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    Home » Revolutionary Method for Detecting Volcanic Eruptions | Sciworthy Insights
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    Revolutionary Method for Detecting Volcanic Eruptions | Sciworthy Insights

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    Volcano scientists dedicate their efforts to monitoring active volcanoes to predict potential eruptions. A significant challenge lies in accurately determining both the probability and the precise timing of these eruptions.

    In response to this critical issue, a research team has developed an innovative early detection system aimed at enhancing volcanic eruption warnings. The motivation behind this advancement stemmed from the shortcomings of previous warning systems, which often failed to recognize the underground volcanic activities that precede eruptions.

    Between 2014 and 2023, researchers carried out extensive tests to effectively detect transient low-frequency oscillations using a seismograph. These transient signals, which typically arise from earthquakes and other surface phenomena, have proven to be crucial for predicting volcanic events. This includes monitoring ground tilting caused by magma movement and volcanic gas emissions. Scientists refer to these signals as “jerk” signals due to their association with sudden physical shifts.

    The experimental setup was established at Piton de la Fournaise, a volcano located on La Réunion Island off Madagascar’s east coast. By analyzing short-term signals from existing seismic data, researchers successfully identified the jerk signal. During live experiments, a signal was detected 8 kilometers (approximately 5 miles) from the volcano at the Rivière-du-Rest seismic observatory, indicating surface changes as magma shifted just minutes or hours before an eruption.

    The jerk signal was quantified in Newton meters per second, providing insights into the speed of physical changes occurring around the volcano. The team not only conducted real-time analyses but also reviewed historical data from the observatory to validate the accuracy of jerk signal emergence preceding eruptions.

    To mitigate the risk of false alarms, researchers implemented a method to differentiate between ocean tidal signal amplitudes and transient jerk signals. They developed computational software to predict ocean tide signals, as ground-based instruments are also sensitive to tidal movements.

    The Jerk system issued its first automated alert in June 2014, signaling the presence of magma on the surface just one hour before the initial volcanic tremor. The final signal recorded in this study was on July 2, 2023, occurring 40 minutes before an eruption, at a slow rate of 1.5 Newton meters per second. Throughout 2014 to 2023, various jerk signals were detected anywhere from a few minutes to eight hours before eruptions.

    To evaluate the jerk signal’s effectiveness, the team reviewed records from past eruptions at Piton de la Fournaise. They discovered that during 24 eruptions from 1998 to 2010, jerk alarms would have triggered 83% of the time. An analysis of 48 eruptions between 1998 and 2023 indicated that about 42 jerk warnings would have been issued. Importantly, real-time analyses demonstrated that the accuracy of jerk signals has significantly improved compared to eruptions from two decades prior.

    Despite the successful detection of pre-eruption signals, the researchers acknowledged that data processing requires at least 10-15 minutes, which can lead to delayed jerk alarms. They reported experiencing two late warnings, on June 11, 2019, and February 10, 2020. After a decade of monitoring jerk signals, the team determined an impressive success rate of 92% for alarms preceding 22 out of 24 eruptions.

    Prior to the implementation of jerk signals, many volcanologists struggled to predict the exact moment of volcanic eruptions. The researchers concluded that by utilizing jerk signals alongside traditional pre-eruption earthquake detection methods, scientists in observatories can now provide timely notifications to authorities, enabling better preparedness for communities living near volcanoes worldwide.

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    Source: sciworthy.com

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