Vortex Detection with the UK Weather Radar Network

Vortices frequently form in the atmosphere and whilst increasing turbulence, their damage is limited. However if the vortex reaches the ground it forms a tornado. In the UK weak tornadoes are frequent although only occasionally does significant damage occur as was the case with an EF2 tornado in London in 2006 (Clark 2011). Vortex detection capability has recently been developed for the UK C-Band weather radar network making use of the Doppler radial wind, reflectivity and SQI (signal quality index) products.

Due in part to the greater frequency of severe tornadoes in the USA, algorithms are in place to detect tornadoes (Mitchell et al. 1998) and mesocyclones (Stumpf et al. 1997). The approach developed here is based on these algorithms. Radial wind observations are filtered against reflectivity and SQI thresholds before feature detection takes place. Considering individual elevation scans 1D shear segments are identified and combined to produce 2D features. A series of decreasing velocity thresholds are used to isolate core vortices within regions of azimuthal shear. An aspect ratio check is performed before horizontally co-located 2D features are combined between elevation scans to identify 3D features of interest.

Here we describe the specification of the UK Doppler radar network and the new real-time vortex detection capability. Several case studies illustrating successfully detected tornadoes in the UK during 2014 and 2015 are presented and limitations of the current approach are identified. Detection performance is most reliable within ~60 km of the radar with increasing chance of overshoot as features of interest are increasing likely fall below the radar horizon at greater range.

This new functionality provides a useful real-time indication of tornadic activity augmenting existing observations and numerical weather prediction.

Clark M.R. Doppler radar observations of mesovortices within a cool-season tornadic squall line over the UK, Atmospheric Research, 2011, Vol 100 749-764

Mitchel E.D. et al. The National Severe Storms Laboratory Tornado Detection Algorithm, Weather and Forecasting, 1998, Vol 13 352-366

Stumpf G.J. et al. The National Severe Storms Laboratory Mesocyclone Detection Algorithm for the WSR-88D, Weather and Forecasting.1997, Vol 13 304-326