Name: Kelsey Britt
Title: Effects of Horizontal Grid Spacing and Inflow Environment on Forecasts of Cyclic Mesocyclogenesis in NSSL’s Warn-on-Forecast System (WOFS)
Location: NWC 5600
Time: 3:00 PM
Series: Convective Meteorology (Mesoscale Dynamics)
Abstract: Cyclic mesocyclogenesis is the process by which a supercell produces multiple mesocyclones with similar life cycles, which have the potential to produce several tornadoes. Therefore, having the ability to forecast the potential and cycling frequency of cyclic supercells may be beneficial to forecasters when issuing watches and warnings. However, idealized simulations of cycling have found it to be highly sensitive to environmental and computational parameters. Thus, whether convective allowing models can resolve and predict cycling has yet to be determined. The purpose of this study is to test the capability of a short-term, storm-scale, ensemble predictive system to resolve the cycling process, whether this process is physically representative of the current understanding of cyclic supercells, and if it can be used to provide useful forecasts of these storms. Two experiments are performed using forecasts generated by NSSLs Warn-on-Forecast System (WOFS) for four cyclic
supercells occurring in May 2017. The first experiment tested the effects of changing the WOFS horizontal grid spacing from 3 km to 1 km. Rare cases of cyclic-like processes were identified at 3 km, but, as expected, cycling occurred more frequently at 1 km. The second experiment analyzed the different inflow environments of the forecasts. Object-based identification was used to identify mesocyclones and extract environmental inflow parameters from a storm-relative sector (r=80 km, 150Â°) from the center of each mesocyclone. Lower magnitudes of storm-scale parameters like 0–1 km SRH, 0–3 km SRH, and STP are present for rapid-cycling supercells and higher values for slow-cycling cases. These results provide initial evidence that high-resolution WOFS forecasts can potentially provide useful guidance on the likelihood and cycling frequency of cyclic supercells.