A collection of research and insights from Stanford experts on where and how earthquakes happen, why prediction remains elusive, advances in detection and monitoring, links to human activities, how to prepare for "The Big One," and more.
Tiny movements in Earth’s outermost layer may provide a Rosetta Stone for deciphering the physics and warning signs of big quakes. New algorithms that work a little like human vision are now detecting these long-hidden microquakes in the growing mountain of seismic data.
Through the course of her career, Xyoli Pérez-Campos has worked to improve the lives of Mexico’s citizens and guide seismological research. Now, the geophysics PhD alumna is the public face of earthquake science and monitoring in Mexico.
NSF is forcing competition while mandating that a single contractor manage its two large facilities for studying Earth’s shape and vibration. This comes as a surprise, “but it’s not dire news. In a way, I kind of welcome it,” says Greg Beroza.
Scientists are training machine learning algorithms to help shed light on earthquake hazards, volcanic eruptions, groundwater flow and longstanding mysteries about what goes on beneath the Earth’s surface.
The 2018 Geophysical Journal International Student Author Award has been awarded to Karianne Bergen, PhD '18, for a paper co-authored with Greg Beroza detailing three new methods for detecting earthquakes.
New research shows manmade and naturally occurring earthquakes in the central U.S. share the same characteristics, information that will help scientists predict and mitigate damage from future earthquakes.
Greg Beroza says a "heroic amount of work" went into a new study that found that the Bay Area is somewhat more likely to get a series of serious quakes rather than one huge one. If that sounds like good news, it isn’t. Inside Science.