The Mediterranean area is subject to a range of destructive weather events, including middle-latitudes storms, Mediterranean sub-tropical hurricane-like storms (“medicanes”), and small-scale but violent local storms. Although predicting large-scale atmosphere disturbances is a common activity in numerical weather prediction, the tasks of recognizing, identifying, and tracing trajectories of such extreme weather events within weather model outputs remains challenging. We present here a new approach to this problem, called StormSeeker, that uses machine learning techniques to recognize, classify, and trace the trajectories of severe storms in atmospheric model data. We report encouraging results detecting weather hazards in a heavy middle-latitude storm that struck the Ligurian coast in October 2018, causing disastrous damages to public infrastructure and private property.
|Titolo:||StormSeeker: A machine-learning-based mediterranean storm tracer|
MONTELLA, Raffaele (Corresponding)
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|