Hail events commonly affect the Western part of Catalonia, producing damage mainly in the agricultural sector. Comparison of the weather radar data with hail pad registers at ground level allows for the diagnosis of hail severity. However, limitations using individual radar fields have led to the use of quantiles of the vertical profiles of reflectivity for a period between 12 min before and after a hailfall. These profiles combine all radar parameters, and are less sensitive to radar functioning anomalies and hailfall nature. The explored dataset was divided into severe and non-severe registers, with two subsets: one larger (90% of cases) for modeling and the second one for validating the results. Results indicate a better estimation of severe hail, but the number of false alarms with non-severe cases was still high. In consequence, future work should focus on minimizing false alarms using more restrictive profile groups. The purpose of the study is the application of a real-time tool for improving surveillance tasks which provides better discrimination between severe and non-severe hail occurrences.
Tomeu Rigo (Fri,) studied this question.