Search USGSSearch

USGS · 70047334

Do aftershock probabilities decay with time?

Abstract

So, do aftershock probabilities decay with time? Consider a thought experiment in which we are at the time of the mainshock and ask how many aftershocks will occur a day, week, month, year, or even a century from now. First we must decide how large a window to use around each point in time. Let's assume that, as we go further into the future, we are asking a less precise question. Perhaps a day from now means 1 day 10% of a day, a week from now means 1 week 10% of a week, and so on. If we ignore c because it is a small fraction of a day (e.g., Reasenberg and Jones, 1989, hereafter RJ89), and set p = 1 because it is usually close to 1 (its value in the original Omori law), then the rate of earthquakes (K=t) decays at 1=t. If the length of the windows being considered increases proportionally to t, then the number of earthquakes at any time from now is the same because the rate decrease is canceled by the increase in the window duration. Under these conditions we should never think "It's a bit late for this to be an aftershock."

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Andrew J. Michael. 2012-07-26. Do aftershock probabilities decay with time?. https://doi.org/10.1785/0220120061

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

KEEP EXPLORING

Related USGS reports

Digitizer Suite: The Albuquerque Seismological Laboratory Digitizer Testing Suite

Laboratory testing of digitizers and seismometers helps ensure that prior to deployment the instrumentation can produce high quality data and is operating within specifications. In this work we detail the software package called: the Albuquerque Seismological Laboratory (ASL) Digitizer Test Suite. This Java software package provides several algorithms to verify various performance parameters of digitizers commonly used for recording analog seismic instruments. The goal of these tests is not to be exhaustive, but to identify common failures that could compromise the integrity of seismic data being recorded on the digitizer. For example, Sandia National Laboratories (e.g., Slad and Merchant, 2018) routinely do comprehensive testing of digitizers for various monitoring missions. While these tests reports are valuable for comprehensively characterizing a recording system, it would be resource intensive to conduct such tests on every seismic recorder used in a network. We focus on tests that include ways to estimate the sensitivity, timing, self-noise, and clip-level of the digitizer, as well as the fidelity of the signal being recorded. The software is publicly available and provides a way for the community to verify the integrity of a digitizer using a minimum amount of outside equipment.

Seismological Research Letters

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters