Precursory worldwide signatures of earthquake occurrences on Swarm satellite data

Abstract

The study of the preparation phase of large earthquakes is essential to understand the physical processes involved, and potentially useful also to develop a future reliable short-term warning system. Here we analyse electron density and magnetic field data measured by Swarm three-satellite constellation for 4.7 years, to look for possible in-situ ionospheric precursors of large earthquakes to study the interactions between the lithosphere and the above atmosphere and ionosphere, in what is called the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC). We define these anomalies statistically in the whole space-time interval of interest and use a Worldwide Statistical Correlation (WSC) analysis through a superposed epoch approach to study the possible relation with the earthquakes. We find some clear concentrations of electron density and magnetic anomalies from more than two months to some days before the earthquake occurrences. Such anomaly clustering is, in general, statistically significant with respect to homogeneous random simulations, supporting a LAIC during the preparation phase of earthquakes. By investigating different earthquake magnitude ranges, not only do we confirm the well-known Rikitake empirical law between ionospheric anomaly precursor time and earthquake magnitude, but we also give more reliability to the seismic source origin for many of the identified anomalies.

Ionosonde Data Analysis in Relation to the 2016 Central Italian Earthquakes

“…The adoption of this kind of relationship between ∆T and M comes from ground observations of various geophysical parameters for a number of EQs with M = 4-8 [54] and resulted in the following dependence: log(∆T•R) = 0.72M − 0.72. Liu et al [21] and Korsunova and Khegai [41,42] also use this type of dependence, and a similar dependence is the Rikitake [55] empirical law between precursor time and EQ magnitude, recently confirmed for ionospheric precursors [31]. It should be noted that De Santis et al [31] also provide a reasonable physical explanation for the Rikitake law [55], which in turn provides the order of magnitude of precursors lead time.…”

“…Pre-EQ ionospheric anomalies are defined as middle-term precursors when they occur up to 1-2 months in advance, while those with lead times from some hours up to 1 day are defined as short-term precursors [14]. Ionospheric parameters like critical frequency of the ionospheric F2-layer (foF2), electron temperature (T e ) at F2-region heights, total electron content (TEC), electron density (N e ) at satellite heights (~460-510 km), as well as magnetic pulsations and low-frequency radio signals are investigated for these purposes [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31].…”

Analysis of Swarm Satellite Magnetic Field Data Before the 2016 Ecuador (Mw = 7.8) Earthquake Based on Non-negative Matrix Factorization

“…The magnetic field data of Swarm satellites are widely used in fields, such as studying the ionospheric current systems (Alken, 2016) and the magnetic storms (Wang et al, 2019), and constructing the magnetic field models (Finlay et al, 2015(Finlay et al, , 2016. Beyond this, the high-precision magnetic field data are also applied to study the ionosphere anomalies, which are possibly related to earthquakes (De Santis et al, 2019b;Marchetti et al, 2019a). After the launch of the Swarm satellites at the end of 2013, some large earthquakes occurred.…”

“…Akhoondzadeh et al (2019) used the magnetic field data collected under quiet geomagnetic conditions to study the 2017 Sarpole Zahab (Mw = 7.3) earthquake and observed ionospheric magnetic anomalies between 8 and 11 days prior to the occurrence of the event. De used the Swarm satellite magnetic field data with |Dst| ≤ 20 nT and a p ≤ 10 nT to study 12 earthquakes with magnitudes from 6.1 to 8.3, and they observed some ionospheric magnetic field anomalies before most of the events (Yan et al, 2013;Marchetti and Akhoondzadeh, 2018;De Santis et al, 2019b;Marchetti et al, 2019a,b). Hattori et al (2004) applied the principal component analysis to decompose the magnetic field data of three ground-based stations (including the data under strong geomagnetic activity).…”

Kinetic Simulation of Segmented Plasma Flow Meter Response in the Ionospheric Plasma

“…Post seismic acoustic and gravity waves have been observed with satellites in low Earth orbit (LEO), and their connection with solid Earth phenomena is well understood from theory and computer simulations (Davies & Archambeau, 1998;Krasnov & Drobzheva, 2005;Rudenko & Uralov, 1995;Yang et al, 2012). Direct observations and statistical analyses have also been reported to support the occurrence of electromagnetic wave signatures prior to large earthquakes (De Santis et al, 2019;Parrot, 2012;Parrot et al, 2006;Ryu et al, 2014;Shen et al, 2018). While not yet demonstrated, the possibility of observing ionospheric perturbations prior to large earthquakes remains a topic of vital interest, especially in countries located in seismically active parts of the planet (ibid).…”