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He, Xiaodan
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- PublicationOpen AccessAnalysis of Swarm Satellite Magnetic Field Data for the 2015 Mw 7.8 Nepal Earthquake Based on Nonnegative Tensor Decomposition(2022-08-04)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; A nonnegative tensor decomposition (NTD) approach has been developed to analyze the ionospheric magnetic field data of the Swarm Alpha and Charlie satellites for the Mw7.8 2015 Nepal earthquake. All available satellite data were analyzed regardless of geomagnetic activity. We used the amplitude time–frequency spectra of the two-satellite data to build third-order tensors and decomposed them into three components. One of these components seems to be more affected by seismicity. In particular, the cumulative number of anomalous tracks of this component displays accelerated growth that conforms to a sigmoid fit from 60 to 40 days before the mainshock. Subsequently, until ten days before the earthquake, it shows a weak accelerating trend that obeys a power-law behavior and then resumes linear growth after the mainshock. Moreover, the cumulative anomaly was indicated not to be caused by geomagnetic activity, solar activity, or other nonseismic factors. An investigation of the foreshocks around the epicenter reveals that the cumulative Benioff strain also exhibited two accelerated growths before the mainshock, which is consistent with the cumulative result of ionospheric anomalies. In the first acceleration stage, seismicity appeared in the region surrounding the epicenter, and most of the ionospheric anomalies were offset away from the epicenter. During the second acceleration stage, some foreshocks occurred closer to or on the mainshock fault, and ionospheric anomalies also appeared near two faults around the epicenter. Furthermore, the correspondence between the ionospheric anomalies and the anomalies in different geolayers can be explained by the lithosphere–atmosphere–ionosphere coupling model.136 89 - PublicationOpen AccessEvaluation of Pre-Earthquake Anomalies of Borehole Strain Network by Using Receiver Operating Characteristic Curve(2021-02-01)
; ; ; ; ; ; ; ; ; ; ; ; ; In order to monitor temporal and spatial crustal activities associated with earthquakes, ground- and satellite-based monitoring systems have been installed in China since the 1990s. In recent years, the correlation between monitoring strain anomalies and local major earthquakes has been verified. In this study, we further evaluate the possibility of strain anomalies containing earthquake precursors by using Receiver Operating Characteristic (ROC) prediction. First, strain network anomalies were extracted in the borehole strain data recorded in Western China during 2010–2017. Then, we proposed a new prediction strategy characterized by the number of network anomalies in an anomaly window, Nano, and the length of alarm window, Talm. We assumed that clusters of network anomalies indicate a probability increase of an impending earthquake, and consequently, the alarm window would be the duration during which a possible earthquake would occur. The Area Under the ROC Curve (AUC) between true predicted rate, tpr, and false alarm rate, fpr, is measured to evaluate the efficiency of the prediction strategies. We found that the optimal strategy of short-term forecasts was established by setting the number of anomalies greater than 7 within 14 days and the alarm window at one day. The results further show the prediction strategy performs significantly better when there are frequent enhanced network anomalies prior to the larger earthquakes surrounding the strain network region. The ROC detection indicates that strain data possibly contain the precursory information associated with major earthquakes and highlights the potential for short-term earthquake forecasting.66 36 - PublicationOpen AccessAnalysis of Swarm Satellite Magnetic Field Data Before the 2016 Ecuador (Mw = 7.8) Earthquake Based on Non-negative Matrix Factorization(2021-04-15)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; 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.128 90 - PublicationOpen AccessWorldwide Statistical Correlation of Eight Years of Swarm Satellite Data with M5.5+ Earthquakes: New Hints about the Preseismic Phenomena from Space(2022)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ;; ; ; ;; ; ; ; ; ; ; ; ; ; ; ;Nowadays, the possibility that medium-large earthquakes could produce some electromagnetic ionospheric disturbances during their preparatory phase is controversial in the scientific community. Some previous works using satellite data from DEMETER, Swarm and, recently, CSES provided several pieces of evidence supporting the existence of such precursory phenomena in terms of single case studies and statical analyses. In this work, we applied a Worldwide Statistical Correlation approach to M5.5+ shallow earthquakes using the first 8 years of Swarm (i.e., from November 2013 to November 2021) magnetic field and electron density signals in order to improve the significance of previous statistical studies and provide some new results on how earthquake features could influence ionospheric electromagnetic disturbances. We implemented new methodologies based on the hypothesis that the anticipation time of anomalies of larger earthquakes is usually longer than that of anomalies of smaller magnitude. We also considered the signal’s frequency to introduce a new identification criterion for the anomalies. We find that taking into account the frequency can improve the statistical significance (up to 25% for magnetic data and up to 100% for electron density). Furthermore, we noted that the frequency of the Swarm magnetic field signal of possible precursor anomalies seems to slightly increase as the earthquake is approaching. Finally, we checked a possible relationship between the frequency of the detected anomalies and earthquake features. The earthquake focal mechanism seems to have a low or null influence on the frequency of the detected anomalies, while the epicenter location appears to play an important role. In fact, land earthquakes are more likely to be preceded by slower (lower frequency) magnetic field signals, whereas sea seismic events show a higher probability of being preceded by faster (higher frequency) magnetic field signals.184 60