Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand
In this study, the authors investigate the predictability of sudden eruptions, motivated by the 2019 eruption at Whakaari (White Island), New Zealand. The paper proposes a machine learning approach that is able to identify eruption precursors in data streaming from a single seismic station at Whakaa...
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Online Access: | https://doi.org/10.1038/s41467-020-17375-2 https://doaj.org/article/9a10873129be47a1b81e8531c5177be5 |
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ftdoajarticles:oai:doaj.org/article:9a10873129be47a1b81e8531c5177be5 2023-05-15T18:43:34+02:00 Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand D. E. Dempsey S. J. Cronin S. Mei A. W. Kempa-Liehr 2020-07-01T00:00:00Z https://doi.org/10.1038/s41467-020-17375-2 https://doaj.org/article/9a10873129be47a1b81e8531c5177be5 EN eng Nature Portfolio https://doi.org/10.1038/s41467-020-17375-2 https://doaj.org/toc/2041-1723 doi:10.1038/s41467-020-17375-2 2041-1723 https://doaj.org/article/9a10873129be47a1b81e8531c5177be5 Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020) Science Q article 2020 ftdoajarticles https://doi.org/10.1038/s41467-020-17375-2 2022-12-31T07:18:14Z In this study, the authors investigate the predictability of sudden eruptions, motivated by the 2019 eruption at Whakaari (White Island), New Zealand. The paper proposes a machine learning approach that is able to identify eruption precursors in data streaming from a single seismic station at Whakaari. Article in Journal/Newspaper White Island Directory of Open Access Journals: DOAJ Articles New Zealand White Island ENVELOPE(48.583,48.583,-66.733,-66.733) Nature Communications 11 1 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Science Q |
spellingShingle |
Science Q D. E. Dempsey S. J. Cronin S. Mei A. W. Kempa-Liehr Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand |
topic_facet |
Science Q |
description |
In this study, the authors investigate the predictability of sudden eruptions, motivated by the 2019 eruption at Whakaari (White Island), New Zealand. The paper proposes a machine learning approach that is able to identify eruption precursors in data streaming from a single seismic station at Whakaari. |
format |
Article in Journal/Newspaper |
author |
D. E. Dempsey S. J. Cronin S. Mei A. W. Kempa-Liehr |
author_facet |
D. E. Dempsey S. J. Cronin S. Mei A. W. Kempa-Liehr |
author_sort |
D. E. Dempsey |
title |
Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand |
title_short |
Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand |
title_full |
Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand |
title_fullStr |
Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand |
title_full_unstemmed |
Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand |
title_sort |
automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at whakaari, new zealand |
publisher |
Nature Portfolio |
publishDate |
2020 |
url |
https://doi.org/10.1038/s41467-020-17375-2 https://doaj.org/article/9a10873129be47a1b81e8531c5177be5 |
long_lat |
ENVELOPE(48.583,48.583,-66.733,-66.733) |
geographic |
New Zealand White Island |
geographic_facet |
New Zealand White Island |
genre |
White Island |
genre_facet |
White Island |
op_source |
Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020) |
op_relation |
https://doi.org/10.1038/s41467-020-17375-2 https://doaj.org/toc/2041-1723 doi:10.1038/s41467-020-17375-2 2041-1723 https://doaj.org/article/9a10873129be47a1b81e8531c5177be5 |
op_doi |
https://doi.org/10.1038/s41467-020-17375-2 |
container_title |
Nature Communications |
container_volume |
11 |
container_issue |
1 |
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1766233992885960704 |