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The dual frequency Global Navigation Satellite System (GNSS) observations could determine the total electron content (TEC) in the ionosphere. In this study, GNSS TEC was applied to detect traveling ionospheric disturbances (TIDs) after the eruption of Hunga Tonga–Hunga Ha'apai (HTHH) on 15 January 2022. The eruption caused two types of tsunamis, first is tsunami generated by atmospheric wave (meteo‐tsunami) and second is caused by eruption induces water displacement or tsunami classic. At the same time with former tsunami, the atmospheric wave (shock and lamb waves) also caused TIDs at a speed of approximately ∼0.3 km/s. We found moderate correlation between this TIDs amplitude and the tsunami wave height model from tide gauge stations in New Zealand (0.64) and Australia (0.65). Further we attempted to reveal 3D structure of the TIDs in New Zealand, South Australia, and Philippines using 3D tomography. The tomography was set up > 1,170 blocks, as large as 1.0° (east–west) × 1.0° (north–south) × 100 km (vertical), up to 600 km altitude over selected regions. Tomogram shows beautiful concentric directivity of the first TIDs generated by atmospheric wave (AW). Key Points: 3D ionospheric disturbances during the 2022 Tonga eruption was investigated with spatial and temporal directionThe highest concentration of the electron disturbances was observed at an altitude of 200–300 km, which decreased at 500–600 kmA correlation between ionospheric disturbances and the height of tsunami associated with eruption was observed [ABSTRACT FROM AUTHOR]

Ionosphere is part of the atmospheric layer located between 50 to 1000 km above the earth's surface which consists of electrons that can influence the propagation of electromagnetic waves in the form of additional time in signal propagation, this depends on Total Electron Content (TEC) in the ionosphere and frequency GPS signal. In high positioning precision with GPS, the effect of the ionosphere must be estimated so that ionospheric correction can be determined to eliminate the influence of the ionosphere on GPS observation. Determination of ionospheric correction can be done by calculating the TEC value using dual frequency GPS data from reference stations or models. In making the TEC model, a polynomial function is used for certain hours. The processing results show that the maximum TEC value occurs at noon at 2:00 p.m. WIB for February 13, 2018 with a value of 35,510 TECU and the minimum TEC value occurs in the morning at 05.00 WIB for February 7, 2018 with a value of 2,138 TECU. The TEC model spatially shows the red color in the area of Surabaya and its surroundings for the highest TEC values during the day around 13.00 WIB to 16.00 WIB.

Variometric Approach for Standalone Engine Displacement Analysis (VADASE) is a technique used in seismology purposes using GPS measurements. VADASE is used to determine the small displacement from the earthquake. The VADASE L1 solution is using the klobuchar ionospheric model. In this study VADASE was used in earthquakes with magnitudes> 7 to> 9 righter scales. In the scale of the earthquake category> 9 used Indian Ocean earthquake of December 26, 2016 with the strength of 9.1 SR by using the closest SAMP station and the Japanese Tohoku earthquake of March 11, 2011 with a power of 9.1 SR using 4 different stations namely MIZU, KMSV, TSK2 and Knii . The earthquake category with a scale of> 8 SR is the offshore earthquake Bio Bio, Chile on February 27, 2010 with a power of 8.8 SR using 2 stations namely ANTC and SANT, the Bengkulu Indonesia earthquake on 12 September 2007 with a power of 8.4 SR using the SAMP station, an illaper earthquake, chile September 16 2015 with 8.3 SR using SANT station, and Tres Piscos earthquake Mexico on September 8, 2017 with a power of 8.2 SR using IENG station. Earthquake with a strength of> 7 SR, namely the amberlay-New Zealand earthquake on November 13, 2016 with a strength of 7.8 SR using MRLL and WGTN stations, Puerto quello-chile earthquake on December 25, 2016 with a strength of 7.6 SR using COYQ station, Java sea earthquake -Indonesia on 8 August 2007 with 7.5 SR power using BAKO station and ayula mexico earthquake on 19 september 2017 with 7.1 SR power using INEG station. From the results of VADASE, the farthest distance from the epicenter to the observation station is 1100 km (INEG station) and the closest distance is 95 km (BAKO station). The highest speed is 0.12 m / s after 5 minutes from the earthquake in the earthquake Offshore Bio Bio-Chile 2010 uses the SANT station and the lowest speed is 0.006 m / s after 10 minutes from the earthquake in the 2007 Bengkulu earthquake using the SAMP station. Whereas in the other earthquakes was the 2011 Tohoku earthquake with a speed of 0.06 m / s after 1 minute using MIZU station, the amberley-New Zealand earthquake 2016 with a speed of 0.015 m / s after 1 minute using the MRLI satellite, Puerto quelloearthquake Chile 2016 with a speed of 0.025 m / s after 40 minutes using the COYQ satellite.

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. [ABSTRACT FROM AUTHOR]

Preliminary research analyzed the Coseismic Ionospheric Disturbances (CIDs) of the strikeslip earthquake that occurred in Palu on September 28, 2018 (Mw = 7.5) and the materialization of a TEC anomaly with an amplitude of 0.4 TECU approximately 10–15 min later. The TEC anomaly amplitude is also affected by the magnitude of the earthquake moment; therefore, 3D analysis is needed to determine the spatial distribution of the ionospheric disturbances. This research aims to analyze the ionospheric disturbance of an earthquake in 3D using the Global Navigation Satellite System (GNSS) from the Geospatial Information Agency (BIG) or InaCORS stations spread over Sulawesi, Kalimantan, West Nusa Tenggara, East Nusa Tenggara, Bali, and Java with a 30 s sampling interval using GLONASS and GPS satellites. The checkerboard accuracy test was also carried out to evaluate the reliability of the 3D tomography model. The result showed that CIDs occur to the north and south of the epicenter around the equator, following the N-S Asymmetry theory. Furthermore, the tomography results indicate the presence of dominant and positive anomaly values at an altitude of 300–500 km. This follows the characteristics of variations in the ionosphere layer, where an altitude of 300–500 km is included in the F layer. The dominant anomaly at an altitude of 300 km is in accordance with the theory of the ionosphere’s height, which experiences maximum ionization at an altitude of ~300 km (F layer) by Chapman’s profile. We also conducted preseismic [ABSTRACT FROM AUTHOR]

Ionospheric Tsunami Power Index (ITPI) has been proposed for tsunami detection. The index is derived from Total Electron Content (TEC) Global Navigation Satellite System (GNSS) data. The ITPI method already used for tsunami detection is limited to two earthquake cases. Therefore, the method needs to be tested before implementing the ITPI method operationally. ITPI testing was conducted for nine tsunami events in Indonesia. The test shows that ITPI can detect tsunami effects on the ionosphere. There are four of nine tsunami events that can be detected with ITPI consistently. The five ITPI tsunami events could not be detected. It is caused by the TEC data being too far from the tsunami epicentre and local tsunamis caused by landslides. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System (GNSS) satellite observations can obtain Total Electron Content (TEC) values in the ionosphere layer. The TEC value is obtained by decreasing the phase difference of the GNSS satellite's two carrier waves (L-band). The calculation of the TEC value using GNSS can be used in disaster phenomena such as earthquakes observed in this study. The earthquake phenomenon can cause vertical deformation in the Earth's crust, resulting in the appearance of acoustic waves propagating towards the ionosphere layer and changes in the ionosphere density in a moment. A propagating gravity wave has a speed of 0.3 km/ s towards the ionosphere layer. This disturbed ionosphere layer was detected within minutes of the mainshock. The anomaly in this study was detected by Global Positioning System (GPS) Pseudo Random Noise (PRN) 16 from 16 observation GNSS stations on the mainland of Turkey. The observed ionosphere anomalies were then modeled using tomography modelling to obtain spatial information from these anomalies. The tomography results found that the PRN 16 GPS satellites contained positive and negative anomalies located northeast of the epicenter. [ABSTRACT FROM AUTHOR]

A real-time Global Navigation Satellite System (GNSS) data managed by the Geospatial Information Agency (BIG) can be developed for indirect tsunami monitoring. This involves using GNSS TEC data due to the atmospheric-ionosphere coupling through tsunamitriggered infrared waves. The application of this method is, however, limited to tsunamis originating from earthquake epicenter which is far from the coast. Meanwhile, the arrival of tsunamis to the coast requires a longer time than the propagation of infrasound waves into the ionosphere. This GNSS signal reflection technique can, therefore, be used to detect tsunamis which are close to shore in order to overcome the detection weakness associated with the GNSS TEC and also routinely used to monitor sea waves. This research conducted a simulation of this technique using single-frequency code distance data to determine the sea level and the results showed its effectiveness in determining sea wave height using one differentiation. It is also possible to ignore the difference in the bias of two receivers of direct and reflected signals by sea-level assuming they are similar and have identical antennas. The use of pseudo distance from the GNSS signal code data makes it possible to estimate the height of the sea waves by simulation with a standard deviation of approximately 5.6 cm. [ABSTRACT FROM AUTHOR]

The Indonesian tsunami early warning system (INATEWS) has been developed and operated after the tsunami struck Aceh in December 2004. The INATEWS is based on a relationship model of earthquake parameters and tsunami potential. At the tsunami observation stage, INATEWS is still experiencing difficulties due to limited buoy stations. Alternative tsunami observations have been investigated using ionospheric TEC data from GPS signal observations. This paper reviews the methods that have been studied and used for tsunami detection using ionosphere total electron content (TEC) from GNSS data. Status and development plans of real-time GNSS resource utilization for TEC measurement in Indonesia and its application for INATEWS augmentation are also discussed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The purpose of the present study is to investigate simultaneously pre-earthquake ionospheric and atmospheric disturbances by the application of different methodologies, with the ultimate aim to detect their possible link with the impending seismic event. Three large earthquakes in Mexico are selected (8.2 Mw, 7.1 Mw and 6.6 Mw during 8 and 19 September 2017 and 21 January 2016 respectively), while ionospheric variations during the entire year 2017 prior to 37 earthquakes are also examined. In particular, Total Electron Content (TEC) retrieved from Global Navigation Satellite System (GNSS) networks and Atmospheric Chemical Potential (ACP) variations extracted from an atmospheric model are analyzed by performing statistical and spectral analysis on TEC measurements with the aid of Global Ionospheric Maps (GIMs), Ionospheric Precursor Mask (IPM) methodology and time series and regional maps of ACP. It is found that both large and short scale ionospheric anomalies occurring from few hours to a few days prior to the seismic events may be linked to the forthcoming events and most of them are nearly concurrent with atmospheric anomalies happening during the same day. This analysis also highlights that even in low-latitude areas it is possible to discern pre-earthquake ionospheric disturbances possibly linked with the imminent seismic events. [ABSTRACT FROM AUTHOR]