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In this paper, we study the impact of lightning and radar reflectivity factor 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 central Italy 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, 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 for the first time. 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. For specific time intervals, the data assimilation is of practical importance for civil protection purposes 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 lightning and radar reflectivity factor data assimilation, its usefulness is partially reduced by the increase in false alarms, especially when both datasets are assimilated. [ABSTRACT FROM AUTHOR]

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 (>40mm/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. [ABSTRACT FROM AUTHOR]

Recent explosive volcanic eruptions recorded worldwide (e.g. Hekla in 2000, Eyjafjallajökull in 2010, Cordòn-Caulle in 2011) demonstrated the necessity for a better assessment of the eruption source parameters (ESPs; e.g. column height, mass eruption rate, eruption duration and total grain-size distribution - TGSD) to reduce the uncertainties associated with the far-travelling airborne ash mass. Volcanological studies started to integrate observations to use more realistic numerical inputs, crucial for taking robust volcanic risk mitigation actions. On 23 November 2013, Etna (Italy) erupted, producing a 10 km height plume, from which two volcanic clouds were observed at different altitudes from satellites (SEVIRI, MODIS). One was retrieved as mainly composed of very fine ash (i.e. PM20) and the second one as made of ice/SO2 droplets (i.e. not measurable in terms of ash mass). An atypical north-easterly wind direction transported the tephra from Etna towards the Calabria and Apulia regions (southern Italy), permitting tephra sampling in proximal (i.e. ∼5-25 km from the source) and medial areas (i.e. the Calabria region, ∼160 km). A primary TGSD was derived from the field measurement analysis, but the paucity of data (especially related to the fine ash fraction) prevented it from being entirely representative of the initial magma fragmentation. To better constrain the TGSD assessment, we also estimated the distribution from the X-band weather radar data. We integrated the field and radar-derived TGSDs by inverting the relative weighting averages to best fit the tephra loading measurements. The resulting TGSD is used as input for the FALL3D tephra dispersal model to reconstruct the whole tephra loading. Furthermore, we empirically modified the integrated TGSD by enriching the PM20 classes until the numerical results were able to reproduce the airborne ash mass retrieved from satellite data. The resulting TGSD is inverted by best-fitting the field, ground-based and satellite-based measurements. The results indicate a total erupted mass of 1.2X109 kg, being similar to the fieldderived value of 1.3X109 kg and an initial PM20 fraction between 3.6 and 9.0 wt %, constituting the tail of the TGSD. [ABSTRACT FROM AUTHOR]