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Earthquake Science Center

The Earthquake Science Center has been the flagship research center of the USGS in the western United States for more than 50 years. It is the largest USGS research center in the West and houses extensive laboratories, scientific infrastructure, and research facilities.

News

(Some) Assembly Required: How to sign your organization up for the Great ShakeOut

(Some) Assembly Required: How to sign your organization up for the Great ShakeOut

USGS seeking Loma Prieta felt reports from 35-year-old earthquake

USGS seeking Loma Prieta felt reports from 35-year-old earthquake

Loma Prieta Earthquake 35th Anniversary Compilation

Loma Prieta Earthquake 35th Anniversary Compilation

Publications

Evidence for low effective stress within the crust of the subducted Gorda plate from the 2022 December Mw 6.4 Ferndale earthquake sequence

Stress levels on and adjacent to megathrust faults at seismogenic depths remain a key but difficult to constrain parameter for assessing seismic hazard in subduction zones. Although strong ground motions have been observed to be generated from distinct, high-stress regions on the downdip end of the megathrust rupture areas in many great earthquakes, we lack direct constraints on the stress level i
Authors
Hao Guo, James W. Atterholt, Jeffrey J. McGuire, Clifford Thurber

Afterslip and creep in the rate-dependent framework: Joint inversion of borehole strain and GNSS displacements for the Mw 7.1 Ridgecrest earthquake

The elusive transition toward afterslip following an earthquake is challenging to capture with typical data resolution limits. A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub-nanostrain precision and sub-second sampling rate of BSMs bridges a gap between conventional seism
Authors
Catherine Hannagan, Richard Bennett, Andrew Barbour, Amanda N. Hughes

Cross-fade sampling: Extremely efficient Bayesian inversion for a variety of geophysical problems

This paper introduces cross-fade sampling, a computationally efficient Markov Chain Monte Carlo simulation method that uses a semi-analytical approach to quickly solve Bayesian inverse problems that do not themselves have an analytical solution. Cross-fading is efficient in two ways. First, it requires fewer samples to obtain the same quality simulation of the target probability density function (
Authors
Sarah E. Minson
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