  Developing methods to predict disastrous natural phenomena is more important
than ever, and tornadoes are among the most dangerous ones in nature. Due to
the unpredictability of the weather, counteracting them is not an easy task and
today it is mainly carried out by expert meteorologists, who interpret
meteorological models. In this paper we propose a system for the early
detection of a tornado, validating its effectiveness in a real-world context
and exploiting meteorological data collection systems that are already
widespread throughout the world. Our system was able to predict tornadoes with
a maximum probability of 84% up to five days before the event on a novel
dataset of more than 5000 tornadic and non-tornadic events. The dataset and the
code to reproduce our results are available at: https://tinyurl.com/3brsfwpk
