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USGS Mendenhall Postdoctoral Research Fellowship Program

S27. Quantification and validation of earthquake ground motions in early warning applications (2-3 positions available)

The USGS along with a coalition of State and university partners is developing and testing the ShakeAlert earthquake early warning (EEW) system for the west coast of the United States. The EEW system is inherently a ground-motion warning system: users’ actions depend on the level of ground motion expected at their site. This requires fast, accurate, and precise algorithms for determining the level and timing of shaking at a location before the shaking reaches damaging levels at that location. This opportunity focuses on investigating and developing new ground-motion estimation methods for EEW through three avenues, which may also be combined together in a symbiotic research proposal. Research is needed to determine optimum parameters for ground-motion estimates from earthquake rupture features available in real-time, to validate these methods with appropriate recorded and synthetic ground motion datasets, and to explore possibilities for ground-motion based alerts. To that end, we solicit proposals touching on one or more of following research areas:

1. Assessment of expected ground motion

Current ShakeAlert algorithms estimate expected ground motions by rapidly estimating the earthquake magnitude and location and then determining the expected ground motion using a ground-motion prediction equation (GMPE). However, there are large inherent uncertainties in both the initial earthquake source information (typically represented as a point source) and GMPEs, and many parameters employed in conventional GMPEs are not available in real-time for use in EEW. Thus, novel approaches are necessary to assess or develop GMPEs for use in EEW that most efficiently utilize the limited information available in real-time.

2. Verification of early warning algorithms

All algorithms employed in the ShakeAlert EEW must meet performance standards before they are accepted for operational use. Research is needed to develop appropriate benchmarks and performance metrics, as well as testing the system against those metrics. As seismic-network density increases, however, many historical earthquakes do not have sufficient recordings to serve as representative data sets for testing the system. Thus, synthetic waveforms for historical and scenario events will likely comprise most of the test data sets. Useful synthetic waveforms may already exist, or new sets of synthetic earthquake data may need to be developed. Validation of existing suites of synthetic waveforms will help guide development of additional suites of earthquake scenarios and new techniques for generating synthetic waveforms.

3. Ground-motion based alert methods

Ground-motion-based alerting methods are being investigated in EEW systems because they naturally handle complexities, such as finite-source effects and multiple events occurring nearly simultaneously that are often the source of errors in source-based methods. In principle, the approach is relatively straightforward – when strong ground motions are observed at a seismic station, an alert is immediately issued to all locations within ~30 km of that station warning those regions to expect similar shaking levels. Research is needed to determine the potential improvements in alerting with a ground-motion type system, and determine the feasibility of this type of alert for the ShakeAlert system, such as considering if this style of EEW provides faster warnings in the near field for strong ground motions, or if it significantly improves the accuracy of the ground motion prediction. A ground-motion based method may be attractive for use with low-cost sensors that can provide dense observations of peak ground acceleration (PGA) and peak ground velocity (PGV).

We seek Mendenhall Postdoctoral Scholars to investigate ground motion considerations in EEW systems. The research should fall within one or more of the three categories described above. Possible topics include:

Applicants are expected to have strong technical skills in earthquake seismology or engineering seismology associated with the proposed work and a desire to contribute to the ShakeAlert project; however, experience in applying the skills towards EEW is not necessary.

Due to the collaborative nature of this proposal as part of the ShakeAlert EEW project, interested applicants are strongly encouraged to contact the advisors below early in the application process to discuss project ideas and how they fit into the larger framework of ShakeAlert. The postdoctoral scholar will also likely interact and collaborate with university partners who are deeply involved in ShakeAlert research and development.

Proposed Duty Station: Menlo Park, California

Areas of Ph.D.: Geophysics or engineering seismology with a focus on ground motion and earthquake physics; 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 Engineer. (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.)

Research Advisor(s): Annemarie Baltay, (650) 329-4759, abaltay@usgs.gov; Sarah Minson, (650) 329-4879, sminson@usgs.gov; Brad Aagaard, (650) 329-4789, baagaard@usgs.gov; Andy Barbour, (650) 329-4803, abarbour@usgs.gov; Jessica Murray, (650) 329-4864, jrmurray@usgs.gov; Thomas Hanks, (650) 329-5634, thanks@usgs.gov.

Human Resources Office Contact: Yumi Sakakibara, 916-278-9384, lsakakibara@usgs.gov


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U.S. Department of the Interior, U.S. Geological Survey
URL: http://geology.usgs.gov/postdoc/opps/2018/S27 Baltay.htm
Direct inquiries to Rama K. Kotra at rkotra@usgs.gov
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Last modified: 17:08:31 Wed 14 Mar 2018
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