Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, Alaska
We describe a multidisciplinary approach to forecast, rapidly detect, and characterize explosive events during the 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc. The eruptive sequence began in December 2016 and included about 70 discrete explos...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-09-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/article/10.3389/feart.2018.00122/full |
| _version_ | 1819073635211542528 |
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| author | Michelle L. Coombs Aaron G. Wech Matthew M. Haney John J. Lyons David J. Schneider Hans F. Schwaiger Kristi L. Wallace David Fee Jeff T. Freymueller Janet R. Schaefer Gabrielle Tepp |
| author_facet | Michelle L. Coombs Aaron G. Wech Matthew M. Haney John J. Lyons David J. Schneider Hans F. Schwaiger Kristi L. Wallace David Fee Jeff T. Freymueller Janet R. Schaefer Gabrielle Tepp |
| author_sort | Michelle L. Coombs |
| collection | DOAJ |
| description | We describe a multidisciplinary approach to forecast, rapidly detect, and characterize explosive events during the 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc. The eruptive sequence began in December 2016 and included about 70 discrete explosive events. Because the volcano has no local monitoring stations, we used distant stations on the nearest volcanoes, Okmok (54 km) and Makushin (72 km), combined with regional infrasound sensors and lightning detection from the Worldwide Lightning Location Network (WWLLN). Pre-eruptive seismicity was detected for 12 events during the first half of the eruption; for all other events co-eruptive signals allowed for detection only. Monitoring of activity used a combination of scheduled checks combined with automated alarms. Alarms triggered on real-time data included real-time seismic amplitude measurement (RSAM); infrasound from several arrays, the closest being on Okmok; and lightning strokes detected from WWLLN within a 20-km radius of the volcano. During periods of unrest, a multidisciplinary response team of four people fulfilled specific roles to evaluate geophysical and remote-sensing data, run event-specific ash-cloud dispersion models, ensure interagency coordination, and develop and distribute of formalized warning products. Using this approach, for events that produced ash clouds ≥7.5 km above sea level, Alaska Volcano Observatory (AVO) called emergency response partners 15 min, and issued written notices 30 min, after event onset (mean times). Factors that affect timeliness of written warnings include event size and number of data streams available; bigger events and more data both decrease uncertainty and allow for faster warnings. In remote areas where airborne ash is the primary hazard, the approach used at Bogoslof is an effective strategy for hazard mitigation. |
| first_indexed | 2024-12-21T17:56:45Z |
| format | Article |
| id | doaj.art-fa13067347a84fb485a9d3d8027c36ea |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-12-21T17:56:45Z |
| publishDate | 2018-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-fa13067347a84fb485a9d3d8027c36ea2022-12-21T18:55:11ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632018-09-01610.3389/feart.2018.00122376183Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, AlaskaMichelle L. Coombs0Aaron G. Wech1Matthew M. Haney2John J. Lyons3David J. Schneider4Hans F. Schwaiger5Kristi L. Wallace6David Fee7Jeff T. Freymueller8Janet R. Schaefer9Gabrielle Tepp10Alaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesAlaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesAlaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesAlaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesAlaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesAlaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesAlaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesAlaska Volcano Observatory, Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, United StatesAlaska Volcano Observatory, Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, United StatesAlaska Volcano Observatory, Alaska Division of Geological and Geophysical Surveys, Fairbanks, AK, United StatesAlaska Volcano Observatory, Volcano Science Center, United States Geological Survey, Anchorage, AK, United StatesWe describe a multidisciplinary approach to forecast, rapidly detect, and characterize explosive events during the 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc. The eruptive sequence began in December 2016 and included about 70 discrete explosive events. Because the volcano has no local monitoring stations, we used distant stations on the nearest volcanoes, Okmok (54 km) and Makushin (72 km), combined with regional infrasound sensors and lightning detection from the Worldwide Lightning Location Network (WWLLN). Pre-eruptive seismicity was detected for 12 events during the first half of the eruption; for all other events co-eruptive signals allowed for detection only. Monitoring of activity used a combination of scheduled checks combined with automated alarms. Alarms triggered on real-time data included real-time seismic amplitude measurement (RSAM); infrasound from several arrays, the closest being on Okmok; and lightning strokes detected from WWLLN within a 20-km radius of the volcano. During periods of unrest, a multidisciplinary response team of four people fulfilled specific roles to evaluate geophysical and remote-sensing data, run event-specific ash-cloud dispersion models, ensure interagency coordination, and develop and distribute of formalized warning products. Using this approach, for events that produced ash clouds ≥7.5 km above sea level, Alaska Volcano Observatory (AVO) called emergency response partners 15 min, and issued written notices 30 min, after event onset (mean times). Factors that affect timeliness of written warnings include event size and number of data streams available; bigger events and more data both decrease uncertainty and allow for faster warnings. In remote areas where airborne ash is the primary hazard, the approach used at Bogoslof is an effective strategy for hazard mitigation.https://www.frontiersin.org/article/10.3389/feart.2018.00122/fulleruption forecastingAlaskavolcano monitoringBogoslofvolcanic infrasoundvolcanic lightning |
| spellingShingle | Michelle L. Coombs Aaron G. Wech Matthew M. Haney John J. Lyons David J. Schneider Hans F. Schwaiger Kristi L. Wallace David Fee Jeff T. Freymueller Janet R. Schaefer Gabrielle Tepp Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, Alaska Frontiers in Earth Science eruption forecasting Alaska volcano monitoring Bogoslof volcanic infrasound volcanic lightning |
| title | Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, Alaska |
| title_full | Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, Alaska |
| title_fullStr | Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, Alaska |
| title_full_unstemmed | Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, Alaska |
| title_short | Short-Term Forecasting and Detection of Explosions During the 2016–2017 Eruption of Bogoslof Volcano, Alaska |
| title_sort | short term forecasting and detection of explosions during the 2016 2017 eruption of bogoslof volcano alaska |
| topic | eruption forecasting Alaska volcano monitoring Bogoslof volcanic infrasound volcanic lightning |
| url | https://www.frontiersin.org/article/10.3389/feart.2018.00122/full |
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