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• Long-term trends in foF2 change remarkably with the solar activity proxy used. • F30 is the only proxy, which provides trends of the same sign for all stations. • I recommend F30 as the best solar proxy for trends of foF2 at midlatitudes. The most studied ionospheric parameter for long-term trends is foF2. The dominant factor of foF2 variability is the solar cycle, which is much stronger than the long-term trends. Therefore its effect in data must be removed. However, several decade long homogeneous measurements of the solar EUV fluxes are not available, so various solar activity proxies (solar activity indices) must be used. The aim of this paper is to study the impact of selection of different solar activity proxies on foF2 long-term trends and to find the best solar activity proxy for foF2 trends at middle latitudes. The results based on yearly average data of six midlatitude stations from four continents (1976–2014) and of six solar activity proxies show that the long-term trends in foF2 depend substantially on the solar activity proxy used, and the only solar proxy, which provides trends of the same sign for all stations and both sub-periods, is F30. Based on results of this paper and that of Laštovička and Burešová (2023) , I can recommend F30 as the best solar proxy for studying long-term trends of foF2 at middle latitudes (at least for yearly average values). [ABSTRACT FROM AUTHOR]

The Triple Ionosophere PhotoMeter (TRIPM) is designed to make the disk observations of the Earth airglow emissions at OI 135.6 nm and N 2 Lyman-Birge-Hopfield (LBH) band that flew aboard the newly launched early morning satellite Fengyun-3E (FY-3E) which was launched on July 5th, 2021. This is the first attempt to obtain the global twilight airglow data in the far ultraviolet band using Ionosophere PhotoMeter. The seasonal behavior of the twilight airglow at the OI 135.6 nm and N 2 LBH band is exhibited and interpreted in the paper. Validity of the TRIPM data is analyzed by comparison with the simulation results of the Global Airglow (GLOW) and the simulation results reveal good consistency with the observational results. Furthermore, based on the ionospheric contributions calculated by GLOW model, we extract the ionospheric information from the TRIPM 135.6 nm emissions. This means the ionospheric signature in the 135.6 nm radiance at the dawn and dusk times can be provided. Comparison between the ionospheric 135.6 nm radiance due to O+ and electron radiative recombination with GPS TEC data shows a similar morphology of equatorial arcs and seasonal variation of the ionosphere. [ABSTRACT FROM AUTHOR]

This work presents a summary of the continuous non-stop (hereinafter 24/7) real-time measurement and warning system for EUV solar activity, which is based on worldwide multifrequency Global Navigation Satellite Systems (GNSS) observations. The system relies on continuous tracking of the intensity of expected global patterns in the Earth's ionosphere's free electron distribution, which are associated with solar flares. The paper includes a discussion on the foundations of GNSS Solar Astronomy, along with details on its real-time implementation that began in 2011. Furthermore, a summary of the corresponding validation is provided, comparing it to external and direct solar EUV flux measurements obtained from SOHO-SEM. Finally, there will be a brief mention of the ongoing efforts to extend this technique to detect huge extra-solar sources. [ABSTRACT FROM AUTHOR]

• For the first time, the ionospheric response to a solar eclipse was observed on a global scale. • Changes in all TEC disturbance parameters depended in a complex manner on relative obscuration area. • Delay time of maximum ionospheric response with respect to maximum eclipse magnitude was 15–25 min. • Duration of ionospheric response to the eclipse exceeded the duration of disturbing source influence. Solar eclipses (SEs) pertain to high-energy sources. They are capable of causing significant disturbances in all geoshells and geophysical fields. Despite the almost century-long history of studying the influence of eclipses on geoshells, the task of observing and analyzing disturbances in them remains relevant. This is explained by the fact that the response of the media significantly depends on the state of atmospheric and space weather, the location and time of observation, the SE magnitude, etc. The aim of this paper is to present the results of a statistical analysis of the features of the total electron content (TEC) variations during the October 25, 2022 SE from high to low latitudes in the Euro-Asian region. Data from Global Navigation Satellite System were used for the analysis. The error in estimating TEC in the vertical column did not exceed 0.1 TECU. For the first time, the response of the ionosphere to an SE has been studied on a global scale (from the Reykjavik station to the Novosibirsk station) using methods of statistical analysis, including the time moments after sunset. The decrease in TEC reached 1.0–19.0 TECU, and the relative decrease was approximately –0.32. Changes in all TEC disturbance parameters depended in a complex manner on the relative obscuration area of the solar disk. This can be explained by non-monotonic changes in electron density during the daytime, by the intensification of the ionosphere–plasmasphere coupling, the disturbance of the ionospheric current system, vertical plasma drift in crossed electric and magnetic fields, as well as the generation of wave disturbances during the SE period. The delay time of the maximum ionospheric response (maximum |δ V | value) with respect to the maximum magnitude of the eclipse was 15–25 min. The duration of the ionospheric response to the SE slightly exceeded the duration of the perturbing source influence. [ABSTRACT FROM AUTHOR]

The total electron content (TEC) of the ionosphere is an important parameter to describe the ionosphere, and it is a great significance to monitor and predict it accurately. In this paper, a hybrid ionospheric TEC prediction model based on the least squares support vector machine (LSSVM) and the Moth-Flame Optimization (MFO) algorithm is proposed. The parameters of the LSSVM model are optimized by the MFO algorithm. We use observation data of 15 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) to extract ionospheric TEC from 2012 to 2019. The ionospheric TEC is forecasted using solar and geomagnetic activity indices in both the low solar activity year (2019) and the high solar activity year (2015). The results show that the prediction performance of the MFO_LSSVM model is significantly better than that of the IRI model, SVM model, and LSSVM model. Compared with the other three models, there are more stable prediction results in the low and high solar activity years. At the same time, the predicted value of the MFO_LSSVM model has a good correlation with the measured value, and it also has good prediction potential in areas with active geomagnetic activity. The comparison with the Long Short-Term Memory (LSTM) model shows that the MFO_LSSVM model has better performance than the single LSTM model. In conclusion, the MFO_LSSVM model can accurately predict ionospheric TEC in China, and has better accuracy than traditional long-term and short-term models. [ABSTRACT FROM AUTHOR]

• Low-latitude topside ionosphere mismodelling made by NeQuick. • Improving of the NeQuick topside representation through COSMIC-1 data. • Different topside tests with different values of the NeQuick topside parameters. This paper deals with the well-known mismodelling characterizing the NeQuick topside ionosphere at low latitudes, i.e., the fact that the model keeps the two electron density humps typical of the equatorial ionization anomaly as the altitude increases from the height of the F2-layer electron density peak, without merging them in a single peak above the geomagnetic equator as expected. This is because the NeQuick topside ionosphere modelling strongly depends on several bottomside ionosphere parameters, which causes an essential coupling between the topside and the bottomside that in many cases behave differently. This means that this kind of topside ionosphere modelling may lead to inaccurate results, as it is the maintenance at low latitudes of the electron density double hump structure in the topside as the altitude increases. On the base of some recently published results, this paper analyzes the role played by the three NeQuick scale height parameters H 0 , g and r in the description of the electron density above the F2 layer peak height. The results of this work pave the way for a possible solution of this low-latitude NeQuick topside ionosphere mismodelling. [ABSTRACT FROM AUTHOR]

In this paper, we propose a gate recurrent unit (GRU) method to forecast ionospheric the total electron content (TEC) at different latitudes and longitudes. This method aims to address the issues of low accuracy in traditional neural networks and the challenges faced in training long-term time series. We construct a GRU model using TEC data from the European Orbit Determination Center (CODE) for the years 2016 to 2018, geomagnetic indices, and solar activity indices (16 points along the latitude and longitude lines of 120°E and 30°N). Comparative experiments are carried out with the international reference ionosphere (IRI) model and the long short-term memory (LSTM) model. The results show that the GRU model outperforms other models in terms of accuracy. On geomagnetic quiet days, the 5-day predicted average residual can reach 0.51 TECU, while on storm days it can reach 0.72 TECU. The root mean square error (RMSE) for these days is 0.64 TECU and 1.01 TECU, respectively. The correlation coefficients are 0.98 and 0.93, respectively. The RMSE of the GRU model ranges from 0.60 TECU to 2.62 TECU for both geomagnetic quiet days and storm days. In terms of TEC forecast accuracy in 2018, the RMSE of the GRU model is 1.6 TECU, which is smaller than that of the IRI model and LSTM model. These results demonstrate that the GRU model performs better than the IRI model and LSTM model. [ABSTRACT FROM AUTHOR]

• In this study, we conducted a statistical analysis of foF2 and TEC data under both ionospheric quiet and disturbed conditions, employing the ionospheric slab thickness model. • The utilization of Kriging with external drift (KED) in generating maps has enhanced their realism. • The inclusion of foF2 data from the map's periphery has resulted in the overall stabilization of the map. • Based on our findings, we can conclude that the correlation distance between ionospheric characteristics should not exceed the range of 120–300 km. The importance of this study lies in its contribution to the field of ionospheric science, particularly in the monitoring and prediction of ionospheric parameters. This study focuses on comparing two techniques for spatio-temporal kriging of critical ionospheric parameters, namely the F2 layer critical frequency (foF2) and Total Electron Content (TEC), under both quiet and disturbed ionospheric conditions. The first technique, Ordinary Kriging (OK), relies solely on foF2 data, while the second technique, Kriging with External Drift (KED), incorporates the dynamic relationship between foF2 and TEC data to improve the interpolation process. This study demonstrates how KED, which utilizes dynamic secondary information, offers advantages over OK. By simultaneously monitoring the ionosphere from a single ionosonde station and collecting data from visible GPS satellites, KED enhances the accuracy of spatial structural analysis, enabling more precise estimations of ionospheric characteristics across interpolation grid nodes. The research highlights that the non-uniform distribution of ionosonde stations, especially in regions with limited foF2 data, can benefit from KED's incorporation of TEC data. Additionally, the study reveals the potential for improving TEC maps by assimilating foF2 data located at the periphery of the observation area. Furthermore, the paper discusses the determination of semivariogram structures for both foF2 and TEC data, emphasizing the spatial correlations between data points. These findings contribute to a better understanding of ionospheric behavior and the potential for enhanced ionospheric modeling. [ABSTRACT FROM AUTHOR]

Many studies have investigated the spatial variations of the ionosphere, but the quantitative characteristics of the ionosphere are rarely reported. In this paper, we utilize the total electron content (TEC) data to evaluate the latitudinal gradient of the ionosphere within 10°-50° N over the China sector. It is found that the magnitudes of latitudinal gradient are significantly higher within 10°-40° N and 45°-50° N, respectively. The database of TEC from 1 November 2018 to 31 October 2022 is processed to figure out the local time, seasonal, and solar activity dependency of the latitudinal gradient. The results suggest that the gradient within 10°-40° N is higher in the daytime and during high solar activity period. They are more noticeable in the spring and autumn, and least visible in the summer. Conversely, the gradient within 45°-50° N strengthens in the nighttime and under lower solar activity, and has larger values in the summer months. Furthermore, the International Reference Ionosphere (IRI-2020) model is assessed in terms of the reproducibility of latitudinal gradient. The IRI-2020 basically represents the latitudinal gradient within 10°-40° N, whereas it overestimates the gradient in the low solar activity period and misses the gradient features near 45°–50° N. [ABSTRACT FROM AUTHOR]

This paper investigates the ionospheric responses to the February and April 2023 geomagnetic storms using Total Electron Content (TEC) derived from the 10 Global Navigation Satellite System (GNSS) stations at the transition of low to mid-latitudes (Approx. 20 ∼ 30°N) across different longitudes in the American and Asian sectors. Significant variations in both sectors were recorded during the recovery phase and were mainly attributed to the Prompt Penetration Electric Field (PPEF), Disturbance Dynamo Electric Field (DDEF) and the thermospheric neutral composition changes as O/N 2 depletion. Similarly, the American and Asian sectors showed TEC enhancements, primarily attributed to the PPEF, during the main phase of the April storm. The negative TEC variations during the recovery phase were observed due to the DDEF and changes in O/N 2. In the Asian sector, positive and negative variations were recorded over Pakistan and China, respectively, during the main phase of the April storm. These variations resulted in high and low concentrations of the O/N 2 ratio due to Magnetosphere-Ionosphere-Thermosphere coupling. [ABSTRACT FROM AUTHOR]

In this paper, we attempt to compare the Antarctic SSW of 2019 with the Arctic SSW of 2013. Despite being a minor SSW, the rare Antarctic event of September 2019 caused a significant enhancement of stratospheric temperature at high latitudes with more temperature deviation than the Arctic major SSW of 2013. On the basis of the duration and extent of stratospheric zonal mean zonal wind, the 2019 SSW is comparable to major SSWs. An exceptionally strong wave 1 planetary wave was observed during the 2019 SSW. We have investigated the response of the ionospheric total electron content (TEC) during both the SSWs over two low mid-latitude locations Okinawa and Darwin, which form magnetic conjugate pair. The extent of maximum ionospheric deviations during the 2019 SSW is almost comparable to the 2013 SSW in their respective hemispheres. We have observed mostly night time enhancement in TEC during the Arctic SSW, while daytime enhancement is noted during the Antarctic SSW. Hemispheric asymmetry is observed during both the SSWs. Minor geomagnetic storm has been noticed coinciding with each SSW during different phases of the warming. The SSW, solar flux, and storm contribution on the TEC have been calculated during both the SSWs, which shows clear contribution of SSW on the total TEC despite the presence of storm and during moderately high solar activity. We have also investigated the foF2 variations from ionosonde and IRI-16 at the same two locations. The peak electron density from ionosonde responds to the warming in a manner similar to TEC. The foF2 of IRI-16 exhibits overestimation during daytime and underestimation during nighttime on quiet days during low solar activity (2019), while during moderate solar activity (2013), it overestimates during morning hours. However, it can not predict the enhancements of foF2 during SSWs. [ABSTRACT FROM AUTHOR]

• IRI-2020 overestimates the GPS-TEC in almost all cases except on some occasions. • Both IRI versions show better predictions over Arequipa than other stations. • Over Turkwel, IRI-2020 overestimated in all seasons except in December solstice. • During storm times, IRI-2020 better reproduced positively enhanced GPS-TEC. • However, both IRI versions do not show the storm effects observed on GPS-TEC. In this paper, we evaluate and report the International Reference Ionosphere (IRI) model's vertical Total Electron Content (TEC) regional profile. Diurnal, monthly, seasonal, and storm-time characteristics of IRI estimates over the equatorial region's ionosphere are validated. We compared the vertical TEC derived from IRI-2020 and its predecessor, IRI-2016, with the GPS-TEC measurements. Results show that IRI (both versions) agrees with observed TEC during solar cycle maximum periods. Exceptionally, over Turkwel station, IRI-2020 produced double peak profiles on the March equinox, June solstice, and September equinox and overestimated with larger discrepancies. Over the other three stations, both IRI versions reproduced the seasonal averaged observed TEC with only slight time lags and discrepancies. During geomagnetically perturbed times, IRI-2020 better indicated positively enhanced GPS-TEC than IRI-2016. However, during the March 17, 2015 storm, IRI-2020 underestimated the storm-enhanced TEC over Bahir Dar station at all phases of the storm. IRI-2016 shows good performances for negative storms where lower TEC measurements are recorded. [ABSTRACT FROM AUTHOR]

This paper reports the results of the most recent validation tests on the performance of the Solar Wind driven autoregression model for Ionospheric Forecast (SWIF). SWIF uses the Interplanetary Magnetic Field (IMF) observations at L1 point as a proxy for upcoming ionospheric storm time disturbances, issuing an alert in case certain quantitative criteria are met. These criteria apply to the IMF total magnitude and the IMF-Bz component. The validation tests address the SWIF alert detection efficiency in the period 2014–2020 and were designed to complement previous efforts and allow the comprehensive discussion of SWIF's alert ability over one and a half solar cycle. The model's efficiency is quantified through probability of detection, false alarm rate and the success ratio for SWIF's users. The results are further discussed in terms of the intensity and the interplanetary causes of the storms to reveal high forecasting ability for specific storm scenarios (i.e. intense storms that are usually driven by coronal mass ejections), but also certain limitations in the efficiency of SWIF's alert criteria in capturing storm related interplanetary structures at L1 point: mainly structures that are not related to coronal mass ejections and typically, drive storms of moderate intensity. Additional results obtained by superposed epoch analysis of IMF key components indicate the potential relevance of the IMF-By component in ionospheric forecasting applications. The consideration of the IMF-By in SWIF's formulation can drive future improvements in its forecasting efficiency in all different faces of solar wind forcing. The findings of this work may also help the better understanding of the processes that control the coupling of the solar wind-magnetosphere-ionosphere. [ABSTRACT FROM AUTHOR]

• A novel approach for regional ionosphere grid model with high spatial-temporal resolution is suggested. • The results of the new model is analyzed at different disturb geomagnetic and solar conditions. • A comparative analysis between the results of new model, GIM, NeQuick and GPS-TEC is made. In this paper, a novel approach based on C1 finite element (FE) interpolation is used to construct a regional ionospheric grid model (RIGM) with high spatio-temporal resolution over Europe. The spatial resolution of the new model is 0.50 for a longitude and latitude and a temporal resolution is 15 min. Observations of 38 GPS stations at different days and seasons with different geomagnetic and solar activity conditions are used to evaluate the new method. All stations are used to discretize the whole domain of the problem into separate triangular patches using a Delaunay triangulation algorithm. In this case, GPS stations would be the vertices of the triangular patches. Also, the position of stations in sun-fixed coordinate system with coordinates of latitude and longitude are chosen in order to consider the temporal variations of vertical total electron content (VTEC). To model the behavior of VTEC in each triangular patch, a particular shape function is defined which is fitted to VTEC values at three vertices of each triangle while it satisfies C1 continuity of VTEC at the common edges of the adjacent triangles. The results of the new model are compared with the VTEC of GPS at 4 control stations as well as global ionosphere map (GIM) and NeQuick models. Statistical parameters, including correlation coefficient, root mean square error (RMSE), standard deviation and dVTEC = |VTEC GPS - VTEC model | have been used to evaluate the error of the models. In low geomagnetic activity (KP < 4), the average RMSE at 4 control stations for FE, GIM and NeQuick models are 0.89, 1.05 and 6.42 TECU, respectively, while in the high geomagnetic activity (KP > 4), they are 1.24, 1.68 and 7.62 TECU, respectively. For further analysis, the accuracy of three models in precise point positioning (PPP) has been also evaluated. In PPP method, there is an improvement of about 1–16 mm compared to GIM and NeQuick models at coordinate components of control stations in high geomagnetic activity. The results of the analysis performed in this paper show that the FE model has a very high capability and accuracy in regional VTEC modeling in high and low geomagnetic conditions. The regional accuracy of this model is higher than GIM and NeQuick models and therefore can be considered as a new model for the ionosphere. [ABSTRACT FROM AUTHOR]

• In the paper the ionospheric manifestations of tropical cyclones are considered. • We studied cyclones 4–5 category in quite geomagnetic conditions. • Ionosphere electron density data obtained by ESA Swarm mission. • The identified disturbances in the ionosphere have acoustic-gravity parameters. • The statistics of the detected phenomena with relative amplitude 4–10% is given. The paper discusses the issues of the disturbances allocations in the ionosphere that are associated with large atmospheric events - tropical cyclones of the 4–5 categories of 2014. On the basis of the characteristic spatio-temporal characteristics of the acoustic-gravity waves from atmospheric disturbances, the method is proposed for the detection of relative disturbances of the electron concentration in the frequency band characteristic of the disturbances. The observation of electron density by Langmuir probes carried out on the ESA Swarm satellites were used as experimental data. In the paper we consider all large 2014 Tropical Cyclones (TC) and discuss the statistics of the identified disturbances from TC in the ionosphere against the background of regular changes in the electron density in quiet geo-heliomagnetic conditions. The obtained results show that the wave mechanism of disturbance transmission from an atmospheric source to ionospheric heights is not the only one. [ABSTRACT FROM AUTHOR]

The east–west electric field and the characterized horizontal configuration of the geomagnetic fields around the equatorial region cause electron redistribution in the ionospheric bottomside F- region. This electric field E in turn causes the flow of current in a narrow band around this region called Equatorial Electrojet (EEJ) current. The paper discusses the robust least square modelling approach for modelling some selected ionospheric profile parameters below the maximum height of the F2 layer from the computed EEJ values at Jicamarca station (12°S, 76.9 °W) in the Southern American sector and Ilorin (8.50°N, 4.68°E) in the West African sector. The modelled parameters are the maximum electron density, NmF2, the maximum height, hmF2 and the thickness parameter, B0 of the F2- layer which were then compared with the recent ionospheric international standard model (IRI-2016). The proposed new model for ionospheric parameters based on ground-based magnetic field data at specific locations improved the model fit for hmF2 with RMSE value ∼ 30 km, an improvement to the IRI hmF2 model options. In addition, the derived NmF2 model performs poorly as compared to the IRI URSI and CCIR model options for NmF2. The model was however able to reproduce the temporal changes in the NmF2, for example, the semi-annual variation in the observational NmF2 value. The specific local features that were not fully reproduced in the IRI B0 model options can be seen in the derived model. [ABSTRACT FROM AUTHOR]

It has been a concern of space scientists and engineers for many decades to have a well-defined proxy to characterize the fluctuations experienced by radio-based signals propagating through the ionosphere. Scintillation indices were deduced using the signal intensity to show the level of fluctuations in phase and amplitude of radio signal passing through the ionosphere. Subsequently, more than two decades now, the rate of change of Total Electron Content (TEC) index (ROTI) was as well used to characterize the level of fluctuations associated to ionospheric irregularities on radio signals. This paper examines the level of relationship between the rate of change of TEC index (ROTI) and the ionospheric amplitude scintillation (S4) within the belt of equatorial ionization anomaly of West African sector. The study was carried out using the Scintillation Network Decision Aid (SCINDA) Global Positioning System (GPS) data obtained from ground-based stations located at Dakar (Senegal) and Cape Verde. The comparative analysis of ROTI and S4 was done with normalized ROTI. The results obtained have shown that the magnitude of normalized ROTI and S4 corresponds very well, higher in Cape Verde compared to Dakar. It was observed that the correlation coefficient could be ∼0.6 when all the satellites are used. However, the relationship increases with individual satellite in which the coefficient of correlation could be up to ∼0.97 and R2 ∼ 0.94. It can be concluded that the relationship between the S4 and ROTI depends on the location and the level of ionospheric disturbance condition as observed in this work. [ABSTRACT FROM AUTHOR]

In this paper, we developed an empirical model for predicting Total Electron Content (TEC) on a single station receiver located within the equatorial anomaly crest region at Helwan – Egypt (29.86°N, 31.32°E & MLAT 27.02°N). The neural network algorithm was developed from several inputs representing diurnal, seasonal, and solar cycle variations, solar and geomagnetic activity, and solar wind parameters using TEC data collected by the SCINDA GPS receiver. The TEC data collected for about nine years from 2009 to 2017 comprises almost the whole solar cycle 24 allowing the developed model to be validated and tested for different solar activity conditions. The 2009 – 2016 dataset was randomly divided into 70% for training, and 30% for validation during model development while the 2017 dataset was reserved for testing the model during independent validation. The validation was done by comparing TEC from the developed model and TEC derived from the GPS scintillation and TEC monitor (GPSTEC). Knowing that TEC modeling over the equatorial anomaly crest regions is challenging since it is characterized by high temporal and spatial variations, the developed model reconstructed diurnal GPSTEC from 2014 to 2016 with a root mean square error (RMSE) of 4.0 TECU and 3.2 TECU for high and low solar activity phases respectively. The neural network (NN) modeled TEC was highly correlated with GPSTEC, that is 0.93 and 0.94 for low and high solar activity respectively. In comparison, the International Reference Ionosphere (IRI)-2016 model predicted the general trend of GPSTEC in 2017 with RMSE of 5.43 TECU better than the developed TEC model with RMSE of 5.74 TECU. However, the NN model predicted diurnal GPSTEC for selected quiet and disturbed days, and seasonal TEC better than the IRI model in 2017. Therefore, the developed model was able to capture temporal ionospheric TEC for diurnal and seasonal variations during low solar activity. It was established that the performance of the empirical model depends on the size and distribution of the data used for model development. It's worth noting that despite the improved performance of the NN algorithm in predicting diurnal and seasonal TEC variation, the NN-modeled TEC performed poorly in reconstructing the nighttime anomalies exhibited in the GPSTEC. The inclusion of the IRI-NmF2 as network input also adds to the improved performance of the network. [ABSTRACT FROM AUTHOR]

Recently, the equivalent slab thickness τ of the ionosphere has attracted great attention. This is due to its role in determining the critical frequency foF 2 from the data of the total electron content TEC, which is important in obtaining the characteristics of the high frequency HF radio waves propagation, especially during disturbances, when vertical sounding data may be absent. Currently, a global Neustrelitz equivalent Slab Thickness Model NSTM model has been developed, for the use of which it is sufficient to have 12 coefficients and an index of solar activity. On the other hand, empirical models, in particular the IRI-Plas model, in which TEC and the maximum density NmF 2 are calculated, are also global and can provide values of τ on a global scale. These models can complement each other, but both need to be testing. Preliminary comparison of the NSTM model with the NGM model whose values were calculated as the quotient of values TEC(NTCM-GL) and NmF2(NPDM) has shown better performance for the τ(NSTM) model. In this paper, τ is compared for the NSTM and IRI-Plas models using the Grahamstown station data for 2001–2010. It is shown that both models reflect the diurnal and seasonal variations of the observational τ. To quantify the correspondence between the model and observational values of τ, standard metrics were used: the mean absolute error (MAE), the root mean-square-error (RMSE), the normalized root-mean-square error (NRMSE). The MAE values were 87.6 km for the NSTM model and 64.7 km for the IRI-Plas model in 2001. The corresponding values in 2007 were 70.2 km and 58 km. The RMSE values were 109.1 km for the NSTM model and 80 km for the IRI-Plas model in 2001. For low solar activity conditions, the RMSE values are 87.0 km and 73.1 km (that is, the values for IRI-Plas are also smaller than for NSTM). The NRMSE values are 25.2 % and 18.4 %, respectively, under high solar activity, and 21.2 % and 18.0 % under low solar activity. The greatest RMSE of the model values concern morning and evening hours: they can reach 180 km for the NSTM model and 120 km for the IRI-Plas model. [ABSTRACT FROM AUTHOR]

• Midlatitude VTEC correlated with EEJ, latitudinal extent of O/N 2 , neutral wind and station location. • Prolonged plasma transport in June 2015 was due to equatorward wind, intense Joule heating and high ionospheric conductivity. • Cases when GUVI O/N 2 did not correlate with VTEC can be explained by plasmaspheric contributions. The present paper reports magnetospheric-thermospheric-ionospheric interactions, observed during geomagnetically disturbed periods in 2015–2016 from mid-latitude stations located in the US-Pacific longitudes (~120°W geographic). These interactions have been analyzed for a series of Coronal Mass Ejection (CME) and High Speed Solar Wind (HSSW) driven geomagnetic storms during the moderate solar activity periods. The geomagnetically disturbed periods under consideration in this paper have an interesting feature of the occurrences of one or more HSSW events following an intense CME driven intense geomagnetic storm. Correlations were observed between the solar and geomagnetic parameters, hemispherically integrated Joule heating, changes in O/N 2 ratio, corresponding changes in neutral wind velocities and mid-latitude Vertical Total Electron Content (VTEC) in most of the cases. Prolonged effects of neutral wind driven equatorward plasma transport process were noticed during the period of the summer solstice (June 23–26, 2015) which was correlated with the hemispherically integrated Joule heating and ionospheric conductivities. The effects of storm onset were observed during March 17–18, 2015. The influences of the 'super-fountain effect' in terms of Prompt Penetration Electric Field (PPEF) were seen during the main phases of the geomagnetic storms from these mid-latitude stations. This is correlated with the strength of Equatorial Electrojet (EEJ). [ABSTRACT FROM AUTHOR]

The ionospheric information retrieved from the Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) system provides valuable and external data sources to examine the quality of existing Global Navigation Satellite System (GNSS) generated ionospheric models. The concept of DORIS differential Slant Total Electron Content (dSTEC) analysis is presented, to check the feasibility of DORIS data in the quality assessment of GNSS derived ionosphere models. Thanks to the large relative frequency ratio between the two frequencies of DORIS, the theoretical precision of DORIS dSTEC is at the level of 0.028 TECu, which is about 10 times better than that of GNSS derived dSTEC. Using 48 co-located DORIS beacon sites of the International DORIS service (IDS) and GNSS stations of the International GNSS Service (IGS), the comparison between DORIS and GNSS dSTEC assessments of Real-Time Global Ionospheric Maps (RT-GIMs) from different analysis centers is performed in this paper. The analysis is performed during the first 110 days of 2022. Based on the analysis results of more than 18,000,000 Jason-3 DORIS ionospheric observables, no systematical deviation is found between DORIS and RT-GIM derived dSTECs, with a mean bias of 0.14 TECu. Compared to DORIS dSTEC, the root-mean-square (RMS) of those RT-GIMs reaches 4.5–5.4 TECu at low-latitudes, which is 2.2–3.6 TECu in mid- and high-latitude regions. The latitudinal variation of RT-GIM errors is clearly observed in DORIS dSTEC analysis. In addition, the Pearson correlation coefficient between Jason-3 DORIS dSTEC RMS and GPS-plus-GLONASS dSTEC RMS is 0.81, and no significant dependence on GPS-only or GLONASS-only data is found. It is suggested to perform the dSTEC analysis with higher satellite elevation cutoff angle, e.g., 45°, to ensure a better consistency between DORIS and GNSS dSTEC assessments. Overall, DORIS dSTEC assessment provides an independent reference for the validation of GNSS based ionosphere maps. [ABSTRACT FROM AUTHOR]

• Multifractal analysis of the Ionosphere Layer. • Intermittence in Ionosphere Layer. • Ionosphere Layer out-of-equilibrium. A digital ionosonde of the type known as Canadian Advanced Digital Ionosonde (CADI) is operational at Jatai ( 17.2 o S , 51.9 o W), Brazil. This ionospheric sounding station is located under the equatorial ionospheric anomaly crest. The F-layer electron density profile presents considerable day-to-day variability, even during the undisturbed conditions, and is still one of the less understood aspects of the physics of the ionosphere. The propagation of waves into the ionosphere may be playing an important role in this day-to-day ionospheric variability. In this paper we used the multifractal approach in order to understand the physical process underlying to rise to plasma bubbles. Results shown that the ionosphere layer is in out-of equilibrium, independent of the presence or not of the planetary waves (PW), equatorial plasma bubbles (EPBs) or another ones. Wavelet techniques are also used to investigate the action of these plasma bubbles over the planetary waves. [ABSTRACT FROM AUTHOR]

This paper proposes a new dual-band difference (DBD) method to retrieve total electron content (TEC) in Martian ionosphere with the dual-band echoes of the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS). It establishes the relationship between the group delay difference of two-band echoes and the plasmas frequency. Then the Martian ionospheric parameters are solved with this equation. Then the TEC is calculated by integrating the vertical distribution model of Mars electron density. This method is used to calculate the TEC of the typical ionosphere in the southern hemisphere of Mars, and the comparison with previous results validates this method. The experiments prove that this method can not only calculate the TEC of dayside and nightside in different periods, but also effectively eliminate the influence of ionospheric dispersion on radar echoes. Moreover, the time variation characteristics of the ionosphere are analyzed. According to the characteristics of this algorithm, the error sources are analyzed. By calculating the influence of different parameters on the results, it is proved that the maximum error of the algorithm is less than 0.1 TECU. [ABSTRACT FROM AUTHOR]

Here, we explore the different characteristics of a possible coupling between tropospheric and ionospheric activities during the impact of tropical cyclones (TC) like Amphan and Nisarga in the Indian subcontinent. We have analyzed the effect of TCs Amphan and Nisarga on the low latitude ionosphere using the measurements from several IGS stations around India and a GPS + NavIC station in Indore, India. For the first time, this study assesses the impact of tropical cyclones on the equatorial ionosphere using both GPS and NavIC. After the landfall of TC Amphan, the VTEC analysis shows a significant drop from nominal values in both NavIC as well in GPS by 5.1 TECU and 3.6 TECU, respectively. In contrast to TC Amphan, Nisarga showed a rise in VTEC which ranged from 0.9 TECU in GPS to 1.7 - 5 TECU in NavIC satellites except for PRN6. The paper examines Outgoing Longwave Radiation as a proxy to the convective activity which may be responsible for the ionospheric variation through the generation of gravity waves. In addition, the horizontal neutral wind observations at the location of TC landfall confirm the presence of ionospheric disturbances. VTEC perturbation analysis using a band-pass filter reveals a variation in differential TEC values between ± 0.4 and ± 0.8 based on the IGS station measurements. This indicates that the gravity wave is one of the responsible mechanisms for the lower–upper atmospheric coupling during both cyclones. [ABSTRACT FROM AUTHOR]

IPM has detected nightside 135.6 nm emission enhancements over a wide latitude range, from the sub-auroral latitudes to the equatorial regions during geomagnetic storms. Our work, presented in this paper, uses the data of IPM to understand these 135.6 nm emission enhancements during of geomagnetic storms and studies the variations of total electron content (TEC) and the F 2 layer peak electron density (NmF2) in the region of enhanced emissions. Middle and low latitude emission enhancements are presented during several medium storms in 2018. The variations of both the integrated electron content (IEC) derived from the nighttime OI 135.6 nm emission by IPM and TEC from the International GNSS Service (IGS) relative to the daily mean of magnetically quiet days of per each latitude bin (30°≦geographic latitude < 40°, 15°≦geographic latitude < 30°, 0°≦geographic latitude < 15°, −15°≦geographic latitude < 0°, −30°≦geographic latitude < -15°, −40°≦geographic latitude < -30°) are investigated and show that on magnetically storm day, IEC by IPM always increases, while TEC from IGC may increase or decrease. Even if both increase, the increase of IEC is greater than that of TEC. From the comparison of IEC and TEC during magnetic storms, it can be seen that the enhancement of the nighttime 135.6 nm emissions is not entirely due to the ionospheric change. The time of IEC enhancements at each latitude bin is in good agreement, which mainly corresponds to the main phase time of the geomagnetic storm event and lasts until the recovery phase. The available ground-based ionosonde stations provide the values of NmF2 which match the 135.6 nm emissions measured by IPM in space and time. The variations of NmF2 squared can characterize the variations of the OI 135.6 nm emissions caused by O+ ions and electrons radiative recombination. The study results show that the OI 135.6 nm emission enhancements caused by O+ ions and electrons radiative recombination (where NmF2 squared increases) are obviously a contribution to the measured 135.6 nm emission enhancements by IPM. The contribution accounts for at least one of all contributions to the measured 135.6 nm emission enhancements by IPM. However, where the NmF2 squared provided by ionosonde decrease or change little (where the OI 135.6 nm emissions cause by O+ ions and electrons radiative recombination also decrease or change little), the emission enhancements measured by IPM at storm-time appear to come from the contributions of other mechanisms, such as energetic neutral atoms precipitation, or the mutual neutralization emission (O+ + O-→2O + hʋ (135.6 nm)) which also occupies a certain proportion in 135.6 nm airglow emission at night. [ABSTRACT FROM AUTHOR]

Total electron data (TEC) from GPS nowadays can be used as a tool for understanding the space weather phenomena. The development of prediction model for TEC is quiet crucial and challenging due to the dynamic behavior of the ionosphere, since it depends on different factors such as seasonal, diurnal and spatial variations, solar geomagnetic conditions etc. In this paper, an attempt is made for predicting the GPS derived TEC values for different GNSS stations over India using a hybrid method based on Ensemble empirical mode decomposition (EEMD) and Long Short-Term Memory (LSTM) deep learning method. The daily TEC time series data from the IISc Bangalore (Latitude 13.021, Longitude 77.570), Lucknow (Latitude 26.912, Longitude 80.956) and Hyderabad (Latitude 17.417, Longitude 78.551) stations over India during the period 2008 to 2015 of solar cycle 23 and 24 is used for analysis. The assessment of model performance for testing predicted output compared with LSTM and EMD-LSTM models, and their comparison results show that the hybrid EEMD-LSTM model presents better than the other models. [ABSTRACT FROM AUTHOR]

In recent years, new techniques and algorithms such as Artificial Neural Networks (ANNs), Fuzzy Inference Systems (FIS) and Genetic Algorithm (GA) have been used as alternative statistical tools in modeling and forecasting issues. These methods have been extensively used in the field of geosciences and atmospheric physics. The main purpose of this paper is to combine FIS and ANNs for local modeling of the ionosphere Total Electron Content (TEC) in Iran. An Adaptive Neuro-Fuzzy Inference System (ANFIS) is developed for TEC modeling. Also, Multi-Layer Perceptron ANN (MLP-ANN) and ANN based on Radial Base Functions (RBF) have been designed for analyzing ANFIS results. Observations of 29 Global Positioning System (GPS) stations from the Iranian Permanent GPS Network (IPGN) have been used in 3 different seasons in 2015 and 2016. These stations are located at geomagnetic low latitudes region. Out of these 29 stations, 24 stations for training and 5 stations for testing and validating were selected. The relative and absolute errors have been used to evaluate the accuracy of the proposed model. Also, the results of this paper are compared with the International Reference Ionosphere model (IRI2016). The maximum values of the average relative error for RBF, MLP-ANN, ANFIS and IRI2016 methods are 13.88%, 11.79%, 10.06%, and 18.34%, respectively. Also, the maximum values of the average absolute error for these methods are 2.38, 2.21, 1.5 and 3.36 TECU, respectively. Comparison of diurnal predicted TEC from the ANFIS, RBF, MLP-ANN and IRI2016 models with GPS-TEC revealed that the ANFIS provides more accurate predictions than the other methods in the test area. [ABSTRACT FROM AUTHOR]

On December 27, 2018, the Beidou-3 System (BDS-3) has completed the deployment of 18 Medium Earth Orbit (MEO) satellites combined as a space constellation. In addition to the augmentation information for the new system signals B1C and B2a, the BDS-3 is compatible with the three augmentation information broadcast by the BDS-2 system for B1I and B3I signals: equivalent clock error correction, User Differential Ranging Error (UDRE) and Grid Ionosphere Vertical Error (GIVE). In this paper, the observation data of Beidou monitoring network are used to analyze the pseudo-range observation quality of the smooth transition signals B1I and B3I of BDS-2 and BDS-3. At the same time, the relationship between the equivalent clock error correction and the prediction error of the satellite clock is analyzed by using the Two-Way Satellite Time and Frequency Transfer (TWSTFT) data. The results show that the correlation between the equivalent clock error correction and the monitored clock error by using the TWSTFT data is greater than 60%. We calculate the UDRE by using the equivalent clock error correction. The results show that the satellite equivalent clock error correction can improve the accuracy of User Equivalent Range Error (UERE) by about 50%. This paper also compares the positioning accuracy of the BDS-2 satellites with the BDS-2 satellites combined BDS-3 satellites. The results show that the three-dimensional positioning accuracy is improved by about 30% after the BDS-3 satellites are added. [ABSTRACT FROM AUTHOR]

Observation of the 3-dimensional (3-D) electron density of the ionosphere is useful to study large-scale physical processes in space weather events. Ionospheric data assimilation and ionospheric tomography are methods that can create an image of the 3-D electron density distribution. While multiple techniques have been developed over the past 30 years, there are relatively few studies that show the accuracy of the algorithms. This paper outlines a novel simulation approach to test the quality of an ionospheric tomographic inversion. The approach uses observations from incoherent scatter radar (ISR) scans and extrapolates them spatially to create a realistic ionospheric representation. A set of total electron content (TEC) measurements can then be simulated using real geometries from satellites and ground receivers. This data set, for which the 'truth' ionosphere is known, is used as input for a tomographic inversion algorithm to estimate the spatial distribution of electron density. The reconstructed ionospheric maps are compared with the truth ionosphere to calculate the difference between the images and the truth. To demonstrate the effectiveness of this simulation framework, an inversion algorithm called MIDAS (Multi-Instrument Data Analysis Software) is evaluated for three geographic regions with differing receiver networks. The results show the importance of the distribution and density of GPS receivers and the use of a realistic prior conditioning of the vertical electron density profile. This paper demonstrates that when these requirements are met, MIDAS can reliably estimate the ionospheric electron density. When the region under study is well covered by GPS receivers, as in mainland Europe or North America, the errors in vertical total electron content (vTEC) are smaller than 1 TECu (2–4%). In regions with fewer and more sparsely distributed receivers, the errors can be as high as 20–40%. This is caused by poor data coverage and poor spatial resolution of the reconstruction, which has an important effect on the calibration process of the algorithm. [ABSTRACT FROM AUTHOR]

A state of the ionosphere can be effectively studied using electromagnetic signals received from global navigation satellite systems (GNSS). Utilization of the dual frequency observations allows estimating values of the total electron content (TEC). They can be used for a number of scientific studies such as detection and monitoring of traveling ionospheric disturbances or plasma bubbles. Moreover, maps of TEC variations allow to classify ionospheric heterogeneities and to evaluate their parameters. However, most of the research describes ionospheric parameters only in 2D space and time. In this paper, we focus on the determination of the height of the ionospheric inhomogeneities. We used a dense network of GPS receivers to obtain the sequences of TEC variation maps for different heights of the ionospheric layer. For each satellite observed above 70°, we constructed separate sets of maps. For each ionospheric height, the cross-correlation function between maps corresponding to different satellites was calculated. The biggest cross-correlation coefficient value determines the height of the ionospheric irregularities. This paper describes the methodology and the results obtained for a geomagnetic storm on St. Patrick's Day in March 2013. We have found that in quiet geomagnetic conditions the ionospheric irregularities are localized predominantly within the interval 180–220 km close to the maximum of the ionospheric F2 layer. In disturbed conditions, the height of their localization was increased up to several hundreds of kilometers. These estimations correspond to the changes in the slab thickness of the ionosphere. [ABSTRACT FROM AUTHOR]

The Venus Express Radio Science Experiment (VeRa) was part of the scientific payload of the Venus Express (VEX) spacecraft and was targeted at the investigation of Venus' atmosphere, surface, and gravity field as well as the interplanetary medium. This paper describes the methods and the required calibrations applied to VEX-VeRa raw radio occultation data used to retrieve vertical profiles of Venus' ionosphere and neutral atmosphere. In this work we perform an independent analysis of a set of 25 VEX, single-frequency (X-band), occultations carried out in 2014, recorded in open-loop at the NASA Deep Space Network. Our temperature, pressure and electron density vertical profiles are in agreement with previous studies available in the literature. Furthermore, our analysis shows that Venus' ionosphere is more influenced by the day/night condition than the latitude variations, while the neutral atmosphere experiences the opposite. Our scientific interpretation of these results is based on two major responsible effects: Venus' high thermal inertia and the zonal winds. Their presence within Venus' neutral atmosphere determine why in these regions a latitude dependence is predominant on the day/night condition. On the contrary, at higher altitudes the two aforementioned effects are less important or null, and Venus' ionosphere shows higher electron density peaks in the probed day-time occultations, regardless of the latitude. [ABSTRACT FROM AUTHOR]

• A CME arrived on 19 December 2015 and caused changes in the ionosphere on 20 and 21. • A positive ionospheric storm was seen with longitudinal differences. • These are explained as combined effect of DD electric field and composition changes. • Morning overshoot in T e showed a response concurrent with the negative storm. This paper investigates the ionospheric storm of December 19–21, 2015, which was initiated by two successive CME eruptions that caused a G3 space weather event. We used the in situ electron density (N e) and electron temperature (T e) and the Total Electron Content (TEC) measurements from SWARM-A satellite, as well as the O/N 2 observations from TIMED/GUVI to study the ionospheric impact. The observations reveal the longitudinal and hemispherical differences in the ionospheric response to the storm event. A positive ionospheric storm was observed over the American, African and Asian regions on 20 December, and the next day showed a negative storm. Both these exhibited hemispheric differences. A positive storm was observed over the East Pacific region on 21 December. It is seen that the net effect of both the disturbance dynamo electric field and composition differences become important in explaining the observed variability in topside ionospheric densities. In addition, we also discuss the T e variations that occurred as a consequence of the space weather event. [ABSTRACT FROM AUTHOR]

• Study of longitudinal ionospheric variations over Asian regions during the intense geomagnetic storms of May and September 2017. • Positive and negative changes were observed during the main and recovery phases of the storms. • Local time variations of the electric field ensure the longitude difference of the TEC variations. This paper presents the longitudinal dependence of ionospheric responses from Global Navigation Satellite System (GNSS) derived Total Electron Content (TEC) during two intense geomagnetic storms of May and September 2017. The GNSS-TEC is retrieved from four stations installed at the verge of low to mid-latitude Asian regions of Pakistan and China. Two ionospheric enhancements were observed during the storm of May 2017. The first one at local noon–afternoon during the storm main phase on 28 May was due to the southward turning of Interplanetary Magnetic Field (IMF-Bz) and eastward Prompt Penetration Electric Field (PPEF), with the maximum TEC enhancement at Wuhan. The second one at nighttime during the recovery phase of the storm on 29 May triggered ionospheric variations, mainly due to the later southward turning of the IMF-Bz as the Asian regions, were on the nightside with the westward PPEF. Negative storm time ionospheric responses were observed on 30 May, related to the change of the thermospheric composition as O/N 2 depletion. Moreover, a significant increase in TEC was recorded during the main phase of the storm on 8 September 2017. This enhancement corresponded with the eastward PPEF and an increase in the O/N 2. The TEC increment was also observed during the recovery phase on 9 September in the Pakistani stations. A minor storm on 7 September also gave rise to TEC enhancements, especially in western regions. However, the negative phase was registered from 9 to 10 September at each station because of the changes in the thermospheric composition as O/N 2 depletion. [ABSTRACT FROM AUTHOR]

Vaporized samarium (Sm) has been released in the ionosphere for artificially creating plasma clouds, which can tailor radio propagation of information systems. The titanium-boron (Ti-B) self-propagating high-temperature synthesis (SHS) reaction can be used to vaporize Sm for releasing in the ionosphere. In this paper, a one-dimensional Fourier combustion model of Sm vaporizing by Ti-B reaction is established, based on the principle of chemical reaction and heat conduction. The Gauss-Seidel iterative algorithm is used to numerically simulate the SHS process of titanium-boron-samarium (Ti-B-Sm) system. This study first investigates the impact of different green compact porosity and content of Sm on the temperature field distribution, stable temperature and wave rate of the combustion process. The calculation shows that the porosity has little effect on the stable combustion temperature. With the increase of porosity, the stable combustion temperature remains basically unchanged, while the combustion wave rate shows a downward trend. The amount of Sm has a significant negative effect on the stable combustion temperature and the combustion wave rate. The higher the amount of Sm is, the more quickly the stable combustion temperature and the combustion wave rate decrease. The theoretical result indicates that, Sm could not exceed 35 % for being heated and vaporized. And the porosity could not exceed 52 % for efficient vaporization of Sm and stability of combustion wave. Finally, taking the Ti-B-Sm system with 30 % Sm contents as an example, several experiments were carried out using green compacts with different porosity. The experiments show that the maximum temperature of the compact during the combustion process is very close when the porosity varies from 30 % to 45 %, about 2075 K, which is in agreement with the simulation. The combustion wave rate is distributed from 5 mm/s to 8 mm/s within the range of 30 % and 50 % of porosity. Finally, the combustion products are detected by diffraction of X-rays (XRD), scanning electron microscope (SEM) and energy dispersive spectrometer (EDS). It shows that the Ti-B-Sm compact with 30 % Sm content and porosity not exceeding 52 % can effectively vaporize Sm, and the vaporization efficiency of Sm is about 75 %. The results of this study provide guidance for payloads of future experimental campaigns in the ionosphere. [ABSTRACT FROM AUTHOR]

The ionospheric effect on radio wave propagation error has a significant impact on navigation, positioning, and real-time measurements. It is the primary source of errors in high precision aviation and measurement systems. A set of eight coefficients is used to correct ionospheric errors for Indian Regional Navigation Satellite System (IRNSS) users. Currently, the Klobuchar model is an effective low computational mathematical model for ionospheric range error mitigation through a set of eight coefficients. It has low accuracy in Equatorial Ionization Anomaly (EIA) regions and can correct up to ∼60% of the ionospheric range error. This paper proposes an ionospheric error correction model that can be applied to such measurements as well as an associated error model to compute accuracy with a differential interval of observations 5 m, 30 m and 60 m. The numerical simulation results show that compared to widely used algorithms, the proposed strategy can enhance the 83.13% ionospheric correction with Klobuchar- like coefficients at a sampling rate of 5 m. The proposed solution could be effective for Regional Navigational Satellite Systems (RNSS) for ionospheric delay corrections in low-latitude regions. [ABSTRACT FROM AUTHOR]

• A self-trained classifier for ionospheric radar data is presented. • Its training is based on finding optimal hidden classes in the data. • The dataset consists from measured parameters and numerically simulated ones. • Found classes could be interpreted from physical point of view. In the paper an algorithm for automatic classification of signals received by decameter coherent scatter radars is described. The algorithm is self-trained on unlabeled dataset and is based on training optimal physics-based classification using clusterization results. The approach allows to find optimal (hidden) classification, based on physically interpretable parameters of the received data, both obtained during physics-based numerical simulation and measured experimentally. As a result we trained the classification artificial neural network and found 11 well-interpretable classes from physical point of view in the available data. Other found classes are not interpretable from physical point of view, demonstrating the importance of taking into account radiowave propagation for correct classification. The advantages of the method include the possibility of its automatic training: it does not require preliminary data analysis by an expert, and it is self-trained to separate available data into the classes, that can be interpreted from a physical point of view. [ABSTRACT FROM AUTHOR]

As a highly variable space plasma, the sophisticated monitoring and expression of the ionosphere are critically important for the performance of Global Navigation Satellite System (GNSS). To satisfy the requirement of more precise positioning and navigation, it is necessary to model and predict the ionosphere in a more accurate way. In this paper, the potential advantages of neural networks in ionosphere modeling and predicting are explored. Radial Basis Function Neural Network (RBF-NN) is used for modeling and the Long- and Short-Term Memory Neural Network (LSTM-NN) is used for predicting. Results validate that performance of the RBF-NN is superior to the traditional spherical harmonic and polynomial model. The average root mean square error of one-day modeling residuals by RBF-NN is 1.2951 Total Electron Content Unit (TECU, 1 TECU = 1016 electron/m2), which is reduced by 0.4172 and 0.2710 TECU respectively, compared with the traditional spherical harmonic and polynomial model. The predicting results show that the LSTM-NN has better short-time performance, compared with the finite Fourier series model and the autoregressive integrated moving average model. Finally, one-day predicted products are used as priori constraints for single-frequency static and dynamic precise point positioning (PPP). Positioning results show that constraint effect of the predicted products is equivalent to that of the International GNSS Services (IGS) final products. Compared with the results without ionospheric constraint, the PPP convergence time is obviously reduced, and the positioning performance in the horizontal direction is significantly improved. [ABSTRACT FROM AUTHOR]

A novel parallel optimization 3D numerical ray-tracing method is proposed in this paper. The method takes the geomagnetic field and the horizontal in-homogeneity of the ionosphere into account. It works in both O-mode and X-mode. High-frequency radiowaves and oblique ionograms are simulated by the method under three different plasma density models with travelling ionospheric disturbances and small-scale irregularities and without them. Both the parallel optimization algorithm (MultiStart) and the parallel traversal algorithm are used during the simulation, which allows multiple rays to be traced simultaneously to shorten the simulation time. The simulation results show the proposed 3D numerical ray-tracing method can sensitively and accurately capture the changes that geomagnetic field, travelling ionospheric disturbances, and small-scale irregularities bring to the high-frequency radiowaves and the oblique ionograms. It is a useful tool for restoring different oblique ionogram characteristics under various parameters on the plasma density models. [ABSTRACT FROM AUTHOR]

A systematic study of ionospheric scintillation at the low-latitudes, especially around the Equatorial Ionization Anomaly (EIA) and the magnetic equator, is essential in understanding the dynamics of ionospheric variation and related physical processes. Our study involves NavIC S 4 C observations over Indore and Hyderabad. Additionally, GPS S 4 C observations over Indore were analyzed, under disturbed as well as quiet time ionospheric conditions from September 2017 through 2019, falling in the declining phase of the solar cycle 24. The S 4 C observations were further analyzed using proxy parameters: ROT and ROTI. These results have been obtained from three satellites of the NavIC constellation (PRNs 2, 5, and 6). The onset times of scintillations were observed to be around 19:30 LT (h) and 20:30 LT (h) for Hyderabad and Indore respectively, while the S 4 C peak values occurred between 22:00 LT (h) and 23:00 LT (h). The reliability of NavIC was evaluated using scattering coefficients that revealed a good correlation across the pair of signals during quiet time ionospheric conditions. The observations clearly show that the amplitude scintillation of the NavIC signal follows the Nakagami-m distribution along with the α - μ distribution as a depiction of the deep power fades caused by scintillation on these signals. This paper shows the impact of such systematic studies near these locations for the first time, in improving the understanding of the dynamic nature of low-latitude ionosphere under low solar activity conditions. [ABSTRACT FROM AUTHOR]

• The M w = 7.3 earthquake near the Iran-Iraq border in west Iran occurred in 12.11.2017. • Median, Kalman filter and NN were implemented to investigate TEC measurements. • Swarm data analysis identifies anomalies 8–11 days prior to the earthquake. • Climatological data analysis identifies anomalies that precede ionospheric anomalies. • The sequence of different anomalies confirms a bottom-up LAIC process. The M w = 7.3 earthquake near the Iran-Iraq border in west Iran (34.911°N, 45.959°E) occurred at 18:18:17 UTC (LT = UTC + 03:30), November 12, 2017 as the result of oblique-thrust faulting at mid-crustal depth (∼19 km). Median, Kalman filter and Neural Network, as three standard, classical and intelligent methods, have been implemented to investigate three months of GPS Total Electron Content (TEC) measurements and to detect the striking anomalous variations around the time and location of the mentioned earthquake. The first method detects unusual variations, 9 days before the event, between 21:00 and 22:00 UTC. The other two methods of Kalman filter and Neural Network detect another clear anomaly on 11 days preceding the earthquake at 16:00 UTC. These findings are two of the outstanding results of GPS-TEC precursor analysis. This paper also presents the results of Swarm satellites (Alpha, Bravo and Charlie) data analysis inside the Dobrovolsky area around the Iran earthquake epicenter during the period from 1 August to 30 November 2017. The time series and orbital analysis of six measured parameters including electron density, electron temperature, magnetic scalar and vectors (X, Y, Z) components indicate irregular variations between 8 and 11 days prior to the occurrence of the earthquake. Since the variations of the solar and geomagnetic indices follow a normal behaviour during the whole period of the observed ionospheric anomalies between 8 and 11 days before the earthquake, it can be concluded that multi-precursors analysis has an important role to acknowledge the seismo-LAI (Lithospheric-Atmospheric-Ionospheric) anomalies associated to strong earthquakes such as this case. Furthermore, some physical and chemical atmospheric parameters from a climatological database are investigated and some interesting anomalies above two standard deviations prior to the earthquake are found. This paper shows not only anomalies in atmosphere and ionosphere but also a contemporary analysis of different data sources to detect the possible Lithosphere Atmosphere Ionosphere Coupling (LAIC) effects. [ABSTRACT FROM AUTHOR]

Abstract In the last 20 years, and in particular in the last decade, the availability of propagation data for GNSS has increased substantially. In this sense, the ionosphere has been sounded with a large number of receivers that provide an enormous amount of ionospheric data. Moreover, the maturity of the models has also been increased in the same period of time. As an example, IGS has ionospheric maps from GNSS data back to 1998, which would allow for the correlation of these data with other quantities relevant for the user and space weather (such as Solar Flux and Kp). These large datasets would account for almost half a billion points to be analyzed. With the advent and explosion of Big Data algorithms to analyze large databases and find correlations with different kinds of data, and the availability of open source code libraries (for example, the TensorFlow libraries from Google that are used in this paper), the possibility of merging these two worlds has been widely opened. In this paper, a proof of concept for a single frequency correction algorithm based in GNSS GIM vTEC and Fully Connected Neural Networks is provided. Different Neural Network architectures have been tested, including shallow (one hidden layer) and deep (up to five hidden layers) Neural Network models. The error in training data of such models ranges from 50% to 1% depending on the architecture used. Moreover, it is shown that by adjusting a Neural Network with data from 2005 to 2009 but tested with data from 2016 to 2017, Neural Network models could be suitable for the forecast of vTEC for single frequency users. The results indicate that this kind of model can be used in combination with the Galileo Signal-in-Space (SiS) NeQuick G parameters. This combination provides a broadcast model with equivalent performances to NeQuick G and better than GPS ICA for the years 2016 and 2017, showing a 3D position Root Mean Squared (RMS) error of approximately 2 m. [ABSTRACT FROM AUTHOR]

The paper presents data from some campaigns at Sura heating facility in 2011–1016. The experiments on probing of the artificial disturbed region of the lower ionosphere were carried out at two observation sites. One of them was located near Vasil’sursk 1 km from Sura facility (56.1°N; 46.1°E) and the other site was located at the Observatory (55.85°N; 48.8°E) of Kazan State University, 170 km to the East. Investigation of the features of the disturbed region of the lower ionosphere based on its diagnostics by the methods of the vertical sounding and oblique backscattering is the main goal of this paper. Ionosphere disturbance was fulfilled by the effect of the powerful radio wave of the ordinary or extraordinary polarization emitted by transmitters of the Sura facility with effective radiated power ERP = 50–120 MW at the frequency of 4.3, 4.7 and 5.6 MHz. Pumping waves were emitted with period from 30 s to 15 min. The disturbed region of the ionosphere in Vasil’sursk was probed by the vertical sounding technique using the partial reflexion radar at the frequency of 2.95 and 4.7 MHz. For the oblique sounding of the disturbed region the modified ionosonde Cyclon-M, operating at ten frequencies from 2.01 to 6.51 MHz was used at the Observatory site. On many heating sessions simultaneous variations of the probing partial reflection signals in Vasil’sursk and backscattered signals in Observatory were observed at the height at 40–100 km below the reflection height of the pumping wave. These observations were correlated with the pumping periods of the Sura facility. Possible mechanisms of the appearance of the disturbance in the lower ionosphere and its effect on the probing radio waves are discussed. [ABSTRACT FROM AUTHOR]

The earthquake (EQ) time coupling processes between equator-low-mid latitude ionosphere are complex due to inherent dynamical status of each latitudinal zone and qualified geomagnetic roles working in the system. In an attempt to identify such process, the paper presents temporal and latitudinal variations of ionization density (foF 2 ) covering 45°N to 35°S, during a number of earthquake events (M > 5.5). The approaches adopted for extraction of features by the earthquake induced preparatory processes are discussed in the paper through identification of parameters like the ‘EQ time modification in density gradient’ defined by δ = (foF 2 max  − foF 2 min )∕τ mm , where τ mm – time span (in days) between EQ modified density maximum and minimum, and the Earthquake time Equatorial Anomaly, i.e. EEA, one of the most significant phenomenon which develops even during night time irrespective of epicenter position. Based on the observations, the paper presents the seismic time coupling dynamics through anomaly like manifestations between equator, low and mid latitude ionosphere bringing in the global Total Electron Content (TEC) features as supporting indices. [ABSTRACT FROM AUTHOR]

In this paper, we examine the climatology structure of the mid-night ionosphere at approximately two o'clock local time of a low-solar-activity year and discrepancies between Ionosphere PhotoMeter (IPM) observations and IRI (International Reference Ionosphere) model-2016 predictions using (1) a global structure for the F 2 layer peak electron density (N m F 2) for four seasons, (2) the mean N m F 2 values at different latitudes by month, and (3) the monthly distribution of the global average of N m F 2. The data is collected by the IPM, a far-ultraviolet nadir- viewing photometer that has been aboard the second-generation, polar-orbiting Chinese meteorological satellite Feng-Yun 3D (FY-3D) since its launch on November 25th, 2017 and has provided excellent opportunities for many scientific investigations of the ionosphere. We collected night glow data under low geomagnetic activity (KP ≤ 4) during 2018, and the data obtained five days before and after a full-moon night were removed to prevent the influence of stray light. Before analysing the climatology of the ionosphere and comparing the results with those obtained from IRI2016, the accuracy of N m F 2 measured by IPM was evaluated by comparison with data from ground-based ionosondes. A statistical comparative analysis of N m F 2 measured by IPM and ionosonde indicated a difference of 20% at middle latitudes and 28% at low latitudes. The global behaviour of N m F 2 measured by IPM and IRI for four seasons shows that the IRI model generally captures the morphology of the latitudinal structure and hemispheric asymmetry in N m F 2 observed by IPM. A comparison between IPM-measured N m F 2 and IRI-predicted N m F 2 indicates that the former is systematically lower than the latter. The difference in the measurements and predictions can be as large as 300%. [ABSTRACT FROM AUTHOR]

There are special ionospheric phenomena in the equatorial and South African region, e.g., equatorial plasma bubbles and broadcast ionospheric model correction anomalies which result in unique ionospheric characteristics. In this paper, we analyze the ionospheric characteristics of the experimental region using the latest GNSS dual-frequency real-world data from 2014 to 2020. This is then used as a benchmark to analyze the performance of IRI-2016, IRI Plas-2017, and NeQuick 2 empirical models and their electron content distribution at different altitudes. Finally, the correlation between the electron content of the African region and the solar activity parameters is explored. The results show that:①The annual variation of electron content in the far equatorial region does not have obvious spring-autumn bimodal structure and the electron content in the near-equatorial region is much higher than that in the far equatorial region.②Empirical models generally overestimate the electron content of the region with the IRI-2016 model consistently achieves the highest performance, the NeQuick 2 model achieves the lowest accuracy in high solar activity years, and the IRI Plas-2017 model is the worst in mid and low solar activity years.③The IRI Plas-2017 model has a relatively stable share of each layer, whereas the NeQuick 2 model has a large share of each layer influenced by solar activity. The top electron content has the largest share of the total electron content, and the plasma layer has the smallest share.④In low solar activity years, the experimental region shows solar activity and electron content correlation anomalies which are negatively correlated. Overall the EUV index has the largest correlation coefficient with the ionosphere, and the SSN has the worst correlation in this region. [ABSTRACT FROM AUTHOR]

This paper studies the response of the ionospheric parameters critical frequency (foF2), their height (hmF2), and Total Electron Content (TEC) at mid, low, and near-equatorial latitudes of the South American sector during the intense geomagnetic storm of 26 August 2018. The ionospheric response at the beginning of the main phase was different depending on latitude (in general, there were decreases in foF2 at near-equatorial and low latitudes and small increases at mid-latitudes). During the recovery, positive storm effects in foF2 and TEC were observed almost all day on 26 August 2018 overall the stations along all the latitudes and also on 27 August. The initial effects were possibly caused by a weak prompt penetration electric field while the enhanced ratio of thermosphere neutral composition i.e. [O]/[N2] was considered as the main cause for the positive storm effects during the recovery phase. [ABSTRACT FROM AUTHOR]

Single-frequency precise point positioning (PPP) is widely used with the advantage of cost-efficient, while its further development and application are limited by the difficulty of ionospheric delay correction and the long-time convergence, especially for real-time positioning. And the development of high-accuracy ionospheric models plays an important role for the correction of ionospheric delay in single-frequency PPP. In this paper, the final and rapid global ionospheric map (GIM) products released by Chinese Academy of Science (CAS), Center for Orbit Determination in Europe (CODE), European Space Agency (ESA), Jet Propulsion Laboratory (JPL), Universitat Politècnica de Catalunya (UPC), Wuhan University (WHU) and International GNSS Service (IGS) were used as external constraints in static, simulation kinematic and kinematic single-frequency PPP respectively. The performance and practicality of each product were analyzed by using IGS station observation data (September 2017 and January 2018, with different ionospheric activity levels) and a kinematic experiment. The results indicate that GIM products may improve convergence time in most areas of middle and high latitudes of the globe. However, the improvement of convergence time of some regions in low latitudes or near the equator with dense and uniform distributed IGS stations show even better performance than the regions in middle and high latitudes. Comparing with standard PPP (S-PPP), the convergence time of static PPP is reduced about 14–42% and 13–29% with GIM final and rapid products respectively. In simulation kinematic PPP, the convergence time improves 10–43% and 12–25% for final and rapid products respectively. In the kinematic positioning, the addition of external ionospheric constraints may speed up the convergence in the early stage of positioning and improve the accuracy to a certain extent. Among all GIM products, the final products show better performance than that of the rapid products obviously. The GIM products from CAS and CODE and UQRG from UPC express the best performance are recommended to process ionospheric delay in the high-accuracy positioning. [ABSTRACT FROM AUTHOR]

NTCM is a relatively simple climatological ionosphere model. However, its weather ionosphere characteristic specification capability is limited. Also, its nowcasting and forecasting performance of the East-African equatorial ionosphere has not yet been tested. Therefore, this paper demonstrates techniques of changing NTCM to an ionospheric weather model that nowcasts and forecasts VTEC for East Africa. It has been done by adapting the model to quiet day VTEC from nineteen GNSS receivers in East Africa in 2013 and 2014. Then, performances of the model in nowcasting and forecasting VTEC, before and after the adaption, have been investigated compared to observed VTEC. We have found that NTCM, after adaptation, represents observed features of diurnal variations of VTEC and equatorial ionization anomaly (EIA) much better than before adaptation. After adaptation, the mean and standard deviation of daily mis-modelings are comparable with the mean and standard deviation of yearly mis-modelings. The study showed that NTCM, after adaptation to a reference station, performs better than before ingestion at the stations nearby the reference station; however, its performance decreases at the locations far away from the reference station. In addition, after ingestion, one hour ahead prediction of NTCM is found to be the best compared to longer time predictions. [ABSTRACT FROM AUTHOR]

The assumption of spherical uniformity while the retrieval of electron density profiles from the Global Navigation Satellite Systems-Radio Occultation (GNSS-RO) observations is often violated and introduces significant errors in the retrieved electron density profile data. This paper presents an improved Abel-inversion technique by incorporating the horizontal gradients in the ionosphere, which are routinely derived from the Artificial Neural Network (ANN) based background NmF2 (peak electron density of F2-layer) model (ANNC2) assimilated with near real-time Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (FORMOSAT-7/COSMIC-2) NmF2 data. The ANNC2-aided Abel inversion is then implemented for more accurate retrieval of electron density profiles from COSMIC-2 in real-time. It is found that the ANNC2-aided inversion has improved the electron density values around the F2-region and below, which yields a clear separation between two anomaly crests. Further, the ANNC2-aided Abel inversion had significantly reduced the artificial plasma caves beneath the equatorial ionization anomaly crests. Furthermore, COSMIC-2 NmF2 observations obtained from both classical and the ANNC2-aided Abel inversion are compared with the ground-based Digisonde data and found that the ANNC2-aided inversion gives the better results. This study provides some new insights on the aided Abel inversion technique assisted by ANN models for the real-time correction of Abel retrieved electron density profiles. [ABSTRACT FROM AUTHOR]