标题：The impact of lightning and radar reflectivity factor data assimilation on the very short-term rainfall forecasts of RAMS@ISAC: application to two case studies in Italy
摘要：In this paper, we study the impact of lightning and radar reflectivityfactor data assimilation on the precipitation VSF (very short-term forecast,3 h in this study) for two severe weather events that occurred in Italy.The first case refers to a moderate and localized rainfall over centralItaly that occurred on 16 September 2017. The second case occurred on 9 and 10 September 2017 and was very intense and caused damages in several geographical areas, especially in Livorno (Tuscany) where nine people died. The first case study was missed by several operational forecasts, includingthat performed by the model used in this paper, while the Livorno case waspartially predicted by operational models. We use the RAMS@ISAC model (Regional Atmospheric Modelling System atInstitute for Atmospheric Sciences and Climate of the Italian NationalResearch Council), whose 3D-Var extension to the assimilation of radarreflectivity factor is shown in this paper for the first time. Results for the two cases show that the assimilation of lightning and radarreflectivity factor, especially when used together, have a significant andpositive impact on the precipitation forecast. For specific time intervals,the data assimilation is of practical importance for civil protectionpurposes because it changes a missed forecast of intense precipitation (≥40 mm in 3 h) to a correct one. While there is an improvement of the rainfall VSF thanks to the lightningand radar reflectivity factor data assimilation, its usefulness is partiallyreduced by the increase in false alarms, especially when both datasetsare assimilated.
