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Intra‐Eruption Forecasting Using Analogue Volcano and Eruption Sets

Journal of Geophysical Research: Solid Earth, 2022
AbstractForecasting the likely style and chronology of activity within an eruption is a complex issue that has received far less attention than forecasting the onset and/or the magnitude. By developing a global data set of coded phases (discrete styles of activity within previous eruptions), we can model the resulting data using a semi‐Markov chain ...
M S Bebbington, Susanna F Jenkins
exaly   +5 more sources

Intra-eruption forecasting [PDF]

Bulletin of Volcanology, 2019
Forecasting eruption onsets has received much attention, in both the short and long term. However, an eruption is not easily reduced to an instant in time, and forecasting what happens after eruption onset has received little attention. Any useful definition of an eruption has to allow for activity over scales ranging from days to decades, and can do ...
M S Bebbington, Susanna F Jenkins
exaly   +4 more sources

Ergodic seismic precursors and transfer learning for short term eruption forecasting at data scarce volcanoes [PDF]

Nature Communications
Seismic 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, David Dempsey, Corentin Caudron, Shane Cronin, Ben Kennedy, Társilo Girona, Diana Roman, Craig Miller, Sally Potter, Oliver D. Lamb, Anto Martanto, Yesim Cubuk-Sabuncu, Leoncio Cabrera, Sergio Ruiz, Rodrigo Contreras, Javier Pacheco, Mauricio M. Mora, Silvio De Angelis   +17 more
doaj   +3 more sources

Toward Forecasting Volcanic Eruptions using Seismic Noise [PDF]

Nature Geoscience, 2007
During inter-eruption periods, magma pressurization yields subtle changes of the elastic properties of volcanic edifices. We use the reproducibility properties of the ambient seismic noise recorded on the Piton de la Fournaise volcano to measure relative
A Grêt, A Nercessian, A Peltier, A Peltier, A Ratdomopurbo, Alexandre Nercessian, B Chouet, B Chouet, B Voight, C Sens-Schönfelder, D Massonnet, D Patanè, D Patanè, F Brenguier, Florent Brenguier, G Poupinet, J Battaglia, KG Sabra, KG Sabra, KG Sabra, L Stehly, L Stieltjes, M Campillo, M Campillo, Michel Campillo, N Shapiro, Nikolai M. Shapiro, NM Shapiro, Olivier Coutant, P McLeod, R Snieder, RL Weaver, S Tait, SR Pride, U Wegler, Valérie Ferrazzini, Zacharie Duputel   +36 more
core   +6 more sources

Hidden patterns in volcanic seismicity: deep learning insights from Mt. Etna’s 2020–2021 activity [PDF]

Scientific Reports
Understanding 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, Zahra Zali, Mariangela Sciotto, Ornella Cocina, Andrea Cannata, Matteo Picozzi, Patricia Martínez-Garzón, Alessandro Vuan, Angela Saraò, Monica Sugan   +9 more
doaj   +2 more sources

Understanding and forecasting sudden explosive eruptions. [PDF]

Bull Volcanol
Abstract 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.
europepmc   +3 more sources

Anticipating volcanic eruptions using rescaled range analysis of volcano-tectonic seismicity [PDF]

Scientific Reports
The 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, Carolina Guardiola-Albert, Alicia Felpeto, David Sanz-Mangas, Nahum Méndez-Chazarra, Rafael Abella, Miguel A. Rodríguez-Pascua, Julio López-Gutierrez   +7 more
doaj   +2 more sources

Probabilistic, Multi‐Sensor Eruption Forecasting

Geophysical Research Letters
We 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
doaj   +3 more sources

Jerk, a promising tool for early warning of volcanic eruptions [PDF]

Nature Communications
Forecasting 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, Geneviève Roult, Valérie Ferrazzini, Aline Peltier, Philippe Jousset, Patrice Boissier, Nicolas Villeneuve   +6 more
doaj   +2 more sources

Mitigation of human cognitive bias in volcanic eruption forecasting

Journal of Applied Volcanology
Modern operational eruption forecasting methods rely heavily on human judgment in the face of uncertainty and are thus susceptible to myriad cognitive biases and errors by the scientist-forecasters.
Heather M. N. Wright, Jeremy D. Pesicek, Stephen A. Spiller   +2 more
doaj   +2 more sources