A Multiparametric Approach to Study the Preparation Phase of the 2019 M7.1 Ridgecrest (California, United States) Earthquake

Santis, Angelo De; Cianchini, Gianfranco; Marchetti, Dedalo; Piscini, Alessandro; Sabbagh, Dario; Perrone, Loredana; Campuzano, Saioa A.; İnan, Sedat

doi:10.3389/feart.2020.540398

Cited by 49 publications

(24 citation statements)

References 48 publications

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“…Combined with the anomalies results of De Santis et al. (2020), it can be concluded that the anomalies may be attributed to LAIC during the preparation period of the Ridgecrest earthquakes.…”

Section: Discussionsupporting

confidence: 55%

Detecting Seismo‐Ionospheric Anomalies Possibly Associated With the 2019 Ridgecrest (California) Earthquakes by GNSS, CSES, and Swarm Observations

Xie

Chen

et al. 2021

JGR Space Physics

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The association between earthquakes and ionospheric precursors has been widely reported in previous studies. The Swarm satellite constellation, the China Seismo‐Electromagnetic Satellite (CSES), and the ground‐based global navigation satellite system (GNSS) observations provide us new opportunities to detect ionospheric precursors to earthquakes for a better understanding of the seismic‐ionospheric coupling. In California, two shallow earthquakes with magnitudes of 6.5 and 7.1, the two higher magnitude events of the Ridgecrest earthquakes sequence, occurred on July 4 and July 6, 2019, respectively. This study adopted total electron content (TEC) data from the GNSS, and electron density (Ne), and electron temperature (Te) data from the CSES and Swarm to study the possible ionospheric perturbations before the Ridgecrest earthquakes. A sliding interquartile range method was used to analyze the TEC data, and a spatial differential method and a revisit trajectory comparison were used to analyze the Ne and Te data. While excluding the influences of various factors including solar and geomagnetic activities, planetary waves, tropospheric convection, and medium‐scale traveling ionospheric disturbances, the cross‐validation of the multi‐source data found that anomalies detected on June 20, June 22, and June 26–29, 2019 could be regarded as precursors of the Ridgecrest earthquakes. A spatial distribution analysis showed that the pre‐earthquake anomalies offset the equatorial direction. TEC anomalies were all positively correlated with the Ne anomalies, with most of them were positive. The Ne and Te anomalies were both positively and negatively correlated with mostly negative, while showing a strong linear negative correlation at nighttime.

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Section: Discussionsupporting

confidence: 55%

Detecting Seismo‐Ionospheric Anomalies Possibly Associated With the 2019 Ridgecrest (California) Earthquakes by GNSS, CSES, and Swarm Observations

Xie

Chen

et al. 2021

JGR Space Physics

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“…They have observed depletion in the cross-correlation coefficient in GPS-TEC one day before, OLR anomaly 19 days before, anomalies in ACP distribution 10 days before, and decrement in b value for the Kamchatka EQ on 20 March 2016. In De Santis et al [38], they have used four parameters, specifically skin temperature, methane, total column water vapor, and aerosol optical thickness. They observed positive increment in all of these chosen parameters before the California EQ on 5 July 2019.…”

Section: Introductionmentioning

confidence: 99%

Pre-Seismic Irregularities during the 2020 Samos (Greece) Earthquake (M = 6.9) as Investigated from Multi-Parameter Approach by Ground and Space-Based Techniques

et al. 2021

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We present a comprehensive analysis of pre-seismic anomalies as computed from the ground and space-based techniques during the recent Samos earthquake in Greece on 30 October 2020, with a magnitude M = 6.9. We proceed with a multi-parametric approach where pre-seismic irregularities are investigated in the stratosphere, ionosphere, and magnetosphere. We use the convenient methods of acoustics and electromagnetic channels of the Lithosphere–Atmosphere–Ionosphere-Coupling (LAIC) mechanism by investigating the Atmospheric Gravity Wave (AGW), magnetic field, electron density, Total Electron Content (TEC), and the energetic particle precipitation in the inner radiation belt. We incorporate two ground-based IGS GPS stations DYNG (Greece) and IZMI (Turkey) for computing the TEC and observed a significant enhancement in daily TEC variation around one week before the earthquake. For the space-based observation, we use multiple parameters as recorded from Low Earth Orbit (LEO) satellites. For the AGW, we use the SABER/TIMED satellite data and compute the potential energy of stratospheric AGW by using the atmospheric temperature profile. It is found that the maximum potential energy of such AGW is observed around six days before the earthquake. Similar AGW is also observed by the method of wavelet analysis in the fluctuation in TEC values. We observe significant energetic particle precipitation in the inner radiation belt over the earthquake epicenter due to the conventional concept of an ionospheric-magnetospheric coupling mechanism by using an NOAA satellite. We first eliminate the particle count rate (CR) due to possible geomagnetic storms and South Atlantic Anomaly (SAA) by the proper choice of magnetic field B values. After the removal of the statistical background CRs, we observe a significant enhancement of CR four and ten days before the mainshock. We use Swarm satellite outcomes to check the magnetic field and electron density profile over a region of earthquake preparation. We observe a significant enhancement in electron density one day before the earthquake. The parameters studied here show an overall pre-seismic anomaly from a duration of ten days to one day before the earthquake.

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“…For the same earthquake, De Santis et al [19] found a chain of Lithosphere-Atmosphere-Ionosphere anomalies even increasing in number toward the event. This work is complementary in the sense that the anomalies depicted in this paper covered the whole preparation phase investigated in De Santis et al [19], with some anomalies with long anticipation time (Figures 2 and 3) until an early anomaly before the earthquake (shown in Figure 1).…”

Section: Discussionmentioning

confidence: 96%

“…In this work, we focus our attention on the Ridgecrest earthquake that occurred on 6 July 2019 and the possible electromagnetic anomalies detected by Swarm satellites during the preparation phase of the earthquake. This represents an extension of a recent paper [19] that analysed different physical quantities in the lithosphere, atmosphere and ionosphere, but here we are focusing especially on the magnetic field data of the Swarm mission. This paper is structured as follows: the first section presents data and methods used; the following section shows the results.…”

Section: Introductionmentioning

confidence: 99%

Swarm Satellite Magnetic Field Data Analysis Prior to 2019 Mw = 7.1 Ridgecrest (California, USA) Earthquake

et al. 2020

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This work presents an analysis of the ESA Swarm satellite magnetic data preceding the Mw = 7.1 California Ridgecrest earthquake that occurred on 6 July 2019. In detail, we show the main results of a procedure that investigates the track-by-track residual of the magnetic field data acquired by the Swarm constellation from 1000 days before the event and inside the Dobrovolsky’s area. To exclude global geomagnetic perturbations, we select the data considering only quiet geomagnetic field time, defined by thresholds on Dst and ap geomagnetic indices, and we repeat the same analysis in two comparison areas at the same geomagnetic latitude of the Ridgecrest earthquake epicentre not affected by significant seismicity and in the same period here investigated. As the main result, we find some increases of the anomalies in the Y (East) component of the magnetic field starting from about 500 days before the earthquake. Comparing such anomalies with those in the validation areas, it seems that the geomagnetic activity over California from 222 to 168 days before the mainshock could be produced by the preparation phase of the seismic event. This anticipation time is compatible with the Rikitake empirical law, recently confirmed from Swarm satellite data. Furthermore, the Swarm Bravo satellite, i.e., that one at highest orbit, passed above the epicentral area 15 min before the earthquake and detected an anomaly mainly in the Y component. These analyses applied to the Ridgecrest earthquake not only intend to better understand the physical processes behind the preparation phase of the medium-large earthquakes in the world, but also demonstrate the usefulness of a satellite constellation to monitor the ionospheric activity and, in the future, to possibly make reliable earthquake forecasting.

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A Multiparametric Approach to Study the Preparation Phase of the 2019 M7.1 Ridgecrest (California, United States) Earthquake

Cited by 49 publications

References 48 publications

Detecting Seismo‐Ionospheric Anomalies Possibly Associated With the 2019 Ridgecrest (California) Earthquakes by GNSS, CSES, and Swarm Observations

Detecting Seismo‐Ionospheric Anomalies Possibly Associated With the 2019 Ridgecrest (California) Earthquakes by GNSS, CSES, and Swarm Observations

Pre-Seismic Irregularities during the 2020 Samos (Greece) Earthquake (M = 6.9) as Investigated from Multi-Parameter Approach by Ground and Space-Based Techniques

Swarm Satellite Magnetic Field Data Analysis Prior to 2019 Mw = 7.1 Ridgecrest (California, USA) Earthquake

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