Hindcasting Magma Reservoir Stability Preceding the 2008 Eruption of Okmok,Alaska
Hindcasting Magma Reservoir Stability Preceding the 2008 Eruption of Okmok,Alaska
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DOI：
10.1029/2019gl083395
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发表时间：
2019-08-16
影响因子：
5.2
通讯作者：
Freymueller, J. T.
中科院分区：
文献类型：
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作者：
Albright, J. A.;Gregg, P. M.;Freymueller, J. T.
火山爆发造成了重大的，有时是不可预测的危险，特别是在系统显示很少或根本没有预警信号。例如，2008年阿拉斯加的奥克莫克火山爆发，尽管多年来一直处于低水平的动荡之中，但明显缺乏可观察到的短期前兆。这种不可预测性突出表明，仅凭直接监测并不总是足以可靠地预测火山爆发。在这项研究中，我们使用Enhancement卡尔曼滤波器（EnKF），以产生一个成功的Okmok岩浆系统在其2008年喷发的铅后投。通过同化大地测量观测的地面变形，有限元模型跟踪不断变化的应力状态的岩浆系统，并评估其稳定性，使用机械故障标准。后报成功地表明，由于2008年喷发前几周的拉伸破坏，喷发的可能性增加。这种后报的有效性表明，EnKF为基础的预测方法可以提供关键信息的系统缺乏明显的precursors.Plain Language摘要火山监测机构通常使用火山动荡的潜在指标增加喷发的概率。然而，对于一些火山爆发，如2008年阿拉斯加奥克莫克火山爆发，这些行为可能是微妙的或完全缺失。在这项研究中，一种新的基于南极洲的火山预测方法被用来测试计算机模型是否能够捕捉到导致2008年事件的喷发可能性增加。这些模型表明，由于岩浆房失败的可能性增加，奥克莫克提前几周就有喷发的趋势。这一成功的测试表明，岩浆房周围的应力是火山稳定性的有力预测因素，这种方法可以适用于活火山系统，并改善减灾工作。
Volcanic eruptions pose a significant and sometimes unpredictable hazard, especially at systems that display little to no precursory signals. For example, the 2008 eruption of Okmok volcano in Alaska notably lacked observable short-term precursors despite years of low-level unrest. This unpredictability highlights that direct monitoring alone is not always enough to reliably forecast eruptions. In this study, we use the Ensemble Kalman Filter (EnKF) to produce a successful hindcast of the Okmok magma system in the lead up to its 2008 eruption. By assimilating geodetic observations of ground deformation, finite element models track the evolving stress state of the magma system and evaluate its stability using mechanical failure criteria. The hindcast successfully indicates an increased eruption likelihood due to tensile failure weeks in advance of the 2008 eruption. The effectiveness of this hindcast illustrates that EnKF-based forecasting methods may provide critical information on eruption probability in systems lacking obvious precursors.Plain Language Summary Volcano monitoring agencies routinely use increases in volcanic unrest as indicators of the potential for eruption. However, for some eruptions, such as the 2008 eruption of Okmok volcano in Alaska, these behaviors can be subtle or missing altogether. In this study, a new statistics-based volcano forecasting approach is used to test whether computer models are able to capture an increase in eruption likelihood leading up to the 2008 event. The models indicate that Okmok was trending toward eruption weeks in advance due to the increased probability of failure of the magma chamber. This successful test indicates that stress around the magma chamber is a strong predictor of volcano stability and that this method could apply to active volcanic systems and improve hazard mitigation efforts.