Closing Date: November 1, 2022
This Research Opportunity will be filled depending on the availability of funds. All application materials must be submitted through USAJobs by 11:59 pm, US Eastern Standard Time, on the closing date.
Please communicate with individual Research Advisor(s) on the right to discuss project ideas and answer specific questions about the Research Opportunity.
How to Apply
The catastrophic eruption of the Hunga Tonga-Hunga Ha’apai (HTHH) volcano in January 2022 highlighted a critical problem for the global geohazards community. The deadly eruption was not forecasted because there was no observed precursor activity. This was likely in part due to a lack of local and/or regional seismic monitoring. Subsequent analyses of distant seismic stations showed that precursor earthquakes did in fact occur. Thus, forecasting might have been possible with better remote seismic monitoring tools. In the days following the HTHH eruption, the USGS National Earthquake Information Center (NEIC) and the USGS Volcano Science Center (VSC) combined expertise and used novel techniques to build and interpret a near-real-time earthquake catalog for the HTHH region. The VSC interpreted the post-eruptive seismicity documented in the catalog and shared a report describing the possibility of future volcanic hazards with the Republic of Tonga and the international community. Additionally, retrospective analyses using template matching techniques enriched the earthquake catalog, allowing the USGS to document post-eruptive collapse or magmatic diking.
We will continue encountering situations like HTHH, where volcano monitoring of intensely hazardous situations requires monitoring from afar. Globally, there are well over 1,000 volcanoes capable of erupting that lack local seismic monitoring. Alaska alone has more than 60 volcanoes in this category, while other more populated areas (e.g., Indonesia) have dozens of unmonitored volcanoes near dense population centers.
Remote volcano monitoring is challenging. However, the largest and most explosive eruptions generate globally observable signals that generally have sizeable seismic precursors capable of detection using regional and teleseismic techniques. For example, the 2008 eruption of the Kasatochi volcano in the Aleutians was successfully forecast using regional seismic data allowing for the successful evacuation of two people. Beyond forecasting, some significant, unexpected eruptions go undetected using NEIC’s current high-frequency (~1Hz) detectors. An example of an undetected event is the 2018 Mayotte eruption that occurred between Comoros and Madagascar. This event produced low-frequency (~0.05 Hz) signals that NEIC did not automatically detect. Had the NEIC implemented low-frequency detectors, the event would have been detected in minutes to hours instead days later when low-frequency signals were first reported. Beyond searching for eruption precursors, understanding details of what happened during an eruption is difficult without local networks. For example, NEIC improved the understanding of the HTHH eruption by extending the standard processing to include waveform template matching and relative surface wave relocations. Implementing these techniques provided new insights, but the methods can be improved and put into routine production.
The purpose of this Mendenhall Research Opportunity is to refine and develop remote seismic monitoring techniques and apply these techniques to 1) automatically detect “unseen” eruptions, 2) forecast potential eruptions, and 3) conduct post-eruption investigations. Studying the different phases of an eruption requires different techniques. Research should target approaches transferable to processing workflows at the NEIC and other monitoring networks. Potential areas of investigation include reducing the current NEIC magnitude detection limit using seismic array processing, application of surface wave event detectors to detect currently missed events, routine implementation of waveform templet matching to detect small events in a volcanic sequence, using machine learning signal detection, and employing relative location techniques to better understand the eruptive process. The research will benchmark teleseismic techniques on eruptive sequences with well-documented seismicity from local seismic networks and improve capabilities to remotely monitor volcanic sequences with no local monitoring and poorly characterized seismicity.
These techniques, when operationalized, will significantly benefit the many communities exposed to unmonitored volcanoes. Additionally, these methods will have operational benefits to the USGS beyond volcano monitoring including, detection of slow earthquakes such as ridge events that sometimes go undetected, global aftershock monitoring to lower magnitude ranges with potential benefits to Operational Aftershock Forecasting, and relocation of remote aftershock sequences for tectonic interpretation. Work will involve travel between the cooperating Science Centers in Colorado, Alaska, and Washington.
Interested applicants are strongly encouraged to contact the Research Advisor(s) early in the application process to discuss project ideas.
Proposed Duty Station(s): Golden, Colorado, Anchorage, Alaska, or Vancouver, Washington
Areas of PhD: Observational seismology, applied volcanology, signal processing, geophysics, statistics, computer science, or related fields (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet one of the following qualifications: Research Geophysicist, Research Computer Scientist, Research Mathematician, Research Physicist, or Research Statistician
(This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)
Human Resources Office Contact: Oluwabukola Alimi, 303-236-9597, email@example.com