An Enhanced Martingale Method for Detecting Seismic Precursors from Swarm Satellite Data

The detection of seismic activity precursor signs as part of an alarm system will provide opportunities for minimization of the social and economic impact seismic events such as earthquakes cause. It has long been theorized that the Earth's electromagnetic field could contain precursor signs before a seismic event with a growing body of empirical evidence. The ability to measure and monitor electromagnetic field activity has increased with each passing year as more sensors and methodologies emerge; missions such as Swarm have enabled researchers to access near-continuous observations of electromagnetic activity at second intervals allowing for more detailed and exciting studies. This poster presents an approach designed to detect precursor anomalies in electromagnetic field data from Swarm satellites and initial analysis results. This works towards developing a continuous and effective monitoring system of seismic activities based on the already deployed tools of Swarm available. We develop an enhanced form linear probabilistic model based on the martingale probability theories that allow for testing the null hypothesis to indicate abnormal changes in electromagnetic field activity. We test this enhanced approach in two experiments; firstly we perform a quantitative comparison on well-understood and popular datasets alongside the classic approach. We find that the enhanced version does not negatively affect the performance of the underlying theory and instead produces more accurate anomaly detections overall. Secondly, we use three case studies of seismic activity (namely earthquakes in Mexico, Greece, and Croatia) to assess our approach. For each case study, we use two grids (500x500km and 1000x1000km, respectively) centered on the epicenters of the earthquakes and find that our method could detect anomalous
phenomena in the electromagnetic data months ahead of the seismic activity when focused on these specific regions, thereby leading up to the study's seismic events.