Climatology of Extreme Weather Events and their Predictability Nature Across Italy

The Mediterranean sea is the key factor to instigating most of the extreme weather events slamming the European countries. Being one of the European country, Italy is regularly impacted by the recurrent of extreme weather events which are being fueled by the Mediterranean sea. Most of these extreme weather events occur predominantly in the summer (JJA) and Autumn (SON) seasons. During the summer and Autumn, the Mediterranean sea is warmer than the Winter and Spring, hence tend to supply adequate amount of heat and moisture necessary for inciting convection that result to evolution of convective storms leading to occurrences of extreme weather events. This dissertation investigates the extreme weather events that hampered Italy. The study is comprised of two tasks; The first task investigates the climatology of the extreme weather events (hailstorms, heavy rains, severe winds, tornadoes, damaging lightning, and snow) that hit Italy in the past three decades (1990-2021) based on the severe weather reports from the European Severe Weather Database (ESWD). In this case, the climatological spatiotemporal patterns, the increasing or decreasing trends, and the temporal evolution of severe convective storms are explored in depth. Spatial, temporal and smoothing techniques are adopted in the analysis focusing on the reported number of severe convective storms as well as the number of days accompanying the storms. Uneven spatial patterns of severe convective storms in the entire country but densely confined over the northern part are revealed. Tornado events are mostly favored over the coastal strip of the country with isolated cases inland. The frequency of occurrences of the severe convective storms is observed to increase progressively with years from 2007 to 2021, and the most appealing trend stroke in 2019-2021. The year 2021 broke the records of a vast number of severe convective storms in the country and in the ESWD archive as well. The summertime is dominated by hailstorms and damaging lightning. Heavy rains, severe winds, and tornadoes prevail with two seasonal peaks, in summer (minor) and autumn (major) for heavy rains and tornadoes. Severe winds are evident in summer (major) and autumn (minor), while snow events are definitely in winter. The second task considers the predictability of heavy rainfall events (between 4th October 2010 and 21st October 2019) over the Liguria region (Northwest), Italy using the Numerical Weather Prediction (NWP) model namely the Weather Research and Forecasting (WRF) model. This is further divided into three parts; the impact of model resolution and Initial/Boundary Conditions in forecasting flood Causing precipitation, RANS and LES face to face for forecasting extreme precipitation events in Liguria region, and the added value of downscaling the high-resolution (HRES) EPS from the ECMWF for extreme precipitation forecasting. The first part uses the WRF model to study a very intense event that hit Côte d’Azur, and in particular the area around the city of Cannes, on 3rd October 2015. The intent is to investigate the impact of horizontal resolution as well as initial and boundary conditions (IBCs) ingested by the WRF model in forecasting flood-causing precipitations. Furthermore, the response of the satellite sea surface temperature (SST) for updating the WRF IBCs is also scrutinized. Thus, different IBCs from different global models are used to initialize the WRF model together with a HRES satellite SST data. The impact of model resolution as well as the IBCs on the quantitative precipitation forecasts (QPF) is analyzed and discussed. In particular, the effect of ingesting a HRES satellite SST is proven to be beneficial in terms of precipitation intensity and location, especially when also associated with the most accurate IBCs. The second part studies seven different extreme precipitation events that conquered the Liguria region, Italy between (4th October 2010 and 21st October 2019) using sub-km resolution numerical simulations of the WRF model. The idea is to evaluate the impact of the Planetary Boundary Layer (PBL) turbulence through a Large-Eddy Simulation (LES) approach versus the classical Reynolds-Averaged Navier–Stokes (RANS) modeling framework on the QPF. To achieve this, three different sets of simulations are carried out. The first set involved the WRF simulations of the three nested domains (10 km × 3.3 km × 1.1 km), where a preliminary sensitivity analysis of PBL on the QPF was performed using the inner domain at 1.1 km to provide the reference simulation. Then, a further nested domain was introduced with horizontal resolution of 367 m, in which both RANS and LES simulations were performed. The QPF were compared with observed rainfall from the Ligurian observation network composed of about 200 stations. Four out of seven events evident LES contribution to improve the model performances on both the intensity and/or location. The improvement is observed in both cases of underestimation and overestimation by the reference simulations and is mostly associated to a better description of low-level dynamics as well as convection triggering and intensity. This suggest the possibility to integrate LES in operational simulations. Besides, the effect of LES in other events is not well remarkable and simulations closely resemble the reference forecast. The last part uses the WRF model with 3-domains (10 km × 3.3 km × 1.1 km), same configuration and events as in the previous part to dynamically downscale the HRES 50 members of the Ensemble Prediction System (EPS) from European Center for Medium Weather Forecasting (ECMWF). The objective is to investigate on whether the WRF dowscaling of the HRES-EPS brings an added value with respect to the raw HRES-EPS. Suitable statistical indices/measures are used to assess the WRF model performances both in terms of mean properties of the ensemble and in terms of its spread. The added value of exploiting the WRF model to dynamically downscale the HRES-EPS from ECMWF clearly emerges in relation to both the intensity of the extreme QPF and the spatial position. Despite the fact that, the HRES dynamical downscaling of many EPS members as done in the present work does not seem doable because of its computational cost, this work motivates researchers to identify ways to select a reasonably small subset of representative EPS members to consider for the HRES dynamical downscaling.