Results 11 to 20 of about 1,142 (253)
Probabilistic, Multi‐Sensor Eruption Forecasting
Geophysical Research LettersWe developed an eruption forecasting model using data from multiple sensors or data streams with the Bayesian network method. The model generates probabilistic forecasts that are interpretable and resilient against sensor outage.
Y. Behr, A. Christophersen, C. Miller
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Ergodic seismic precursors and transfer learning for short term eruption forecasting at data scarce volcanoes [PDF]
Nature CommunicationsSeismic data recorded before volcanic eruptions provides important clues for forecasting. However, limited monitoring histories and infrequent eruptions restrict the data available for training forecasting models.
Alberto Ardid +17 more
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Hidden patterns in volcanic seismicity: deep learning insights from Mt. Etna’s 2020–2021 activity [PDF]
Scientific ReportsUnderstanding the temporal evolution of volcanic activity is crucial for eruption forecasting and hazard assessment. We use an unsupervised machine learning method, Deep Embedded Clustering, to classify daily seismic spectrograms of Mount Etna between ...
Waed Abed +9 more
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Anticipating volcanic eruptions using rescaled range analysis of volcano-tectonic seismicity [PDF]
Scientific ReportsThe possibility of forecasting volcanic eruptions remains a major challenge for the volcanological scientific community. To date, various techniques based on volcano-tectonic seismicity, endogenous gas emission and satellite imagery have been widely ...
Raúl Pérez-López +7 more
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Jerk, a promising tool for early warning of volcanic eruptions [PDF]
Nature CommunicationsForecasting volcanic eruptions remains a great civil defense challenge in many parts of the world. Although instrumental monitoring networks provide a variety of signals interpretable as eruption precursors, volcano observatories still lack a systemic ...
François Beauducel +6 more
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Understanding and forecasting sudden explosive eruptions. [PDF]
Bull VolcanolAbstract Explosive eruptions of VEI ≤ 3 commonly occur with few warning signs. Such eruptions can be magmatic, phreatomagmatic, or phreatic in nature, and they are driven by the catastrophic release of pressurized gas. Our challenge is how to better forecast these eruptions and better understand them with existing and new tools.
Stix J, de Moor JM, Aiuppa A.
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A unified probabilistic framework for volcanic hazard and eruption forecasting [PDF]
Natural Hazards and Earth System Sciences, 2021 The main purpose of this article is to emphasize the importance of clarifying the probabilistic framework adopted for volcanic hazard and eruption forecasting. Eruption forecasting and volcanic hazard analysis seek to quantify the deep uncertainties that
W. Marzocchi, J. Selva, T. H. Jordan
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Nature Geoscience, 2008 Florent Brenguier, Valerie Ferrazzini and their colleagues braved tropical cyclones and crater collapses while recording continuous seismological data on the Piton de la Foumaise volcano.
Brenguier, F., Ferrazzini, V.
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A physics-based source model for real-time tephra-dispersal forecasting for weak eruption plumes
Journal of Applied Volcanology, 2022 A physics-based model to estimate source conditions for a tephra-dispersal model is developed. The source condition is generally expressed by a distribution of released particles along an eruption plume (referred to as “source magnitude distribution” SMD)
Kensuke Ishii +3 more
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Forecasting Eruptions at Poorly Known Volcanoes Using Analogs and Multivariate Renewal Processes
Geophysical Research Letters, 2022 Forecasting future destructive eruptions from re‐awakening volcanoes remains a challenge, mainly due to a lack of previous event data. This sparks a search for similar volcanoes to provide additional information, especially those with better compiled and
Ting Wang +3 more
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