Search Results (33)

To explore the spatiotemporal evolution characteristics of pre-earthquake GPS TEC anomalies and their correlation with seismic activities, a statistical analysis was performed on pre-earthquake ionospheric GPS TEC anomalies associated with Ms ≥ 6.0 earthquakes in Mainland China from 2012 to 2022 using GPS TEC observational data. Two statistical metrics were adopted, namely average anomaly frequency and anomaly earthquake percentage. Classified statistical analyses were carried out from the perspectives of anomaly polarity, earthquake magnitude, focal depth, and different azimuths of the epicenter to systematically investigate the evolutionary characteristics of TEC anomalies from 30 days pre-earthquake to the earthquake day. The results show that the two core statistical indicators of pre-earthquake TEC anomalies present a significant increasing trend around the 25th, 15th, and 5th days before the earthquake and on the earthquake day. Moreover, the values of the two metrics corresponding to positive pre-earthquake TEC anomalies were higher than those corresponding to negative anomalies. Specifically, the values of the two metrics for pre-earthquake TEC anomalies of strong earthquakes with 6.8–7.6 were higher than those for 6.0–6.8 earthquakes. The spatial distribution of pre-earthquake TEC anomalies is characterized by inhomogeneity and time-dependent characteristics. Compared with earthquakes at a focal depth of 0–10 km, earthquakes at a focal depth of 10–20 km show more significant pre-earthquake TEC anomaly signals. Perturbation characteristics of pre-earthquake ionospheric GPS TEC were statistically analyzed, providing a reference for further elucidating the seismo-ionospheric coupling mechanism and identifying ionospheric precursors of earthquakes. Full article

Detection of pre-seismic ionospheric electric field perturbation remains an open challenge in the scientific community, hindered by methodological biases and a lack of reproducible frameworks. In this study, we investigate the existence of ionospheric perturbations associated with earthquakes by developing a deep learning framework for detecting anomalous patterns in global ionospheric electric field measurements provided by the DEMETER satellite and evaluating their statistical relationship with global seismicity. We developed an unsupervised LSTM autoencoder framework trained under a rolling-window scheme with two alternative optimisation strategies. The iterative rolling-window approach enabled the preservation of long-term temporal continuity while adapting to the non-stationary ionospheric background. Anomalies detected by the model were subjected to a seismic association and evaluated statistically. Findings were consistent across multiple network configurations, independent training optimisation strategies and different segments of the dataset, demonstrating strong methodological robustness. Our study suggests that modern sequential deep-learning models, when combined with an adaptive temporal training approach and statistical evaluation, provide an effective tool for the systematic detection and statistical quantification of associations between ionospheric electric field perturbations and seismic events. Full article

This study presents a comprehensive analysis of pre- and co-seismic ionospheric disturbances associated with the 2023 Ms6.2 Jishishan earthquake by leveraging the unique observational strengths of BDS, particularly its high-orbit satellites. A multi-parameter space weather index was employed to effectively isolate seismogenic signals from geomagnetic disturbances, confirming that the main shock occurred during geomagnetically quiet conditions. Statistical analysis of 41 historical earthquakes (Mw ≥ 5.5) reveals that 47.2% were associated with detectable Total Electron Content (TEC) anomalies. An inverse correlation between earthquake magnitude and anomaly detectability within a 31-day window suggests prolonged precursor durations for larger events may produce longer-duration precursory signals, which challenge conventional detection methods. The synergistic capabilities of BDS Geostationary Earth Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites were demonstrated: GEO satellites provide unprecedented temporal stability for continuous TEC monitoring, while IGSO satellites enable high-resolution spatial mapping of Co-seismic Ionospheric Disturbances (CIDs). The detected CIDs propagated at velocities below 1.6 km/s, consistent with acoustic gravity wave (AGW) mechanisms. A case study during a geomagnetically active period further reveals modulated CID propagation characteristics, indicating potential coupling between seismic forcing and space weather. Our findings validate BDS as a powerful and precise tool for ionospheric seismology and provide critical insights into Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) dynamics. Full article

A series of multi-parameter, multi-layer observations was conducted to study possible electromagnetic precursors associated with the M 6.7 earthquake that struck Iburi, Hokkaido, Japan, at 18:07:59 UT on 5 September 2018. The most significant observation is seismogenic lower-ionospheric perturbations in the propagation anomalies of sub-ionospheric VLF/LF signals recorded in Japan and Russia. Other substantial observations include the GIM-TEC irregularities, the intensification of stratospheric atmospheric gravity waves (AGWs), and the satellite and ground monitoring of air temperature (T), relative humidity (RH), atmospheric chemical potential (ACP), and surface latent heat flux (SLHF). We have found that there were very remarkable VLF/LF anomalies indicative of lower-ionospheric perturbations observed on 4 and 5 September just before the EQ date and even after it from the observations in Japan and Russia. In particular, the anomaly was detected for a particular propagation path from the JJY transmitter (Fukushima) to a VLF station at Wakkanai one day before the EQ, i.e., on 4 September, and is objectively confirmed by machine/deep learning analysis. An anomaly in TEC occurred only on 5 September, but it is unclear whether it is related to a pre-EQ effect or a minor geomagnetic storm. We attempted to determine whether any seismo-related atmospheric gravity wave (AGW) activity occurred in the stratosphere. Although numerous anomalies were detected, they are most likely associated with convective weather phenomena, including a typhoon. Finally, the Earth’s surface parameters based on satellite monitoring seem to indicate some anomalies from 29 August to 3, 4, and 5 September, a few days prior to EQ data, but the ground-based observation close to the EQ epicenter has indicated a clear T/RH and ACP on 2 September with fair weather, but no significant data on subsequent days because of severe meteorological activities. By integrating multi-layer observations, the LAIC (lithosphere–atmosphere–ionosphere coupling) process for the Hokkaido earthquake appears to follow a slow diffusion-type channel, where ionospheric perturbations arise a few days after ground thermal anomalies. This study also provides integrated evidence linking concurrent lower-ionospheric, atmospheric, and surface thermal anomalies, emphasizing the diagnostic value of such multi-parameter observations in understanding EQ-associated precursor signatures. Full article

It has recently been recognized that the ionosphere is highly sensitive to pre-seismic effects, and the detection of ionospheric perturbations associated with earthquakes (EQs) is one of the most promising candidates for short-term EQ prediction. In this review, we focus on a possible use of VLF/LF (very low frequency (3–30 kHz)/low frequency (30–300 kHz)) radio sounding of seismo-ionospheric perturbations to study seismogenic effects. Because an understanding of the early history in any area will provide a lot of crucial insights to the readers (especially to young scientists) working in the field of seismo-electromagnetics, we provide a brief history (mainly results reported by a Russian group of scientists) of the initial application of subionospheric VLF/LF propagation for the study of ionospheric perturbations associated with EQs, and then we present our first convincing evidence on the ionospheric perturbation for the disastrous Kobe EQ in 1995, with a new analysis method based on the shifts in terminator times in VLF/LF diurnal variations (minima in the diurnal variations in amplitude and phase). We then summarize our latest results on further evidence of seismo-ionospheric perturbations. Firstly, we present a few statistical studies on the correlation between VLF/LF propagation anomalies and EQs based on long-term data. Secondly, we showcase studies for a few large, recent EQs (including the 2011 Tohoku EQ). Building on those EQ precursor studies, we demonstrate scientific topics and the underlying physics that can be studied using VLF/LF data, highlighting recent achievements including the revolutionary perspective of lithosphere–atmosphere–ionosphere coupling (LAIC) (or how the ionosphere is perturbed due to the lithospheric pre-EQ activity), modulation in VLF/LF data by atmospheric gravity waves (AGWs), Doppler-shift observation, satellite observation of VLF/LF transmitter signals, etc., together with the recommendation of the application of new technologies such as artificial intelligence and critical analysis to VLF/LF analysis. Finally, we want to emphasize again the essential significance of the information on lower-ionospheric perturbations within LAIC studies. Full article

Anomalous ionospheric disturbances have been observed as potential precursors to earthquakes. This study utilized data from the CSES satellite to investigate anomalies in the ULF band ionospheric electric field and electron density preceding earthquakes with magnitudes of Ms ≥ 6.0 in China and neighboring regions from 2019 to 2021. Comparative analysis with a randomly generated earthquake catalog indicated that these anomalies were spatially concentrated over the epicenter and temporally clustered on specific dates prior to the events. To assess the global relevance of these findings, the analysis was extended to earthquakes with Ms ≥ 7.0 worldwide during the same period, revealing consistent spatiotemporal patterns of ionospheric anomalies in both regional and global datasets. Furthermore, by combining the two earthquake catalogs and classifying events into oceanic and continental categories, additional statistical analyses were conducted to identify distinct ionospheric disturbance patterns associated with these different tectonic environments. These results provide a solid foundation for future research aimed at identifying and extracting ionospheric anomalies as potential pre-earthquake indicators. Full article

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

Earthquake prediction is one of the most challenging enterprises of science. Any prediction system must be based on the search for a precursor appearing during the preparation phase of an earthquake in the ground, atmosphere, or ionosphere that can anticipate its occurrence. We present methods to detect potential pre-earthquake anomalies. In particular, we show the analysis of lithospheric, atmospheric, and ionospheric data and the detection of anomalies under specific criteria. When we apply these methods retrospectively, we find that their accuracy goes from 69% to 83%. The combination of two or more methods is expected to improve the accuracy. Full article

Focusing on major earthquakes (EQs; MS ≥ 7) in Western China, this study primarily analyzes the fluctuation in Atmospheric Chemical Potential (ACP) before and after the Wenchuan, Yushu, Lushan, Jiuzhaigou, and Maduo EQs via Climatological Analysis of Seismic Precursors Identification (CAPRI). The distribution of vertical ACP revealed distinct altitude-dependent characteristics. The ACP at lower atmospheric layers (100–2000 m) exhibited a high correlation, and this correlation decreased with increasing altitude. Anomalies were detected within one month prior to each of the five EQs studied, with the majority occurring 14 to 30 days before the events, followed by a few additional anomalies. The spatial distribution of anomalies is consistent with the distribution of fault zones, with noticeable fluctuation in surrounding areas. The ACP at an altitude of 200 m gave a balance between sensitivity to seismic signals and minimal surface interference and proved to be optimal for EQ monitoring in Western China. The results offer a significant reference for remote sensing studies related to EQ monitoring and the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) model, thereby advancing our understanding of pre-seismic atmospheric variations in Western China. Full article

This paper presents a multi-parameter ionospheric disturbance analysis of the total electron content (TEC), density (Ne), temperature (Te), and critical frequency foF2 variations preceding two significant earthquake events (2015 Mw 7.5 and 2023 Mw 6.3) that occurred in Afghanistan. The analysis from various ground stations and low-Earth-orbit satellite measurements involved employing the sliding interquartile method to process TEC data of Global Ionospheric Maps (GIMs), comparing revisit trajectories to identify anomalies in Ne and Te from Swarm satellites, applying machine learning-based envelope estimation for GPS-derived TEC measurements, utilizing the least square method for foF2 data and ionograms obtained from available base stations in the Global Ionosphere Radio Observatory (GIRO). After excluding potential influences caused by solar and geomagnetic activities, the following phenomena were revealed: (1) The GIM-TEC variations displayed positive anomalies one day before the 2015 Mw 7.5 earthquake, while significant positive anomalies occurred on the shock days (7, 11, and 15) of the 2023 Mw 6.3 earthquake; (2) the Swarm satellite observations (Ne and Te) for the two earthquakes followed almost the same appearance rates as GIM-TEC, and a negative correlation between the Ne and Te values was found, with clearer appearance at night; (3) there were prominent positive TEC anomalies 8 days and almost 3 h before the earthquakes at selected GPS stations, which were nearest to the earthquake preparation area. The anomalous variations in TEC height and plasma density were verified by analyzing the foF2, which confirmed the ionospheric perturbations. Unusual ionospheric disturbances indicate imminent pre-seismic events, which provides the potential opportunity to provide aid for earthquake prediction and natural hazard risk management in Afghanistan and nearby regions. Full article

In our exploration, we aimed at identifying seismic anomalies using limited ionospheric data for earthquake forecasting and we meticulously compiled datasets under conditions of minimal geomagnetic disturbance. Our systematic evaluation affirmed the ITransformer as a potent tool for the feature extraction of ionospheric data, standing out within the domain of transformer-based time series prediction models. We integrated the maximum entropy principle to fully leverage the available information, while minimizing the influence of presuppositions on our predictions. This led to the creation of the MaxEnt SeismoSense Model, a novel composite model that combines the strengths of the transformer architecture with the maximum entropy principle to improve prediction accuracy. The application of this model demonstrated a proficient capability to detect seismic disturbances in the ionosphere, showcasing an improvement in both recall rate and accuracy to 71% and 69%, respectively, when compared to conventional baseline models. This indicates that the combined use of transformer technology and the maximum entropy principle could allow pre-seismic anomalies in the ionosphere to be sensed more efficiently and could offer a more reliable and precise approach to earthquake prediction. Full article

From August to October 2018, a series of strong earthquake (EQ) events occurred in southeast Asia and northern Oceania (22°S to 0°N, 115°E to 170°E) within 50 days. In this paper, we analyze the features of ionospheric plasma perturbations, recorded by the Plasma Analyzer Package (PAP) and Langmuir probe (LAP) onboard the China Seismo-Electromagnetic Satellite (CSES-01), before four EQs with magnitudes of Ms 6.9 to Ms 7.4. The ion parameters such as the oxygen ion density (No⁺), the ion drift velocity in the vertical direction (V_z) under the conditions of geomagnetic storms, and strong EQs are compared. The results show that within 1 to 15 days before the strong EQs, the No⁺ and the electron density (Ne) increased while the electron temperature (Te) decreased synchronously. Meanwhile, the V_z significantly increased along the ground-to-space direction. The relative variation of No⁺ and V_z before the strong EQs is more prominent, and the V_z is not easily influenced by the geomagnetic storm but is susceptible to the seismic activities. Our results suggest that the anomaly of ionospheric plasma perturbations occurring in this area is possibly related to the pre-EQ signatures. Full article

This contribution describes the acquisition and trigger system for the HEPD-02 calorimeter that will be used onboard the CSES-02 satellite for the CSES/Limadou mission. This mission arises from the collaboration between the Chinese Space Agency (CNSA) and the Italian Space Agency (ASI) and plans the realization of a constellation of satellites which will monitor ionospheric parameters supposed to be related to earthquakes. It will also monitor the solar activity and the interaction with the magnetosphere and will study the cosmic rays in low energy ranges, extending data from PAMELA and AMS. The CSES-02 satellite will be equipped with various instruments, including the High-Energy Particle Detector (HEPD-02), which was designed to measure the energy of particles coming from Van Allen belts. Signals from the HEPD-02 are acquired and digitized by an electronic board that also produces the trigger for the experiment. A new generation ASIC (CITIROC) for the amplification, shaping and memorization of signals from PMTs will be used on this board. The new ASIC allows the use of the peak detector feature, optimizing the acquisition of signals with different temporal characteristics. Along with this, new algorithms for trigger generation have been developed, providing trigger pre-scaling, concurrent trigger masks and Gamma Ray Burst detection. Using pre-scaled concurrent triggers will allow the study of very sensitive regions of a satellite’s orbit such as the South Atlantic Anomaly and polar regions and to detect rare events such as GRBs while still monitoring particle bursts. In this contribution, the progress status of this work will be presented along with the measurements and tests made to finalize the flight model of the board. Full article

Investigating various geophysical parameters from the Earth’s crust to the upper atmosphere is considered a promising approach for predicting earthquakes. Scientists have observed that changes in these parameters can occur days to months before earthquakes. Understanding and studying the impending abnormal phenomena that precede earthquakes is both urgent and challenging. On 5 September 2022, a magnitude 6.8 earthquake occurred in Sichuan, China, at 4:52:18 (Universal Time). The earthquake happened approximately 175 km away from an instrumental array established in 2021 for monitoring vibrations and perturbations in the lithosphere, atmosphere, and ionosphere (MVP-LAI). This array consisted of over 15 instruments that regularly monitor changes in various geophysical parameters from the subsurface up to an altitude of approximately 350 km in the ionosphere. Its purpose was to gain insights into the mechanisms behind the coupling of these different geospheres during natural hazards. The seven geophysical parameters from the MVP-LAI system simultaneously exhibited abnormal behaviors approximately 3 h before the Luding earthquake. These parameters include ground tilts, air pressure, radon concentration, atmospheric vertical electric field, geomagnetic field, wind field, and total electron content. The abnormal increase in radon concentration suggests that the chemical channel could be a promising mechanism for the coupling of geospheres. Furthermore, air pressure, the geomagnetic field, and total electron content exhibited abnormal characteristics with similar frequencies. Horizontal wind experienced temporary cessation or weakening, while vertical wind displayed frequent reversals. These anomalies may be attributed to atmospheric resonance before the earthquake. The results demonstrate that the coupling of geospheres, as indicated by the anomalous phenomena preceding an earthquake, could be influenced by multiple potential mechanisms. The multiple anomalies observed in this study provided approximately 3 h of warning for people to prepare for the seismic event and mitigate hazards. Full article

The ionospheric anomalies before an earthquake may be related to earthquake preparation. The study of the ionospheric anomalies before an earthquake provides potential value for earthquake prediction. This paper proposes a method for detecting ionospheric total electron content (TEC) anomalies before an earthquake, taking the M_S 7.8 earthquake in Türkiye on 6 February 2023 as an example. First, the data of four ground-based GNSS stations close to the epicenter were processed by using the sliding interquartile range method and the long short-term memory (LSTM) network. The anomaly dates detected by the two methods were identified as potential pre-earthquake TEC anomaly dates after eliminating solar and geomagnetic interference. Then, by using the sliding interquartile range method to process and analyze the CODE GIM (Center for Orbit Determination in Europe, Global Ionospheric Map) data from a global perspective, we further verified the existence of TEC anomalies before the earthquake on the above TEC anomaly days. Finally, the influence of the equatorial ionospheric anomaly (EIA) on the TEC anomaly disturbance was excluded. The results show that the ionospheric TEC anomalies on January 20, January 27, February 4, and February 5 before the Türkiye earthquake may be correlated with the earthquake. Full article