Eric M Thompson
Eric Thompson is a research geophysicist with the USGS in Golden. He joined the USGS in 2015 where he participates in research, development, and operations of many earthquake hazard products, including near-real-time earthquake hazard products.
Professional Experience
5/2015-Present: Research Geophysicist, USGS, Golden, Colorado.
4/2013-4/2015: Adjunct Professor, Geological Sciences, San Diego State University.
1/2014-3/2015: Lecturer, Department of Civil and Environmental Engineering, University of California, Los Angeles.
9/2010-9/2013: Research Assistant Professor, Civil and Environmental Engineering, Tufts University.
3/2009-8/2010: Postdoctoral Researcher/Lecturer, Civil and Environmental Engineering, Tufts University.
Education and Certifications
2009 Ph.D., Tufts University, Civil and Environmental Engineering.
2002 B.S., University of California at Santa Cruz, Earth Science.
Honors and Awards
2022: Superior Service Award for activities in the planning and development of ground motion processing software named gmprocess.
2019: FEMA Certificate of Appreciation for outstanding contributions in support of national level earthquake exercise.
2018: Western States Seismic Policy Council (WSSPC) Award for Excellence Use of Technology for developing the ShakeMap Scenario Suite.
Science and Products
The 2018 update of the US National Seismic Hazard Model: Overview of model and implications
Ground-motion amplification in Cook Inlet region, Alaska from intermediate-depth earthquakes, including the 2018 MW=7.1 Anchorage earthquake
Ground failure from the Anchorage, Alaska, earthquake of 30 November 2018
Evaluation of ground motion models for USGS seismic hazard forecasts: Induced and tectonic earthquakes in the Central and Eastern U.S.
Preliminary 2018 national seismic hazard model for the conterminous United States
Ground motions from induced earthquakes in Oklahoma and Kansas
The case for mean rupture distance in ground‐motion estimation
Improving near‐real‐time coseismic landslide models: Lessons learned from the 2016 Kaikōura, New Zealand, earthquake
Spatial and spectral interpolation of ground-motion intensity measure observations
A flatfile of ground motion intensity measurements from induced earthquakes in Oklahoma and Kansas
An open repository of earthquake-triggered ground-failure inventories
Estimating rupture distances without a rupture
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
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Filter Total Items: 77
The 2018 update of the US National Seismic Hazard Model: Overview of model and implications
During 2017–2018, the National Seismic Hazard Model for the conterminous United States was updated as follows: (1) an updated seismicity catalog was incorporated, which includes new earthquakes that occurred from 2013 to 2017; (2) in the central and eastern United States (CEUS), new ground motion models were updated that incorporate updated median estimates, modified assessments of the associatedAuthorsMark D. Petersen, Allison Shumway, Peter M. Powers, Charles Mueller, Morgan P. Moschetti, Arthur Frankel, Sanaz Rezaeian, Daniel E. McNamara, Nicolas Luco, Oliver S. Boyd, Kenneth S. Rukstales, Kishor Jaiswal, Eric M. Thompson, Susan M. Hoover, Brandon Clayton, Edward H. Field, Yuehua ZengGround-motion amplification in Cook Inlet region, Alaska from intermediate-depth earthquakes, including the 2018 MW=7.1 Anchorage earthquake
We measure pseudospectral and peak ground motions from 44 intermediate‐depth Mw≥4.9 earthquakes in the Cook Inlet region of southern Alaska, including those from the 2018 Mw 7.1 earthquake near Anchorage, to identify regional amplification features (0.1–5 s period). Ground‐motion residuals are computed with respect to an empirical ground‐motion model for intraslab subduction earthquakes, and weAuthorsMorgan P. Moschetti, Eric M. Thompson, John Rekoske, Mike Hearne, Peter M. Powers, Daniel E. McNamara, Carl TapeGround failure from the Anchorage, Alaska, earthquake of 30 November 2018
Investigation of ground failure triggered by the 2018 MwMw 7.1 Anchorage earthquake showed that landslides, liquefaction, and ground cracking all occurred and caused significant damage. Shallow rock falls and rock slides were the most abundant types of landslides, but they occurred in smaller numbers than global models that are based on earthquake magnitude predict; this might result from the 2018AuthorsRandall W. Jibson, Alex R. R. Grant, Robert C. Witter, Kate E. Allstadt, Eric M. Thompson, Adrian BenderEvaluation of ground motion models for USGS seismic hazard forecasts: Induced and tectonic earthquakes in the Central and Eastern U.S.
Ground motion model (GMM) selection and weighting introduces a significant source of uncertainty in United States Geological Survey (USGS) seismic hazard models. The increase in moderate moment magnitude induced earthquakes (Mw 4 to 5.8) in Oklahoma and Kansas since 2009, due to increased wastewater injection related to oil and gas production (Keranen et al., 2013; 2014; Weingarten et al., 2015;AuthorsDaniel E. McNamara, Mark D. Petersen, Eric M. Thompson, Peter M. Powers, Allison Shumway, Susan M. Hoover, Morgan P. Moschetti, Emily WolinPreliminary 2018 national seismic hazard model for the conterminous United States
The 2014 U.S. Geological Survey national seismic hazard model for the conterminous U.S. will be updated in 2018 and 2020 to coincide with the Building Seismic Safety Council’s Project 17 timeline for development of new building code design criteria. The two closely timed updates are planned to allow more time for the Provisions Update Committee to analyze the consequences of the hazard model changAuthorsMark D. Petersen, Allison Shumway, Peter M. Powers, Charles Mueller, Sanaz Rezaeian, Morgan P. Moschetti, Daniel E. McNamara, Eric M. Thompson, Oliver S. Boyd, Nicolas Luco, Susan M. Hoover, Kenneth S. RukstalesGround motions from induced earthquakes in Oklahoma and Kansas
Improved predictions of earthquake ground motions are critical to advancing seismic hazard analyses and earthquake response. The high seismicity rate from 2009 to 2016 in Oklahoma and Kansas provides an extensive data set for examining the ground motions from these events. We evaluate the ability of three suites of ground‐motion prediction equations (GMPEs)—appropriate for modeling tectonic earthqAuthorsMorgan P. Moschetti, Eric M. Thompson, Peter M. Powers, Susan M. Hoover, Daniel E. McNamaraThe case for mean rupture distance in ground‐motion estimation
This article advocates for the use of mean rupture distances that we contend are more physically representative of the distance to an earthquake and are simpler than minimum distances. Many current ground‐motion models (GMMs) rely on numerous modifications of minimum rupture distances to accurately model near‐source ground motions. These modifications, that include additional distance definitionsAuthorsEric M. Thompson, Annemarie S. BaltayImproving near‐real‐time coseismic landslide models: Lessons learned from the 2016 Kaikōura, New Zealand, earthquake
The U.S. Geological Survey (USGS) is developing near‐real‐time global earthquake‐triggered‐landslide products to augment the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system. The 14 November 2016 MwMw 7.8 Kaikōura, New Zealand, earthquake provided a test case for evaluating the performance and near‐real‐time response applicability of three published global seismically inducAuthorsKate E. Allstadt, Randall W. Jibson, Eric M. Thompson, Chris Massey, David J. Wald, Jonathan W. Godt, Francis K. RengersSpatial and spectral interpolation of ground-motion intensity measure observations
Following a significant earthquake, ground‐motion observations are available for a limited set of locations and intensity measures (IMs). Typically, however, it is desirable to know the ground motions for additional IMs and at locations where observations are unavailable. Various interpolation methods are available, but because IMs or their logarithms are normally distributed, spatially correlatedAuthorsCharles Worden, Eric M. Thompson, Jack W. Baker, Brendon A. Bradley, Nicolas Luco, David J. WaldA flatfile of ground motion intensity measurements from induced earthquakes in Oklahoma and Kansas
We have produced a uniformly processed database of orientation-independent (RotD50, RotD100) ground motion intensity measurements containing peak horizontal ground motions (accelerations and velocities) and 5-percent-damped pseudospectral accelerations (0.1–10 s) from more than 3,800 M ≥ 3 earthquakes in Oklahoma and Kansas that occurred between January 2009 and December 2016. Ground motion time sAuthorsSteven B. Rennolet, Morgan P. Moschetti, Eric M. Thompson, William L. YeckAn open repository of earthquake-triggered ground-failure inventories
Earthquake-triggered ground failure, such as landsliding and liquefaction, can contribute significantly to losses, but our current ability to accurately include them in earthquake-hazard analyses is limited. The development of robust and widely applicable models requires access to numerous inventories of ground failures triggered by earthquakes that span a broad range of terrains, shaking characteAuthorsRobert G. Schmitt, Hakan Tanyas, M. Anna Nowicki Jessee, Jing Zhu, Katherine M. Biegel, Kate E. Allstadt, Randall W. Jibson, Eric M. Thompson, Cees J. van Westen, Hiroshi P. Sato, David J. Wald, Jonathan W. Godt, Tolga Gorum, Chong Xu, Ellen M. Rathje, Keith L. KnudsenEstimating rupture distances without a rupture
Most ground motion prediction equations (GMPEs) require distances that are defined relative to a rupture model, such as the distance to the surface projection of the rupture (RJB) or the closest distance to the rupture plane (RRUP). There are a number of situations in which GMPEs are used where it is either necessary or advantageous to derive rupture distances from point-source distance metrics, sAuthorsEric M. Thompson, Charles WordenNon-USGS Publications**
Thompson, E.M., Baise, L.G., Tanaka, Y. and Kayen, R.E., 2012. A taxonomy of site response complexity. Soil Dynamics and Earthquake Engineering, 41, pp.32-43.Boore, D.M. and Thompson, E.M., 2012. Empirical improvements for estimating earthquake response spectra with random‐vibration theory. Bulletin of the Seismological Society of America, 102(2), pp.761-772.Kaklamanos, J., Bradley, B.A., Thompson, E.M. and Baise, L.G., 2013. Critical parameters affecting bias and variability in site‐response analyses using KiK‐net downhole array data. Bulletin of the Seismological Society of America, 103(3), pp.1733-1749.Kaklamanos, J., Baise, L.G., Thompson, E.M. and Dorfmann, L., 2015. Comparison of 1D linear, equivalent-linear, and nonlinear site response models at six KiK-net validation sites. Soil Dynamics and Earthquake Engineering, 69, pp.207-219.Moss, R.E., Thompson, E.M., Kieffer, D.S., Tiwari, B., Hashash, Y.M., Acharya, I., Adhikari, B.R., Asimaki, D., Clahan, K.B., Collins, B.D. and Dahal, S., 2015. Geotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks. Seismological Research Letters, 86(6), pp.1514-1523.Thompson, E.M., Baise, L.G. and Vogel, R.M., 2007. A global index earthquake approach to probabilistic assessment of extremes. Journal of Geophysical Research: Solid Earth, 112(B6).Zhu, J., Daley, D., Baise, L.G., Thompson, E.M., Wald, D.J. and Knudsen, K.L., 2015. A geospatial liquefaction model for rapid response and loss estimation. Earthquake Spectra, 31(3), pp.1813-1837.Thompson, E.M., Hewlett, J.B., Baise, L.G. and Vogel, R.M., 2011. The Gumbel hypothesis test for left censored observations using regional earthquake records as an example. Natural Hazards and Earth System Sciences, 11(1), pp.115-126.Baise, L.G., Lenz, J.A. and Thompson, E.M., 2008. Discussion of “Mapping liquefaction potential considering spatial correlations of CPT measurements” by Chia-Nan Liu and Chien-Hsun Chen. Journal of geotechnical and geoenvironmental engineering, 134(2), pp.262-263.**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
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