Tornadoes are one of nature's most destructive and unpredictable forces, causing billions of dollars in damages and claiming lives every year. Though they are difficult to predict, a new open-source dataset created by researchers from the MIT Lincoln Laboratory, known as TorNet, offers hope in improving our detection and prediction abilities. Composed of radar images…
Researchers at MIT Lincoln Laboratory have introduced an open-source dataset called TorNet in an attempt to enable enhanced detection and prediction of tornadoes. The dataset comprises radar returns from thousands of tornadoes that struck the US over the past decade and includes copies of storms that generated tornadoes as well as other extreme weather events…
Springtime in the Northern Hemisphere marks the onset of tornado season, and while the dust and debris-filled spiral of a tornado may seem an unmistakable sight, these violent weather phenomena often evade detection until it's too late. Recognizing the need for better ways of predicting these occurrences, researchers at MIT Lincoln Laboratory have compiled a…
The arrival of spring in the Northern Hemisphere brings with it the commencement of tornado season. Meteorologists use radar to track these dangerous natural phenomena, but understanding exactly when a tornado has formed or why can be a challenge. However, a new dataset may provide some answers.
Known as TorNet, this dataset compiled by researchers from…
Every spring, tornado season returns to the Northern Hemisphere. While the twisted funnel of a tornado may seem like an easily recognizable sight, it remains difficult for radar -- the primary tool of meteorologists -- to detect as they form. Predicting tornadoes also remains challenging, due to an unclear understanding of why they form. Over…
Researchers at MIT Lincoln Laboratory have developed a new open-source dataset, named TorNet, to detect and predict tornadoes. By using artificial intelligence (AI) models trained on TorNet, researchers hope to improve tornado forecasts and warning accuracy, potentially saving lives and minimizing damage.
Tornadoes are challenging to predict, and this represents a high false alarm rate…
Around 1,200 tornadoes occur every year in the U.S., causing billions of dollars in damage and claiming an average of 71 lives. Predicting tornadoes is notoriously difficult due to gaps in understanding the precise conditions that cause them to form. The team from MIT's Lincoln Laboratory hopes to address this challenge, using a new open-source…
Meteorologists in the northern hemisphere have released a new, open-source dataset to aid in the detection and prediction of tornadoes. Given the working title "TorNet," the dataset was curated by Mark Veillette and James Kurdzo and includes radar data from thousands of US tornadoes over the past decade. Along with the dataset, models trained on…
With the arrival of spring in the Northern Hemisphere, tornado season begins. Despite their appearance being easily recognizable, detecting tornadoes with radar presents a challenge, making it difficult to pinpoint when and why these destructive phenomena occur. A breakthrough may be on the horizon with the TorNet dataset, recently released as open source by researchers…