## 4 Discussion and Conclusions
A seasonal migration of occurrences from the land in the summer to the coastal areas and sea in the fall and in the winter is in agreement the analysis by [PERSON] et al. [34] obtained by AMSU-B/MHS cross-track scanning radiometer observations for the period of 2005-2008. The identification of potential halistorms follows the radar-based and radiometer-based approach adopted by [PERSON] et al. [28], and it has confirmed the value of using the GPM-CO for detecting strong updrafts associated with severe convection. Both methods provide results in agreement with what observed for the most intense PFs, despite the different number of potential halistorms detected with the two methods: the number of potential halistorms identified with the radar-based method is about twice the one found with the radiometer-based method. The radiometer-based approach seems to be more suitable to identify potential halistorms. The low 89 GHz and 37 GHz PCTs, especially over land, respectively below 180 K and 230 K, corresponds to a hail probability that should exceed the 60-80% according to [PERSON] and [PERSON] [38]. It is interesting to note that the most extreme PFs associated with potential hail (as well as to OPFs), with a minimum 37 and 89 GHz PCTs below 120 K and 100 K, respectively, are observed over the sea. The analysis of OPFs and potential hailstorms has emphasized how in the selected domain, the fall is the season with most precipitation associated with these events, almost evenly distributed over land and sea, followed by the summer, for which a relevant contribution comes from the deep convection over land, favored by the solar heating. The occurrence of intense convective systems also over the sea is an important aspect that confirms the significance of the use of microwave instruments on board LEO satellites, especially for scientific and operational purposes, as in all those cases where ground-based instruments are not available for severe storm detection. However, the analysis presented has some limitations that are worth mentioning. First of all, different thresholds and methods lead to a different number and typologies of detected events: further studies are needed to explain and understand which criteria are the most suitable for specific regions. Especially, the radiometer-based methods do not always allow inference of the effect of deep convection at the surface, since the passive microwave signal originates from column-integrated precipitation microphysics and from processes in the middle and upper levels of the deep convective cloud [21]. For example, hailstones can melt prior to reaching the surface (as a matter of fact, the term \"potential hailstorm\" is used throughout the study). Previous works, such as [PERSON] [20], [PERSON] et al. [28], and [PERSON] and [PERSON] [38], push their analysis further to infer hail size at the surface in probabilistic terms. Indeed, although the main interest is to identify storms with hail at the surface, microwave measurements from space are important to identify consistent signatures of clouds characterized by the presence of hail and large graupel which can be potentially dangerous, as demonstrated by the very recent studies by [PERSON] et al. [32; 33]. Although some severe events reported in the literature or in weather reports have been identified in the most extreme PF classes of the present study, a further step would be a more extensive use of ground-based measurements at weather stations, as done in [PERSON] et al. [28] for the United States. It is also necessary to underline that criteria and empirical relationships derived for a particular region should not be applied a priori everywhere. Generally, for a finer analysis, the results should be scaled based on the regional environmental conditions and typical vertical radar profiles [21], through empirical relationships that would account for the local characteristics of a specific region. Finally, it is worth reminding that the analysis carried out in this study is conditioned to the GPM-CO temporal and spatial sampling.