Clouds are formed by the condensation of water vapor onto nuclei in a rising mass of moist air. This produces droplets with sizes of the order of several microns. To precipitate, such droplets have to grow to millimeter sizes, either by coagulating together or by freezing and capturing the water evaporating from super-cooled droplets (Bergeron process). Air turbulence might strongly affect these fundamental microphysical mechanisms, whose understanding is crucial for determining the cloud droplet size distribution and the timescales of rain activation. Their accurate modeling as a function of the dynamical properties of the cloud represents a formidable challenge.
The proposed work aims at providing a detailed knowledge of the influence of turbulence on these processes and more particularly of the contribution of strong fluctuations to their overall contribution.
Condensation and evaporation
The idea is to quantify the turbulence-induced broadening of the droplet-size distribution at the initial stage of cloud formation. Recent work either focuses on the role of entrainment/mixing of dry air inside the cloud or uses stochastic condensation techniques based on turbulent closures. The idea is to develop analytically tractable models that unify both approaches. One of the objectives will be to describe the mechanisms responsible for the presence in clouds of droplets with radii much larger than the maximal size predicted by the models where isolated rising volumes of cloud are considered. Such “super-adiabatic” droplets have experienced violent fluctuations of the super-saturation field along their path. Their description requires thus detailing the intermittent spatial jumps associated to extremely sharp gradients of the water vapor content.
Coalescence of droplets in warm clouds
Two mechanisms have been recently identified as intensifying collisions between droplets: the presence of large concentration fluctuations and the formation of caustics (also referred to as the “sling effect”), enhancing velocity differences between close particles. A first objective is to quantify these effects for polydisperse droplets and as a function of the flow dynamical properties (statistics of large accelerations, Reynolds number, anisotropies and inhomogeneities). These effects can be implemented in effective collision kernels that are used in kinetic models (Smoluchowsky equation). A second objective is here to determine the limits of validity of such mean-field approaches by identifying and controlling the fluctuations responsible for local strong deviations from the average.
Formation of crystals
Ice nucleation and crystal growth are currently modeled using standard turbulence closures. Understanding the detailed microphysics of these processes in a fluctuating turbulent environment is still an open problem. The growth of crystals implies both deposition of water vapor and aggregation. Based on the two previous points, it is proposed to give a better knowledge of the influence of turbulence on the balance between these two physical mechanisms.
