Using Predictive Analytics to Improve Tornado Warnings

A new way of examining weather data has been used by researchers to try and predict extreme weather patterns. It is hoped that the big data analytics approach can be used to gain improved predictions for tornadoes.

Scientists based at Penn State University have collected data from recent next-generation satellites to use in a numerical weather-prediction model. The model has improved the ability for meteorologists in relation to tornadic thunderstorm forecasting and in providing guidance to governments, businesses and members of the public.

The focus of the work was on the U.S. Thunderstorms account for 40 percent of all severe weather events in the U.S., causing 14 percent of damage and 17 percent of related deaths. In 2018 (up to the start of October), there were eleven weather and climate disaster events with losses exceeding $1 billion each. The aim of the research is to increase the warning time for tornados, which is currently averaging at 14 minutes.

Read more at Digital Journal

The Government Technology & Services Coalition's Homeland Security Today (HSToday) is the premier news and information resource for the homeland security community, dedicated to elevating the discussions and insights that can support a safe and secure nation. A non-profit magazine and media platform, HSToday provides readers with the whole story, placing facts and comments in context to inform debate and drive realistic solutions to some of the nation’s most vexing security challenges.

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