Statistical Analysis of Pre‐earthquake Electromagnetic Anomalies in the ULF Range

• Published in: Journal of geophysical research. Space physics 2020-10, Vol.125 (10), p.n/a
• Main Authors: Warden, Sheldon, MacLean, Laura, Lemon, Jim, Schneider, Dan
• Format: Article
• Language: English
• Subjects: Anomalies; Data analysis; earthquake precursors; Earthquake prediction; Earthquakes; Extremely low frequencies; Frequencies; geomagnetic field; Geomagnetism; Observatories; Outliers (statistics); Rejection; Seismic activity; short‐term earthquake prediction; Statistical analysis; superposed epoch analysis (SEA); ULF; wavelet transform analysis; Windows (intervals)
• ISSN: 2169-9380; 2169-9402
• DOI: 10.1029/2020JA027955

Assessing the statistical significance of electromagnetic anomalies in the ultralow frequency (ULF) range observed prior to earthquakes is a necessary step toward determining whether these perturbations constitute actual earthquake precursors. A statistical epoch analysis (SEA) was recently performed by Han et al. (2014, https://doi.org/10.1002/2014JA019789) to analyze earthquakes happening between 2001 and 2010 near the geomagnetic observatory of Kakioka, Japan; the authors found a significant number of anomalies 6 to 15 days prior to the earthquake day within 100 km from Kakioka, while no significant pre‐earthquake activity was observed for the farther region 100 to 216 km from the observatory. In this current paper, we describe the application of our independent software implementation of their method. Despite using a different outlier rejection scheme, we manage to approximate their results. Upon validation of our program, we conduct multiple sensitivity studies. First, we explore how different outlier rejection schemes impact the results. We then restrict the analysis to only mantle earthquakes, highlighting a marginally significant number of anomalies prior to the earthquake day. Next, we test a higher band‐pass filter than the one initially used but find no anomalous pre‐earthquake activity in this higher‐frequency band. We then use a different catalog to establish the list of qualifying “earthquake days” which also leads the anomalous pre‐earthquake episode to vanish, thus raising concerns about the robustness of the results. Finally, we apply the SEA to another time window, ranging from 2013 to 2018: No significant pre‐earthquake episode can be observed for this interval. We conclude our study by providing guidelines for upcoming work. Key Points We reproduce the results of Han et al. (2014), introducing an algorithm aiming to assess the significance of prequake magnetic signals We show the sensitivity of this method to the choice of outlier rejection scheme, hypocentral depth, frequency band, and earthquake catalog This method does not highlight precursory activity when applied to an interval (2013–2018) newer than the one initially used (2001–2010)