Characterizing potential earthquake signals on the Stanford-USGS ultra-low frequency electromagnetic (ULFEM) array

Anomalous ultra-low frequency (0.01-10 Hz) electromagnetic signals have been reported prior to and during M ≥ 6.0 earthquakes in a variety of places around the world, most notably prior to the 1989 Ms 7.1 Loma Prieta earthquake in California. Stanford University, in conjunction with the USGS and UC Berkeley, has maintained five ULFEM recording stations along the San Andreas Fault. We are searching our ULFEM data for anomalous signals before earthquakes. Previous reports of possible ULFEM precursors, or their absence following exhaustive searches of available data, define a crude distance-magnitude relationship with larger-closer earthquakes capable of producing detectable precursors. No earthquakes exceeding this distance-magnitude relationship have yet occurred within 500 km of our network; therefore our study is as yet mostly an attempt to develop appropriate methodologies. We examined 40 Hz EM data around the arrival time of the largest/closest earthquakes to our array, focusing on co-shaking signals and pulsations as have been described preceding the 10/31/2007 Alum Rock M 5.4 earthquake. For the three stations in the Bay Area, our search included data from when the BART electric train was operating and also dormant. We observed co-shaking signals at stations between 10-40 km from the epicenters of earthquakes with varying magnitudes (M 2.6-M 6.0). A search of data in the week prior to the Alum Rock earthquake on our closest station (41 km from the epicenter) has thus far identified pulsations of similar duration and polarity as those identified by other workers on a station 2 km from the epicenter (~9 km from the hypocenter). The amplitudes of the majority of the pulsations identified in this study are within several standard deviations of background noise levels and are otherwise not distinguishable from other signals of similar frequency in the time series. To establish and maintain the integrity of the data recorded from the stations in our array, a permanent calibration method is being designed and implemented. The calibration system is an air-core magnetic coil producing an AC magnetic field powered by an in-house built waveform generator.