size distributions (PSD). We derived an equation to estimate the mean supersaturation from the PSD and the injected aerosol properties. We also derived an equation for water mass sedimentation through the chamber's floor. These equations are valid in steady state conditions.

We tested this method using particle-resolving simulations of the Pi Chamber. We used the Cloudy One-Dimensional Turbulence (CODT) model, and two direct numerical simulation (DNS) models (from NSF NCAR and University of Notre Dame). Each estimate had less than 5% error compared to modeled mean supersaturation.