Showing papers on "Total electron content published in 2020"

A Causal Long Short-Term Memory Sequence to Sequence Model for TEC Prediction Using GNSS Observations

Abstract: The necessity of predicting the spatio-temporal phenomenon of ionospheric variability is closely related to the requirement of many users to be able to obtain high accuracy positioning with low cost equipment. The Precise Point Positioning (PPP) technique is highly accepted by the scientific community as a means for providing high level of position accuracy from a single receiver. However, its main drawback is the long convergence time to achieve centimeter-level accuracy in positioning. Hereby, we propose a deep learning-based approach for ionospheric modeling. This method exploits the advantages of Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNN) for timeseries modeling and predicts the total electron content per satellite from a specific station by making use of a causal, supervised deep learning method. The scope of the proposed method is to compare and evaluate the between-satellites ionospheric delay estimation, and to aggregate the Total Electron Content (TEC) outcomes per-satellite into a single solution over the station, thus constructing regional TEC models, in an attempt to replace Global Ionospheric Maps (GIM) data. The evaluation of our proposed recurrent method for the prediction of vertical total electron content (VTEC) values is compared against the traditional Autoregressive (AR) and the Autoregressive Moving Average (ARMA) methods, per satellite. The proposed model achieves error lower than 1.5 TECU which is slightly better than the accuracy of the current GIM products which is currently about 2.0–3.0 TECU.

Neural network based model for global Total Electron Content forecasting

Abstract: We introduce a novel empirical model to forecast, 24 h in advance, the Total Electron Content (TEC) at global scale. The technique leverages on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and applies a nonlinear autoregressive neural network with external input (NARX) to selected GIM grid points for the 24 h single-point TEC forecasting, taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a global scale, the technique makes use of the NeQuick2 Model fed by an effective sunspot number R12 (R12eff), estimated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same GIM grid points. The novel approach is able to reproduce the features of the ionosphere especially during disturbed periods. The performance of the forecasting approach is extensively tested under different geospatial conditions, against both TEC maps products by UPC (Universitat Politecnica de Catalunya ) and independent TEC data from Jason-3 spacecraft. The testing results are very satisfactory in terms of RMSE, as it has been found to range between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-h forecasting technique even over the oceans. The validation of the forecasting during five geomagnetic storms reveals that the model performance is not deteriorated during disturbed periods. This 24-h empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to support different classes of GNSS users.

Ionospheric and Magnetic Signatures of a Space Weather Event on 25–29 August 2018: CME and HSSWs

Abstract: We present a study concerning a space weather event on 25–29 August 2018, accounting for its ionospheric and magnetic signatures at low latitudes and midlatitudes. The effects of a storm in several longitudinal sectors (Asia, Africa, America, and the Pacific) have been analyzed using various parameters such as total electron content (TEC), geomagnetic field, and column [O/N2] ratio. Positive ionospheric storms are found in all the longitudinal sectors having its maximum effects in the Asian sector, whereas the negative ionospheric storms have been observed in the summer hemisphere (Northern Hemisphere). A large decrease in [O/N2] ratio in the Northern Hemisphere is a possible cause of the observed negative storm effects. Ionospheric F2 region maximum electron density (NmF2) and TEC have shown a positive correlation during this storm. The study suggests that storm time‐generated wind does not have a uniform planetary extension and mainly affects dayside (America and Pacific) and duskside (Africa) sectors. During the space weather event, we observe an asymmetric variation of the magnetic field as a function of the longitude. On the other hand, the magnetic variations at midlatitudes are found to be symmetric in both hemispheres. A signature of the disturbance dynamo (anti‐Sq circulation) has been observed, mainly at low latitudes. We emphasize that the partial ring current (PRC), estimated by the ASYM‐H magnetic index, must also be taken into account along with the SYM‐H index for a better approximation of ionospheric currents. The study further suggests existence of several electric current cells in the ionosphere, which is consistent with the Blanc‐Richmond model.

Response of the low- to mid-latitude ionosphere to the geomagnetic storm of September 2017

Abstract: . We study the impact of the geomagnetic storm of 7–9 September 2017 on the low- to mid-latitude ionosphere. The prominent feature of this solar event is the sequential occurrence of two SYM-H minima with values of −146 and −115 nT on 8 September at 01:08 and 13:56 UT, respectively. The study is based on the analysis of data from the Global Positioning System (GPS) stations and magnetic observatories located at different longitudinal sectors corresponding to the Pacific, Asia, Africa and the Americas during the period 4–14 September 2017. The GPS data are used to derive the global, regional and vertical total electron content (vTEC) in the four selected regions. It is observed that the storm-time response of the vTEC over the Asian and Pacific sectors is earlier than over the African and American sectors. Magnetic observatory data are used to illustrate the variation in the magnetic field particularly, in its horizontal component. The global thermospheric neutral density ratio; i.e., O∕N2 maps obtained from the Global UltraViolet Spectrographic Imager (GUVI) on board the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite are used to characterize the storm-time response of the thermosphere. These maps exhibit a significant storm-time depletion of the O∕N2 density ratio in the northern middle and lower latitudes over the western Pacific and American sectors as compared to the eastern Pacific, Asian and African sectors. However, the positive storm effects in the O∕N2 ratio can be observed in the low latitudes and equatorial regions. It can be deduced that the storm-time thermospheric and ionospheric responses are correlated. Overall, the positive ionospheric storm effects appear over the dayside sectors which are associated with the ionospheric electric fields and the traveling atmospheric disturbances. It is inferred that a variety of space weather phenomena such as the coronal mass ejection, the high-speed solar wind stream and the solar radio flux are the cause of multiple day enhancements of the vTEC in the low- to mid-latitude ionosphere during the period 4–14 September 2017.

Analysis of Plasma Bubble Signatures in Total Electron Content Maps of the Low-Latitude Ionosphere: A Simplified Methodology

Abstract: The ionosphere over the Brazilian region has particular characteristics due to the large geomagnetic declination angle over most of the territory. Furthermore, the equatorial ionization anomaly southern crest is located over the Brazilian territory. In this region, plasma irregularities may arise in the post-sunset hours. These ionospheric irregularities develop in the form of magnetic field-aligned plasma depletions, known as equatorial plasma bubbles, which may seriously affect radio signals that propagate through them. These irregularity structures can cause amplitude and phase scintillation of the propagating signals, thereby compromising the availability, performance, and integrity of satellite-based communication and navigation systems. Additionally, the total electron content (TEC) introduces propagation delays that can contribute to range measurement errors for global positioning system (GPS) users. The ionospheric characteristics change significantly according to the time of day, season, as well as the solar and geomagnetic activities, among other factors. Indeed, the ionosphere is one of the most significant sources of errors in the positioning and navigation systems based on the GPS satellites. Due to these features, there is a strong interest by the scientific community in better understanding and characterizing the ionospheric behavior. In this context, the TEC analysis has wide applicability for space plasma studies and is a well-established tool for investigating the ionospheric behavior and its potential impact on space-based navigation systems. One of the goals of these studies is the generation of TEC maps for a geographic region based on GPS observations. In the present work, some electrodynamic processes of the low-latitude ionosphere are reviewed and the TEC estimation based on GPS measurements is revisited in detail. A methodology aimed at creating the TEC maps is presented and validated by comparison with results from other geophysical instruments, such as all-sky imagers and ionosondes. Finally, examples of the ionospheric behavior displayed by TEC maps during equatorial plasma bubble events and a geomagnetic storm are fully described and discussed.

The MAVEN Radio Occultation Science Experiment (ROSE)

Abstract: The Radio Occultation Science Experiment (ROSE) is part of the scientific payload of the Mars Atmosphere Volatile EvolutioN (MAVEN) spacecraft. Here we motivate the science objectives of the MAVEN ROSE investigation, which are (1) to determine the vertical structure of plasma in the ionosphere and (2) to identify the density, altitude, and width of the ionospheric density peak. MAVEN ROSE achieves these science objectives by performing two-way X-band radio occultations. Data are acquired ingress and egress opportunities using the high-gain antenna and a carrier-only signal. They are also acquired on ingress opportunities using the low-gain antenna with telemetry on the signal. Raw data are processed to yield vertical profiles of the electron density in the ionosphere of Mars with an accuracy on the order of $10^{9}\mbox{ m}^{-3}$ , a vertical resolution on the order of 1 km, and a vertical range on the order of 100–500 km. Data products are archived at the NASA Planetary Data System. In order to ensure the reproducibility of the results of the MAVEN ROSE investigation, software programs to determine MAVEN ROSE electron density profiles from time series of frequency residuals accompany this article. Furthermore, here we examine what the MAVEN ROSE observations reveal about the behavior of the ionosphere of Mars. Peak density, peak altitude, and total electron content mostly display the expected trends with solar zenith angle. However, deviations from those trends are present. Peak density at fixed dayside solar zenith angle can vary by 30% and M1 layer density at fixed solar zenith angle can vary even more. Solar irradiance variations are the most likely cause of these variations. Peak altitude at fixed dayside solar zenith angle can vary by 20 km or more. Thermospheric responses to lower atmospheric dust events are the most likely cause of these variations. Several instances of unusual ionospheric features are present in the dayside electron density profiles. A layer with density $3 \times 10^{10}\mbox{ m}^{-3}$ that appears to occur at 60 km altitude may be a horizontally-confined region of larger density that actually occurs at higher altitudes. Significant changes in density over short vertical distances around 160 km altitude may be caused by ionospheric dynamics in the presence of strong crustal magnetic fields. Topside plasma layers around 200 km altitude may reflect sharp gradients in electron temperature.

SIMuRG: System for Ionosphere Monitoring and Research from GNSS

Abstract: Currently, more than 6000 operating GNSS receivers deliver observations to multiple servers. Ionospheric data are derived from these measurements providing outstanding space coverage and time resolution. There are about 200 million independent measurements daily. Researchers need sophisticated software tools to deal with such a large amount of data. We present recent advances and products from the System for Ionosphere Monitoring and Research from GNSS (SIMuRG). Currently, SIMuRG provides the total electron content (TEC) variations filtered within 2–10 min, 10–20 min, and 20–60 min, the Rate of the TEC Index, the Along Arc TEC Rate index, and the vertical TEC. SIMuRG is an online service at http://simurg.iszf.irk.ru . The system can be used free of charge and allows calculating both maps and series for arbitrary time intervals and geographic regions. All the data products are available in the form of data or figures. We discuss the system and its geophysics applications.

Longitudinal Responses of the Equatorial/Low-Latitude Ionosphere Over the Oceanic Regions to Geomagnetic Storms of May and September 2017

Abstract: This study presents the longitudinal dependence of responses of the equatorial/low latitude ionosphere over the oceanic regions to geomagnetic storms of 28th May and 8th September, 2017. We investigated the interplanetary origins of the storms. Total Electron Content (TEC) data were obtained from Global Navigation Satellite System stations, located around the oceanic areas in the equatorial/low latitude regions. The Rate of change of TEC Index (ROTI) was used as a proxy for ionospheric irregularities over the study locations. Further, variations of the horizontal component of the Earth's magnetic fields, obtained from ground-based magnetometers were studied. We used ionospheric disturbance currents, polar cap and auroral electrojet indices to monitor the storm-time electric fields. The May, 2017 storm was driven by sheath and magnetic cloud fields, while the September, 2017 storm was driven by sheath fields. We observed a comparative dominance of TEC intensities over the Oceans than over the landlocked areas. Empirically, our results validated a theoretical suggestion of the existence of a dynamic ocean-ionosphere coupling made by Godin et al. [2015]. Prompt Penetration Electric Fields (PPEF) was observed to be a key factor that controls TEC responses to storms. PPEFs caused TEC enhancements, mainly over the Pacific Ocean longitudes during the May, 2017 storm and enhanced TEC over the Atlantic Ocean and the Pacific Oceans longitudes during the September, 2017 storm. These PPEFs triggered irregularities over the Pacific

Ionosphere time series modeling using adaptive neuro-fuzzy inference system and principal component analysis

Abstract: The total electron content (TEC) is one of the most important parameters for studying the behavior of the ionosphere. The global ionosphere maps (GIMs) can be used to study the TEC time series variations. The time resolution of the GIM-TEC is 2 h, whereas the frequency of the ionospheric temporal behavior can be less than 2 h. To solve this problem, we present a new method for ionosphere time series modeling and prediction in Iran. The adaptive neuro-fuzzy inference system (ANFIS) and principal component analysis are combined to model the TEC of the ionosphere. In fact, the observations are decomposed into principal components before entering to the ANFIS network and only a few main components are used for training the network. The main advantage of this combination is to increase the accuracy of the results and reduce the time of convergence to achieve an optimal solution. To evaluate the proposed method, we used observations of a Tehran GNSS station in 2016 and 2017. The root-mean-square error, correlation coefficient, and dVTEC = |VTECGPS − VTECmodel| were used to assess the accuracy of the proposed method. Also, all results are compared with the International Reference Ionosphere 2016 (IRI2016), GIM-TEC, and artificial neural networks (ANNs) ionosphere models. The results indicate a 1 to 4.72 TECU improvement in the temporal resolution of TEC modeling with the proposed method, compared to the IRI2016, GIM, and ANNs in the Iranian region.

NeQuick-G performance assessment for space applications

Abstract: Other than traditional single-layer ionosphere models for global navigation satellite system (GNSS) receivers, the NeQuick-G model of Galileo provides a fully three-dimensional description of the electron density and obtains the ionospheric path delay by integration along the line of sight. While optimized for users on or near the surface of the earth, NeQuick-G can thus as well be used for ionospheric correction of single-frequency observations from spaceborne platforms. Based on slant and total electron content measurements obtained in the Swarm mission, the performance of NeQuick-G for users in low earth orbit is assessed for periods of high and low solar activity as well as different orientations of the orbital plane with respect to the sun and the region of high total electron content. A slant range correction performance of better than 70% is achieved in more than 85% of the examined epochs in good accord with the performance reported for terrestrial users. Likewise, the positioning errors can be notably reduced when applying the NeQuick-G corrections in single-frequency navigation solutions. For users at orbital altitudes, it is furthermore shown that vertical total electron predictions from NeQuick-G may be favorably combined with an elevation-dependent thick-layer mapping function to reduce the high computational effort associated with the integration of the electron density along the ray path for each tracked GNSS satellite.

Small-Scale Ionospheric Irregularities of Auroral Origin at Mid-latitudes during the 22 June 2015 Magnetic Storm and Their Effect on GPS Positioning

Abstract: Small-scale ionospheric irregularities affect navigation and radio telecommunications. We studied small-scale irregularities observed during the 22 June 2015 geomagnetic storm and used experimental facilities at the Institute of Solar-Terrestrial Physics of the Siberian Branch of the Russian Academy of Sciences (ISTP SB RAS) located near Irkutsk, Russia (~52°N, 104°E). The facilities used were the DPS-4 ionosonde (spread-F width), receivers of the Irkutsk Incoherent Scatter Radar (Cygnus A signal amplitude scintillations), and GPS/GLONASS receivers (amplitude and phase scintillations), while 150 MHz Cygnus A signal recording provides a unique data set on ionosphere small-scale structure. We observed increased spread-F, Cygnus A signal amplitude scintillations, and GPS phase scintillations near 20 UT on 22 June 2015 at mid-latitudes. GPS/GLONASS amplitude scintillations were at a quiet time level. By using global total electron content (TEC) maps, we conclude that small-scale irregularities are most likely caused by the auroral oval expansion. In the small-scale irregularity region, we recorded an increase in the precise point positioning (PPP) error. Even at mid-latitudes, the mean PPP error is at least five times that of the quiet level and reaches 0.5 m.

GNSS-Based Non-Negative Absolute Ionosphere Total Electron Content, its Spatial Gradients, Time Derivatives and Differential Code Biases: Bounded-Variable Least-Squares and Taylor Series

Abstract: Global navigation satellite systems (GNSS) allow estimating total electron content (TEC). However, it is still a problem to calculate absolute ionosphere parameters from GNSS data: negative TEC values could appear, and most of existing algorithms does not enable to estimate TEC spatial gradients and TEC time derivatives. We developed an algorithm to recover the absolute non-negative vertical and slant TEC, its derivatives and its gradients, as well as the GNSS equipment differential code biases (DCBs) by using the Taylor series expansion and bounded-variable least-squares. We termed this algorithm TuRBOTEC. Bounded-variable least-squares fitting ensures non-negative values of both slant TEC and vertical TEC. The second order Taylor series expansion could provide a relevant TEC spatial gradients and TEC time derivatives. The technique validation was performed by using independent experimental data over 2014 and the IRI-2012 and IRI-plas models. As a TEC source we used Madrigal maps, CODE (the Center for Orbit Determination in Europe) global ionosphere maps (GIM), the IONOLAB software, and the SEEMALA-TEC software developed by Dr. Seemala. For the Asian mid-latitudes TuRBOTEC results agree with the GIM and IONOLAB data (root-mean-square was 10 TECU). About 9% of vertical TECs from the TuRBOTEC estimates exceed (by more than 1 TECU) those from the same algorithm but without constraints. The analysis of TEC spatial gradients showed that as far as 10–15° on latitude, TEC estimation error exceeds 10 TECU. Longitudinal gradients produce smaller error for the same distance. Experimental GLObal Navigation Satellite System (GLONASS) DCB from TuRBOTEC and CODE peaked 15 TECU difference, while GPS DCB agrees. Slant TEC series indicate that the TuRBOTEC data for GLONASS are physically more plausible.

Mapping topside ionospheric vertical electron content from multiple LEO satellites at different orbital altitudes

Abstract: In this paper, we present an approach to generating a global topside ionospheric map (GTIM) using dual-frequency global positioning system (GPS) data from multiple low Earth orbit (LEO) satellites at different orbital altitudes. NeQuick2 is employed to normalize LEO data to the same observation range, and 13 LEO satellites from 2015/01/01 to 2015/09/27 are used to generate GTIM-500 (with an ionospheric range from 500 km to 20,200 km) and GTIM-800 (with an ionospheric range from 800 km to 20,200 km). First, we use the coinciding pierce point technique to study the error induced by altitude normalization. The results show that the relative bias error is approximately 1%. Then, the performance and accuracy of the GTIMs as well as the differential code bias (DCB) of GPS receivers onboard LEO and GPS satellites are compared and analyzed. The statistical results of the differences between the official LEO-DCB products and the LEO-DCBs estimated by our different solutions show a RMS improvement of 23% and 41% for GTIM-500 and GTIM-800, respectively. The improvement in RMS of GPS-DCBs for the proposed method is approximately 20%. Finally, the accuracy of GTIM is evaluated by the dSTEC assessment method. The results show that the RMS of GTIM-500 is 0.50 TECU (total electron content unit) for both methods. In terms of GTIM-800 estimated by the proposed method, the RMS has an improvement of 24%.

Prediction of the thermospheric and ionospheric responses to the 21 June 2020 annular solar eclipse

Abstract: On 21 June 2020, an annular solar eclipse will traverse the low latitudes from Africa to Southeast Asia. The highest latitude of the maximum eclipse obscuration is approximately 30°. This low-latitude solar eclipse provides a unique and unprecedented opportunity to explore the impact of the eclipse on the low-latitude ionosphere–thermosphere (I–T) system, especially in the equatorial ionization anomaly region. In this study, we describe a quantitative prediction of the impact of this upcoming solar eclipse on the I–T system by using Thermosphere–Ionosphere–Electrodynamics General Circulation Model simulations. A prominent total electron content (TEC) enhancement of around 2 TEC units occurs in the equatorial ionization anomaly region even when this region is still in the shadow of the eclipse. This TEC enhancement lasts for nearly 4.5 hours, long after the solar eclipse has ended. Further model control simulations indicate that the TEC increase is mainly caused by the eclipse-induced transequatorial plasma transport associated with northward neutral wind perturbations, which result from eclipse-induced pressure gradient changes. The results illustrate that the effect of the solar eclipse on the I–T system is not transient and linear but should be considered a dynamically and energetically coupled system.

Comparison of TEC from IRI-2016 and GPS during the low solar activity over Turkey

Abstract: This paper presents the performance of the latest version of the International Reference Ionosphere (IRI-2016) model for estimating the Total Electron Content (TEC) variations in the mid-latitudinal Turkish regions during low solar activity years (2015–2018). Moreover, TEC is estimated from dual-frequency Global Navigation Satellite System (GNSS) receivers operating in different regions of Turkey: Zonguldak (41.44 °N, 31.77 °E), Ankara (39.88 °N, 32.75 °E) and Antalya (36.88 °N, 30.66 °E). The diurnal, monthly and seasonal variations in the measured TEC are compared with the prediction of modelled TEC. The results reveal minimum variations in the diurnal TEC after midnight hours 21:00–24:00 Universal Time ( $\text{UT}=\text{LT}+3{:}00~\text{hrs}$ ) and maximum TEC enhancement during the daytime from 9:00–15:00 UT (12:00–18:00 LT). The monthly mean TEC from measured and modelled estimation depicts the highest and lowest values in April and December during the years 2015–2018, respectively. Moreover, the low and high seasonal variations are observed in equinoxes and winter solstice, respectively. Furthermore, it is observed that IRI-2016 model underestimates the measured values, especially during the daytime (12:00–18:00 LT) at each station. The correlation coefficient between the measured and modelled TEC is found in the range ( $R=0.81\text{--}0.85$ ) during the years 2015–2018, which exhibits a high positive correlation over the regions. The model predicted TEC is showing a good agreement with measured TEC of the ionospheric dynamics over the regions, which manifests the radio signals accuracy over the mid-latitude regions, particularly Turkey.

Ionospheric Response at Conjugate Locations During the 7–8 September 2017 Geomagnetic Storm Over the Europe-African Longitude Sector

Abstract: This paper focuses on unique aspects of the ionospheric response at conjugate locations over Europe and South Africa during the 7–8 September 2017 geomagnetic storm including the role of the bottomside and topside ionosphere and plasmasphere in influencing electron density changes. Analysis of total electron content (TEC) on 7 September 2017 shows that for a pair of geomagnetically conjugate locations, positive storm effect was observed reaching about 65% when benchmarked on the monthly median TEC variability in the Northern Hemisphere, while the Southern Hemisphere remained within the quiet time variability threshold of ±40%. Over the investigated locations, the Southern Hemisphere midlatitudes showed positive TEC deviations that were in most cases twice the comparative response level in the Northern Hemisphere on the 8 September 2017. During the storm main phase on 8 September 2017, we have obtained an interesting result of ionosonde maximum electron density of the F2 layer and TEC derived from Global Navigation Satellite System (GNSS) observations showing different ionospheric responses over the same midlatitude location in the Northern Hemisphere. In situ electron density measurements from SWARM satellite aided by bottomside ionosonde-derived TEC up to the maximum height of the F2 layer (hmF2) revealed that the bottomside and topside ionosphere as well as plasmasphere electron content contributions to overall GNSS-derived TEC were different in both hemispheres especially for 8 September 2017 during the storm main phase. The differences in hemispheric response at conjugate locations and on a regional scale have been explained in terms of seasonal influence on the background electron density coupled with the presence of large-scale traveling ionospheric disturbances and low-latitude-associated processes. The major highlight of this study is the simultaneous confirmation of most of the previously observed features and their underlying physical mechanisms during geomagnetic storms through a multi–data set examination of hemispheric differences. © 2020. American Geophysical Union. All Rights Reserved.

Adaptive Modeling of the Global Ionosphere Vertical Total Electron Content

Abstract: The Kalman filter (KF) is widely applied in (ultra) rapid and (near) real-time ionosphere modeling to meet the demand on ionosphere products required in many applications extending from navigation and positioning to monitoring space weather events and naturals disasters. The requirement of a prior definition of the stochastic models attached to the measurements and the dynamic models of the KF is a drawback associated with its standard implementation since model uncertainties can exhibit temporal variations or the time span of a given test data set would not be large enough. Adaptive methods can mitigate these problems by tuning the stochastic model parameters during the filter run-time. Accordingly, one of the primary objectives of our study is to apply an adaptive KF based on variance component estimation to compute the global Vertical Total Electron Content (VTEC) of the ionosphere by assimilating different ionospheric GNSS measurements. Secondly, the derived VTEC representation is based on a series expansion in terms of compactly supported B-spline functions. We highlight the morphological similarity of the spatial distributions and the magnitudes between VTEC values and the corresponding estimated B-spline coefficients. This similarity allows for deducing physical interpretations from the coefficients. In this context, an empirical adaptive model to account for the dynamic model uncertainties, representing the temporal variations of VTEC errors, is developed in this work according to the structure of B-spline coefficients. For the validation, the differential slant total electron content (dSTEC) analysis and a comparison with Jason-2/3 altimetry data are performed. Assessments show that the quality of the VTEC products derived by the presented algorithm is in good agreement, or even more accurate, with the products provided by IGS ionosphere analysis centers within the selected periods in 2015 and 2017. Furthermore, we show that the presented approach can be applied to different ionosphere conditions ranging from very high to low solar activity without concerning time-variable model uncertainties, including measurement error and process noise of the KF because the associated covariance matrices are computed in a self-adaptive manner during run-time.