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Heavy and localized summer events are very hard to predict and, at the same time, potentially dangerous for people and properties. This paper focuses on an event occurred on 15 July 2020 in Palermo, the largest city of Sicily, causing about 120 mm of rainfall in 3 h. The aim is to investigate the event predictability and a potential way to improve the precipitation forecast. To reach this aim, lightning (LDA) and radar reflectivity data assimilation (RDA) was applied. LDA was able to trigger deep convection over Palermo, with high precision, whereas the RDA had a key role in the prediction of the amount of rainfall. The simultaneous assimilation of both data sources gave the best results. An alert for a moderate–intense forecast could have been issued one hour and a half before the storm developed over the city, even if predicting only half of the total rainfall. A satisfactory prediction of the amount of rainfall could have been issued at 14:30 UTC, when precipitation was already affecting the city. Although the study is centered on a single event, it highlights the need for rapidly updated forecast cycles with data assimilation at the local scale, for a better prediction of similar events. [ABSTRACT FROM AUTHOR]

On 10 October 2018 an intense storm, characterized by heavy rainfall, hit the Sardinia island, reaching a peak of 452 mm of rain measured in 24 h. Among others, two particularly intense phases were registered between 3 and 6 UTC (Universal Coordinated Time), and between 18 and 24 UTC. The forecast of this case study is challenging because the precipitation was heavy and localized. In particular, the meteorological model used in this paper, provides a good prediction only for the second period over the eastern part of the Sardinia island. In this work, we study the impact of lightning data assimilation and horizontal grid resolution on the Very Short-term Forecast (VSF, 3 and 1 h) for this challenging case, using the RAMS@ISAC meteorological model. The comparison between the 3 h VSF control run and the simulations with lightning data assimilation shows the considerable improvement given by lightning data assimilation, especially for the precipitation that occurred in the eastern part of the island. Reducing the VSF range to 1 h, resulted in higher model performance with a good precipitation prediction over eastern and south-central Sardinia. In addition, the comparison between simulated and observed reflectivity shows an important improvement of simulations with lightning data assimilation compared to the control forecast. However, simulations assimilating lightning overestimated the precipitation in the last part of the day. The increasing of the horizontal resolution to 2 km grid spacing reduces the false alarms and improves the model performance. [ABSTRACT FROM AUTHOR]