Search USGS⌕ Search

USGS · 70015786

Stochastic summation of empirical Green's functions

Abstract

Two simple strategies are presented that use random delay times for repeatedly summing the record of a relatively small earthquake to simulate the effects of a larger earthquake. The simulations do not assume any fault plane geometry or rupture dynamics, but realy only on the ω−2 spectral model of an earthquake source and elementary notions of source complexity. The strategies simulate ground motions for all frequencies within the bandwidth of the record of the event used as a summand. The first strategy, which introduces the basic ideas, is a single-stage procedure that consists of simply adding many small events with random time delays. The probability distribution for delays has the property that its amplitude spectrum is determined by the ratio of ω−2 spectra, and its phase spectrum is identically zero. A simple expression is given for the computation of this zero-phase scaling distribution. The moment rate function resulting from the single-stage simulation is quite simple and hence is probably not realistic for high-frequency (>1 Hz) ground motion of events larger than ML ∼ 4.5 to 5. The second strategy is a two-stage summation that simulates source complexity with a few random subevent delays determined using the zero-phase scaling distribution, and then clusters energy around these delays to get an ω−2 spectrum for the sum. Thus, the two-stage strategy allows simulations of complex events of any size for which the ω−2 spectral model applies. Interestingly, a single-stage simulation with too few ω−2 records to get a good fit to an ω−2 large-event target spectrum yields a record whose spectral asymptotes are consistent with the ω−2 model, but that includes a region in its spectrum between the corner frequencies of the larger and smaller events reasonably approximated by a power law trend. This spectral feature has also been discussed as reflecting the process of partial stress release (Brune, 1970), an asperity failure (Boatwright, 1984), or the breakdown of ω−2 scaling due to rupture significantly longer than the width of the seismogenic zone (Joyner, 1984).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Leif Wennerberg. 1990. Stochastic summation of empirical Green's functions. https://doi.org/10.1785/bssa08006a1418

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Re-evaluation of shaking, dynamic strain, and the source of the 1886 Charleston, South Carolina, earthquake

As the largest historical event in the eastern United States, the 1886 Charleston, South Carolina, earthquake, plays a prominent role in our nation’s seismological and human history and an outsized role in our probabilistic ground‐motion hazard estimates, affecting building codes, insurance rates, and geophysical monitoring. Thus, constraining the characteristics of the 1886 earthquake source, as well as the nature of its shaking distribution and impacts to the extent possible, is essential. Given its vintage, however, societal, geological, and geophysical datasets are limited compared with those used in modern seismological analyses. Because of these limitations, some characteristics of the rupture model are fundamentally nonunique. Still, by re‐evaluating all available data, I can constrain several key aspects of this earthquake. I show that several interpretations in recent analyses are inconsistent regarding the inferred source; shaking; ground failure; and, particularly, railway impacts. Importantly, I have shown that although dynamic strain caused the ground failure that led to track deformation, without the intermediate liquefaction step, dynamic strain alone was unlikely to be the source of rail deformation, contrary to earlier studies. Had earlier pronouncements that dynamic strain is a real concern for bending railways held true, there would be serious ramifications for railway engineering as well as for other above‐ and below‐ground linear infrastructure.

South Carolina↗

ETAS-positive: Extracting unbiased epidemic-type aftershock models from incomplete earthquake catalogs

Earthquake catalogs are inherently incomplete, and short-term fluctuations in catalog completeness can strongly bias estimates of seismicity parameters. Here, we extend the positive statistics framework recently introduced for estimating Gutenberg–Richter a and b values to the Epidemic-Type Aftershock Sequence (ETAS) model. The approach focuses on complete magnitude–time intervals defined by pairs of earthquakes in which the second event is larger than the first. Comprehensive synthetic tests demonstrate that the proposed ETAS + method retrieves nearly unbiased parameter estimates even from highly incomplete catalogs, whereas parameters obtained using classical estimation approaches are strongly biased. Application to Southern California reveals a similar trend, with the productivity scaling parameter α approaching the b value, consistent with self-similar earthquake triggering within estimation uncertainties. Owing to its robustness against catalog incompleteness and computational efficiency, the ETAS + method provides a powerful new tool for seismicity analysis and earthquake forecasting.

California↗