Validating the Swiss automatic mesocyclone detection algorithm over the Highveld of South Africa: A case study event

Supercell thunderstorms, characterised by a rotating updraft (mesocyclone), are known to produce severe weather. They frequent the South African Highveld during spring and early Summer (October to December). On the 28^th of November 2013 at least seven supercells moved across the Gauteng province, with golf to tennis ball sized hailstones reported. This event was one of the two supercell event days in that month, that contributed to just over EUR 101 million in insurance claims. While supercells can be manually identified using Doppler radar, algorithms to automatically detect the mesocyclone on the Doppler velocity field were first developed in the 1980s and have since been improved and adopted globally. The use of such algorithm is novel to South Africa. This study aims to evaluate the performance of the mesocyclone detection algorithm developed by Switzerland (with the same operational parameters), in detecting supercell thunderstorms on the Irene single polarised S-band radar, during the 28^th of November 2013 case study. This case study was chosen for its complex thunderstorm dynamics within a highly sheared environment, including the development of severe multicells, supercells and bow echoes. The results of the mesocyclone detection algorithm for cyclonic (clockwise) rotation were compared to the manual supercell database. In addition, the reflectivity and Doppler velocity field were reanalysed to ensure events were not missed. All supercells within the manual database were identified by the algorithm and some additional events and time steps were accurately detected. However, at least 5 events were not associated with a supercell and events were often identified earlier and/or ended later than manually detected. Cyclonic rotation associated with the poleward side of a bow echo often occurred within this case study. This is a first step towards automatically identifying supercells with an overall goal of improving the nowcast and warning of such events. Future work will include adjusting the algorithm thresholds to improve detection, as it was originally set to account for the complex terrain and lower shear environment over Switzerland.