NSF Award
2422971
Volcanic eruptions create sudden extreme hazards to nearby populations and commercial air traffic. Volcanologists need to better understand the timescales and processes that trigger unrest in a magmatic system to reduce risks to humans and property destruction. This is especially critical for volcanoes that lack strong warning signals (e.g., earthquakes) before an eruption. This project will combine erupted products with modern monitoring techniques. Scientists will focus on Okmok Volcano, Alaska, a frequently active volcanic system that produces a range of eruption sizes and volumes but tends to have very short (~4-5 hours preceding eruption onset) indicators of imminent eruption. Their study will generate data that will help them understand the signals and timing of unrest by studying four earlier eruptions. They will collaborate with scientists from the University of Alaska Fairbanks and the Alaska Volcano Observatory (AVO). This work will support one postdoctoral fellow, one master’s student, and 10 undergraduate students. In addition, co-PI Moore-Nall will develop a 1-credit seminar surrounding Indigenous ways of knowing and volcanic landscapes, in collaboration with Cheryl Cameron at the AVO, further honoring the land-grant mission of Montana State University and the state constitution to provide Indian Education for All.<br/><br/><br/>One avenue to strengthen the volcanology community’s ability to respond when volcanic unrest begins is to have a thorough understanding of the timescales of subsurface processes that led to different size and styles of eruptions, which can be accomplished through investigation of the petrologic record. This team seeks to test whether a system that lacks strong precursory seismicity showed other signs of unrest that were missed due to a lack of understanding the pre-eruptive timescales of magmatic processes (recharge, mixing, ascent) at depth. Through a retrospective approach, they will study the petrologic record of a frequently erupting volcano to elucidate the magmatic processes that occurred prior to four volcanic eruptions, two of which have external datasets (deformation, seismicity, satellites) to compare to their petrologic insights. This project will focus on Okmok Volcano, Alaska, a frequently active volcanic system (~10-to-30-year timescale) that produces a range of eruption sizes and volumes but tends to have very short (~4-5 hours preceding eruption onset) duration seismic precursors. They will address three main questions: Q1. How do deep magmatic processes and their associated timescales of unrest vary over eruptive cycles? Q2. Do these processes scale with erupted volume, ascent rate, eruption style and volcano explosivity index? Q3. Were there missed geophysical signals that scale with eruption intensity that could be used to forewarn about future unrest? This team will measure and model Fe–Mg and H gradients from individual crystals of olivine and clinopyroxene (cpx), techniques that have initially proven to be successful for integrating with geophysical datasets, but further pushing the field forward through the integration of multi-phase crystal cluster analysis. Multi-phase crystal clusters are defined as a group of minerals with a shared history but various chemical and/or textural changes, which when considered as an entity could potentially allow petrologists to better resolve the specific magma processes that lead to their formation, an interpretation that might be oversimplified if just assessing an individual phase. Ultimately the dataset afforded by this project will allow them to ask whether they can see evidence from the petrologic record for links between the run-up and ascent times for eruptions with different eruptive styles, volumes, and volcano explosivity indexes (VEI), and test whether for the more modern eruptions, there were missed geophysical signals that can be better turned for future monitoring.<br/><br/>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.
