Testing eruption-triggering mechanisms at Axial Caldera using statistical data assimilation

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Millions of people around the world live in the shadows of active volcanic systems. In the United States, active volcanoes in California, the Pacific Northwest, Alaska, and Hawaii are monitored both by ground based instruments and satellite observations to provide early warning of potential eruptions and hazards for local communities. On land, GPS and satellite observations can detect volcano inflation and provide early warning of unrest. However, the link between surface deformation and eruption remains unclear. This project will address this link at the submarine Axial Volcano located on the Juan de Fuca Ridge off of the coast of Oregon. Unlike volcanoes on land, deformation of Axial Volcano appears to be closely linked to eruption. Still, the ultimate eruption triggering mechanism at Axial Volcano remains unknown. Three decades of observations spanning three eruption cycles will provide the data necessary to 'hind-cast' past eruptions at Axial and look for specific eruption precursors in the deformation signal leading up to eruption. Axial Volcano is an ideal natural laboratory to test hypotheses for eruption triggering mechanisms and the link between deformation and eruption at active volcanoes. This project supports the training of a Ph.D. student.In this project statistical data assimilation techniques will be used to combine ground deformation observations with finite element models of Axial Volcano to produce hind casts of the 1998, 2011, and 2015 eruptions and investigate what mechanisms might have triggered eruption of Axial. The first step in the investigation will test eruption precursors and triggering mechanism. The second step will develop a method for utilizing data from the Ocean Observatory Initiative Axial Regional Node in near-real time to forecast future unrest at Axial Volcano. These advancements will provide critical insight into the evolution of the Axial volcanic system. Axial Volcano is the only system with a successful deformation based eruption prediction and it could provide an important missing link for understanding how eruptions are triggered at volcanoes.