Ergodic seismic precursors and transfer learning for short term eruption forecasting at data scarce volcanoes
Date
Authors
Ardid, Alberto
Dempsey, David
Caudron, Corentin
Cronin, Shane J.
Kennedy, Ben
Girona, Társilo
Roman, Diana C.
Miller, Craig
Potter, Sally H.
Lamb, Oliver D.
Martanto, Anto
Çubuk Sabuncu, Ye?im
Cabrera, Leoncio
Ruiz, Sergio
Contreras-Arratia, Rodrigo
Pacheco, J. F.
Mora, Mauricio M.
De Angelis, Silvio
Dempsey, David
Caudron, Corentin
Cronin, Shane J.
Kennedy, Ben
Girona, Társilo
Roman, Diana C.
Miller, Craig
Potter, Sally H.
Lamb, Oliver D.
Martanto, Anto
Çubuk Sabuncu, Ye?im
Cabrera, Leoncio
Ruiz, Sergio
Contreras-Arratia, Rodrigo
Pacheco, J. F.
Mora, Mauricio M.
De Angelis, Silvio
Authors
Date
Datos de publicación:
10.1038/s41467-025-56689-x
Keywords
Biodiversidad - Ecología de ecosistemas - Ecología de aguas dulces
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Abstract
Abstract 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. We propose a transfer machine learning approach that identifies eruption precursors signals that consistently change before eruptions across multiple volcanoes. Using seismic data from 41 eruptions at 24 volcanoes over 73 years, our approach forecasts eruptions at unobserved (out-of-sample) volcanoes. Tested without data from the target volcano, the model demonstrated accuracy comparable to direct training on the target and exceeded benchmarks based on seismic amplitude. These results indicate that eruption precursors exhibit ergodicity, sharing common patterns that allow observations from one group of volcanoes to approximate the behavior of others. This approach addresses data limitations at individual sites and provides a useful tool to support monitoring efforts at volcano observatories, improving the ability to forecast eruptions and mitigate volcanic risks.
Description
Keywords
Biodiversidad , Ecología de ecosistemas , Ecología de aguas dulces
Citation
10.1038/s41467-025-56689-x