Abstract
In this paper, based on non-negative matrix factorization (NMF), we analyzed the ionosphere magnetic field data of the Swarm Alpha satellite before the 2016 (Mw = 7. 8) Ecuador earthquake (April 16, 0.35°N, 79.93°W), including the whole data collected under quiet and disturbed geomagnetic conditions. The data from each track were decomposed into basis features and their corresponding weights. We found that the energy and entropy of one of the weight components were more concentrated inside the earthquake-sensitive area, which meant that this weight component was more likely to reflect the activity inside the earthquake-sensitive area. We focused on this weight component and used five times the root mean square (RMS) to extract the anomalies. We found that for this weight component, the cumulative number of tracks, which had anomalies inside the earthquake-sensitive area, showed accelerated growth before the Ecuador earthquake and recovered to linear growth after the earthquake. To verify that the accelerated cumulative anomaly was possibly associated with the earthquake, we excluded the influence of the geomagnetic activity and plasma bubble. Through the random earthquake study and low-seismicity period study, we found that the accelerated cumulative anomaly was not obtained by chance. Moreover, we observed that the cumulative Benioff strain S, which reflected the lithosphere activity, had acceleration behavior similar to the accelerated cumulative anomaly of the ionosphere magnetic field, which suggested that the anomaly that we obtained was possibly associated with the Ecuador earthquake and could be described by one of the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) models.
Highlights
Earthquakes are the most energetic phenomena in the lithosphere and on the Earth (Bolt, 1999)
We found that the accelerated cumulative anomaly of Hs1 component is similar to the results of the other two studies on the Ecuador earthquake, which used the magnetic field data of the Swarm satellites but excluded the influences of the geomagnetic activity
We suggest that our paper promotes the development from the search of anomalies that are likely to be related to earthquakes at the quiet geomagnetic conditions to the search of the anomalies that are likely to be related to earthquakes without considering the geomagnetic activity
Summary
Earthquakes are the most energetic phenomena in the lithosphere and on the Earth (Bolt, 1999). Based on the advantage of NMF that could obtain local features from the overall data, in this paper, we used the NMF to analyze the ionosphere magnetic field data of Swarm Alpha satellite, including the data collected under quiet geomagnetic conditions and those under strong geomagnetic conditions, to explore the 2016 Ecuador earthquake (April 16, 0.35◦N, 79.93◦W). When α remains small enough, the reconstruction error does not increase during an iteration step, and very satisfactory results are obtained To optimize this function, we used an efficient multiplicative update algorithm introduced by Lee and Seung (2000); the iterative updated rules of basis matrix, W and weight matrix, H are shown in Equations (3) and (4). Some of these anomalies could have local features, and through NMF, we can potentially obtain the components which represent the anomalies possibly related to the earthquake
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