Between 2008 and 2022, researchers identified over 86,000 hidden earthquakes at Yellowstone, ten times more than previously detected. More than half of these occurred in swarms, known to precede volcanic activity, indicating increasing geological stress. These swarms were found along fault lines deep beneath the Yellowstone Caldera, likely triggered by hot, mineral-rich water. Traditional manual seismic data analysis proved inefficient, prompting the use of machine learning techniques to reveal missed earthquake clusters, suggesting significant geological transformations. An eruption could have catastrophic impacts, affecting millions across large portions of the US.
Researchers discovered over 86,000 hidden earthquakes at Yellowstone between 2008 and 2022, marking a significant increase compared to previous detections, prompting concerns of impending eruption.
The study revealed that more than half of the detected earthquakes occurred in swarms, which are known precursors to volcanic activity, hinting at increasing geological tensions.
Machine learning techniques were employed to analyze past seismic data, uncovering tens of thousands of earthquake swarms missed by manual inspections, highlighting the inefficiencies of traditional methods.
If the Yellowstone supervolcano erupts, it could devastate large areas, with ash falling across two-thirds of the US and rendering entire states uninhabitable due to toxic air.
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