Dispersion Aerosol Indirect Effect in Turbulent Clouds: Laboratory Measurements of Effective Radius.

Cloud optical properties are determined not only by the number density n d and mean radius r ¯ of cloud droplets but also by the shape of the droplet size distribution. The change in cloud optical depth with changing n d , due to the change in distribution shape, is known as the dispersion effect. Droplet relative dispersion is defined as d = σ r / r ¯ . For the first time, a commonly used effective radius parameterization is tested in a controlled laboratory environment by creating a turbulent cloud. Stochastic condensation growth suggests d independent of n d for a nonprecipitating cloud, hence nearly zero albedo susceptibility due to the dispersion effect. However, for size-dependent removal, such as in a laboratory cloud or highly clean atmospheric conditions, stochastic condensation produces a weak dispersion effect. The albedo susceptibility due to turbulence broadening has the same sign as the Twomey effect and augments it by order 10%.

Influence of Turbulent Fluctuations on Cloud Droplet Size Dispersion and Aerosol Indirect Effects.

Cloud droplet relative dispersion, defined as the standard deviation over the mean cloud droplet size, is of central importance in determining and understanding aerosol indirect effects. In recent work, it was found that cloud droplet size distributions become broader as a result of supersaturation variability and that the sensitivity of this effect is inversely related to cloud droplet number density. The subject is investigated in further detail using an extensive dataset from a laboratory cloud chamber capable of producing steady-state turbulence. An extended stochastic theory is found to successfully describe properties of the droplet size distribution, including an analytical expression for the relative dispersion. The latter is found to depend on the cloud droplet removal time, which in turn increases with the cloud droplet number density. The results show that relative dispersion decreases monotonically with increasing droplet number density, consistent with some recent atmospheric observations. Experiments spanning fast to slow microphysics regimes are reported. The observed dispersion is used to estimate time scales for autoconversion, demonstrating the important role of the turbulence-induced broadening effect on precipitation development. An initial effort is made to extend the stochastic theory to an atmospheric context with a steady updraft, for which autoconversion time is the controlling factor for droplet lifetime. As in the cloud chamber, relative dispersion is found to increase with decreasing cloud droplet number density.