Timescales of Evolution for Supercell Updrafts and their Impact on Hail Trajectories

Recent hail trajectory modeling studies have identified pathways for large hail growth that are complex and strongly impacted by sub-updraft scale dynamics in the supercooled layer of a storm. In the hail growth region of a supercell, thermal-like behavior, vortex shedding, and dynamical rotors, among other phenomena, cause an updraft to evolve dynamically on short timescales that may not be clearly resolved by operational radars, which perform volume scans on timescales of 5 min or greater.  

Here, we examine the evolution of the mixed phase region of a supercell storm’s updraft modeled in CM1 with 5-second temporal output. This dataset provides a sandbox in which to explore the timescales of evolution for a variety of updraft quantities and can shed light on the temporal resolution necessary to resolve properties of a storm’s updraft important for hail trajectories. Techniques including Fourier analysis, wavelet analysis, and variability indices are presented as tools for identifying and isolating updraft variability on a variety of timescales associated with physical and dynamical processes in the modeled supercell. 

We hypothesize that the treatment of updraft variability in numerical hail trajectory modeling is impactful on the nature of hail trajectories produced (i.e., do hail trajectories have differing complexity if computed in composited storm fields, in frozen snapshots of a storm, or in fully time-varying fields?). To understand the role of temporal variability in hail growth, we run hail trajectories to compare the impact of these different ways of representing storm fields. We examine how allowing or restricting the evolution of a storm impacts the behavior and complexity of numerically modeled hail trajectories.  

On the recent ICECHIP field campaign, Hailsondes (small probes that are released into a storm, accrete mass, and fall out as pseudo-hailstones) were released to measure hail-like trajectories in real storms. We compare our modeled trajectories to Hailsonde trajectories to analyze the realism of modeled hail trajectories in an evolving storm.