Object-based tracking and nowcasting of gust fronts

Abstract

<p>Thunderstorm gust fronts threaten human safety and property, especially in industries such as aviation and construction. The ability to predict the precise time and location of gust front arrivals would mitigate risk and reduce damage. </p><p>Existing methods for nowcasting gust front locations are based on detecting the gust fronts from individual Doppler weather radars or scanning lidars. Even though these methods are locally effective, they have so far not been applied to large-scale radar mosaics to generate forecasts that could benefit society at large. To address this gap, an object-based method is proposed for nowcasting gust fronts by any number of ground-based Doppler weather radars.  </p><p>The gust fronts are first detected from the radar measurements and presented as objects consisting of spline curves. Given the one-dimensional geometry of the curves, existing object-based tracking methods, designed for tracking thunderstorms and based on two-dimensional polygons, cannot be applied to the gust front objects. Instead, a tracking method is formulated that matches multiple observations of the same gust front based on the location and length of the curves. The tracking considers possible splitting and merging of the gust front objects. After matching the gust front instances between consecutive timesteps, the location of the gust front is nowcast with a Kalman filter algorithm.  </p><p>The methodology is demonstrated with case studies of gust fronts related to mesoscale convective systems (MCS) in Finland. MCSs occur frequently in Finland during summer and cause significant wind and other storm-related damage. Spatially and temporally accurate forecasting of MCS events would aid preparedness and reduce the risk posed to society. The methodology presented in this work can be used to nowcast the gust front trajectory and thus increase preparedness especially for the wind damage related to MCS events. The methodology can also be combined with existing object-based methods for nowcasting convective storm cells, to create comprehensive hazard forecasting systems for thunderstorms.</p>