Search Results (6)

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

Previous earthquake polarization (as the ratio of vertical and horizontal components) studies using geomagnetic data were all performed with ground data. The advantage of satellite data is that it is not limited by geography. Therefore, in this work, we tried to select 12 typical earthquakes in Northeast Asia with Ms > 5.0 and an epicenter depth ≤ 40 km within the longitude 105° E–145° E and latitude 38° N–58° N ranges from December 2018 to January 2023 for analysis by using the satellite data of the high-precision magnetometer (HPM) payload onboard the China Seismo-Electromagnetic Satellite (CSES) for the first time in a quiet magnetic environment. The geomagnetic three-component vector data were investigated, and the minimum study period was divided into 10 s intervals. Fourier transform was performed to obtain 0.01–0.2 Hz geomagnetic three-component dynamic spectra, and the time series of the polarization (as the ratio of vertical and horizontal components) data was then obtained. The average value of the polarization data over four years was used to obtain the time series of the polarization perturbation amplitude, after which joint research was conducted. The results showed that (1) earthquakes with larger magnitudes are more likely to exhibit anomaly perturbations recorded by satellites; (2) among all earthquakes with anomalies, the horizontal east–west component perturbation is the largest, the vertical component perturbation is the smallest, and the east–west component may be the dominant component in seismic anomaly observations; (3) the applicability of the polarization method to space-based earthquake-related data is limited; (4) the perturbation amplitude of polarization data can be used as a reference for extracting seismic anomalies; and (5) ion velocity Vx data from the plasma analyzer package (PAP) can be considered to approximately verify the physical mechanism of the anomaly perturbation of the horizontal component in the ionospheric magnetic field, and the two kinds of data (PAP and HPM) can be combined in seismic prediction research. Full article

This research examines the correlation between seismic activity and variations in ionospheric electron density (Ne) using the data from the Langmuir probe (LAP) onboard the China Seismo-Electromagnetic Satellite (CSES) during nighttime. Statistical analysis of Ms ≥ 6.8 earthquakes that occurred globally between August 2018 and March 2023 is conducted, as well as Ms ≥ 6.0 earthquakes in China during the same period, using the quartile analysis method for fixed revisiting orbits. The main conclusions are that: (1) the larger the magnitude of the earthquake, the more anomalous the phenomena that appear; (2) the anomalies on the east side of the epicenter are significantly higher than those on the west side, and the anomalies in the Northern Hemisphere are mostly distributed southward from the epicenter, while those in the Southern Hemisphere are mostly distributed northward from the epicenter; (3) anomalies appear with a higher frequency on several specific time intervals, including the day of the earthquake (likely co-seismic effect) and 2, 7, and 11 days before the earthquake (possible precursor candidates); and (4) for the 15 earthquakes of Ms ≥ 6.0 in China over the past five years, anomalous Ne mainly occurred southwest of the epicenter, with the highest frequency observed 5 days before the earthquake, and there were continuous anomalous phenomena between 9 days and 5 days before the earthquake. This study concludes that Ne, measured by CSES, can play a fundamental role in studying earthquake-related ionospheric disturbances. Full article

On 6 February 2023, a powerful earthquake at the border between Turkey and Syria caused catastrophic consequences and was, unfortunately, one of the deadliest earthquakes of the recent decades. The moment magnitude of the earthquake was estimated to be 7.8, and it was localized in the Kahramanmaraş region of Turkey. This article aims to investigate the behavior of more than 50 different lithosphere–atmosphere–ionosphere (LAI) anomalies obtained from satellite data and different data services in a time period of about six months before the earthquake to discuss the possibility of predicting the mentioned earthquake by an early warning system based on various geophysical parameters. In this study, 52 time series covering six months of data were acquired with: (i) three identical satellites of the Swarm constellation (Alpha (A), Bravo (B) and Charlie (C); and the analyzed parameters: electron density (Ne) and temperature (Te), magnetic field scalar (F) and vector (X, Y and Z) components); (ii) the Google Earth Engine (GEE) platform service data (including ozone, water vapor and surface temperature), (iii) the Giovanni data service (including the aerosol optical depth (AOD), methane, carbon monoxide and ozone); and (iv) the USGS earthquake catalogue (including the daily seismic rate and maximum magnitude for each day), around the location of the seismic event from 1 September 2022 to 17 February 2023, and these were analyzed. The results show that the number of seismic anomalies increased since about 33 days before the earthquake and reached a peak, i.e., the highest number, one day before. The findings of implementing the proposed predictor based on the Mamdani fuzzy inference system (FIS) emphasize that the occurrence of a powerful earthquake could be predicted from about nine days to one day before the earthquake due to the clear increase in the number of seismo-LAI anomalies. However, this study has still conducted a posteriori, knowing the earthquake’s epicenter and magnitude. Therefore, based on the results of this article and similar research, we emphasize the urgency of the creation of early earthquake warning systems in seismic-prone areas by investigating the data of different services, such as GEE, Giovanni and various other global satellite platforms services, such as Swarm. Finally, the path toward earthquake prediction is still long, and the goal is far, but the present results support the idea that this challenging goal could be achieved in the future. Full article

In this study, we conduct a correlation analysis between the daily occurrence times of the increase and decrease anomalies in the global total electron content (TEC) in the ionosphere, and the daily earthquake energy release within 110–130°E longitude over the following three latitude regions: A: 13°S–0.5°S (22.3°S–10°S geomagnetic), B: 0.5°S–19.5°N (10°S–10°N geomagnetic), and C: 19.5°N–32.1°N (10°N–22.5°N geomagnetic). The TEC data from global ionosphere maps (GIMs) during earthquake events of M ≥ 2.5 that occurred in 2015–2018 are used in this study. The time series of daily seismic wave energy releases within the three regions and the daily occurrence times of the TEC anomalies in each GIM grid are computed. By time-shifting the time series, the correlations are calculated and compared globally, and the temporal characteristics are also examined. The disturbance storm time (Dst) index, planetary geomagnetic index Kp, and daily observed 10.7 cm solar flux (F10.7) are used to remove data associated with space weather variations. Although the seismo-ionospheric precursor is not confirmed by the statistical investigations, the greater occurrence times of TEC decrease anomalies are observed in the southeast in Region A, and the conjugate point 13 days prior to a M6.9 earthquake in Region A, which occurred on 5 August 2018, in accordance with the statistical results. Therefore, it is required to apply more parameters to understand the causes of the ionospheric TEC variations and investigate whether ionospheric variations are caused by earthquakes. Full article

Changes in the underlying conductivity around hypocenters are generally considered one of the promising mechanisms of seismo-electromagnetic anomaly generation. Parkinson vectors are indicators of high-conductivity materials and were utilized to remotely monitor conductivity changes during the M_W 6.5 Jiuzhaigou earthquake (103.82°E, 33.20°N) on 8 August 2017. Three-component geomagnetic data recorded in 2017 at nine magnetic stations with epicenter distances of 63–770 km were utilized to compute the azimuths of the Parkinson vectors based on the magnetic transfer function. The monitoring and background distributions at each station were constructed by using the azimuths within a 15-day moving window and over the entire study period, respectively. The background distribution was subtracted from the monitoring distribution to mitigate the effects of underlying inhomogeneous electric conductivity structures. The differences obtained at nine stations were superimposed and the intersection of a seismo-conductivity anomaly was located about 70 km away from the epicenter about 17 days before the earthquake. The anomaly disappeared about 7 days before and remained insignificant after the earthquake. Analytical results suggested that the underlying conductivity close to the hypocenter changed before the Jiuzhaigou earthquake. These changes can be detected simultaneously by using multiple magnetometers located far from the epicenter. The disappearance of the seismo-conductivity anomaly after the earthquake sheds light on a promising candidate of the pre-earthquake anomalous phenomena. Full article