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Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection-Cloud Chamber generates a turbulent cloud with a microphysical steady-state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and co-located Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damk{\"o}hler number ($Da$), under conditions corresponding to $Da \lesssim 1$, i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such that $Da \lesssim 1$ is satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth.


The accompanying file "Saturation Ratio Variability" contains the data supporting Figures 1 through 7 in the paper by Anderson et al., "Droplet growth or evaporation does not buffer the variability in supersaturation in clean clouds", submitted to The Journal of the Atmospheric Sciences (JAS) in June 2023.

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