Vertical Total Electron Content Research Articles

A Stacked Machine Learning Model for the vertical Total Electron Content Forecasting

A Stacked Machine Learning Model for the vertical Total Electron Content Forecasting

Ionospheric behaviors and characteristics in Asian sector during the April 2023 geomagnetic storm with multi-instruments observations

Geomagnetic storms frequently affect satellite navigation, communication and satellite orbits. Monitoring and understanding the ionospheric disturbances and responses to geomagnetic storms are crucial. The detailed ionospheric responses and physical mechanisms to various geomagnetic storms, however, have not yet been extensively studied. In this paper, the ionospheric variation behaviors and features following the April 2023 magnetic storm along the Asian sector are thoroughly studied using multi-instrument observation data, including the Global Navigation Satellite System (GNSS), ionosonde, and other satellites. Large-scale Traveling Ionospheric disturbances (LSTIDs) are observed from BeiDou Geostationary Earth Orbit (GEO) satellites, GPS and GLONASS. LSTIDs traveled with a speed of 760–1300 m/s from high latitude region to low latitude region with a period of about 40 min. The equatorial propagating LSTIDs were generated by coronal mass ejections (CMEs), which occurred in April 2023 with periodic energy input from the auroral area. The poleward LSTIDs are also observed with a velocity of approximately 600–750 m/s and the period is similar. Neutral wind also influenced the characteristics of the ionospheric response. The [O]/[N2] ratio declined during the storm, which led to the formation of the negative storm phases. The largest vertical total electron content (VTEC) is found, and the strengthened region of TEC is mainly centered between ± 20° within geographical latitude. Equatorial Ionospheric Anomaly (EIA) is also observed, which is probably influenced by the electric field. As the time goes on, the peak on the south side of the EIA is disappearing. Meanwhile, the height of the ionospheric maximum electron density rises, and the electron density falls.

Physics-informed loss functions for vertical total electron content forecast

AbstractWe design physics-informed loss functions for training Artificial Neural Network (ANN) models to forecast the ionospheric vertical Total Electron Content (vTEC) from 1 to 24 hours in advance. The ANN models exploit our physics-informed loss functions, data provided by the Global Navigation Satellite Systems (GNSS) receiver installed at Tsukuba (36.06$$^{o}$$ o N, 140.05$$^{o}$$ o E), Japan, and external drivers (solar and geomagnetic indices). The time series used span from January 1, 2006, to December 31, 2018, i.e., a full solar cycle. A proper set of external drivers for the ANN models training are selected by ranking their importance in relation to the vTEC dynamics at different forecasting horizons. They result to be the 10.7 cm Solar Flux (F10.7), the magnitude of the Interplanetary Magnetic Field (IMF) $$\boldsymbol{B}_{\boldsymbol{T}}$$ B T , and the Auroral Electrojet (AE) index. Moreover, a second set of indices among those available has been considered as constraints in the design of the physics-informed loss functions. They are the Disturbance Storm Time (Dst) index, the solar wind speed $$\boldsymbol{v}, \boldsymbol{B}_{\boldsymbol{T}}$$ v , B T , and the By and Bz components of the interplanetary magnetic field. To assess the performance of the resulting ANN models, we use the statistical parameter coefficient of determination ($$\boldsymbol{R}^{{\textbf {2}}}$$ R 2 ), the standard deviation (SD), and the Wilcoxon non-parametric signed ranked test. We show that, in the testing period analyzed (from 2017-09-13, at 04:40:00, to 2018-12-31, at 23:55:00), one of our physics-informed loss functions provides a better performance of the ANN with regard to the standard loss function commonly adopted. In particular, when the new loss function is used in the ANN model, the average SD is minimized across all forecasting horizons in the training, validation and test datasets. SD is 0.2560 TECU, 0.3183 TECU and 0.4240 TECU for the training, validation and test dataset respectively, where 1 TECU = $${\textbf {10}}^{{\textbf {16}}}$$ 10 16 electrons/$$\boldsymbol{m}^{{\textbf {2}}}$$ m 2 . The ANN model, incorporating the new loss function and applied to the test dataset, shows a significant improvement according to the Wilcoxon signed ranked test. In fact by selecting a significance level $$\boldsymbol{\alpha }~ \mathbf {= 0.05}$$ α = 0.05 , the probability to obtain results by chance with the new loss function as compared to the standard loss function is 0.01504 (i.e., $$<\alpha $$ < α ), which implies that the new loss function gives a statistical improvement to the forecasting capability of the ANN model. To the best of our knowledge, this is the first time a physics-informed loss function has been designed for the task of forecasting the ionospheric vTEC.

Variability of the equatorial ionization anomaly over the South American sector: Effects of electric field and effective meridional wind

Vertical Total Electron Content (VTEC) Maps over the South American Continent were utilized to investigate the temporal and longitudinal climatology of Equatorial Ionization Anomaly (EIA) using more than 350 Global Navigation Satellite Systems (GNSS) receivers. At a temporal resolution of 10 min, the EIA motions, morphologies, and evolutions were mapped using VTEC keogram along magnetic meridians lines. Between 2014 and 2019, characteristics of the EIA were studied at two different South American magnetic meridians (i.e., 3.36° E and 7.58° E) separated by ∼555 km at an altitude of 300 km. The aim of this study is to examine the EIA’s variability, monthly variations and occurrences at evenly spaced longitudinal sectors. The effects of effective meridional winds component and E × B drift velocity on the daytime asymmetry of EIA anomalies were studied using a physics-based numerical model, Sheffield University Plasmasphere-Ionosphere model at Instituto Nacional de Pesquisas Espaciais (SUPIM-INPE). We found that the EIA parameters such as strength, shape, intensity, and latitudinal positions are affected by the eastward electric field and effective meridional wind. The monthly variations in the EIA over two magnetic meridian sectors demonstrate a semiannual variation. The EIA crests were more symmetric in equinox than in solstice seasons. The asymmetries of the EIA observed during the December solstice are more intense than during the June solstice, whereas September equinox is less symmetric than March equinox seasons. Moreover, this study indicates that the vertical drift and the meridional neutral wind plays a very significant role in the development of the EIA asymmetry by transporting the plasma up the field lines. There was a notable contraction of the EIA southern hemispheric (SH) crests from the December solstice to the June solstice. Meanwhile, the EIA crest positions in the northern hemisphere (NH) expand from the December solstice to the June solstice. According to our observations, the March equinox season had the most EIA occurrences, which were then followed by the September equinox, the December and June solstices. The intensities of the EIA crests also considerably decreased with solar descending phases. Through modeling, this work provides the scientific community with new insights into the evolution/development of EIA and their latitudinal asymmetry, as well as the role of E × B drift and thermospheric neutral wind in assessing the statistical analysis of EIA variability using the largest VTEC database over the South American sector.

Statistical Analysis of Ionospheric Correlation for Shortwave System

AbstractStatistical analysis of the temporal and spatial variations in the ionosphere is necessary to improve the shortwave system. Based on the standardized Euclidean distance algorithm, multisource ionospheric assimilation data, International GNSS Service vertical total electron content data, and ionosonde data are used to statistically analyze the ionospheric correlation distance, and the variation of ionospheric correlation distances with local times, magnetic latitudes, and seasons are obtained. The statistical analysis results show that the zonal ionospheric correlation distance presents minima in the equatorial ionospheric anomaly crest regions. Additionally, the meridional correlation distance in middle magnetic latitudes is greater than that in other regions. The zonal ionospheric correlation distance presents obvious local‐time variability. The variation trends of the meridional and zonal correlation distance during spring and autumn are similar. The patterns of the ionospheric correlation range variation with local times, magnetic latitudes, and seasons can be used to select the optimal locations or spacing for ionosonde stations, shortwave multi‐station systems, and shortwave radio beacons.

Modeling Ionospheric TEC Using Gradient Boosting Based and Stacking Machine Learning Techniques

AbstractAccurately predicting and modeling the ionospheric total electron content (TEC) can greatly improve the accuracy of satellite navigation and positioning and help to correct ionospheric delay. This study assesses the effectiveness of four different machine learning (ML) models in predicting hourly vertical TEC (VTEC) data for a single‐station study over Ethiopia. The models employed include gradient boosting machine (GBM), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM) algorithms, and a stacked combination of these algorithms with a linear regression algorithm. The models relied on input variables that represent solar activity, geomagnetic activity, season, time of the day, interplanetary magnetic field, and solar wind. The models were trained using the VTEC data from January 2011 to December 2018, excluding the testing data. The testing data comprised the data for the year 2015 and the initial 6 months of 2017. The RandomizedSearchCV algorithm was used to determine the optimal hyperparameters of the models. The predicted VTEC values of the four ML models were strongly correlated with the GPS VTEC, with a correlation coefficient of ∼0.96, which is significantly higher than the corresponding value of the International Reference Ionosphere (IRI 2020) model, which is 0.87. Comparing the GPS VTEC values with the predicted VTEC values based on diurnal and seasonal characteristics showed that the predictions of the developed models were generally in good agreement and outperformed the IRI 2020 model. Overall, the ML models used in this study demonstrated promising potential for accurate single‐station VTEC prediction over Ethiopia.

Ionospheric response of the March 2023 geomagnetic storm over European latitudes

The present study describes a spatial and temporal analysis of the ionospheric variability over the European sector during a major storm event from 23 to 24 March 2023. The analysis is mainly based on ionospheric characteristics such as foF2, hmF2 and Vertical Total Electron Content (VTEC) over ten Digisondes and co-located GNSS receivers. The event started at 12:00UT on 23 March as a positive ionospheric storm followed by a negative ionospheric storm to 04:00 UT on the next day SYM-H<-183nT. A notable latitude dependence of the ionospheric response is more prominent over the northern mid-latitude region attributed to the equatorward displacement of the Midlatitude Ionospheric Trough (MIT). To verify this hypothesis, Swarm latitudinal electron density profiles from in-situ Langmuir probe measurements over Europe were considered. These profiles demonstrate a clear MIT displacement from ∼65°N on 22 March to ∼55°N on 23 March with a subsequent recovery around ∼65°N on 25 March.

Improvement of topside ionosphere and plasmasphere estimation in ionospheric simulation system

This work is based on the results for a complete solar cycle of 11 years (2011–2021) from the ionospheric simulation system used in the Brazilian Space Weather program. The electron density profiles generated were integrated in height and compared to the International GNSS Service (IGS) vertical total electron content (vTEC) data. Experiments have shown an inadequate electron concentration decay with height which led to an overestimation in TEC values. We propose an improvement for the topside ionosphere and plasmasphere modeling in the system, considering recent advances in empirical modeling through observational data. The idea is to combine bottomside ionosphere estimates from the physical-based core model with NeQuick analytical formulation for ionospheric profile above hmF2. Our approach also calculates the ionospheric parameters for topside modeling using bottomside estimates. The ionospheric density profile decay obtained with the proposed approach was smoother and sharper, reaching a reduction of approximately 1 to 2 orders of magnitude of electron concentration in plasmasphere. It was observed a coherent reduction of high altitudes ionosphere/plasmasphere contribution to TEC. Also, the TEC values obtained using this hybrid solution were much closer to the International GNSS Service (IGS) data for the considered dataset, with root mean squared error (RMSE) of only 2.64 TECU for the entire period.

Characteristics of ionospheric disturbances during the 2021 Typhoon Chanthu based on GPS and GLONASS

Severe typhoons often result in substantial economic and human losses. Therefore, near-real-time monitoring and forecasting of severe typhoons hold significant importance. This study uses Typhoon Chanthu (No. 2114) as an example. We calculate high-precision de-trended and filtered ionospheric vertical total electron content (VTEC) data based on GPS and GLONASS data from intensive Global Navigation Satellite System (GNSS) observations at 30-second intervals in Taiwan. Based on the VTEC values, we analyze the characteristics of ionospheric disturbances caused by Typhoon Chanthu. This analysis covers aspects such as the time of appearance of ionospheric disturbances, changes in the magnitude of these disturbances, alterations in two-dimensional disturbances, fluctuations in the speed of disturbance propagation, and shifts in the frequency spectrum. The results reveal that both GPS-TEC and GLONASS-TEC exhibit noticeable disturbances during the specified timeframe. These disturbances are accompanied by the occurrence of “N”-type anomalies in electron density. Notably, at the occurrence of the disturbance, the elevation angle of GPS PRN32 and GLONASS PRN1 satellites is approximately 50°-55°, and their respective distances from the typhoon eye are roughly 350 km and 150 km. The propagation velocity and center frequency of the ionospheric disturbances observed in this study fall within the range of gravity waves. Specifically, the disturbances propagation speeds of GPS PRN32 and GLONASS PRN1 are approximately 129.36 m/s and 128.33 m/s, respectively, while the center frequencies are about 1.17 mHz and 1.43 mHz. We find that the ionospheric perturbations observed by GPS and those observed by GLONASS exhibit certain similarities and differences, which provide valuable insights into the relationship between typhoons and ionospheric disturbances.

Response to geomagnetic storm on 23–24 March 2023 long-lasting longitudinal variations of the global ionospheric TEC

This study examines the global behavior of the ionospheric TEC anomalies, i.e. their structures and temporal variability, during the initial, main and recovery phase of the geomagnetic storm occurring on 23–24 March 2023. For this purpose the global vertical TEC maps, generated by the NASA JPL IGS Ionosphere center, have been used and the geomagnetically forced anomalies have been presented in 2D (longitude-modip latitude) and polar maps. The main peculiar features of the TEC response could be summarized as: (i) the TOI-like event observed at the SH midnight hours during the main storm phase, and (ii) a clear longitude asymmetry between the TEC response at low and middle latitudes of the western and eastern hemispheres was seen; while the long-lasting positive response was evident for a full day in the western hemisphere the negative response or almost the lack of response was a characteristic of the eastern part. The study presented possible explanations of the above mentioned basic type of TEC anomalies by using the GUVY [O/N2] ratio maps and geomagnetic data from eight magnetometric stations situated at low latitudes for the separation of the effect generated by the DDEF. An attempt was made the observed TEC response during different storm phases to be reproduced. The presented reconstructions described in almost perfect way the real TEC responses and the RMSE assessments provided clear evidence for this evaluation.

Investigating the Global Performance of the BDS-2 and BDS-3 Joint Real-Time Undifferenced and Uncombined Precise Point Positioning Using RTS Products from Different Analysis Centers

Compared to the traditional ionospheric-free (IF) precise point positioning (PPP) model, the undifferenced and uncombined (UU) PPP has the advantages of lower observation noise and the ability to obtain ionospheric information. Thanks to the IGS (International GNSS Service), real-time service (RTS) can provide RT vertical total electron content (VTEC) products, and an enhanced RT UU-PPP based on the RT-VTEC constraints can be achieved. The global performance of the BeiDou Navigation Satellite System-2 (BDS-2) and BDS-3 joint RT UU-PPP using different RTS products was investigated. There is not much difference in the RTS orbit accuracy of medium earth orbit (MEO) satellites among all analysis centers (ACs), and the optimal orbit accuracy is better than 5, 9, and 7 cm in the radial, along-track, and cross-track directions, respectively. The orbit accuracy of inclined geosynchronous orbit (IGSO) satellites is worse than that of MEO satellites. Except for CAS of 0.46 ns, the RTS clock accuracy of MEO satellites for other ACs achieves 0.2–0.27 ns, and the corresponding accuracy is about 0.4 ns for IGSO satellites. In static positioning, due to the limited accuracy of RT-VTEC, the convergence time of the enhanced RT UU-PPP is longer than that of RT IF-PPP for most ACs and can be better than 25 and 20 min in the horizontal and vertical components, respectively. After convergence, the 3D positioning accuracy of the static RT UU-PPP is improved by no more than 8.7%, and the optimal horizontal and vertical positioning accuracy reaches 3.5 and 7.0 cm, respectively. As for the kinematic mode with poor convergence performance, with the introduction of RT-VTEC constraints, the convergence time of RT UU-PPP can be slightly shorter and reaches about 55 and 60 min in the horizontal and vertical components, respectively. Both the horizontal and vertical positioning accuracies of the kinematic RT UU-PPP can be improved and achieve around 7.5 and 10 cm, respectively.

A novel ionospheric TEC mapping function with azimuth parameters and its application to the Chinese region

The ionospheric mapping function (MF) for Global Navigation Satellite System (GNSS), a mutual projection method for the slant total electron content (STEC) and vertical total electron content, is one of the significant factors affecting the performance of ionospheric models. The commonly used MF assumes isotropic TEC variations and takes into account only the satellite elevation angle, which may result in significant ionospheric projection errors, especially at low elevation angles. Based on the single-layer model, we propose an additional azimuth parameter mapping function (APMF). The APMF was estimated and evaluated by the NeQuick model during the periods of January 2014 and January 2022 from the aspect of simulation and measured STEC during the periods of 2014 and 2022 from the aspect of actual measurements over China, respectively. Compared to the modified single-layer model mapping function (MSLM-MF), the experimental results indicate that (1) The APMF can significantly reduce the ionospheric projection error, and the fluctuation in errors with different azimuth angles is small. (2) According to the evaluation based on the NeQuick simulation during the TEC peak time, when the ionosphere is quite active, the upper and lower quartiles of the absolute projection error boxplot of the APMF relative to the MSLM-MF in January 2014 are reduced by 56.1% and 60.0%, respectively, and in January 2022, they are reduced by 67.7% and 65.2%, respectively. Similarly, the upper whiskers in the boxplot are reduced by 54.7% and 67.5% in January 2014 and January 2022, respectively; the APMF performance in terms of the root mean square error (RMSE) is improved by 47.0% in January 2014 and 58.3% in January 2022. (3) According to the evaluation based on the measured STEC from GNSS raw data during the TEC peak time, the upper and lower quartiles of the absolute mapping error boxplot of the APMF relative to the MSLM-MF in 2014 are reduced by 48.9% and 46.9%, respectively, while in 2022, they are reduced by 48.3% and 41.2%, respectively. The upper whiskers in the boxplot are reduced by 41.8% and 35.2% in 2014 and 2022, respectively; the APMF performance in terms of RMSE is improved by 44.6% in 2014 and 39.2% in 2022.

Ionospheric equivalent slab thickness ingestion into the NeQuick model

The ionospheric equivalent slab thickness (τ), defined as the ratio of the vertical total electron content (vTEC) to the ionospheric F2-layer electron density maximum (NmF2), is a parameter providing useful information on the shape of the vertical electron density profile. However, the use of this information is of difficult practical application in empirical ionosphere models, such as the NeQuick model, because by design they do not explicitly include τ as a modelling parameter. In this work, we investigated the opportunity of using measured τ values to improve the empirical modelling of the ionosphere vertical electron density profile by NeQuick. Measured τ values were obtained through NmF2 observations and vTEC measurements obtained between 2001 and 2019 by an ionosonde and a ground-based GNSS receiver, respectively, co-located at Rome ionospheric station (41.8° N, 12.5° E; Italy). NeQuick τ was obtained as the ratio between modelled NmF2 and vTEC values, the latter obtained by integration of the vertical profile. As a first step, τ values modelled by NeQuick were compared with corresponding values measured at Rome station to highlight diurnal, seasonal, and solar activity differences. Then, measured τ values were ingested in NeQuick through a three-parameter assimilation procedure which first assimilate F2-layer peak characteristics to constrain the F2-layer anchor point, and then assimilate vTEC to optimize the F2-layer shape through the NeQuick F2-layer thickness parameter, namely B2bot. The assimilation procedure provides information on how the NeQuick B2bot has to be modified to match measured τ values, and then on how the shape of the F2-layer profile has to be changed accordingly. Our results highlight that, in many cases, the NeQuick B2bot has to be increased to match observations, which has implications on the modelling of the NeQuick bottomside and topside effective scale heights.

Multi-Time-Scale Analysis of Chaos and Predictability in vTEC

Theoretical modelling of the local ionospheric medium (LIM) is made difficult by the occurrence of irregular ionospheric behaviours at many space and time scales, making prior hypotheses uncertain. Investigating the LIM from scratch with the tools of dynamical system theory may be an option, using the vertical total electron content (vTEC) as an appropriate tracer of the system variability. An embedding procedure is applied to vTEC time series to obtain the finite dimension (m∈N) of the phase space of an LIM-equivalent dynamical system, as well as its correlation dimension (D2) and Kolmogorov entropy rate (K2). In this paper, the dynamical features (m,D2,K2) are studied for the vTEC on the top of three GNSS stations depending on the time scale (τ) at which the vTEC is observed. First, the vTEC undergoes empirical mode decomposition; then (m,D2,K2) are calculated as functions of τ. This captures the multi-scale structure of the Earth’s ionospheric dynamics, demonstrating a net distinction between the behaviour at τ≤24h and τ≥24h. In particular, sub-diurnal-scale modes are assimilated to much more chaotic systems than over-diurnal-scale modes.

The Spectrum of Global Electron Content: A New Potential Indicator of Space Weather Activity.

The time evolution of the total number of free electrons in the Earth's ionosphere, i.e., the Global Electron Content (GEC), during more than two solar cycles is analyzed in this work. The GEC time series has been extracted from the Global Ionospheric Maps (GIMs) of Vertical Total Electron Content (VTEC) estimated by UPC-IonSAT with TOMION-v1 software from global GPS measurements since the end of 1996. A dual-layer voxel-based tomographic model solved with a forward Kalman scalar filter, from dual-frequency carrier GPS data only, provides the so-called UQRG GIM after VTEC kriging interpolation, with a resolution of 15 min in time, 5° in longitude and 2.5° in latitude. UQRG is one of the best behaving GIMs in the International GNSS Service (IGS).In this context, the potential application of the GEC spectrum evolution as a potential space weather index is discussed and demonstrated.

Three‐Dimensional Ionospheric Evolution and Asymmetry of the Electron Density Depletion Generated by the 21 June 2020 Annular Solar Eclipse

AbstractThe three‐dimensional computerized ionospheric tomography (3DCIT) technique has been used to reconstruct the ionospheric response to the 21 June 2020 annular solar eclipse and the results are evaluated by constellation observing system for meteorology, ionosphere, and climate observations. The 3DCIT‐derived electron density (Ne) difference between the eclipse and quiet days showed that the Ne depletion was between 200 and 550 km and the maximum magnitude was about −3.0 × 1011 el/m3 which was at 280 km in altitude. The contributions from below 250 and 350 km altitudes to Vertical Total Electron Content (VTEC) depletion were ∼30% and ∼60%, respectively. Significant asymmetry of Ne depletion with respect to the eclipse path was captured in 3DCIT results, and the deviation conditions between the Ne depletion central line and eclipse path varied at different altitudes. Simulations with the thermosphere‐ionosphere‐electrodynamics general circulation model generally showed consistent ionospheric variations with GNSS (Global Navigation Satellite System) VTEC and 3DCIT electron density. Furthermore, term analysis on the ion continuity equation indicates that the asymmetry of Ne depletion was mainly induced by the neutral wind disturbance which converged toward the eclipse region and caused opposite transport effects on both sides of the eclipse path. The thermospheric composition was also changed by disturbed neutral wind and impacted plasma production and loss rates, contributing to the Ne depletion asymmetry.

The Lithosphere-Atmosphere-Ionosphere Coupling of Multiple Geophysical Parameters Approximately 3 Hours Prior to the 2022 M6.8 Luding Earthquake

Investigating various geophysical parameters from the Earth’s crust to the upper atmosphere is considered a promising approach for predicting earthquakes. Scientists have observed that changes in these parameters can occur days to months before earthquakes. Understanding and studying the impending abnormal phenomena that precede earthquakes is both urgent and challenging. On 5 September 2022, a magnitude 6.8 earthquake occurred in Sichuan, China, at 4:52:18 (Universal Time). The earthquake happened approximately 175 km away from an instrumental array established in 2021 for monitoring vibrations and perturbations in the lithosphere, atmosphere, and ionosphere (MVP-LAI). This array consisted of over 15 instruments that regularly monitor changes in various geophysical parameters from the subsurface up to an altitude of approximately 350 km in the ionosphere. Its purpose was to gain insights into the mechanisms behind the coupling of these different geospheres during natural hazards. The seven geophysical parameters from the MVP-LAI system simultaneously exhibited abnormal behaviors approximately 3 h before the Luding earthquake. These parameters include ground tilts, air pressure, radon concentration, atmospheric vertical electric field, geomagnetic field, wind field, and total electron content. The abnormal increase in radon concentration suggests that the chemical channel could be a promising mechanism for the coupling of geospheres. Furthermore, air pressure, the geomagnetic field, and total electron content exhibited abnormal characteristics with similar frequencies. Horizontal wind experienced temporary cessation or weakening, while vertical wind displayed frequent reversals. These anomalies may be attributed to atmospheric resonance before the earthquake. The results demonstrate that the coupling of geospheres, as indicated by the anomalous phenomena preceding an earthquake, could be influenced by multiple potential mechanisms. The multiple anomalies observed in this study provided approximately 3 h of warning for people to prepare for the seismic event and mitigate hazards.

Long-term equatorial ionosphere variations over Ethiopia

This paper focuses on the investigation of the long-term behavior of the equatorial ionosphere in Ethiopia. To explore the extended ionospheric variations, we analyze Total Electron Content (TEC) fluctuations in conjunction with solar activity indices, including F10.7 radio flux, EUV radiation, and Sunspot Number (SSN). The dataset used encompasses GPS-derived TEC records spanning 11 consecutive years from 2007 to 2017, corresponding to the period of solar cycle 24. Our analysis shows that the highest TEC levels generally occur during the post-noon hours, while the lowest values are observed around post-midnight or early morning. Notably, exceptions to this pattern are found in 2011 and 2013 when the highest TEC levels are observed during the December solstice. Otherwise, the seasonal TEC variation exhibits a semi-annual pattern, with peak TEC values occurring during the equinoxes and the lowest values during the solstices. Further examination demonstrates that in both solar activity phases, TEC magnitude is higher during the March Equinox compared to the September Equinox, and slightly higher during the December Solstice compared to the June Solstice. This reveals an asymmetry in the seasonal variations, encompassing the equinoxes, solstices, and the ascending and descending phases of the solar cycle. Our study confirms that long-term fluctuations in ionospheric TEC closely correspond to variations in solar activity indices. Correlation analysis indicates a strong link between all solar activity indices and TEC. Notably, while a negative correlation is observed in 2007, the correlation in 2011 is remarkably stronger. Additionally, we find that the long-term TEC variation exhibits stronger correlations with EUV and F10.7 radio flux than with SSN, with correlation coefficients of 0.86, 0.85, and 0.78, respectively. Lastly, our study extends previous research by identifying the long-term trends of vertical TEC (vTEC) in relation to various driving factors such as F10.7, SSN, and EUV.

Tracking tsunami propagation and Island’s collapse after the Hunga Tonga Hunga Ha’apai 2022 volcanic eruption from multi-space observations

The quantity and accuracy of satellite-geodetic measurements have increased over time, revolutionizing the monitoring of tectonic processes. Global Navigation Satellite System (GNSS) and satellite radar signals provide observations beyond ground deformation, including how earthquake and tsunami processes affect variations in the ionosphere. Here, we study the Hunga Tonga Hunga Ha’apai (HTHH) volcanic eruption 2022 and its associated tsunami propagation with the analysis GNSS derived Total Electron Content (TEC), Synthetic Aperture Radar (SAR) Sentinel-1 data, complemented with tide gauge observations. We utilize GNSS sites data within a ~ 5000 km radius from the volcanic eruption for estimating the ionospheric perturbation as Vertical TEC. We give evidence on the detection of acoustic gravity, internal gravity, and atmospheric Lamb waves signatures in the TEC perturbation. In particular, the internal gravity waves that concentrated in the southwest of Tonga, directly correlates with the observed tsunami propagation direction as accounted by the tide gauge measurements. However, the acoustic gravity wave signature in the TEC is dominant in the north direction suggesting a surface deformation, which could be verified using Sentinel-1A SAR amplitude data. The analysis presented herein shows that within 5 h of the volcanic eruption, the central part of the HTHH island landscape disappeared with the biggest explosion. The unprecedented detail resolved by integrating satellite data yields previously unknown details of the deformation of the 2022 HTHH volcano eruption.

Effects of Topside Ionosphere Modeling Parameters on Differential Code Bias (DCB) Estimation Using LEO Satellite Observations

Given the potential of low-earth orbit (LEO) satellites in terms of navigation enhancement, accurately estimating the differential code bias (DCB) of GNSS satellites and LEO satellites is an important research topic. In this study, to obtain accurate DCB estimates, the effects of vertical total electron content (VTEC) modeling parameters of the topside ionosphere on DCB estimation were investigated using LEO observations for the first time. Different modeling parameters were set in the DCB estimations, encompassing modeling spacing in the dynamic temporal mode and degree and order (D&amp;O) in spherical harmonic modeling. The DCB precisions were then evaluated, and the impacts were analyzed. Thus, a number of crucial and beneficial conclusions are drawn: (1) The maximum differences in the GPS DCB estimates after adopting different modeling spacings and different D&amp;Os exhibit that the different modeling spacings or D&amp;Os both affect the GPS DCB estimates and their root-mean square (RMS), and the effects of the two are at the same level. (2) The maximum differences in receiver DCBs using different modeling spacings indicate that the modeling spacing has a significant impact on the receiver DCBs, compared with GPS DCBs. Whereas, the maximum differences in receiver DCBs with different modeling D&amp;Os are inferior to the differences in the GPS DCBs. That is, the modeling spacing has a greater impact on the LEO DCBs than those of the modeling D&amp;O. (3) The experimental results indicate that the GPS DCB estimates using a modeling spacing of 12H have higher precisions than the others, whereas LEO receiver DCBs using a spacing of 4H or 6H obtain optimal STD. In terms of modeling D&amp;O, adopting 8D&amp;O in the LEO-based VTEC modeling can attain superior estimates and precisions for both GPS and LEO DCBs. The research conclusions can provide references for LEO-augmented DCB estimation.