12A.6 Impacts of Hail on Simulated ZDR Arc Identification

Thursday, 31 August 2023: 9:15 AM
Great Lakes BC (Hyatt Regency Minneapolis)
Robin L. Tanamachi, Purdue Univ., West Lafayette, IN; and A. LaFleur and D. T. Dawson II

It has been observed that hail fallout complicates the automatic identification of ZDR arcs, a polarimetric feature of supercells thought to be linked to tornadogenesis. A polarimetric radar simulator (CAPS-PRS) was used to generate ZDR fields in ensembles of nine tornadic and nine non-tornadic supercells simulated using Cloud Model 1 (CM1). Next a random forest algorithm was used to automatically identify the synthetic ZDR arcs. It was found that, much like in real ZDR observations, transient hail fallout can disrupt synthetic ZDR arcs.

To gauge the impact of hail on the ZDR arc identification, synthetic ZDR arcs were regenerated using different hail settings in the CAPS-PRS. The first experiment, called the “wet hail” experiment, treats hail conventionally and is used as a control. In the second experiment, called “dry hail,” wet growth and melting of hail are excluded. In the third experiment, called “no hail,” the contribution to ZDR from the hail hydrometeor category is excluded entirely. We examined the impacts of these changes on ZDR arc intensity and area. It was found that the presence of hail does impact the size and intensity of the algorithmically identified arcs. Arc area in the “no hail” experiments increased by a factor of four when compared to the “wet hail” experiments, whereas mean and maximum values of ZDR remained similar in the “wet hail” and “no hail” experiments. The “dry hail” experiments had lower mean and maximum ZDR values in the arcs by about 0.3-0.5 dB. We offer some informed speculation as to how the configuration of the CAPS-PRS may influence our results.
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