Storm Cell Identification and Tracking (SCIT) applications in the North-eastern Italian Region Veneto

The Centro Meteorologico di Teolo (CMT), regional meteorological service of the North-eastern Italian region Veneto has a relatively long tradition in using radar for monitoring convection. Recently, the Hydromet Decision Support System (HDSS) was installed to process data from two C-band radar located on Mt. Grande and Concordia Sagittaria. In this study, data from five warms seasons (May-Sep 2005-2009) of the Mt. Grande radar will be analyzed by means of the Storm Cell Identification and Tracking (SCIT), an algorithm developed by NSSL. SCIT keeps track of some 40 parameters which characterize the storm cells it identifies, including position, maximum reflectivity, vertically integrated liquid water, probability of hail, and more.

First, a systematic evaluation of the SCIT performance was undertaken, stratified according to storm intensity (in terms of reflectivity) and storm type. Then, the collected SCIT information is used to construct a sort of climatology, or frequency of occurrence of convective cells. This can be done for all cells as well as for selected SCIT parameter sets which single out particularly relevant storms. For example, cells featuring a probability of hail of 75% and larger form a distinct maximum near the Lake of Garda, an area well known to forecasters for the genesis of severe storms that often move eastward hitting the Venetian Prealps. More aspects of the convective activity in Veneto and the adjacent regions will be investigated and documented. In more detail, preferred genesis regions, times of the day, and tracks for convective activities can be identified in dependence of the various months of the convective seasons, as well as stratified according to various parameters characterizing the strength of the cells, like maximum dBZ, cell volume, height of max dBZ, and others. Such a characterization of convective activity can be used as the basis for the evaluation of new generation operational numerical weather prediction guidance related to severe weather.

Then, the SCIT output is applied to construct a thunderstorm predictor with the help of instability indices derived from radio soundings. Here SCIT provides the information on type of convection that occurred in a specific half-day period which, in turn, can be characterized by one or several instability indices. This information serves as basis for finding the optimal value, in terms of the Heidke Skill Score for instance, of one or more indices as thunderstorm predictors.