Non-Terminal Hydrometeor Fall Speed Effects on Modeled Rain Processes

Recent observational studies have shown hydrometeors exhibit non-terminal fall speeds with three important characteristics: 1) hydrometeor fall speeds have some variance around the expected terminal velocity; 2) there is a tendency for large particles (D > 1.5 mm) to display sub-terminal fall speeds and small particles (D < 0.5 mm) to display super-terminal fall speeds; 3) there is a tendency for large particles to have narrower fall speed distributions than small particles. The goal of this study is to understand how these non-terminal fall speeds affect the collision, coalescence, and breakup of raindrops in a Lagrangian cloud model called the Cloud Particle Model (CPM). The CPM uses the method of limited volume (MLV) to limit computational cost rather than the super droplet method commonly used in Lagrangian models. The MLV samples a fixed number of particles at each time step to calculate collisional interactions rather than combining multiple particles of the same size into super droplets. This makes the CPM more sensitive to random fluctuations than the super droplet method, a desirable feature for studying random variation in fall speeds.

To understand the effects of non-terminal fall speeds on hydrometeor evolution and the development of an equilibrium raindrop size distribution from the competing effects of coalescence and collision-induced breakup, a series of sensitivity studies was performed. The first sensitivity study, varying the width of the fall speed distribution, showed that there was a critical width of the velocity variations, which if not exceeded, resulted in an approach to an equilibrium distribution that was statistically indistinguishable from the equilibrium distribution approached using deterministic terminal velocities. The exact value of this width of the velocity variation depends strongly on the assumed initial distribution. The second sensitivity test involved adding a bias term, which resulted in large particles (D > 0.9 mm) falling at sub-terminal speeds and small particles (D < 0.9 mm) falling at super-terminal speeds. This sensitivity study showed that the bias had a 33 times larger impact on the rain rate when compared to the random noise term, mostly due to the differences in velocity profiles between the biased and unbiased models. The last sensitivity study, which scaled the variance of large particles, found that the scaling term had a very small effect on any moment of the approached equilibrium distribution, including the number concentration (7% change between scaling terms, and 18% change between bias terms) and rain rate (1.3% change between scaling terms and 5% change between bias terms), which lessens the impact of the term compared to the bias and width of velocity variation.