Abstract
A large magnitude 7.8 earthquakes occurred in Ecuador at 23:58:36 Coordinated Universal Time (UTC) on April 16, 2016. In this paper, we revisit this earthquake by simultaneously analyzing the magnetic field data of Swarm satellite A and satellite C based on principal component analysis (PCA), and the eigenvalues and principal components are calculated throughout 2016. We find that the first principal component mainly contains the signal originating from solar-terrestrial effects such as geomagnetic activity since the first eigenvalue and the geomagnetic index are highly correlated. Therefore, the second principal component is used to extract the anomalies associated with the Ecuador earthquake in terms of skewness and kurtosis. The anomalous tracks of the S-K (Skewness-Kurtosis) coefficient are accumulated from 90 days before the event to 30 days after. The cumulative number follows an accelerating power-law behavior before the earthquake and decelerating recovery behavior after the earthquake; moreover, the inflection point of the sigmoidal fitting curve is close to the time of the earthquake. The cumulative number of anomalous tracks in the random regions shows a linear increase, further verifying the correlation between anomalies extracted and the Ecuador earthquake. This phenomenon could be related to the preparation phase and the aftershock phase of the Ecuador earthquake.
Highlights
Short-term earthquake prediction is one of the most challenging issues in the world
We calculate an S-K coefficient of the second PC based on skewness and kurtosis to extract the anomalies associated with the 2016 M7.8 Ecuador earthquake, and the accumulation of anomalous tracks is calculated over time to study the preparation phase and aftershock phase of the earthquake
This paper attempts to use the advantages of Swarm satellite constellation monitoring to simultaneously analyze the magnetic field data of Swarm A and C satellites to extract the anomalies associated with the Ecuador earthquake
Summary
Short-term earthquake prediction is one of the most challenging issues in the world. Electromagnetic disturbances associated with earthquakes were discussed a few decades ago [1]–[3] and are probably the most promising candidates as possible precursor signals. Based on the high-precision magnetic field of the Swarm satellites, ionospheric anomalies that occur before earthquakes have been studied. Studies on the magnetic field in the ULF-band recorded by the Swarm satellites before the 2015 Nepal earthquake further demonstrate the possible coupling between the lithosphere and the ionosphere [33]. For ground-based stations, PCA (principal component analysis) has been applied to ULF magnetic field data from three stations to separate signals generated by different sources and extract the main anomalous features of an earthquake [36]. We calculate an S-K coefficient of the second PC (principal component) based on skewness and kurtosis to extract the anomalies associated with the 2016 M7.8 Ecuador earthquake, and the accumulation of anomalous tracks is calculated over time to study the preparation phase and aftershock phase of the earthquake. We determine the correlation between the extraction anomalies and the earthquake by comparing the cumulative number of anomalous tracks in the random regions with that in the actual seismic region
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