BERNARDI M.

Lightning is one of the most dangerous natural phenomena, able to produce high impacts and damage on human beings and infrastructures (civil, electric, telecommunications, etc.) even though perception of it as a hazard is low. The aim of this study is to provide a detailed analysis of lightning occurrence throughout the Italian territory to...

The most accepted killing model for the Permian-Triassic mass extinction (PTME) postulates that massive volcanic eruption (i.e., the Siberian Traps Large Igneous Province) led to geologically rapid global warming, acid rain and ocean anoxia. On land, habitable zones were drastically reduced, due to the combined effects of heating, drought and...

This paper discusses the use of Random Forest (RF), a popular Machine Learning (ML) algorithm, to perform spatially explicit nowcasting of cloud-to-ground lightning occurrence. An application to the Italian territory and the surrounding seas is then presented. Specifically, a dataset including eighteen geo-environmental features has been used...

In this paper a multidisciplinary approach to develop a regression algorithm to nowcast cloud-to-ground lightning activity one hour in advance is presented. The algorithm is developed using atmospheric variables retrieved from remote sensing, numerical weather prediction model outcomes and lightning location systems' data. Gaussian Process...

The relation between the increase in the frequency and the effects of extreme events with climate change has been widely demonstrated and the related consequences are a global concern. In this framework, the strong correlation between significant lightning occurrence and intense precipitation events has been also documented. Consequently, the...

This article presents the Lightning Performance (LP) assessment of a realistic portion of the Italian distribution network with the use of probability distributions for lightning parameters inferred from local data recorded by a Lightning Location System (LLS). The procedure considers downward negative first, negative subsequent, and positive...