Effects of Turbulence on Hydrometeor Fall speeds and Collisions: Synergistic analysis of a Labratory-based parameterization and Field campaign data

The impact of turbulence on clouds and precipitation has always been a significant challenge to represent in numerical models. Turbulence can affect the growth rate of particles in cold and warm clouds (by influencing the rate of collision) and can also influence the fall speed of particles, which could lead to errors in weather model predictions of precipitation amounts and spatial distributions. To address this issue, we developed an analytical relationship between the fall speed of particles and both turbulence and particle properties (i.e., size) based on laboratory experiments, and this relationship was implemented for snow in the Predicted Particle Properties (P3) microphysics scheme in the Weather Research and Forecasting (WRF) model. Furthermore, we aim to validate the impact of turbulence on cloud microphysical processes obtained from both idealized and real case model simulations through a rigorous analysis of airborne field campaign data.

First simulations were performed using the WRF model for an orographic snowfall event in the mountains of southern Wyoming and northern Colorado. For comparison, a simulation was run with both the aforementioned relationship between turbulence and fall speed enhancement, as well as the standard fall speed formulation for snow, which assumes quiescent air motions (control). The results indicated that, in the orographic precipitation event, as a result of the particle fall speed being enhanced by turbulence, precipitation might increase, and spatial deviations in snowfall become evident. Overall, we find a trend in which snowfall moves toward the windward side of the mountains. By comparing multiple physical and dynamic parameters, we have identified several mechanisms that explain these results. First, the residence time of particles in the cloud is reduced, allowing particles to fall out of the cloud faster. Second, in areas close to the boundary layer, the collision-coalescence effects of particles are also enhanced due to the differing effect of turbulence on particles of different sizes. Lastly, we find evidence of enhanced fall speeds in the turbulence region in cloud-top generating cells, which acts to further enhance snow production in the studied event. While prior studies have shown that turbulence can affect the verticle velocity of falling hydrometeors, thus enhancing collisions rates, through our work, we have identified a potential mechanism by which particles of differing sizes experience different turbulence-related impacts, which could either increase or decrease the differential fall speeds, depending on both the particles sizes and turbulence. To determine if this is in fact occurring, we further aimed to analyze in situ data collected from the Olympic Mountains Experiment (OLYMPEX), identifying areas in cloud where the Droplet Distribution(DSD) changes toward larger particles by the cloud mass remains unchanged and number decreases, to identify collision events, and then apply the KiD model to back out whether that collision event experienced enhancement due to some other factors, e.g., turbulence