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We have analyzed the total electron content (TEC) derived from dual-frequency GPS receivers (GPS TEC) at the Chumpon station, Thailand, during the period 2004–2006. The diurnal, monthly, and seasonal variation in the measured TEC is compared with the TEC derived from the IRI-2007 model as well as the TEC obtained from the International GNSS service (IGS). To date, TEC data at equatorial latitudes are limited. The Chumphon station (10.72°N, 99.37°E) is located at the equatorial latitude and the dip latitude of 3°N. The TEC from the IRI-2007 model is based on the actual F 2 plasma frequency ( f o F 2 ) measurement. The results of our study show that the TEC derived from the IRI-2007 model agrees with the GPS TEC data mostly in the morning hours, but that it generally underestimates the GPS TEC. The maximum differences are about 15 TECU during the daytime and 5 TECU during the nighttime. The underestimation is more evident at daytime than at nighttime. The noon-bite out phenomena are clearly seen for the IRI-2007 TEC, but not on the IGS TEC and GPS TEC. The general underestimation of the IRI-2007 model can be explained from the exclusion of the plasmasphere, whereas the large difference during noon bite-outs is caused by the difference in the slab thickness in the ionosphere between the IRI-2007 model and the actual measurement. When compared with the TEC from the IGS model, the TEC measurements at Chumpon appear to be quite similar.

The 2011 March 11 Tohoku‐Oki earthquake (Mw9.0) caused vast damages to the country. Large events beneath dense observation networks could bring breakthroughs to seismology and geodynamics, and here I report one such finding. The Japanese dense network of Global Positioning System (GPS) detected clear precursory positive anomaly of ionospheric total electron content (TEC) around the focal region. It started ∼40 minutes before the earthquake and reached nearly ten percent of the background TEC. It lasted until atmospheric waves arrived at the ionosphere. Similar preseismic TEC anomalies, with amplitudes dependent on magnitudes, were seen in the 2010 Chile earthquake (Mw8.8), and possibly in the 2004 Sumatra‐Andaman (Mw9.2) and the 1994 Hokkaido‐Toho‐Oki (Mw8.3) earthquakes, but not in smaller earthquakes. Key Points Positive TEC anomaly appears before M9 class events The anomaly occurs above the epicenter and lasts ~1 hour M9 class earthquakes can be predicted

For the purposes of routinely providing reliable and low-latency Global Ionosphere Maps (GIMs), a method of estimating hourly updated near real-time GIM with a time latency of about 1–2 h based on a 24-h data sliding window of Global Navigation Satellite System (GNSS) near real-time observations and real-time data streams was presented. On the basis of the implementation of near real-time GIM estimation, an hourly updated GIM nowcasting method was further proposed to improve the accurate of short-term total electron content (TEC) prediction. We estimated the Shanghai Astronomical Observatory near real-time GIM (SHUG) and nowcasting GIM (SHPG) in the solar relatively active year (2014) and quiet year (2021), and employed GIMs provided by the International GNSS Service, the Global Positioning System (GPS) differential slant TECs (dSTECs) extracted from global independent GNSS stations, and the vertical TECs (VTECs) inverted from satellite altimetry as the references to validate the estimated results. The GPS dSTECs evaluation results show that SHUG behaves fairly consistent with the rapid GIMs, with a discrepancy of less than 1 TEC unit (TECu) overall. The standard deviations (STDs) of SHUG with respect to Jason-2/-3 VTECs are no more than 10% over the majority of rapid GIMs due to the instability of observations. The performance of 1-h nowcasting SHPG is significantlybetter than the Center for Orbit Determination in Europe (CODE) 1-day predicted GIM (C1PG). GPS dSTEC validation results indicate that 1-h nowcasting SHPG is 1 to 2 TECu more reliable than C1PG in eventful ionospheric electron activity regions, and it outperforms the C1PG by 10% overall versus Jason-2/-3 VTECs. The hourly updated SHUG and SHPG have relatively high reliability and low time latency, and thus can provide excellent service for (near) real-time users and offer more accurate TEC background information than daily predicted GIM for real-time GIM estimation.

The global ionospheric map (GIM) is used to observe variations in the total electron content (TEC) of the global positioning system (GPS) associated with 35 M ≥ 6.0 earthquakes that occurred in China during the 10‐year period of 1 May 1998 to 30 April 2008. The statistical result indicates that the GPS TEC above the epicenter often pronouncedly decreases on day 3–5 before 17 M ≥ 6.3 earthquakes. The GPS TEC of the GIM and electron density profiles probed by six microsatellites of FORMOSAT3/COSMIC (F3/C) are further employed to simultaneously observe seismoionospheric anomalies during an Mw7.9 earthquake near Wenchuan, China, on 12 May 2008. It is found that GPS TEC above the forthcoming epicenter anomalously decreases in the afternoon period of day 6–4 and in the late evening period of day 3 before the earthquake, but enhances in the afternoon of day 3 before the earthquake. The spatial distributions of the anomalous and extreme reductions and enhancements indicate that the earthquake preparation area is about 1650 km and 2850 km from the epicenter in the latitudinal and longitudinal directions, respectively. The F3/C results further show that the ionospheric F2 peak electron density, NmF2, and height, hmF2, significantly decreases approximately 40% and descends about 50–80 km, respectively, when the GPS TEC anomalously reduces.

The Global Positioning System (GPS) has become a powerful tool for ionospheric studies. In addition, ionospheric corrections are necessary for the augmentation systems required for Global Navigation Satellite Systems (GNSS) use. Dual-frequency carrier-phase and code-delay GPS observations are combined to obtain ionospheric observables related to the slant total electron content (sTEC) along the satellite-receiver line-of-sight (LoS). This observable is affected by inter-frequency biases [IFB; often called differential code biases (DCB)] due to the transmitting and the receiving hardware. These biases must be estimated and eliminated from the data in order to calibrate the experimental sTEC obtained from GPS observations. Based on the analysis of single differences of the ionospheric observations obtained from pairs of co-located dual-frequency GPS receivers, this research addresses two major issues: (1) assessing the errors translated from the code-delay to the carrier-phase ionospheric observable by the so-called levelling process, applied to reduce carrier-phase ambiguities from the data; and (2) assessing the short-term stability of receiver IFB. The conclusions achieved are: (1) the levelled carrier-phase ionospheric observable is affected by a systematic error, produced by code-delay multi-path through the levelling procedure; and (2) receiver IFB may experience significant changes during 1 day. The magnitude of both effects depends on the receiver/antenna configuration. Levelling errors found in this research vary from 1.4 total electron content units (TECU) to 5.3 TECU. In addition, intra-day vaiations of code-delay receiver IFB ranging from 1.4 to 8.8 TECU were detected.[PUBLICATION ABSTRACT]

In this study the statistics of ionospheric total electron content (TEC), derived from a GSV4004B dual-frequency Global Positioning System (GPS) receiver at Agartala station (23.450°N, 91.150°E) located in northern equatorial ionization anomaly (EIA) crest region of the Indian subcontinent, is reported with a performance analysis of IRI-2016 and IRI-2012 models during the ascending, maxima, declining and minima phases (2013-2018) of the solar cycle 24. Variations of model total electron content, as obtained from the IRI-2016 and IRI-2012 for the three options of topside electron density namely NeQuick, IRI 2001 and IRI 01-corr, are compared with the observed total electron content during different periods of interest viz. monthly, seasonal, annual and the correlations with solar activity parameters viz. sunspot number (SSN), 10.7 cm solar radio flux (F10.7), solar EUV flux, are also investigated. All the three options of IRI-2016 and IRI-2012 models show an earlier occurrence of diurnal maximum total electron content, as compared to the observed diurnal maximum GPS total electron content, throughout all the months during the complete period of observation. As the solar activity decreases (from 2015 to 2018), the model starts underestimating GPS total electron content, which becomes significantly high during the very low solar activity period of 2017-18 for all the months. IRI-2016 model underestimates the GPS total electron content before the hours of diurnal maximum and overestimates after the hours of diurnal maximum in the years from 2013-2018. IRI-2012 model underestimates the GPS total electron content before the hours of diurnal maximum and overestimates after the hours of diurnal maximum in the years from 2013-17 but overestimate during the whole day in the year of 2018. Overestimation by IRI-2012 is much more than that by IRI-2016 in the year of 2018. Predictions given by IRI-2016 are better than that given by IRI-2012 for our region. The seasonal mean maximum total electron content values are highest during the spring equinox months and lowest during the winter months except the year of 2014 and 2013. The correlation analysis, between the GPS total electron content and solar indices, show that the correlation coefficient is higher for the solar EUV flux, as compared to the sunspot number (SSN) and 10.7 cm solar radio flux (F10.7).

In this paper, the potential extrapolation capabilities and limitations of artificial neural networks (ANNs) are investigated. This is primarily done by generating total electron content (TEC) predictions using the regional southern Africa total electron content prediction (SATECP) model based on the Global Positioning System (GPS) data and ANNs with the aid of multiple inputs intended to enable the software to learn and correlate the relationship between their variations and the target parameter, TEC. TEC values are predicted over regions that were not covered in the model's development, although it is difficult to validate their accuracy in some cases. The SATECP model is also used to forecast hourly TEC variability 1 year ahead in order to assess the forecasting capability of ANNs in generalizing TEC patterns. The developed SATECP model has also been independently validated by ionosonde data and TEC values derived from the adapted University of New Brunswick Ionospheric Mapping Technique (UNB‐IMT) over southern Africa. From the comparison of prediction results with actual GPS data, it is observed that ANNs extrapolate relatively well during quiet periods while the accuracy is low during geomagnetically disturbed conditions. However, ANNs correctly identify both positive and negative storm effects observed in GPS TEC data analyzed within the input space. Key Points Investigation of the extrapolation capability of neural networks Comparison of global IRI model and regional SATECP model Validation of SATECP model with UNB‐IMT derived TEC values

Changes in strain (Linear and triangular) rate and Ionosphere Total Electron Content (TEC) before Mw 7.9 2018 Alaska Earthquake are investigated. Ten years of global positioning system (GPS) time series solutions were used for strain estimation in the region before the occurrence of the earthquake using the Haversine formula and triangulation method. Linear strain values suggest an anomaly in strain variation trend near the epicenter. Additionally, daily TEC variations for 30 days before the earthquake occurred were monitored and analysed. Analysis suggests TEC depletion on December 26 2017, and January 16 2018, respectively. TEC values from 60 GPS stations data were interpolated to study the spatial variations of TEC anomaly. Hourly TEC data derived from GPS stations on December 26 2017, and January 16 2018, suggest low TEC zone concentration near to the earthquake epicenter during 1 to 4 UTC. Spatial distribution of TEC values in 2-Dimension corresponding to anomaly time at 60 GPS stations in the vicinity of study area suggests lowest TEC values at stations that lie closer to the epicenter. The study suggests Lithosphere-Ionosphere coupling before Mw 7.9 2018 Alaska Earthquake and recommends developing a TEC-Strain Monitoring System for further validation of the work and for the better study of earthquake precursors based on TEC-Strain anomalies.

In this study, a potential precursor related to the Mw 7.2 Mexico earthquake on April 4, 2010, was investigated by analysing ionosphere total electron content (TEC) fluctuations derived from Global Positioning System data collected from 200 Continuously Operating Reference Stations (CORS) in Mexico and the western United States. Abnormal TEC variations were statistically identified within a 30-day time frame prior to the earthquake event. The two nearest stations at distances of 45 km and 53 km from the epicentre (IID2 and P500) were employed as benchmarks for the detection of anomalous days and time in TEC variations. Notably, a distinctive anomaly was observed on April 2, 2010, a couple of days before the earthquake, featuring a TEC unit deviation of 3–4 (TECU) from the baseline (15-day average value). Maximum TEC deviations (the time of anomaly) were recorded at 14.75 UTC on April 2, 2010. The analysis indicated a decrease in TEC concentration at a rate of 0.0017 TECU per kilometre towards the epicentre, supported by data collected from 200 CORS stations in the region. Spatial interpolation of TEC data from these stations further highlighted a distinct zone of low TEC density in the ionosphere above the epicentre at 14.75 UTC. This low TEC density zone was concentrated in areas with higher density points of geological structures (faults). The study suggests that the low TEC zone may be detected before the earthquake within proximity of the earthquake preparation zone above the epicentre.

We performed a comprehensive comparison between GPS global ionosphere map (GIM) and TOPEX/Jason (T‐J) total electron content (TEC) data for the periods of 1998–2009 in order to assess the performance of GIM over the global ocean where the GPS ground stations are very sparse. Using the GIM model constructed by the Center for Orbit Determination in Europe at the University of Bern, the GIM TEC values were obtained along the T‐J satellite orbit at specific locations and times of measurements and then binned into various geophysical conditions for direct comparison with the T‐J TEC. On the whole, the GIM model was able to reproduce the spatial and temporal variations of the global ionosphere as well as the seasonal variations. However, the GIM model was not accurate enough to represent the well‐known ionospheric structures such as the equatorial anomaly, the Weddell Sea Anomaly, and the longitudinal wave structure. Furthermore, a fundamental limitation of the model seems to be evident in the unexpected negative differences (i.e., GPS < T‐J) in the northern high‐latitude and the southern middle‐ and high‐latitude regions in comparison with the T‐J TECS. The positive relative differences (i.e., GIM > T‐J) at night represent the plasmaspheric contribution to GPS TEC, which is maximized, reaching up to 100% of the corresponding T‐J TEC values in the early morning sector. In particular, the relative differences decreased with increasing solar activity, and this may indicate that the plasmaspheric contribution to the maintenance of the nighttime ionosphere does not increase with solar activity, which is different from what we normally anticipate.