Now, there is a computer model
that can help forecasters recognize potential severe storms more quickly and
accurately, thanks to a team of researchers at Penn State, AccuWeather, Inc.,
and the University of AlmerÃa in Spain. They have developed a framework based
on machine learning linear classifiers (a kind of artificial intelligence) that
detects rotational movements in clouds from satellite images that might have
otherwise gone unnoticed. This AI solution ran on the Bridges supercomputer at
the Pittsburgh Supercomputing Center. The very best forecasting incorporates as
much data as possible. There's so much to take in, as the atmosphere is
infinitely complex. By using the models and the data we have a snapshot of the
most complete look of the atmosphere.
In their study, the researchers analyzed
more than 50,000 historical U.S. weather satellite images. In them, experts
identified and labeled the shape and motion of ‘comma-shaped’ clouds. These
cloud patterns are strongly associated with cyclone formations, which can lead
to severe weather events including hail, thunderstorms, high winds and
blizzards. Then, using computer vision and machine learning techniques, the
researchers taught computers to automatically recognize and detect comma-shaped
clouds in satellite images. The computers can then assist experts by pointing
out in real time where, in an ocean of data, could they focus their attention
in order to detect the onset of severe weather.
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