Abstract.A model-based fuzzy classification method for Cband polarimetric radar data, named Fuzzy Radar Algorithm for Hydrometeor Classification at C-band (FRAHCC), is presented. Membership functions are designed for best fitting simulation data at C-band, and they are derived for ten different hydrometeor classes by means of a scattering model, based on T-Matrix numerical method. The fuzzy logic classification technique uses a reduced set of polarimetric observables, i.e. copolar reflectivity and differential reflectivity, and it is finally applied to data coming from radar sites located in Gattatico and S. Pietro Capofiume in North Italy. The final purpose is to show qualitative accuracy improvements with respect to the use of a set of ten bidimensional MBFs, previously adopted and well suited to S-band data but not to C-band data.

During the last years, the Emilia-Romagna Apennines have been severely affected by debris flows, a type of landslide that is relatively uncommon in this area. These phenomena occur as a result of intense rainfall. The two most significant events are the one that affected the Province of Parma in October 2014 and the one that affected the Province of Piacenza in September 2015, in the night between the 13th and 14th. The objective of this work is to identify relationships between rainfall and debris flows occurrence for the Piacenza 2015 event, through the analysis of the distribution of debris flows with respect to rainfall data from weather radar and rain gauges recorded by ARPAE. The analysis of the relationships between spatial occurrence of debris flows and rainfall peaks has been based on the definition of the % of debris flow triggering points that can be contoured inside isohyets and on the ROC curve method. Moreover, we analyzed possible correlations between rainfall intensity and density or number of lighting flashes. The rainfall intensity vs duration plot showed that the September 2015 event largely exceeded debris-flows triggering thresholds proposed in literature. Analysis of debris flows occurrence with respect to hourly precipitation peaks retrieved by weather radar data, evidenced that 100% of the debris flows points occurred above the 30 mm/h isohyet, 97%, above the 50 mm/h isohyet and 82.5% above the 60 mm/h isohyet. Using ROC curves, the spatial distribution of debris flows triggering points can be more precisely predicted by considering, rainfall peaks at 1 h and 30 min over the event or by considering hourly rainfall between 02:00 and 03:00 of 15/09/2015. Rainfall classes of the best cut-off points in these ROC curves, i.e. most significant classifiers of the location debris flows points, are 75–90 mm/1 h and 45–60 mm/30 min. The analysis of lightning data shows that rainfall intensity was directly correlated to the lightning density but, also, that in some sub-areas a better correlation is obtained by considering rainfall intensity versus the lightning density recorded in the previous 30 mi

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