Postdoctoral Fellowship: EAR-PF: Establishing a new eruption classification with a multimethod approach

Explosive volcanic eruptions produce ground-hugging hot rock and gas avalanches (pyroclastic density currents, PDCs) that devastate local communities and umbrella-shaped ash and gas clouds (umbrella clouds) that threaten aviation and can cause abrupt climate shifts lasting years. The severity and duration of eruption hazards to society, which can last years and affect the entire globe, depend on fluctuations in the rate at which erupted mass exits the volcano (mass eruption rate) and micrometer scale processes.

Current eruption classifications do not consider the effects of varying mass eruption rate during an eruption nor micrometer-scale processes on eruption hazards and are, therefore, ill-equipped for informing eruption response plans. The advancements of satellite and ground-based remote-sensing methods to monitor eruptions in real-time combined with increasingly sophisticated eruption computer simulations provide exciting new ways to classify eruption behavior and inform real-time eruption response.

However, leveraging these advances in eruption monitoring and modelling methods requires development of basic multiphase fluid mechanics theory to simply characterize the effects of variations in mass eruption rate and micrometer-scale processes in governing eruption behavior. Dr. Johan Gilchrist proposes to develop new fluid mechanics theory that will form the basis for a new “Eruption Stability Diagram” classification that captures the effects of varying mass eruption rate and micrometer-scale processes to predict the evolution of hazards during an eruption.

Dr. Gilchrist will conduct the next generation of laboratory experiments and computer simulations and compare the results with remote-sensing observations of eruptions to explore the full range of expected eruption behaviors and hazards for historical, ancient, and future eruptions in the Eruption Stability Diagram. The laboratory experiments will provide a rich learning experience for a diverse group of employed undergraduate researchers.

The project includes a collaboration with the National Museum of Natural History (Smithsonian Institute) to develop public-friendly versions of the Eruption Stability Diagram to clearly communicate eruption behaviors, hazards, and mitigation strategies to policymakers and the public.

During explosive volcanic eruptions rocks, ash and gases spreading in the atmosphere as umbrella ash clouds and along the ground as deadly pyroclastic density currents (PDCs) threaten people, infrastructure and drive major shifts in climate. In large eruptions volcanic material is simultaneously partitioned to spreading umbrella ash-clouds and PDCs.

Furthermore, during individual eruptive phases the rate at which erupted material is delivered to the atmosphere from a volcano can vary significantly compared to time-averaged mean rates (“unsteady eruption source parameters”, ESPs), causing mass partitioning to be highly time-dependent. Popular eruption classifications neither consider eruptive mass partitioning nor address the time-dependence that is inherent to most eruptive phases.

Dr. Gilchrist proposes to work with Dr. Josef Dufek (University of Oregon; UO) and Dr.

Benjamin Andrews (Smithsonian Institute; SI) to develop in greater detail two new eruption source parameter metrics that Dr. Gilchrist discovered during his PhD: the jet stability number to capture multiphase jet strength and the source Pulsation number to capture source unsteadiness, and combine them with the source particle volume fraction to form a new three-dimensional (3D) “Eruption Stability Diagram” classification scheme.

At UO Drs. Gilchrist and Dufek will design, build and conduct the next generation of analog experiments on multiphase jets to test the Eruption Stability Diagram’s reliability for predicting mass partitioning in multiphase jets between spreading clouds and ground-hugging gravity currents. Concurrently, they will work with Dr.

Eric Breard (U. of Edinburgh) to validate the next generation of 3D multiphase flow (MFIX) computer simulations using the experimental dataset. They will also collaborate with volcano radar expert Dr. Franck Donnadieu (U.

Clermont Auvergne, France) to use a Doppler radar-based dataset of unsteady ESPs that were measured in-situ at Sabancaya volcano, Peru (2018) to run and validate 3D MFIX eruption simulations. This research project aligns with the study of volcanology in the Petrology and Geochemistry program in the Earth Science division of NSF and the EAR research theme “issues related to scales”.

The Eruption Stability Diagram will be the first construct to classify all eruption styles on the basis of mean or time-varying eruption source parameters, predict erupted mass delivered to umbrella clouds and PDCs and, in turn, improve forecasting of eruption hazards and volcano-climate effects, generally. Moreover, characteristic evolutions of eruption source parameters typical of many eruptive phases will trace unique paths through the Eruption Stability Diagram allowing classes of eruptions to be understood through their evolution, a novel new way to classify eruptions.

This second way of classifying eruptions may reveal eruptive evolutionary paths diagnostic of specific volcanoes, types of volcanoes, or tectonic environments. The Eruption Stability Diagram will replace the current most popular Volcanic Explosivity Index classification used widely to understand the size and effects of volcanic eruptions on Earth. This project will also advance the multimethod approach of using complementary analog experiments and numerical simulations validated with field data to investigate volcanic phenomena.

The analog experiments will be the first to facilitate dissection of the deposit constructed by multiphase jets with varying source parameters to identify deposit features that are diagnostic of eruption column regimes and regime transitions, which will guide eruption deposit field studies. In parallel, the new 3D MFIX simulations will push the limits of multiphase flow simulations by explicitly modeling centimeter-scale particle inertial and buoyancy effects on the kilometer-scale bulk flow.

Crucial for eruption monitoring, the ESP and synthetic Doppler radar datasets produced by MFIX simulations of eruptions will be publicly available to inform interpretation of volcanic radar data.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.