Search Results (8)

With the rapid development of global navigation satellite systems (GNSS) and their increasingly wide range of applications in atmospheric science, total electron content (TEC) data are widely used in the theoretical study of layer coupling related to seismicity. This study detected and analyzed pre-earthquake ionospheric anomalies (PEIA) by using TEC data from the Royal Observatory of Belgium (ROB), and analyzed coseismic ionospheric disturbance (CID) with vertical TEC (VTEC) from the GPS stations in earthquake preparation areas. The results show that PEIA appear to increase continuously from 08:00–12:00 UT in the 3 days before a seismic swarm of Mw > 5.0. The ionosphere over the seismogenic zones exhibited large-scale anomalies when multiple seismogenic zones of the Balkan Peninsula spatially and temporally overlapped. Moreover, the TEC around the earthquake centers showed a positive anomaly lasting for 7 h. In a single seismogenic zone in Greece, the TEC around the earthquake center reached over +3.42 TECu. In addition, the CID observed from GPS stations shows that with the increase in the number of earthquakes, the ionosphere over the seismogenic area is more obviously disturbed, and after three strong earthquakes, TEC suddenly decreased over the seismogenic area and formed a phenomenon similar to an ionospheric hole. We conclude that a lithosphere–atmosphere–ionosphere coupling mechanism existed before the seismic swarm appeared in the Balkan Peninsula. Earthquake-induced VTEC anomalies occurred more frequently within a 3–10 day window before the earthquake. This phenomenon is particularly evident when multiple seismogenic zones overlap spatiotemporally. Full article

Ionospheric disturbances caused by the 2016 West Sumatra earthquake have been studied using total electron content (TEC) measurements by Global Navigation Satellite System (GNSS) observation stations evenly distributed in Sumatra and Java, Indonesia. Previous observation focused on the coseismic ionospheric disturbances (CID) detected 11–16 min after the earthquake. The maximum TEC amplitude measured was 2.9 TECU (TEC Unit) with speed between 1 and 1.72 km/s. A comprehensive analysis needs to be done to see how the growth and direction of the movement of the CID due to the earthquake is using the 3D tomography method. The dimensions of 3D tomographic model are setup to 1° × 1.2° × 75 km. The continuity constraints were used to stabilize the solution, and multiple resolution tests with synthetic data were conducted to evaluate the precision of the results. This research focuses on the anomalous movement of the ionosphere observed in three dimensions. From the model, the positive anomaly initially appeared 11 min after the earthquake at the altitude of 300 km, which is the highest ionization layer and correspond to the electron density profile using IRI model. The anomalous movement appeared 12 min after the mainshock and moved 1° toward the geomagnetic field every minute. The density anomaly of the ionosphere began to weaken 8 min after the appearance of CID. To check the accuracy of the 3D tomography model, we carried out two types of tests, namely checkerboard resolution test and the second resolution test. Full article

The current tsunami early warning systems always issue alarms once large undersea earthquakes are detected, inevitably resulting in false warnings since there are no deterministic scaling relations between earthquake size and tsunami potential. In this paper, we assess tsunami potential by analyzing co-seismic ionospheric disturbances (CIDs). We examined CIDs of three megathrusts (the 2014 M_w 8.2 Iquique, the 2015 M_w 8.3 Illapel, and the recent 2021 M_w 8.2 Alaska events) as detected by Global Navigation Satellite System (GNSS) observations. We found that CIDs near the epicenter generated by the 2021 M_w 8.2 Alaska event were significantly weaker than those of the two Chilean events, despite having similar earthquake magnitudes. The propagation direction of CIDs from the M_w 8.2 Alaska earthquake further revealed ruptures toward the deeper seismogenic zone, implying less seafloor uplift and hazardous flooding. Our work sheds light on incorporating GNSS-based CIDs for more trustworthy tsunami warning systems. Full article

The study of ionospheric disturbances associated with the two large strike-slip earthquakes in Indonesia was investigated, which are West Sumatra on 2 March 2016 (Mw = 7.8), and Palu on 28 September 2018 (Mw = 7.5). The anomalies were observed by measuring co-seismic ionospheric disturbances (CIDs) using the Global Navigation Satellite System (GNSS). The results show positive and negative CIDs polarization changes for the 2016 West Sumatra earthquake, depending on the position of the satellite line-of-sight, while the 2018 Palu earthquake shows negative changes only due to differences in co-seismic vertical crustal displacement. The 2016 West Sumatra earthquake caused uplift and subsidence, while the 2018 Palu earthquake was dominated by subsidence. TEC anomalies occurred about 10 to 15 min after the two earthquakes with amplitude of 2.9 TECU and 0.4 TECU, respectively. The TEC anomaly amplitude was also affected by the magnitude of the earthquake moment. The disturbance signal propagated with a velocity of ~1–1.72 km s⁻¹ for the 2016 West Sumatra earthquake and ~0.97–1.08 km s⁻¹ for the 2018 Palu mainshock earthquake, which are consistent with acoustic waves. The wave also caused an oscillation signal of ∼4 mHz, and their azimuthal asymmetry of propagation confirmed the phenomena in the Southern Hemisphere. The CID signal could be identified at a distance of around 400–1500 km from the epicenter in the southwestern direction. Full article

The Mw7.9 Alaska earthquake at 09:31:40 UTC on 23 January 2018 occurred as the result of strike slip faulting within the shallow lithosphere of the Pacific plate. Global positioning system (GPS) data were used to calculate the slant total electron contents above the epicenter. The singular spectrum analysis (SSA) method was used to extract detailed ionospheric disturbance information, and to monitor the co-seismic ionospheric disturbances (CIDs) of the Alaska earthquake. The results show that the near-field CIDs were detected 8–12 min after the main shock, and the typical compression-rarefaction wave (N-shaped wave) appeared. The ionospheric disturbances propagate to the southwest at a horizontal velocity of 2.61 km/s within 500 km from the epicenter. The maximum amplitude of CIDs appears about 0.16 TECU (1TECU = 10¹⁶ el m⁻²) near the epicenter, and gradually decreases with the location of sub-ionospheric points (SIPs) far away from the epicenter. The attenuation rate of amplitude slows down as the distance between the SIPs and the epicenter increases. The direction of the CIDs caused by strike-slip faults may be affected by the horizontal direction of fault slip. The propagation characteristics of the ionospheric disturbance in the Alaska earthquake may be related to the complex conditions of focal mechanisms and fault location. Full article

Earthquakes generate energy that propagates into the ionosphere and incurs co-seismic ionospheric disturbances (CIDs), which can be observed in ionospheric delay measurements. In most cases, the CID has a weak signal strength, because the energy in the atmosphere transferred from the earthquake dissipates as it travels toward the ionosphere. It is particularly hard to observe at reference stations that are located far from the epicenter. As the number of Global Navigation Satellite System stations and their positions are restricted, it is important to employ weak CID data in the analysis by improving the detection performance of CIDs. In this study, we suggest a new method of detecting CIDs, which mainly uses a sequential measurement combination of the carrier phase-based ionospheric delay data, with a 1-second interval. The proposed method’s performance was compared with conventional methods, including band-pass filters and a representative time-derivative method, using data from the 2011 Tohoku earthquake. As a result, the maximum CID-to-noise ratio can be increased by a maximum of 13% when the proposed method is used, and consequently, the detection performance of the CID can be improved. Full article

In order to study the coupling relationship between large earthquakes and the ionosphere, the techniques of ionosphere data acquisition were refined by the Crustal Movement Observation Network of China (CMONOC) to detect the pre-earthquake ionospheric abnormal and coseismic ionospheric disturbances (CID) of the Mw 6.6 Lushan earthquake on 20 April 2013. Based on the regional ionosphere maps (RIMs) derived from the Global Positioning System (GPS) observations of CMONOC, the ionospheric local effects near the epicenter of the Lushan earthquake one month prior to the shock were analyzed. The results show that the total electron content (TEC) anomalies appeared 12–14 (6–8 April), 19 (1 April), and 25–27 (24–26 March) days prior to the Lushan earthquake, which are defined as periods 1, 2, and 3, respectively. Multi-indices including the ring current index (Dst), geomagnetic planetary (Kp) index, wind plasma speed (Vsw) index, F10.7, and solar flares were utilized to represent the solar–terrestrial environment in different scales and eliminate the effects of solar and geomagnetic activities on the ionosphere. After the interference of solar–terrestrial activity and the diurnal variation in the lower thermosphere were excluded, the TEC variations with obvious equatorial ionospheric anomaly (EIA) in period-1 were considered to be related to the Lushan earthquake. We further retrieved precise slant TECs (STECs) near the epicenter to study the coseismic ionospheric disturbance (CID). The results show that there was clear STEC disturbance occurring within half an hour after the Lushan earthquake, and the CID propagation distance was less than the impact radius of the Lushan earthquake (689 km). The shell models with different altitudes were adopted to analyze the propagation speed of the CID. It is found that at the F2-layer with the altitude of 277 km, which had a CID horizontal propagation velocity of 0.84 ± 0.03 km/s, was in accordance with the acoustic wave propagation velocity. The calculated velocity acoustic wave from the epicenter to the ionospheric pierce points of this shell model was about 0.53 ± 0.03 km/s, which was also consistent with its actual velocity within the altitude of 0–277 km. Affected by the geomagnetic field, the CID mainly propagated along the southeast direction at the azimuth of 190°, which was almost parallel to the local magnetic line. Full article

Big earthquakes often excite the acoustic resonance between the earth’s surface and the lower atmosphere. The perturbations can propagate upward into the ionosphere and trigger ionospheric anomalies detected by dual-frequency GPS observations, but coseismic ionospheric disturbance (CID) directivity and mechanism are not clear. In this paper, the ionospheric response to the Mw = 7.9 Alaska earthquake on 23 January 2018 is investigated from about 100 continuous GPS stations near the epicenter. The fourth-order zero-phase Butterworth band-pass filter with cutoffs of 2.2 mHz and 8 mHz is applied to obtain the ionospheric disturbances. Results show that the CIDs with an amplitude of up to 0.06 total electron content units (TECU) are detected about 10 min after the Alaska earthquake. The CIDs are as a result of the upward propagation acoustic waves triggered by the Rayleigh wave. The propagation velocities of TEC disturbances are around 2.6 km/s, which agree well with the wave propagation speed of 2.7 km/s detected by the bottom pressure records. Furthermore, the ionospheric disturbances following the 2018 Mw = 7.9 Alaska earthquake are inhomogeneous and directional which is rarely discussed. The magnitude of ionospheric disturbances in the western part of the epicenter is more obvious than in the eastern part. This phenomenon also corresponds to the data obtained from the seismographs and bottom pressure records (BPRs) at the eastern and western side of the epicenter. Full article