The impact of lightning and radar data assimilation on the performance of very short term rainfall forecast for two case studies in Italy

In this paper, we study the impact of lightning and radar reflectivity factor data assimilation on the precipitation VSF (Very Short-term Forecast, 3 hours in this study) for two relevant case studies occurred over Italy. The first case refers to a moderate localised rainfall over Central Italy happened on 16 September 2017. The second case, occurred on 09 and 10 September 2017, was very intense and caused damages in several parts of Italy, while nine people died around Livorno, in Tuscany. The first case study was missed by most operational forecasts over Italy, including that performed by the model used in this paper, while the Livorno case was partially predicted by operational models. We use the RAMS@ISAC model (Regional Atmospheric Modelling System at Institute for Atmospheric Sciences and Climate of the Italian National Research Council), whose 3D-Var extension to the assimilation of RADAR reflectivity factor is shown in this paper. Results for the two cases show that the assimilation of lightning and radar reflectivity factor, especially when used together, have a significant and positive impact on the precipitation forecast. The improvement compared to the control model, not assimilating lightning and radar reflectivity factor, is systematic because occurs for all the Very Short-term Forecast (VSF, 3h) of the events considered. For specific time intervals, the data assimilation is of practical importance for Civil Protection purposes because it transforms a missed forecast of intense precipitation (> 40 mm/3h) in a correct forecast. While there is an improvement of the rainfall VSF thanks to the lightning and radar reflectivity factor data assimilation, its impact is reduced by the increase of the false alarms in the forecast assimilating both types of data.