Under the Hood of the Earthquake Machine: Toward Predictive Modeling of the Seismic Cycle

<jats:title>Earthquake Model Shakedown</jats:title> <jats:p> The Parkfield segment of the San Andreas Fault in California experiences Magnitude 6.0 earthquakes at a surprisingly regular interval—roughly every 22 years. This area is one of the most well studied fault segments in the world, yet computational models often struggle to integrate the wealth of observational data with theoretical predictions. <jats:bold> Barbot <jats:italic>et al.</jats:italic> </jats:bold> (p. <jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="doi" page="707" related-article-type="in-this-issue" vol="336" xlink:href="10.1126/science.1218796">707</jats:related-article> ; see the Perspective by <jats:bold> <jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="doi" issue="6082" page="676" related-article-type="in-this-issue" vol="336" xlink:href="10.1126/science.1220946">Segall</jats:related-article> </jats:bold> ) constructed a dynamic model of a fault segment which, when integrated with previous observations, reproduces the behavior of the Parkfield segment over the entire earthquake cycle. Because the model is based on realistic fault physics, it not only explains the distribution of small earthquakes but also the recurrence interval of large earthquakes and the amount of geodetic strain accumulated postseismically. It also reveals how smaller earthquakes can influence this region's semiregular earthquake cycle. </jats:p>