A digital twin to accelerate volcano science and unify geodetic and seismic observations
Emerging computational and data assimilation approaches and increasing data volumes imply an opportunity to greatly accelerate both fundamental volcano science and hazard assessment and forecasting.
Volcano observatories in the United States and globally rely on data informing ground deformation and seismic activity to understand unrest at the world’s highest risk volcanoes and forecast hazards. However, despite both being measurements of ground motions at different frequencies, geodetic and seismic observations are rarely considered together during volcanic unrest. Emerging computational and data assimilation approaches and increasing data volumes imply an opportunity to greatly accelerate both fundamental volcano science and hazard assessment and forecasting by building technical infrastructure associated with model-data fusion and bringing together the communities of scientists who work on these problems. Over two years and two Powell Center meetings, we will build the framework of a “Digital Twin” for volcano deformation and seismic imaging, consisting of interacting virtual and physical representations of two High Threat template systems for the National Volcano Early Warning System, Mount St. Helens and Yellowstone.
Principal Investigators
Leif Karlstrom (University of Oregon)
Brandon Schmandt (Rice University)
Michael Poland (U.S. Geological Survey)
Kyle Anderson (U.S. Geological Survey)
Emerging computational and data assimilation approaches and increasing data volumes imply an opportunity to greatly accelerate both fundamental volcano science and hazard assessment and forecasting.
Volcano observatories in the United States and globally rely on data informing ground deformation and seismic activity to understand unrest at the world’s highest risk volcanoes and forecast hazards. However, despite both being measurements of ground motions at different frequencies, geodetic and seismic observations are rarely considered together during volcanic unrest. Emerging computational and data assimilation approaches and increasing data volumes imply an opportunity to greatly accelerate both fundamental volcano science and hazard assessment and forecasting by building technical infrastructure associated with model-data fusion and bringing together the communities of scientists who work on these problems. Over two years and two Powell Center meetings, we will build the framework of a “Digital Twin” for volcano deformation and seismic imaging, consisting of interacting virtual and physical representations of two High Threat template systems for the National Volcano Early Warning System, Mount St. Helens and Yellowstone.
Principal Investigators
Leif Karlstrom (University of Oregon)
Brandon Schmandt (Rice University)
Michael Poland (U.S. Geological Survey)
Kyle Anderson (U.S. Geological Survey)