  The distribution of liquid water in ice-free clouds determines their
radiative properties, a significant source of uncertainty in weather and
climate models. Evaporation and turbulent mixing cause a cloud to display large
variations in droplet-number density, but quite small variations in droplet
size [Beals et al. (2015)]. Yet direct numerical simulations of the joint
effect of evaporation and mixing near the cloud edge predict quite different
behaviors, and it remains an open question how to reconcile these results with
the experimental findings. To infer the history of mixing and evaporation from
observational snapshots of droplets in clouds is challenging because clouds are
transient systems. We formulated a statistical model that provides a reliable
description of the evaporation-mixing process as seen in direct numerical
simulations, and allows to infer important aspects of the history of observed
droplet populations, highlighting the key mechanisms at work, and explaining
the differences between observations and simulations.
