The Philofluid Research Group is proud to announce that Mina Golshan has successfully finalized her doctoral dissertation on “Cloud Turbulence Microphysics at Interfaces: A DNS Model with Phase Change and Droplet Interaction” at the Politecnico di Milano, Department of Aerospace Science and Technology (DAER). The dissertation was completed on February 22, 2023.

In this groundbreaking work, Mina addressed key problems in small-scale cloud dynamics using direct numerical simulations (DNS) to study the temporal evolution of perturbations located in the turbulent layer that separates a cloud from the surrounding clear air. The research primarily focused on the behavior of turbulent kinetic energy, temperature, humidity, and droplet distributions under varying stratification conditions.

The first part of the dissertation involved exploring initial value problems where the evolution of turbulent kinetic energy and droplet distributions was carefully observed. The study revealed that intense stratification altered the mixing dynamics, resulting in the formation of a sub-layer inside the shear-less layer. Under stable thermal conditions, this sub-layer acted as a trap for kinetic energy, while turbulent kinetic energy exhibited transient growth under unstable conditions, creating an energy peak just beneath the center of the shearless layer.

The research also investigated the behavior of monodisperse (15 µm) and polydisperse droplet populations (ranging from 0.6 to 40 µm) and their interactions within the homogeneous cloudy region and anisotropic interface mixing zones. The DNS simulations showed that fluctuations in supersaturation led to broader droplet size distributions and increased collision rates, in contrast to non-turbulent condensation that typically narrows droplet distributions.

The study revealed that although the turbulent kinetic energy of the cloud airflow decreased by 90% over the simulation period, the collision activity within the cloud decreased by 40%, whereas it increased by 25% in the mixing region. Notably, the size distribution of droplets in the mixing layer exhibited a 15-times faster standard deviation growth compared to the cloud region.

The research also found that a clustering of phase, reaction, and evaporation times occurred around 20-30 seconds in the mixing layer, just before the location where the maximum turbulent supersaturation flux was observed. This finding suggests a quasi-linear relationship between the supersaturation field and the longitudinal velocity derivatives of the carrier airflow.

The second part of the dissertation focused on field experiments using mini-green radiosondes, developed as part of the H2020 COMPLETE Marie Curie Network. This section, still ongoing, presents preliminary results and proof-of-concept for studying water droplet dispersion in warm clouds. The experimental data, collected using radiosondes, was analyzed using distance-neighbor graphs, a statistical approach introduced by L.F. Richardson in 1926. This part complements the DNS work by investigating large-scale dispersion and offering a Lagrangian perspective on the state changes that moist air parcels undergo in the atmosphere.

Mina’s research presents a holistic approach to understanding cloud turbulence microphysics at both small and large timescales, contributing valuable insights to the interaction between droplets and turbulence in cloud dynamics.

We extend our sincere congratulations to Mina for her impressive dissertation and look forward to seeing her future contributions to the field of atmospheric and fluid dynamics.