Automatic Identification and Alert of Gust Fronts

Gust fronts often cause serious ground gale and strong wind shear. Therefore, the short-term forecast, nowcasting and civil aviation department pay high attention to the research of gust fronts. Based on the echo characteristics of gust fronts in reflectivity field and velocity field of Doppler radar, an identification algorithm for gust fronts is designed. In the velocity field, the convergence line is identified by finding the consistent decreasing radial velocity and inspected by using a convergence parameter threshold, a grads threshold and a flux threshold. In the reflectivity field, the reflectivity data are classified into different levels. Then, the narrowband is identified by an algorithm called bilateral grads, which is designed by fully using the narrowband geometrical characteristic, the interval between narrowband and echo matrix. The bilateral grads algorithm can effectively filter out the wide range of precipitation echoes and reserve the narrowband in reflectivity image. Meanwhile, in order to filter out the remainder noise, length calculated and image thinning technique are used during above processes. According to the consistency of narrowband and the convergence line in the space, the gust front can be identified. The achievement of alert function uses an image flicker and some physical quantities output to represent the strength of the gust front. Finally, 98 volume-scanning data from 3 radar stations and the automatic weather station data and I_CS are used to evaluate the identification effect. The bilateral grads algorithm can effectively filter out the big range precipitation echo and keep the narrowband signal, it has an important relationship with the distance between the narrowband and maternal storm echo. Combined with the composite reflectivity to contrast all-layer reflectivity, the narrowband or the stronger reflectivity doesn't exist at the higher elevation, therefore, the algorithm simply handles the low elevation, which can improve the identification efficiency. The convergence line can be identified effectively by this method, and at the same time, it can also identify the low-level wind shear. The identification rate evaluated by I_CS from 98 volume-scanning data reaches 68.4%, indicating that the identification algorithm has the capacity of identifying gust fronts.