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Abstract The China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate pre-earthquake ionospheric anomalies (PEIAs) and ionospheric space weather. The CSES probes manifest longitudinal features of four-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs. CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric disturbances induced by an intense storm with the Dst index of − 175 nT on 26 August 2018. Anomalous increases (decreases) in the GIM TEC and CSES plasma density (temperature) frequently appear specifically over the epicenter days 1–5 before the M7.0 earthquake and followed earthquakes, when the geomagnetic conditions of these PEIA periods are relatively quiet, Dst: − 37 to 19 nT. In contrast, TEC and CSES plasma parameter anomalies occur globally in the southern hemisphere during the storm days of 26–28 August 2018. The CSES ion velocity shows that the electric fields of PEIAs associated with the M7.0 earthquake are 0.21/0.06 mV/m eastward and 0.11/0.10 mV/m downward at post-midnight/post-noon on 1–3 August 2018, while the penetration electric fields during the storm periods of 26–28 August 2018 are 0.17/0.45 mV/m westward/downward at post-midnight of 02:00 LT and 0.26/0.26 mV/m eastward/upward at post-noon of 14:00 LT. Spatial analyses on CSES plasma discriminate PEIAs from global effects and locate the epicenter of possible forthcoming large earthquakes. CSES ion velocities are useful to derive PEIA- and storm-related electric fields in the ionosphere.

Abstract Intense eruptions of the Tonga volcano activated prominent traveling atmospheric disturbances (TADs) at 04:05UT on 15 January 2022. Himawari‐8 satellite images depict that TADs of the tropospheric Lamb wavefront propagate with a speed of 315 m/s and arrive in Taiwan at 11:30UT. Networks of 98 barometers, 28 tide gauges, an ionosonde, and 10 magnetometers are used to study the responses of magnetic fields to TADs in Taiwan. The horizontal components in magnetic field changes of the Taiwan magnetometers all point toward and away from the Tonga volcano at 11:00–12:00UT upon the tropospheric Lamb wavefront arrival and at 22:00–23:00UT when the thermospheric Lamb wavefront with speeds of 487 m/s coming, respectively. Analyses of the raytracing and beamforming techniques on the horizontal components in magnetic field changes of 69 INTERMAGNET magnetometers show that both tropospheric and thermospheric Lamb waves efficiently activate traveling ionospheric disturbances and modify ionospheric currents of the globe.

YRY-4 borehole strainmeters have been installed in Sichuan Province, China, since 2008, aimed at monitoring the crustal activities associated with earthquakes. In this study, data from six YRY-4 strainmeters at the southwestern endpoint of the Longmenshan fault zone were analysed, to study the relationship of tectonic strain changes with the 2013 Lushan earthquake. We developed a state-space model to remove the strain response due to air pressure, solid tides and the changes in the water level to preferentially isolate non-tectonic disturbances. Strain responses to each influencing factor were estimated using the environmental coefficients computed in the state-space model by an adaptive Kalman filter with measurement noise. The results were consistent with the expected response of the strainmeter systems. The corrected strain considered to originate from underground tectonics provides new insights into the changes in the pre-earthquake strain. Approximate negentropy (ApNe) and ${b}$ value were introduced to quantify the probability distribution of the corrected borehole strain and compared with the local seismic activities. The nearest station and two further stations, almost simultaneously recorded short-term ApNe anomalies six to four months before the earthquake. The anomalous region also had a correspondingly low ${b}$ value. Moreover, the anomaly acceleration rates of each station were dependent on the epicentral distances. Further comparison with the strain of random periods illustrated the significance of the extracted anomalies. Our results indicate that the corrected strain may contain seismogenic information and reflect the accelerated strain accumulation of focal areas before the earthquake.

Abstract The 28 September 2018 magnitude Mw7.8 Palu, Indonesia earthquake (0.178° S, 119.840° E, depth 13 km) occurred at 10:02 UTC. The major earthquake triggered catastrophic liquefaction, landslides, and a near-field tsunami. The ionospheric total electron content (TEC) derived from records of 5 ground-based global navigation satellite system (GNSS) receivers is employed to detect tsunami traveling ionospheric disturbances (TTIDs). In total, 15 TTIDs have been detected. The ray-tracing and beamforming techniques are then used to find the TTID source location. The bootstrap method is applied in order to further explore the possible location of the tsunami source based on results of the two techniques, which show the beamforming technique has a slightly better performance on finding possible locations of the tsunami source. Meanwhile, the circle method is employed to examine tsunami signatures of the sea-surface height and video records, and find possible tsunami origin locations. The coincidence of the TTID source location and the tsunami location shows that the ionospheric TEC recorded by local ground-based GNSS receivers can be used to confirm the tsunami occurrence, find the tsunami location, and support the tsunami early warning.

Due to their potential application in earthquake forecasting, seismo-electromagnetic phenomena were intensively studied for several decades all over the world. At present, measurements from ground to space have accumulated a large amount of observation data, proving an excellent opportunity for seismo-electromagnetic study. Using a variety of analytical methods to examine past earthquake events, many electromagnetic changes associated with earthquakes have been independently reported, supporting the existence of pre-earthquake anomalies. This study aimed to give a brief review of the seismo-electromagnetic studies preceding earthquakes and to discuss possible ways for the application of seismo-electromagnetic signals at the current stage. In general, seismo-electromagnetic signals can be classified into electric and magnetic changes in the lithosphere and perturbations in the atmosphere. We start with seismo-electromagnetic research in the lithosphere, and then we review the studies in the lower atmosphere and upper atmosphere, including some latest topics that aroused intense scholarly interest. The potential mechanisms of seismo-electromagnetic phenomena are also discussed. It was found that although a number of statistical tests show that electromagnetic anomalies may contain predictive information for major earthquakes, with probability gains of approximately 2–6, it is still difficult to make use of seismo-electromagnetic signals efficiently in practice. To address this, finally, we put forward some preliminary ideas about how to apply the seismo-electromagnetic information in earthquake forecasting.

Early studies have shown evidence of the seismo-ionospheric perturbations prior to large earthquakes. Due to dynamic complexity in the ionosphere, the identification of precursory ionospheric changes is quite challenging. In this study, we analyze the total electron content (TEC) in the global ionosphere map and investigate the TEC changes prior to M ≥ 6.0 earthquakes in the Chinese Mainland during 1998–2013 to identify possible seismo-ionospheric precursors. Singular spectrum analysis is applied to extract the trend and periodic variations including diurnal and semi-diurnal components, which are dominated by solar activities. The residual ΔTEC which is mainly composed of errors and possible perturbations induced by earthquakes and geomagnetic activities is further investigated, and the root-mean-square error is employed to detect anomalous changes. The F10.7 and Dst index is also used as criterion to rule out the anomalies when intense solar or geomagnetic activities occur. Our results are consistent with those of previous studies. It is confirmed that the negative anomalies are dominant 1–5 days before the earthquakes at the fixed point (35°N, 90°E) during 0600–1000 LT. The anomalies are more obvious near the epicenter area. The singular spectrum analysis method help to establish a more reliable variation background of TEC and thus may improve the identification of precursory ionospheric changes.

The Gutenberg–Richter b value describes the ratio between large and small events. A number of studies have suggested that the b value decreases before large earthquakes. In this study, we investigate the temporal variation of the b value of an area along the main rupture zone of the 2008 Wenchuan earthquake (M8.0) prior to the great event. Before estimating b values, we tested the earthquake catalog to make sure that we use the reliable frequency–magnitude distribution by the calculation of MC (completeness of magnitude). We define parameter P (ΔAIC ≧ 2) values to examine the significance level of b-value changes in the temporal variation by combining a boostrap method with Akaike’s Information Criterion (AIC). The b value in the main rupture zone shows a long-term decrease trend. We then focus on a smaller area where the initial rupture starts. The results show that b values significantly changed about 3 months before the 2008 Wenchuan earthquake in the initial rupture area, indicating that the b value has a potential capability to monitor and detect precursory phenomena of great earthquakes.

This paper utilizes 10 stations of co-located seismometer, QuakeFinder/infrasound to observe co-seismic signatures triggered by the 6 February 2016 M 6.6 Meinong Earthquake. Each QuakeFinder system consists of a 3-axes induction magnetometer, an air conductivity sensor, a geophone, and temperature/relative humidity sensors. There are no obvious charges in the positive/negative ions, the temperature, and the humidity, while the magnetometer, the geophone, and infrasound data detect clear co-seismic signatures, similar to seismic waves recorded by seismometers. The magnetometers register high-frequency pulsations, like seismic waves, and superimpose with low-frequency variations, which could be caused by the magnetometer shaking/tilting and/or the underground water level change, respectively, upon the arrival of seismic waves. The spectrum centering around 2.0 Hz of the co-seismic geophone fluctuations is similar to that of the seismic waves. However, the energy of co-seismic geophone fluctuations (also magnetometer pulsations) yields an exponential decay to the distance of a station to the epicenter, while the energy of the seismic waves is inversely proportional to the square of the distance. This suggests that the mechanisms for detecting seismic waves of the QuakeFinder system and seismometers are different. In general, the geophone and magnetometer/infrasound system are useful to record high- and low-frequency seismic waves, respectively.

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.

In order to find out whether the geomagnetic storms and large-mega earthquakes are correlated or not, statistical studies based on Superposed Epoch Analysis (SEA), significance analysis, and Z test have been applied to the Dst index data and M ≥ 7.0 global earthquakes during 1957–2020. The results indicate that before M ≥ 7.0 global earthquakes, there are clearly higher probabilities of geomagnetic storms than after them. Geomagnetic storms are more likely to be related with shallow earthquakes rather than deep ones. Further statistical investigations of the results based on cumulative storm hours show consistency with those based on storm days, suggesting that the high probability of geomagnetic storms prior to large-mega earthquakes is significant and robust. Some possible mechanisms such as a reverse piezoelectric effect and/or electroosmotic flow are discussed to explain the statistical correlation. The result might open new perspectives in the complex process of earthquakes and the Lithosphere-Atmosphere-Ionosphere (LAI) coupling.

To investigate the nonlinear spatio-temporal behavior of earthquakes, a complex network has been built using borehole strain data from the southwestern endpoint of the Longmenshan fault zone, Sichuan-Yunnan region of China, and the topological structural properties of the network have been investigated based on data from 2011–2014. Herein, six observation sites were defined as nodes and their edges as the connections between them. We introduced Multi-channel Singular Spectrum Analysis (MSSA) to analyze periodic oscillations, earthquake-related strain, and noise in multi-site observations, and then defined the edges of the network by calculating the correlations between sites. The results of the daily degree centrality of the borehole strain network indicated that the strain network anomalies were correlatable with local seismicity associate with the earthquake energy in the strain network. Further investigation showed that strain network anomalies were more likely to appear before major earthquakes rather than after them, particularly within 30 days before an event. Anomaly acceleration rates were also found to be related to earthquake energy. This study has revealed the self-organizing pre-earthquake phenomena and verified the construction of borehole networks is a powerful tool for providing information on earthquake precursors and the dynamics of complex fault systems.

We proposed a cloud discrimination method applicable in Japan using MODIS nighttime data, monitored the singularity of the spatiotemporal correlation of surface temperature anomalies and investigated the possibility of detecting and monitoring lava activity in Shinmoedake. With the aim to detect lava eruption activity in 2011, nine years of data from 2003 to 2011 were analyzed. As a result, the first anomalous singularity in brightness temperature was detected on 26 January 2011. Moreover, the maximum value was detected on 30 January 2011. The values showed larger ones until early February 2011. When an anomalous singularity appeared, it was the only period with the magma-related volcanic activity for Shinmoedake over the analyzed period of nine years. The above facts indicate the effectiveness of the proposed singularity method to monitor the lava activity for Shinmoedake. Therefore, it is concluded that if cloud discrimination is realized with high accuracy, no spurious changes will come to arise, and no false detection of hotspots will be given.

In order to clarify ultra-low-frequency (ULF) seismomagnetic phenomena, a sensitive geomagnetic network was installed in Kanto, Japan since 2000. In previous studies, we have verified the correlation between ULF magnetic anomalies and local sizeable earthquakes. In this study, we use Molchan’s error diagram to evaluate the potential earthquake precursory information in the magnetic data recorded in Kanto, Japan during 2000–2010. We introduce the probability gain (PG′) and the probability difference (D′) to quantify the forecasting performance and to explore the optimal prediction parameters for a given ULF magnetic station. The results show that the earthquake predictions based on magnetic anomalies are significantly better than random guesses, indicating the magnetic data contain potential useful precursory information. Further investigations suggest that the prediction performance depends on the choices of the distance (R) and size of the target earthquake events (Es). Optimal R and Es are about (100 km, 108.75) and (180 km, 108.75) for Seikoshi (SKS) station in Izu and Kiyosumi (KYS) station in Boso, respectively.

In this work, we assessed the possible relation of ionospheric perturbations observed by Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER), Global Positioning System total electron content (GPS TEC), National Oceanic and Atmospheric Administration (NOAA)-derived outgoing longwave-Earth radiation (OLR), and atmospheric chemical potential (ACP) measurements, with volcanic and Saharan dust events identified by ground and satellite-based medium infrared/thermal infrared (MIR/TIR) observations. The results indicated that the Mt. Etna (Italy) volcanic activity of 2006 was probably responsible for the ionospheric perturbations revealed by DEMETER on 4 November and 6 December and by GPS TEC observations on 4 November and 12 December. This activity also affected the OLR (on 26 October; 6 and 23 November; and 2, 6, and 14 December) and ACP (on 31 October–1 November) analyses. Similarly, two massive Saharan dust episodes, detected by Robust Satellite Techniques (RST) using Spinning Enhanced Visible and Infrared Imager (SEVIRI) optical data, probably caused the ionospheric anomalies recorded, based on DEMETER and GPS TEC observations, over the Mediterranean basin in May 2008. The study confirmed the perturbing effects of volcanic and dust events on tropospheric and ionospheric parameters. Further, it demonstrated the advantages of using independent satellite observations to investigate atmospheric phenomena, which may not always be well documented. The impact of this increased detection capacity in reducing false positives, in the framework of a short-term seismic hazard forecast based on the study of ionospheric and tropospheric anomalies, is also addressed.

The Gutenberg-Richter Law describes the frequency-magnitude distribution of earthquakes. A number of studies have shown that the slope (b value) of the relationship between frequency and magnitude decreased before large earthquakes. In this paper, we investigate the temporal variation of the b value off the Pacific coast of Tokachi, Hokkaido, Japan, during 1990–2014. The magnitude of completeness (Mc) in the catalog is evaluated by combining the maximum curvature (MAXC) technique and the bootstrap approach. Then, the b value, and its uncertainty, is computed by using the maximum likelihood estimation. The Akaike Information Criterion (AIC) with the bootstrap approach is introduced to statistically assess the temporal variation of b values and quantify the significance level. The results show a decrease in trends of the b value prior to two large earthquakes (26 September 2003 (M8.0) and 11 September 2008 (M7.1)) in the analyzed area. In addition, the decrease of b values shows certain statistical significance three months before the 2003 Earthquake off the Pacific coast of Tokachi (M8.0). It is concluded that the b value with statistical assessment may contain potential information for future large earthquake preparation off the Pacific coast of Tokachi, Hokkaido, Japan.

ULF (ultra-low-frequency) electromagnetic emission is recently recognized as one of the most promising candidates for short-term earthquake prediction. This paper reviews previous convincing evidence on the presence of ULF emissions before a few large earthquakes. Then, we present our network of ULF monitoring in the Tokyo area by describing our ULF magnetic sensors and we finally present a few, latest results on seismogenic electromagnetic emissions for recent large earthquakes with the use of sophisticated signal processings.

This study uses a network that is comprised of 10 total intensity magnetometers to detect azimuthal propagation of seismo-magnetic emission waves during 26 earthquakes that occurred between July 2007 and December 2008 in Taiwan. The propagation azimuth and phase velocity of the seismo-magnetic waves are calculated using frequency wavenumber analysis at the ultra low frequency of 0.05 Hz every 30 min. We superimpose the derived azimuths within a moving window of 30 days as the monitored distributions, and the entire dataset as the background distribution. We also find the propagation azimuths of the seismomagnetic anomalies of each earthquake by subtracting the background from the monitored distributions. The results show that frequency wavenumber analysis can be applied to evaluate azimuthal propagation of seismo-magnetic emission waves using a scalar of geomagnetic total intensity fields. The success detection rate of seismo-magnetic anomalies increases from 62% of the 26 earthquakes to 77% using the surface magnetic anomalous reference tip (SMART) to substitute the epicenters. Meanwhile, the odds proportions between the azimuths of the seismomagnetic emission waves towards and away from SMART reveal the associated anomalous propagation.

One of the strongest earthquakes, with magnitude M 8.9, occurred at the sea bottom near to the east coast of Japan on March 11, 2011. This study is devoted to the investigation of anomaly disturbances in the main magnetic field of the Earth and in ultra-low frequency magnetic variations (F

Scientists analyzed temporal variations of local data recorded in Taiwan and reported anomalous reductions in the ionospheric to talelectron content (TEC) on days 4 and 3 be fore (17 and 18 September) the Chi-Chi earthquake (Mw 7.6, ML 7.3), and days 3 and 1 prior to (19 and 21 October) the Chia-Yi earthquake (ML 6.4) in Taiwan. In this paper, we propose a spatial analysis which compares the data recorded inside and outside of the earthquake area around Taiwan to discriminate whether the anomalies are local (earth quake related) or global (non-earth quake related) phenomena. Results suggest that the anomalies appearing day 3 before the Chi-Chi earthquake, and days 3 and 1 before the Chia-Yi earthquake are local (earthquake related) phenomena and the anomaly appearing on 17 September 1999 (day 4 be fore) might be the result of both global phenomena (i.e., a geomagnetic storm) and the local effect of the Chi-Chi earthquake.

Indonesia is one of the most seismically active regions in the world, containing numerous active volcanoes and subject to frequent earthquakes with epicenters distributed along the same regions as volcanoes. In this paper, a case study is carried out to investigate pre-earthquake ionospheric anomalies in total electron content (TEC) during the Sulawesi earthquakes of 1993 - 2002, and the Sumatra-Andaman earthquake of 26 December 2004, the largest earthquake in the world since 1964. It is found that the ionospheric TECs remarkably decrease within 2 - 7 days before the earthquakes, and for the very powerful Sumatra-Andaman earthquake, the anomalies extend up to about 1600 km from the epicenter.

Indonesia is one of the most seismically active regions in the world, containing numerous active volcanoes and subject to frequent earthquakes with epicenters distributed along the same regions as volcanoes. In this paper, a case study is carried out to investigate pre-earthquake ionospheric anomalies in total electron content (TEC) during the Sulawesi earthquakes of 1993 - 2002, and the Sumatra-Andaman earthquake of 26 December 2004, the largest earthquake in the world since 1964. It is found that the ionospheric TECs remarkably decrease within 2 - 7 days before the earthquakes, and for the very powerful Sumatra-Andaman earthquake, the anomalies extend up to about 1600 km from the epicenter.