Science Alert October 10, 2022
Magnetic field changes as earthquake precursors have been the subject of numerous studies and some controversy. Infrequent large earthquakes and sparse magnetometer coverage along fault zones complicate statistical analysis. A team of researchers in the US (Google Research, industry) analyzed ground-based magnetic time-series measurements before 19 earthquakes in California drawing from over 330,000 site-days of measurement spanning a decade. They applied a pre-specified statistical analysis with two key ideas – combining signals from nearby sites via spectral cross-power, and then looking for large spikes in frequency domain 0.016–25 Hz. They used the machine learning concept of rigorously separated train and test sets of earthquakes which were generated via a rule-based query of the USGS earthquake catalog. They trained a model based on Linear Discriminant Analysis and applied the discriminator to the test set revealing a modest effect in the days leading up to an earthquake. According to the researchers while the observed effect size was not directly useful for earthquake prediction, it suggests a relationship which should be further investigated for a physical link… read more. Open Access TECHNICAL ARTICLE
Overview of computational pipeline, fully described in Sections 3 and 4. Credit: JGR Solid Earth, Volume127, Issue10, October 2022, e2022JB024109