Alaska Volcano Observatory Alert and Forecasting Timeliness: 1989–2017

Abstract

The Alaska Volcano Observatory (AVO) monitors volcanoes in Alaska and issues notifications and warnings of volcanic unrest and eruption. We evaluate the timeliness and accuracy of eruption forecasts for 53 eruptions at 20 volcanoes, beginning with Mount Redoubt’s 1989–1990 eruption. Successful forecasts are defined as those where AVO issued a formal warning before eruption onset. These warning notifications are now part of AVO’s Aviation Color Code and Volcanic Alert Level. This analysis considers only the start of an eruption, although many eruptions have multiple phases of activity. For the 21 eruptions at volcanoes with functioning local seismic networks, AVO has high forecasting success at volcanoes with: >15 yr repose intervals and magmatic eruptions (4 out of 4, 100%); or larger eruptions (Volcanic Explosivity Index (VEI) 3 or greater; 6 out of 10, 60%). AVO successfully forecast all four monitored, longer-repose period, VEI 3+ eruptions: Redoubt 1989-1990 and 2009, Spurr 1992, and Augustine 2005–2006. For volcanoes with functioning seismic monitoring networks, success rates are lower for: volcanoes with shorter repose periods (3 out of 16, 19%); more mafic compositions (3 out of 18, 17%); or smaller eruption size (VEI 2 or less, 1 out of 11, 9%). These eruptions (Okmok, Pavlof, Veniaminof, and Shishaldin) often lack detectable precursory signals. For 32 eruptions at volcanoes without functioning local seismic networks, the forecasting success rate is much lower (2, 6%; Kasatochi 2008 and Shishaldin 2014). For remote volcanoes where the main hazard is to aviation, rapid detection is a goal in the absence of in situ monitoring. Eruption detection has improved in recent years, shown by a decrease in the time between eruption onset and notification. Even limited seismic monitoring can detect precursory activity at volcanoes with certain characteristics (intermediate composition, longer repose times, larger eruptions), but difficulty persists in detecting subtle precursory activity at frequently active volcanoes with more mafic compositions. This suggests that volcano-specific characteristics should be considered when designing monitoring programs and evaluating forecasting success. More proximally-located sensors and data types are likely needed to forecast eruptive activity at frequently-active, more mafic volcanoes that generally produce smaller eruptions.