Search Results (25)

This study investigates pre-seismic ionospheric anomalies preceding the 2023 Jishishan Ms6.2 earthquake using total electron content (TEC) data derived from BDS geostationary orbit (GEO) satellites. Multi-scale analysis integrating Butterworth filtering and wavelet transforms resolved TEC disturbances into three distinct frequency regimes: (1) high-frequency perturbations (0.56–3.33 mHz) showed localized disturbances (amplitude ≤ 4 TECU, range < 300 km), potentially associated with near-field acoustic waves from crustal stress adjustments; (2) mid-frequency signals (0.28–0.56 mHz) exhibited anisotropic propagation (>1200 km) with azimuth-dependent N-shaped waveforms, consistent with the characteristics of acoustic–gravity waves (AGWs); and (3) low-frequency components (0.18–0.28 mHz) demonstrated phase reversal and power-law amplitude attenuation, suggesting possible lithosphere–atmosphere–ionosphere (LAI) coupling oscillations. The stark contrast between near-field residuals and far-field weak fluctuations highlighted the dominance of large-scale atmospheric gravity waves over localized acoustic disturbances. Geometry-based velocity inversion revealed incoherent high-frequency dynamics (5–30 min) versus anisotropic mid/low-frequency traveling ionospheric disturbance (TID) propagation (30–90 min) at 175–270 m/s, aligning with theoretical AGW behavior. During concurrent G1-class geomagnetic storm activity, spatial attenuation gradients and velocity anisotropy appear primarily consistent with seismogenic sources, providing insights for precursor discrimination and contributing to understanding multi-scale coupling in seismo-ionospheric systems. Full article

Lightning-generated whistlers (LW) play a crucial role in understanding magnetosphere–ionosphere coupling mechanisms and, perhaps, identifying precursor signals of natural disasters, such as volcanic eruptions and earthquakes. Traditional frequency–time image recognition techniques require approximately 40 years to analyze seven years of observational data from the China Seismo-Electromagnetic Satellite (CSES), which fails to meet the requirements for practical implementation. To address this issue, a novel and highly efficient model for LW recognition is proposed, integrating speech processing technology with a parallel bidirectional Simple Recurrent Unit (SRU) neural network. The proposed model significantly outperforms traditional methods in computational efficiency, reducing the parameter count by 99% to 0.1 M and enhancing processing speed by 99%, achieving 20 ms per sample. Despite these improvements, the model maintains excellent performance metrics, including 93% precision, 88.7% recall, and 90.7% F1-score, which is a measure of predictive performance. As a result, the model can process seven years of data in just 33 days, marking a 442-fold increase in processing speed compared to conventional approaches. Full article

Driven by the scientific objective of geophysical field detection and natural hazard monitoring from space, China launched an electromagnetic satellite, which is known as the China Seismo-Electromagnetic Satellite (CSES-01), on 2 February 2018, into a circular sun-synchronous orbit with an altitude of about 507 km in the ionosphere. The CSES-01 has been in orbit for over 6 years, successfully exceeding its designed 5-year lifespan, and will continually operate as long as possible. A second identical successor (CSES-02) will be launched in December 2024 in the same orbit space. The ionosphere is a highly dynamic and complicated system, and it is necessary to comprehensively understand the electromagnetic environment and the physical effects caused by various disturbance sources. The motivation of this report is to introduce the typical electromagnetic waves, mainly in the ELF/VLF band (i.e., ~100 Hz to 25 kHz), recorded by the CSES-01 in order to call the international community for deep research on EM wave activities and geophysical sphere coupling mechanisms. The wave spectral properties and the wave propagation parameters of those typical EM wave activities in the upper ionosphere are demonstrated in this study based on wave vector analysis using the singular value decomposition (SVD) method. The analysis shows that those typical and common natural EM waves in the upper ionosphere mainly include the ionospheric hiss and proton whistlers in the ELF band (below 1 kHz), the quasiperiodic (QP) emissions, magnetospheric line radiations (MLR), the falling-tone lightning whistlers, and V-shaped streaks in the ELF/VLF band (below 20 kHz). The typical artificial EM waves in the ELF/VLF band, such as power line harmonic radiation (PLHR) and radio waves in the VLF band, are also well recorded in the ionosphere. Full article

This study presents the spatio–temporal evolution of the electric and magnetic fields recorded by the China Seismo–Electromagnetic Satellite (CSES) and the thermal infrared remote sensing data observed by the Chinese stationary meteorological satellites Feng Yun–2G (FY–2G) associated with the 2021 Mw7.3 Maduo earthquake. Specifically, we analyzed the power spectrum density (PSD) data of the electric field in the extremely low frequency (ELF) band, the geomagnetic east–west vector data, and the temperature of brightness blackbody (TBB) data to investigate the spatio–temporal evolution characteristics under quiet space weather conditions (Dst > −30 nT and Kp < 3). Results showed that (1) the TBB radiation began to increase notably along the northern fault of the epicenter ~1.5 months prior to the occurrence of the earthquake. It achieved its maximum intensity on 17 May, and the earthquake occurred as the anomalies decreased. (2) The PSD in the 371 Hz–500 Hz and 700 Hz–871 Hz bands exhibited anomaly perturbations near the epicenter and its magnetic conjugate area on May 17, with particularly notable perturbations observed in the latter. The anomaly perturbations began to occur ~1 month before the earthquake, and the earthquake occurred as the anomalies decreased. (3) Both the magnetic –east–west component vector data and the ion velocity Vx data exhibited anomaly perturbations near the epicenter and the magnetic conjugate area on 11 May and 16 May. (4) The anomaly perturbations in the thermal infrared TBB data, CSES electric field, and magnetic field data all occurred within a consistent perturbation time period and spatial proximity. We also conducted an investigation into the timing, location, and potential causes of the anomaly perturbations using the Vx ion velocity data with magnetic field –east–west component vector data, as well as the horizontal –north–south and vertical component PSD data of the electric field with the magnetic field –east–west component vector data. There may be both chemical and electromagnetic wave propagation models for the “lithosphere—atmosphere—ionosphere” coupling (LAIC) mechanism of the Maduo earthquake. Full article

A recent study the detection of coseismic ionospheric disturbances or ionoquakes less than 400 s from the earthquake’s onset. The study also associates these rapid ionoquakes with the seismo-atmosphere–ionosphere (SAI) coupling mechanism energized by acoustic-gravity waves (AGWs) and the subsequent formation of coseismic thermospheric disturbances (CSTDs). The present study outlines a new analytical simulation code for AGWs that resolves the governing equations in the time–altitude and wavenumber domain and confirms the rapid arrival of AGWs in the thermosphere (earlier than the estimated arrival time from the ray-tracing simulation). The rapid arrivals of AGWs are associated with long wavelengths that connect to thermospheric altitudes and propagate with thermospheric sound speeds, avoiding averaging effects from the lower atmosphere. The fast simulation traces the rapid arrival of AGWs in the thermosphere and produces rapid CSTDs within 250–300 s from the earthquake’s onset. The simulation time is much shorter than the formation time of near-field CSTDs, a scenario favorable for the forecasting of CSTDs before observations of ionoquakes. In essence, the fast simulation offers an alternative tool for tracking the evolution of CSTDs. Full article

On 14 August 2021, an earthquake of moment magnitude Mw = 7.2 hit Haiti Island. Unfortunately, it caused several victims and economic damage to the island. While predicting earthquakes is still challenging and has not yet been achieved, studying the preparation phase of such catastrophic events may improve our knowledge and pose the basis for future predictions of earthquakes. In this paper, the six months that preceded the Haiti earthquake are analysed, investigating the lithosphere (by seismic catalogue), atmosphere (by climatological archive) and ionosphere by China Seismo-Electromagnetic Satellite (CSES-01) and Swarm satellites, as well as Total Electron Content (TEC) data. Several anomalies have been extracted from the analysed parameters using different techniques. A comparison, especially between the different layers, could increase or decrease the probability that a specific group of anomalies may be (or not) related to the preparation phase of the Haiti 2021 earthquake. In particular, two possible coupling processes have been revealed as part of the earthquake preparation phase. The first one was only between the lithosphere and the atmosphere about 130 days before the mainshock. The second one was about two months before the seismic event. It is exciting to underline that all the geo-layers show anomalies at that time: seismic accumulation of stress showed an increase of its slope, several atmospheric quantities underline abnormal atmospheric conditions, and CSES-01 Ne depicted two consecutive days of ionospheric electron density. This suggested a possible coupling of lithosphere–atmosphere and ionosphere as a sign of the increased stress, i.e., the impending earthquake. Full article

The successive tidal force (TF) at the epicenter of the Jiashi M6.6 earthquake in Xinjiang, China, was calculated for the period from 13 December 2019 to 10 February 2020. With periodic changes in tide-generating forces, the variations in the electron density (Ne) data recorded by the China Seismo-Electromagnetic Satellite (CSES) and outgoing longwave radiation (OLR) data provided by NOAA on a large scale at N25°–N55°, E65°–E135° were studied. The results show that (1) in the four cycles during which the TF changes from trough to peak, the earthquake occurred during one peak time when the OLR changed around the epicenter via calm–rise processions and in other similar TF phases, and neither an increase in the OLR nor earthquake occurred. (2) With a change in the TF, the spatiotemporal evolution of the OLR from seismogenic processes to its occurrence was as follows: microenhancement–enhancement–microattenuation–enhancement–calmness; this is consistent with the evolution of outward infrared radiation when rocks break under stress loading: microrupture–rupture–locking–accelerated rupture–rupture. (3) Ne increased significantly during the seismogenic period and was basically consistent with OLR enhancement. The results indicate that as the TF increases, the Earth’s stress accumulates at a critical point, and the OLR increases and transfers upward. The theoretical hypothesis underlying the conducted study is that the accumulated electrons on the surface cause negatively charged electrons in the atmosphere to move upward, resulting in an increase in ionospheric Ne near the epicenter, which reveals the homology of seismic stress variations in the spatial coupling process. The quasi-synchronous change process of these three factors suggests that the TF changed the process of the stress accumulation–imbalance in the interior structure of this earthquake and has the effect of triggering the earthquake, and the spatiotemporal variations in the OLR and ionospheric Ne could be indirect reflections of in situ stress. Full article

The spaceborne Electric Field Detector (EFD) is one of the payloads of the China Seismo-Electromagnetic Satellite (CSES-01), which can measure electric field data at near-Earth orbit for investigating fundamental scientific topics such as the dynamics of the top-side ionosphere, lithosphere–atmosphere–ionosphere coupling, and electromagnetic field emissions possibly associated with earthquake occurrence. The Extremely Low-Frequency (ELF) waveform shows anomalous step variations, and this work proposes an automatic detection algorithm to identify steps and analyze their characteristics using a convolutional neural network. The experimental results show that the developed detection method is effective, and the identification performance reaches over 90% in terms of both accuracy and area under the curve index. We also analyze the rate of the occurrence of steps in the three components of the electric field. Finally, we discuss the stability of the statistical results on steps and their relevance to the probe’s function. The research results provide a guideline for improving the quality of EFD data, and further applications in monitoring the low-Earth electromagnetic environment. Full article

The purpose of this work is to investigate the responses of multiple parameters to the Madoi earthquake preparation. A new method is employed to extract anomalies in a geomagnetic field. The results show that there were abnormal changes in the lithosphere, atmosphere, and ionosphere near the epicenter before the earthquake. Despite the differences in spatial and temporal resolutions, the increase in geomagnetic residuals in the lithosphere exhibits similar temporal characteristics to the enhancement of thermal infrared radiation in the atmosphere. Two high–value regions are present in the ground–based geomagnetic high residuals and the ionospheric disturbances. The northern one is around the epicenter of the Madoi earthquake. Near the southern one, an M6.4 Yangbi earthquake occurred four hours before the Madoi earthquake. In this study, we have observed almost all of the physical phenomena that can occur during the preparation of an earthquake, as predicted using the electrostatic channel model. It can be inferred that the electrostatic channel is a possible mechanism for coupling between the lithosphere, atmosphere, and ionosphere during the Madoi earthquake. Full article

Understanding the seismo–ionospheric coupling mechanism requires a quiet geomagnetic condition, as this represents an ideal situation to detect abnormal variations in the geomagnetic field. In reality, continuous interactions between solar wind and Earth’s magnetosphere create many fluctuations in the geomagnetic field that are more related to sun–magnetosphere interactions than to seismotectonic causes. A triaxial magnetometer was installed at the Muntele Rosu Observatory near the Vrancea seismic zone in 1996 to measure the local magnetic field. Since 2002, the data have become more consistent, allowing for the representation of long time series. Since then, variations have been observed on the eastern component (B_y) of the magnetic field, which sometimes overlaps with significant earthquakes. Previous studies have shown that high decreases in amplitude recorded on the B_y component of the magnetic field measured at Muntele Rosu have been accompanied by higher seismicity, while small decreases have been accompanied by lower seismic energy release. This research analyzes the geomagnetic data collected between September 2002 and May 2008 from two geomagnetic observatories, one located in the proximity of the Vrancea seismic zone and another one situated 120 km away. For each geomagnetic anomaly identified, the daily seismic energy released was plotted logarithmically, along with seismicity and Kp indices. Additionally, the daily seismic energy released was also plotted logarithmically for all earthquakes with Mw ≥3. To identify variations in the B_y component, datasets recorded at Muntele Rosu (MLR) were compared with those recorded at Surlari National Geomagnetic Observatory (SUA), to discriminate between global magnetic variations associated with solar activity and possible seismo–electromagnetic variations. The standard deviation (SD_By) was calculated for each anomaly recorded on the B_y component of the magnetic field and compared with the cumulative seismic energy release. To determine if this type of variation was present in other components of the magnetic field, the following ratios were calculated for all data recorded at Muntele Rosu: B_z/B_x, B_z/B_y, and B_z/B_H. The size of the anomalies resulting from the standard deviation measured on the B_y component (SD_By) partially validates the relationship between the size of the anomalies and the seismic energy release during the anomaly. The relationship between the released seismic energy and the anomaly magnitude is vaguely respected, but these variations seem to follow two patterns. One pattern is described by smooth decreases, and the other pattern involves decreases where the B_y component varies significantly over short periods, generating decreases/increases in steps. It was noticed that seismic activity is greater for the second pattern. Additionally, using standard deviation measured on the magnetic field represents a great tool to discriminate external magnetic field variations from local, possibly seismo–magnetic variations. Full article

Geophysical natural hazards, such as earthquakes and volcano eruptions, can have catastrophic effects on the population depending on the location and quality of construction. From the geophysical point of view, several aspects are still debated in the preparation phase of such events. In particular, several theories propose that prior to an earthquake or volcano eruption, the releases of gas, fluids or charged particles from the lithosphere (e.g., from the fault for the earthquake) could create some effects on the atmosphere and ionosphere. In this work, several single examples will be shown of possible candidates of pre-earthquake ionospheric disturbances recorded by the China National Space Administration (in partnership with the Italian Space Agency), China Seismo Electromagnetic Satellite (CSES) and European Space Agency Swarm constellation. The examples show anomalous ionospheric status in terms of magnetic disturbances or increase of electron density before earthquakes, such as Mw = 7.1 Ridgecrest (US) 2019, or during the large recent volcano eruption of Hunga Tonga-Hunga Ha’Apai on 15 January 2022. In these cases, some couplings between the lithosphere and ionosphere are proposed. Finally, verifying if such pre-event ionospheric disturbances are by “chance” or are really linked to the incoming event is a crucial point. For this purpose, we perform worldwide statistical studies, not only supporting the recurrence of such phenomena for about 15% of M5.5+ shallow earthquakes but also showing a link between the magnitude of the upcoming seismic events and the pre-earthquake anticipation time. Furthermore, we also show the influence of the location (sea or land) on the frequency of the ionospheric electromagnetic disturbance. Full article

Several studies focusing on the anomalies of one specific parameter (such as magnetic, ionospheric, radon release, temperature, geodetic, etc.) before impending earthquakes are constantly challenged because their results can be regarded as noise, false positives or are not related to earthquakes at all. This rise concerns the viability of studying isolated physical phenomena before earthquakes. Nevertheless, it has recently been shown that all of the complexity of these pre-earthquake anomalies rises because they could share the same origin. Particularly, the evolution and concentration of uniaxial stresses within rock samples have shown the generation of fractal crack clustering before the macroscopic failure. As there are studies which considered that the magnetic anomalies are created by lithospheric cracks in the seismo-electromagnetic theory, it is expected that the crack clustering is a spatial feature of magnetic and non-magnetic anomalies measurements in ground, atmospheric and ionospheric environments. This could imply that the rise of multiparametric anomalies at specific locations and times, increases the reliability of impending earthquake detections. That is why this work develops a general theory of fractal-localization of different anomalies within the lithosphere in the framework of the seismo-electromagnetic theory. In addition, a general description of the fractal dimension in terms of scaling entropy change is obtained. This model could be regarded as the basis of future early warning systems for catastrophic earthquakes. Full article

Based on the multi-data of the global ionospheric map (GIM), ionospheric total electron content (TEC) inversed from GPS observations, the critical frequency of the F2 layer (f_OF₂) from the ionosonde, electron density (Ne), electron temperature (Te), and He⁺ and O⁺ densities detected by the China Seismo-Electromagnetic Satellite (CSES), the temporal and spatial characteristics of ionospheric multi-parameter perturbations were analyzed around the Maerkang Ms6.0 earthquake swarm on 9 June 2022. The results showed that the seismo-ionospheric disturbances were observed during 2–4 June around the epicenter under quiet solar-geomagnetic conditions. All parameters we studied were characterized by synchronous changes and negative anomalies, with a better consistency between ionospheric ground-based and satellite observations. The negative ionospheric anomalies for all parameters appeared 5–7 days before the Maerkang Ms6.0 earthquake swarm can be considered as significant signals of upcoming main shock. The seismo-ionospheric coupling mechanism may be a combination of two coupling channels: an overlapped DC electric field and an acoustic gravity wave, as described by the lithosphere–atmosphere–ionosphere coupling (LAIC). In addition, in order to make the investigations still more convincing, we completed a statistical analysis for the ionospheric anomalies of earthquakes over Ms6.0 in the study area (20°~40° N, 92°~112° E) from 1 January 2019 to 1 July 2022. The nine seismic events reveal that most strong earthquakes are preceded by obvious synchronous anomalies from ground-based and satellite ionospheric observations. The anomalous disturbances generally appear 1–15 days before the earthquakes, and the continuity and reliability of ground-based ionospheric anomaly detection are relatively high. Based on the integrated ionospheric satellite–ground observations, a cross-validation analysis can effectively improve the confidence level of anomaly identification and reduce the frequency of false anomalies. Full article

The study of electrical currents in the topside ionosphere is of great importance, as it may allow a better understanding of the processes involved in the Sun–Earth interaction and magnetosphere–ionosphere–thermosphere coupling, two crucial aspects debated by the Space Weather scientific community. In this context, investigating the electrical conductivity parallel to the geomagnetic field in the topside ionosphere is of primary importance because: (1) it provides information on the capability of the ionosphere to conduct currents; (2) it relates current density and electric field through Ohm’s law; (3) it can help to quantify the dissipation of currents; (4) it is generally modeled and not locally measured by in situ missions. In this work, we used in situ measurements of electron density and temperature recorded between 2019 and 2021 by the China Seismo-Electromagnetic Satellite (CSES-01) flying with an orbital inclination of 97.4° and at an altitude of about 500 km to compute the parallel electrical conductivity in the topside ionosphere at low and middle latitudes at the two fixed local times (LT) characterizing the CSES-01 mission: around 02 and 14 LT. The results, which are discussed in light of previous literature, highlight the dependence of conductivity on latitude and longitude and are compared with those obtained using values both measured by the Swarm B satellite (flying at a similar altitude) and modeled by the International Reference Ionosphere in the same time period. In particular, we found a diurnal variation in parallel electrical conductivity, with a slight hemispheric asymmetry. Daytime features are compatible with Sq and equatorial electrojet current systems, containing “anomalous” low values of conductivity in correspondence with the South Atlantic region that could be physical in nature. Full article

In this paper, we focused on the characteristics of the seismo-ionospheric effects related to two successive earthquakes, namely, the earthquakes in 2022 in Taitung Sea, Taiwan, China, with magnitudes (M) of 6.7 and 6.3, at 23.45° N, 121.55° E and 23.39° N, 121.52° E and with the same focal depth of 20 km, which were detected by the China Seismo-Electromagnetic Satellite (CSES). By applying the sliding interquartile range method to electron density (Ne) data acquired by the Langmuir probe (LAP) onboard the CSES and the grid total electron content (TEC) data obtained from the Center for Orbit Determination in Europe (CODE), positive anomalies were found under quiet geomagnetic conditions on 2–3 March and 8–9 March 2022—that is, 19–20 and 13–14 d before the earthquakes, respectively, and the global ionospheric mapping (GIM) TEC data suggested that anomalies may also have been triggered in the magnetic conjugate area 13–14 d prior to the earthquakes occurrences. In addition, the CSES Ne data showed enhancements 3 and 5 d before the earthquakes occurred. Furthermore, 138 earthquakes with M ≥ 5.0 that occurred in Taiwan and the surrounding region during the period February 2019 to March 2022 were statistically analyzed using the CSES Ne data. The results show that most of the Ne anomalies were positive. Moreover, the greater the earthquake magnitude, the greater the frequency of the anomalies; however, the amplitude of the anomalies did not increase with the earthquake magnitude. The anomalies were concentrated during the period of 10 d before to 5 d after the earthquakes. No increase in the amplitude of anomalies was observed as the time of the earthquakes approached. Finally, based on evidence relating to earthquake precursor anomalies, we conclude that it is possible that earthquakes in Taiwan and the surrounding region affect the ionosphere through the geochemical, acoustic, and electromagnetic channels, as described by the lithosphere–atmosphere–ionosphere coupling (LAIC) model, and that the two studied earthquakes in Taiwan may have induced ionospheric effects through the geochemical channel. Full article