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Abstract 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.
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Geodetic Data Assimilation for Evaluating Volcanic Unrest
Ensemble based data assimilation approaches, such as the Ensemble Kalman Filter (EnKF), have been widely and successfully implemented to combine observations with dynamic forecast models. In this study the EnKF is adapted to assimilate ground deformation observations from interferometric synthetic-aperture radar (InSAR) and GPS into thermomechanical finite element models (FEM) to evaluate volcanic unrest. Two eruption hindcasts are investigated: the 2008 eruption of Okmok volcano, Alaska and the 2018 eruption of Sierra Negra volcano, Galápagos, Ecuador. At Okmok, EnKF forecasts tensile failure and the lateral movement of the magma from a central pressure source in the lead up to its 2008 eruption indicating potential for diking. Alternatively, at Sierra Negra, the EnKF forecasts significant shear failure coincident with a Mw 5.4 earthquake that preceded the 2018 eruption. These successful hindcasts highlight the flexibility and potential of the volcano EnKF approach for near real time monitoring and hazard assessment at active volcanoes worldwide.
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- PAR ID:
- 10272179
- Date Published:
- Journal Name:
- IEEE IGARSS
- Page Range / eLocation ID:
- 3618 to 3621
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IGARSS39084.2020.9323109
