Swarm-TEC Satellite Measurements as a Potential Earthquake Precursor Together With Other Swarm and CSES Data: The Case of Mw7.6 2019 Papua New Guinea Seismic Event

Abstract

On May 14, 2019, a strong Mw = 7.6 shallow earthquake occurred in Papua New Guinea. This paper explores for the first time the analysis of total electron content (TEC) products measured for 6 months by GPS antenna onboard Swarm satellites, to detect possible seismo-ionospheric anomalies around the time and location of the above-mentioned earthquake. The night-time vertical total electron content (VTEC) time series measured using Swarm satellites Alpha and Charlie, inside the earthquake Dobrovolsky’s area show striking anomalies 31 and 35 days before the event. We successfully verified the possible presence of concomitant anomalous values of in situ electron density detected by the new Chinese satellite dedicated to search for electromagnetic earthquake precursors [China Seismo-Electromagnetic Satellite (CSES)-01]. On the other hand, the analysis of VTEC night time measured by Swarm Bravo shows gradual and abnormal increase of the VTEC parameter from about 23 days before the earthquake, which descends 3 days before the earthquake and reaches its lowest level around the earthquake day. We also analyzed the time series and tracks of other six in situ parameters measured by Swarm satellites, electron density from CSES, and also GPS-TEC measurements. As it is expected from the theory, the electron density anomalous variations acknowledge the Swarm VTEC anomalies, confirming that those anomalies are real and not an artifact of the analysis. The comparative analysis with measurements of other Swarm and CSES sensors emphasizes striking anomalies about 2.5 weeks before the event, with a clear pattern of the whole anomalies typical of a critical system as the earthquake process is for Earth. A confutation analysis outside the Dobrovolsky area and without significant seismicity shows no anomalies. Therefore based on our study, the VTEC products of Swarm satellites could be an appropriate precursor aside from the other measured plasma and magnetic parameters using Alpha, Bravo, and Charlie Swarm and CSES satellites that can be simultaneously analyzed to reduce the overall uncertainty.

Developing a Fuzzy Inference System Based on Multi-Sensor Data to Predict Powerful Earthquake Parameters

“…We also analysed as another case study an M w = 7.3 strong earthquake that took place at 18:18:17 UTC (LT = 21:22:07) on 12 November 2017 along the border region between Iran and Iraq close to the town of Sarpol-e Zahab (34.911 • N, 45.959 • E, 19.00 km depth) [25]. The third analysed earthquake had a magnitude M w = 7.6 and happened at 12:58:25 UTC (LT = 23:08:48) on 14 May 2019, 46 km South-Southeast of Namatanai in Papua New Guinea (4.051 • S, 152.597 • E) at a shallow estimated depth of about 10 km [26]. The fourth strong earthquake of M w = 7.1 occurred at 14:07:50 UTC (LT = 23:34:55) on 13 February 2021 near the east coast of Honshu, Japan (37.727 • N, 141.775 • E, 44 km depth) as the result of thrust faulting near the subduction zone interface plate boundary between the Pacific and North America plates [23].…”

“…It is seen that 50, 47, 61, 58, and 51 precursors were investigated for Ecuador, Iran, Papua New Guinea, Japan and Haiti earthquakes, respectively. The details of the investigated data and implemented methods are found in [23][24][25][26]. As mentioned before in the methodology section, the Dx values for all detected anomalies during the quiet solar and geomagnetic activities were obtained and applied as input data for the proposed fuzzy inference system.…”

Quick Report of the ML=3.3 on 1 January 2023 Guidonia (Rome, Italy) Earthquake: Evidence of a Seismic Acceleration

“…Swarm mission is composed by three identical satellites in low Earth quasipolar orbits, called Alpha, Bravo and Charlie aiming to measure the geomagnetic field with the best precision available at the state of art [19]. The use of Swarm data to study the preparation of the earthquakes has been explored by several researches in the last years using a single case study approach [18,[20][21][22][23][24][25][26][27][28][29][30][31] or even statistically correlating the magnetic and electron density anomalies of Swarm with M5.5+ earthquakes occurred in the first 4.7 years of Swarm mission by De Santis et al [32], the first 8 years by Marchetti et al [33] or using Machine Learning by Xiong et al [34].…”

Statistical analysis of electric field perturbations in ELF based on the CSES observation data before the earthquake

“…On 2 February 2018, China's first seismic electromagnetic monitoring test satellite, the CSES, was successfully launched. It has been operating for more than 4 years now, and researchers have used its observed data to conduct a large number of scientific experiments (Ambrosi et al, 2018;Cao et al, 2018;Marchetti et al, 2020;Piersanti et al, 2020;Shen et al, 2018;Ouyang et al, 2019;Huang et al, 2021;Akhoondzadeh et al, 2022). Researchers verified that the CSES and its payload functioned properly after launch by different scientific methods (Huang et al, 2018;Lin et al, 2018;Scotti and Osteria, 2019;Diego et al, 2020); On 25 August 2018, the CSES was hit by the first geomagnetic solid storm event since its launch, Yang et al (2020) verified the excellent performance of the CSES and its corresponding payloads by performing a joint analysis with other detectors such as the Swarm satellite; Li et al (2020) compared the ion and electron densities observed by the DEMETER and the CSES by comparing different parameters and time resolutions, showing that the CSES can effectively follow ionospheric perturbations; Nepeina (2021) used data from the CESE to observe the relationship between space weather and earthquakes occurring in seismically active regions, compared the changes in ground-based geomagnetic or electromagnetic sounding data, and concluded that the results of the comparison could be used in future short-term earthquake prediction techniques.…”