Obtaining number concentrations of activated CCN from vertical profiles of Re in deep convective clouds

The number of activated CCN into cloud droplets is the most fundamental microphysical property of a convective cloud. It determines the rate of droplet growth with cloud depth and conversion into precipitation sized particles and affects the radiative properties of the clouds. However, measuring this number is not always possible since entrainment of sub-saturated ambient air into the cloud dilutes the cloud and decreases the cloud droplet concentrations. Even the cores of deep convective clouds, where measurements are normally avoided due to the strong vertical motions and icing hazards, can be affected by entrainment. In previous studies we found though, that entrainment affects only the cloud droplet concentrations but hardly the shape of their spectra, so their effective radii (Re) is very robust for a given cloud depth (when adiabatic fraction is greater than ~0.1) as can be seen in the example given in fig.1. This means that the clouds are in-homogeneously mixed, i.e. the time scale of droplet evaporation is much smaller than the turbulent mixing of the cloud.

Here we describe a technique to derive the number of activated CCN based on the robustness of Re with respect to the cloud mixing. We use the slope of the strong linear relationship between the adiabatic water and Re³, shown in fig. 2, to derive the number of activated CCN and compare them with the independent CCN measurements. It is also evident that clouds with higher number of activated CCN need to develop higher to allow the cloud droplets to turn into precipitation-sized particles, as expected. This technique was applied successfully to data from different campaigns with only slight quantitative differences, which confronts the precision of the CCN and cloud droplet spectra measurements.

Quantifying these effects, based on more examples from other projects and cloud models is essential. The derived parameterizations should be included in non-cloud resolving models in order to take into account the important effects of aerosols on precipitation formation processes.