Eric Geist
Eric Geist is a research geophysicist with the USGS in Moffett Field, California, where he has worked for over three decades. Throughout his career, he has focused on computer modeling of geophysical phenomena, including large-scale deformation of the earth in response to tectonic forces and the physics of tsunami generation.
For over a decade now, Eric's research has focused on improving our ability to forecast tsunamis and their sources. Eric has authored over 120 journal articles and abstracts, including an article in Scientific American on the devastating 2004 Indian Ocean tsunami and several review papers on tsunamis.
Research Statement
Natural hazards are the product of complex physical systems. Eric’s research currently focuses on the new field of earthquake combinatorics. This research examines combinations and arrangements of earthquakes on faults to explain a variety of geophysical and geological datasets. Tackling the size of combinatorial problems for fault-scale systems has only recently been made possible through advances in applied mathematics and computer science over the last decade. With newly developed computer algorithms, earthquake combinatorics provides an avenue to investigate earthquake hazards for both offshore and onshore faults.
Eric also investigates the interplay between nonlinear dynamics and a probabilistic description of geophysical processes, particularly as applied to natural hazards and their sources. Recent developments in statistical physics provide many avenues for understanding natural hazards, including how source sizes and outcomes are distributed and how individual natural hazard events occur through time. In addition, stochastic models provide a way to quantify uncertainty associated with source processes as applied to hazard assessments. A natural product of this research is development of new probabilistic methods to forecast natural hazards.
Eric has also examined nonlinear processes associated with long-term and large-scale deformation of the Earth’s lithosphere. Specific projects have included understanding the seismotectonics of island arcs and determining the state of stress and slip rates along major plate-boundary fault systems.
Research Management
2012 – 2017: Co-Leader of Marine Geohazards Project, USGS
2005 – 2012: Co-Leader of Caribbean Tsunami Hazards Project, USGS
2004 – 2007: Co-Leader of FEMA Probabilistic Tsunami Pilot Study: Seaside, Oregon
1998 – 2004: Leader of Modeling and Probabilistic Analysis of Coastal Change Hazards Project, USGS
1989 – 1994: Leader of Geodynamic Modeling of Island Arcs Project, USGS
Professional Experience
1992 – Present: Research Geophysicist, U.S. Geological Survey, Menlo Park, CA
1986 – 1991: Operational Geophysicist, U.S. Geological Survey, Menlo Park, CA
1985 – 1986: Physical Science Technician, U.S. Geological Survey, Menlo Park, CA
Education and Certifications
1985 - M.Sc. in Geophysics, Stanford University
1983 – B.Sc. in Geophysical Engineering, Colorado School of Mines
Honors and Awards
2002, 2011, 2018: American Geophysical Union, Editor’s Citation for Excellence in Refereeing
2005: USGS Western Region, Communicator of the Year Award (co-honoree)
1994: Department of the Interior Superior Service Award
1994: Fellow, Geological Society of America
Science and Products
Source characterization and tsunami modeling of submarine landslides along the Yucatán Shelf/Campeche Escarpment, southern Gulf of Mexico
Reconstruction of far-field tsunami amplitude distributions from earthquake sources
A submarine landslide source for the devastating 1964 Chenega tsunami, southern Alaska
Non-linear resonant coupling of tsunami edge waves using stochastic earthquake source models
Dynamic models of an earthquake and tsunami offshore Ventura, California
Great (≥Mw8.0) megathrust earthquakes and the subduction of excess sediment and bathymetrically smooth seafloor
Tsunamis: stochastic models of occurrence and generation mechanisms
Assessment of tsunami hazard to the U.S. Atlantic margin
A framework for the probabilistic analysis of meteotsunamis
Source processes for the probabilistic assessment of tsunami hazards
Book review: Three great tsunamis: Lisbon (1755), Sumatra-Andaman (2004), and Japan (2011)
Undersampling power-law size distributions: effect on the assessment of extreme natural hazards
Science and Products
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Filter Total Items: 118
Source characterization and tsunami modeling of submarine landslides along the Yucatán Shelf/Campeche Escarpment, southern Gulf of Mexico
Submarine landslides occurring along the margins of the Gulf of Mexico (GOM) represent a low-likelihood, but potentially damaging source of tsunamis. New multibeam bathymetry coverage reveals that mass wasting is pervasive along the Yucatán Shelf edge with several large composite landslides possibly removing as much as 70 km3 of the Cenozoic sedimentary section in a single event. Using GIS-based aAuthorsJason D. Chaytor, Eric L. Geist, Charles K. Paull, David W Caress, Roberto Gwiazda, Jaime Urrutia Fucugauchi, Mario Rebolledo VieyraReconstruction of far-field tsunami amplitude distributions from earthquake sources
The probability distribution of far-field tsunami amplitudes is explained in relation to the distribution of seismic moment at subduction zones. Tsunami amplitude distributions at tide gauge stations follow a similar functional form, well described by a tapered Pareto distribution that is parameterized by a power-law exponent and a corner amplitude. Distribution parameters are first established foAuthorsEric L. Geist, Thomas E. ParsonsA submarine landslide source for the devastating 1964 Chenega tsunami, southern Alaska
During the 1964 Great Alaska earthquake (Mw 9.2), several fjords, straits, and bays throughout southern Alaska experienced significant tsunami runup of localized, but unexplained origin. Dangerous Passage is a glacimarine fjord in western Prince William Sound, which experienced a tsunami that devastated the village of Chenega where 23 of 75 inhabitants were lost – the highest relative loss of aAuthorsDaniel S. Brothers, Peter J. Haeussler, Lee Liberty, David Finlayson, Eric L. Geist, Keith A. Labay, Michael ByerlyNon-linear resonant coupling of tsunami edge waves using stochastic earthquake source models
Non-linear resonant coupling of edge waves can occur with tsunamis generated by large-magnitude subduction zone earthquakes. Earthquake rupture zones that straddle beneath the coastline of continental margins are particularly efficient at generating tsunami edge waves. Using a stochastic model for earthquake slip, it is shown that a wide range of edge-wave modes and wavenumbers can be excited, depAuthorsEric L. GeistDynamic models of an earthquake and tsunami offshore Ventura, California
The Ventura basin in Southern California includes coastal dip-slip faults that can likely produce earthquakes of magnitude 7 or greater and significant local tsunamis. We construct a 3-D dynamic rupture model of an earthquake on the Pitas Point and Lower Red Mountain faults to model low-frequency ground motion and the resulting tsunami, with a goal of elucidating the seismic and tsunami hazard inAuthorsKenny J. Ryan, Eric L. Geist, Michael Barall, David D. OglesbyGreat (≥Mw8.0) megathrust earthquakes and the subduction of excess sediment and bathymetrically smooth seafloor
Using older and in part flawed data, Ruff (1989) suggested that thick sediment entering the subduction zone (SZ) smooths and strengthens the trench-parallel distribution of interplate coupling. This circumstance was conjectured to favor rupture continuation and the generation of high-magnitude (≥Mw8.0) interplate thrust (IPT) earthquakes. Using larger and more accurate compilations of sediment thiAuthorsDavid W. Scholl, Stephe H. Kirby, Roland E. von Huene, Holly F. Ryan, Ray E. Wells, Eric L. GeistTsunamis: stochastic models of occurrence and generation mechanisms
The devastating consequences of the 2004 Indian Ocean and 2011 Japan tsunamis have led to increased research into many different aspects of the tsunami phenomenon. In this entry, we review research related to the observed complexity and uncertainty associated with tsunami generation, propagation, and occurrence described and analyzed using a variety of stochastic methods. In each case, seismogenicAuthorsEric L. Geist, David D. OglesbyAssessment of tsunami hazard to the U.S. Atlantic margin
Tsunami hazard is a very low-probability, but potentially high-risk natural hazard, posing unique challenges to scientists and policy makers trying to mitigate its impacts. These challenges are illustrated in this assessment of tsunami hazard to the U.S. Atlantic margin. Seismic activity along the U.S. Atlantic margin in general is low, and confirmed paleo-tsunami deposits have not yet been found,AuthorsUri S. ten Brink, Jason Chaytor, Eric L. Geist, Daniel S. Brothers, Brian D. AndrewsA framework for the probabilistic analysis of meteotsunamis
A probabilistic technique is developed to assess the hazard from meteotsunamis. Meteotsunamis are unusual sea-level events, generated when the speed of an atmospheric pressure or wind disturbance is comparable to the phase speed of long waves in the ocean. A general aggregation equation is proposed for the probabilistic analysis, based on previous frameworks established for both tsunamis and stormAuthorsEric L. Geist, Uri S. ten Brink, Matthew D. GoveSource processes for the probabilistic assessment of tsunami hazards
The importance of tsunami hazard assessment has increased in recent years as a result of catastrophic consequences from events such as the 2004 Indian Ocean and 2011 Japan tsunamis. In particular, probabilistic tsunami hazard assessment (PTHA) methods have been emphasized to include all possible ways a tsunami could be generated. Owing to the scarcity of tsunami observations, a computational approAuthorsEric L. Geist, Patrick J. LynettBook review: Three great tsunamis: Lisbon (1755), Sumatra-Andaman (2004), and Japan (2011)
“Three Great Tsunamis: Lisbon (1755), Sumatra–Andaman (2004), and Japan (2011)” is published in Springer’s new series SpringerBriefs. According to Springer’s website, the SpringBriefs volumes are intended to provide “concise summaries of cutting-edge research and practical applications across a wide spectrum of fields”. Among the several categories considered for SpringerBriefs are in-depth case sAuthorsEric L. GeistUndersampling power-law size distributions: effect on the assessment of extreme natural hazards
The effect of undersampling on estimating the size of extreme natural hazards from historical data is examined. Tests using synthetic catalogs indicate that the tail of an empirical size distribution sampled from a pure Pareto probability distribution can range from having one-to-several unusually large events to appearing depleted, relative to the parent distribution. Both of these effects are arAuthorsEric L. Geist, Thomas E. Parsons - News