Understanding turbulent processes in clouds is one of the most important challenges in atmospheric physics and one of the main sources of uncertainty in climate models. Clouds regulate the hydrological cycle and the Earth’s energy balance, but the mechanisms that control their dynamics are still only partly understood. The classical turbulence theory by Kolmogorov (K41), while fundamental, is based on three assumptions — stationarity, homogeneity, and isotropy — which are rarely satisfied in real atmospheric flows. Nu- merical simulations try to address these limits, but at the current state of the art they can only cover small portions of reality: DNS are restricted to domains of a few meters, while global models work with grids of several kilometers, which cannot describe local microphysical processes.