Lithosphere–Atmosphere–Ionosphere Coupling Effects Based on Multiparameter Precursor Observations for February–March 2021 Earthquakes (M~7) in the Offshore of Tohoku Area of Japan

The purpose of this paper is to discuss the lithosphere–atmosphere–ionosphere coupling (LAIC) effects with the use of multiparameter precursor observations for two successive Japanese earthquakes (EQs) (with a magnitude of around 7) in February and March 2021, respectively, considering a seemingly significant difference in seismological and geological hypocenter conditions for those EQs. The second March EQ is very similar to the famous 2011 Tohoku EQ in the sense that those EQs took place at the seabed of the subducting plate, while the first February EQ happened within the subducting plate, not at the seabed. Multiparameter observation is a powerful tool for the study of the LAIC process, and we studied the following observables over a 3-month period (January to March): (i) ULF data (lithospheric radiation and ULF depression phenomenon); (ii) ULF/ELF atmospheric electromagnetic radiation; (iii) atmospheric gravity wave (AGW) activity in the stratosphere, extracted from satellite temperature data; (iv) subionospheric VLF/LF propagation data; and (v) GPS TECs (total electron contents). In contrast to our initial expectation of different responses of anomalies to the two EQs, we found no such conspicuous differences of electromagnetic anomalies between the two EQs, but showed quite similar anomaly responses for the two EQs. It is definite that atmospheric ULF/ELF radiation and ULF depression as lower ionospheric perturbation are most likely signatures of precursors to both EQs, and most importantly, all electromagnetic anomalies are concentrated in the period of about 1 week–9 days before the EQ to the EQ day. There seems to exist a chain of LAIC process (cause-and-effect relationship) for the first EQ, while all of the observed anomalies seem to occur nearly synchronously in time for the send EQ. Even though we tried to discuss possible LAIC channels, we cannot come to any definite conclusion about which coupling channel is plausible for each EQ.

Feasibility analysis of GNSS-based ionospheric observation on a fast-moving train platform (GIFT)

The ionospheric effect plays a crucial role in the radio communications. For ionospheric observing and monitoring, the Global Navigation Satellite System (GNSS) has been widely utilized. The ionospheric condition can be characterized by the Total Electron Contents (TEC) and TEC Rate (TECR) calculated from the GNSS measurements. Currently, GNSS-based ionospheric observing and monitoring largely depend on a global fiducial network of GNSS receivers such as the International GNSS Service (IGS) network. We propose a new approach to observe the ionosphere by deploying a GNSS receiver on a Hong Kong Mass Transit Railway (MTR) train. We assessed the TECR derived from the MTR-based GNSS receiver by comparing it with the TECR derived from a static GNSS receiver. The results show that the Root-Mean-Squares (RMS) errors of the TECR derived from the MTR-based GNSS receiver is consistently approximately 23% higher than that derived from the static GNSS receiver. Despite the increased error, the findings suggest that the GNSS observation on a fast-moving platform is a feasible approach to observe the ionosphere over a large region in a rapid and cost-effective way.

Co-Seismic Ionospheric Disturbance with Alaska Strike-Slip Mw7.9 Earthquake on 23 January 2018 Monitored by GPS

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.

Regional Ionosphere Mapping Using Zero Difference GPS Carrier Phase

Ionospheric delay, can be derived from dual frequency GNSS signals, and then converted into the Vertical Total Electron Contents (VTEC) along the signal path. Various models were devised to calculate VTEC. Examples of such models are the polynomial function model and spherical harmonics model. A common hypothesis of these models is that they are constructed based on the assumption that the entire electron content in the ionosphere is concentrated in a single thin shell at a selected height above Earth. The primary goal of the current research to develop an algorithm capable of producing VTEC maps on an hourly basis, using carrier phase observations from dual frequency GPS receiver. The developed algorithm uses a single GPS station (Zero-difference) to map VTEC over a regional area. The carrier phase measurements are much more precise than the code pseudorange measurements, but they contain an ambiguous term. If such ambiguities are fixed, thence the carrier phase measurements become as unambiguous pseudoranges, but accurate at the level of few millimeters. In current research Sequential Least Square Adjustment (SLSA) was considered to fix ambiguity term in carrier phase observations. The proposed algorithm was written using MATLAB and Called (ZDPID). Two GPS stations (ANKR and BSHM) were used from IGS network to evaluate the developed code, VTEC values were estimated over these two stations. Results of the proposed algorithm were compared with the Global Ionosphere Maps (GIMs), which is generally used as a reference. The results show that the mean difference between VTEC from GIM and estimated VTEC at ANKR station is ranging from −2.1 to 3.67 TECU and its RMS is 0.44. The mean difference between VTEC from GIM and estimated VTEC at BSHM station is ranging from −0.29 to 3.65 TECU and its RMS is 0.38. Another three GPS stations in Egypt were used to generate regional ionosphere maps over Nile Delta, Egypt. The mean differences between VTEC from GIM and estimated VTEC at SAID station is ranging from −1.1 to 3.69 TECU and its RMS is 0.37, from −1.29 to 3.27 TECU for HELW station with RMS equal 0.39, and from 0.2 to 4.2 TECU for BORG station with RMS equal 0.46. Therefore, the proposed algorithm can be used to estimate VTEC efficiently.

Review of variations in <i>M</i>_w < 7 earthquake motions on position and tec (<i>M</i>_w = 6.5 aegean sea earthquake sample)

Turkey is a country located in Middle Latitude zone and in which tectonic activity is intensive. Lastly, an earthquake of magnitude 6.5Mw occurred at Aegean Sea offshore on date 24 May 2014 at 12:25 UTC and it lasted approximately 40 s. The said earthquake was felt also in Greece, Romania and Bulgaria in addition to Turkey. In recent years seismic origin ionospheric anomaly detection studies have been done with TEC (Total Electron Contents) generated from GNSS (Global Navigation Satellite System) signals and the findings obtained have been revealed. In this study, TEC and positional variations have been examined seperately regarding the earthquake which occurred in the Aegean Sea. Then The correlation of the said ionospheric variation with the positional variation has been investigated. For this purpose, total fifteen stations have been used among which the data of four numbers of CORS-TR stations in the seismic zone (AYVL, CANA, IPSA, YENC) and IGS and EUREF stations are used. The ionospheric and positional variations of AYVL, CANA, IPSA and YENC stations have been examined by Bernese 5.0v software. When the (PPP-TEC) values produced as result of the analysis are examined, it has been understood that in the four stations located in Turkey, three days before the earthquake at 08:00 and 10:00 UTC, the TEC values were approximately 4 TECU above the upper limit TEC value. Still in the same stations, one day before the earthquake at 06:00, 08:00 and 10:00 UTC, it is being shown that the TEC values were approximately 5 TECU below the lower limit TEC value. On the other hand, the GIM-TEC values published by the CODE center have been examined. Still in all stations, it has been observed that three days before the earthquake the TEC values in the time portions of 08:00 and 10:00 UTC were approximately 2 TECU above, one day before the earthquake at 06:00, 08:00 and 10:00 UTC, the TEC values were approximately 4 TECU below the lower limit TEC value. Again, by using the same fifteen numbers of stations, positional variation investigation before and after the earthquake has been made for AYVL, CANA, IPSA and YENC stations. As result of the analysis made, positional displacements has been seen before and after earthquake at CANA station which is the nearest station to earthquake center. It is about 10 and 3 cm before three days and one day earthquake.