Modal analysis reveals imprint of snowflake shape on wake vortex structures

Snowflakes falling behaviour is crucial for climate model parametrisation and snow distribution on the ground. The irregular shape of snowflakes makes their falling trajectories elaborate and produces intricate wake structures, which affect the snow particle drag coefficient and settling velocity (Tagliavini et al., 2021). In previous work based on a fixed-particle, Delayed-Detached Eddy Simulation, we found that the particle porosity reduces the vortex shedding, while low particle flatness increases the velocity fluctuations (Tagliavini et al., 2021). This is further investigated here using modal analysis (Taira et al., 2021) that decomposes numerical data of the wake flow into separated structures in space and in time, creating a reduced model of the system. This allows us to work with pairs of eigenmodes (spatial behaviour) and eigenvalues (temporal behaviour) that can be directly related to snowflake shape to identify its effect on the wake characteristics and on the snow particle falling motion. Fig. 1(b) shows the wake dominated by only one mode (mean flow) for the dendrite D1 (high porosity), while for the rosette MR (low flatness) more modes with lower amplitude contribute to the meandering wake. This study will unveil the spatial and temporal flow patterns in the snow particle wake with a direct impact on the particle drag and falling behaviour.