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A summary of the main concepts on global ionospheric map(s) [hereinafter GIM(s)] of vertical total electron content (VTEC), with special emphasis on their assessment, is presented in this paper. It is based on the experience accumulated during almost two decades of collaborative work in the context of the international global navigation satellite systems (GNSS) service (IGS) ionosphere working group. A representative comparison of the two main assessments of ionospheric electron content models (VTEC-altimeter and difference of Slant TEC, based on independent global positioning system data GPS, dSTEC-GPS) is performed. It is based on 26 GPS receivers worldwide distributed and mostly placed on islands, from the last quarter of 2010 to the end of 2016. The consistency between dSTEC-GPS and VTEC-altimeter assessments for one of the most accurate IGS GIMs (the tomographic-kriging GIM ‘UQRG’ computed by UPC) is shown. Typical error RMS values of 2 TECU for VTEC-altimeter and 0.5 TECU for dSTEC-GPS assessments are found. And, as expected by following a simple random model, there is a significant correlation between both RMS and specially relative errors, mainly evident when large enough number of observations per pass is considered. The authors expect that this manuscript will be useful for new analysis contributor centres and in general for the scientific and technical community interested in simple and truly external ways of validating electron content models of the ionosphere.

The ionosphere effective height (IEH) is a very important parameter in total electron content (TEC) measurements under the widely used single-layer model assumption. To overcome the requirement of a large amount of simultaneous vertical and slant ionospheric observations or dense “coinciding” pierce points data, a new approach comparing the converted vertical TEC (VTEC) value using mapping function based on a given IEH with the “ground truth” VTEC value provided by the combined International GNSS Service Global Ionospheric Maps is proposed for the determination of the optimal IEH. The optimal IEH in the Chinese region is determined using three different methods based on GNSS data. Based on the ionosonde data from three different locations in China, the altitude variation of the peak electron density (hmF2) is found to have clear diurnal, seasonal and latitudinal dependences, and the diurnal variation of hmF2 varies from approximately 210 to 520 km in Hainan. The determination of the optimal IEH employing the inverse method suggested by Birch et al. (Radio Sci 37, 2002. doi:10.1029/2000rs002601) did not yield a consistent altitude in the Chinese region. Tests of the method minimizing the mapping function errors suggested by Nava et al. (Adv Space Res 39:1292–1297, 2007) indicate that the optimal IEH ranges from 400 to 600 km, and the height of 450 km is the most frequent IEH at both high and low solar activities. It is also confirmed that the IEH of 450–550 km is preferred for the Chinese region instead of the commonly adopted 350–450 km using the determination method of the optimal IEH proposed in this paper.

Accurate 1‐day global total electron content (TEC) forecasting is essential for ionospheric monitoring and satellite communications. However, it faces challenges due to limited data and difficulty in modeling long‐term dependencies. This study develops a highly accurate model for 1‐day global TEC forecasting. We utilized generative TEC data augmentation based on the International Global Navigation Satellite Service (IGS) data set from 1998 to 2017 to enhance the model's prediction ability. Our model takes the TEC sequence of the previous 2 days as input and predicts the global TEC value for each hourly step of the next day. We compared the performance of our model with 1‐day predicted ionospheric products provided by both the Center for Orbit Determination in Europe (C1PG) and Beihang University (B1PG). We proposed a two‐step framework: (a) a time series generative model to produce realistic synthetic TEC data for training, and (b) an auto‐correlation‐based transformer model designed to capture long‐range dependencies in the TEC sequence. Experiments demonstrate that our model significantly improves 1‐day forecast accuracy over prior approaches. On the 2018 benchmark data set, the global root mean squared error (RMSE) of our model is reduced to 1.17 TEC units (TECU), while the RMSE of the C1PG model is 2.07 TECU. Reliability is higher in middle and high latitudes but lower in low latitudes (RMSE < 2.5 TECU), indicating room for improvement. This study highlights the potential of using data augmentation and auto‐correlation‐based transformer models trained on synthetic data to achieve high‐quality 1‐day global TEC forecasting.

The Denoising Wavelet Transform Convolutional Long Short-Term Memory Network (DWTConvLSTM) is a novel ionospheric total electron content (TEC) spatiotemporal prediction model proposed in 2025 that can simultaneously consider high-frequency and low-frequency features while suppressing noise. However, it also has flaws as it only considers unidirectional temporal features in spatiotemporal prediction. To address this issue, this paper adopts a bidirectional structure and designs a bidirectional DWTConvLSTM model that can simultaneously extract bidirectional spatiotemporal features from TEC maps. Furthermore, we integrate a lightweight attention mechanism called Convolutional Additive Self-Attention (CASA) to enhance important features and attenuate unimportant ones. The final model was named CASA-BiDWTConvLSTM. We validated the effectiveness of each improvement through ablation experiments. Then, a comprehensive comparison was performed on the 11-year Global Ionospheric Maps (GIMs) dataset, involving the proposed CASA-BiDWTConvLSTM model and several other state-of-the-art models such as C1PG, ConvGRU, ConvLSTM, and PredRNN. In this experiment, the dataset was partitioned into 7 years for training, 2 years for validation, and the final 2 years for testing. The experimental results indicate that the RMSE of CASA-BiDWTConvLSTM is lower than those of C1PG, ConvGRU, ConvLSTM, and PredRNN. Specifically, the decreases in RMSE during high solar activity years are 24.84%, 16.57%, 13.50%, and 10.29%, respectively, while the decreases during low solar activity years are 26.11%, 16.83%, 11.68%, and 7.04%, respectively. In addition, this article also verified the effectiveness of CASA-BiDWTConvLSTM from spatial and temporal perspectives, as well as on four geomagnetic storms.

The International Global Navigation Satellite Systems Service (IGS) ionospheric total electron content (TEC) data are used to study the periodic perturbation in the ionosphere during the 2019 Antarctic sudden stratospheric warming (SSW) event, a rare Southern Hemisphere minor SSW event in the last 40 years. A 14.5 day periodic signal with a zonal wavenumber of 0 is observed in the mesosphere and the lower thermosphere (MLT) region and the ionosphere during this SSW period, which could be related to the lunar tide. The 14.5 day periodic disturbance in the IGS TEC exhibits local time dependence and latitudinal variation, with the maximum amplitude appearing between 1000 and 1600 LT in the equatorial ionization anomaly (EIA) crest regions. Additionally, the 14.5 day periodic oscillation shows an obvious longitudinal variability, with the weakest amplitude appearing in the longitudinal region of 30° W–60° E.

The effect of geomagnetic storms on low latitude ionosphere has been investigated with the help of Global Positioning System Total Electron Content (GPS-TEC) data. The investigation has been done with the aid of TEC data from the Indian equatorial region, Port Blair (PBR) and equatorial ionization anomaly region, Agartala (AGR). During the geomagnetic storms on 24th April and 15th July 2012, significant enhancement up to 150% and depression up to 72% in VTEC is observed in comparison to the normal day variation. The variations in VTEC observed from equatorial to EIA latitudes during the storm period have been explained with the help of electro-dynamic effects (prompt penetration electric field (PPEF) and disturbance dynamo electric field (DDEF)) as well as mechanical effects (storm-induced equatorward neutral wind effect and thermospheric composition changes). The current study points to the fact that the electro-dynamic effect of geomagnetic storms around EIA region is more effective than at the lower latitude region. Drastic difference has been observed over equatorial region (positive storm impact) and EIA region (negative storm impact) around same longitude sector, during storm period on 24th April. This drastic change as observed in GPS-TEC on 24th April has been further confirmed by using the O/N 2 ratio data from GUVI (Global Ultraviolet Imager) as well as VTEC map constructed from IGS data. The results presented in the paper are important for the application of satellite-based communication and navigational system.

Powerful lightning strikes generate broadband electromagnetic signals. At Extremely Low Frequencies (ELF), the signal partly leaks into the ionosphere and produces whistlers that can be detected by satellites. Indeed, the satellites of the European Space Agency (ESA) Swarm Earth Explorer mission can detect those signals during 250 Hz burst‐mode acquisition campaigns of their Absolute Scalar Magnetometers (ASM). The dispersion of these whistlers depends on their propagation path and the distribution of ionization in the ionosphere crossed along that path. In this paper, we introduce a technique to derive a new measure of ionosphere electron content, the Total square‐Root Electron Content (TREC), using the arrival times of two frequencies of the whistler signal. We validate this approach by using data from ionosondes and from in situ measurements of the electron density at Swarm location. This technique brings new opportunities for sounding the ionosphere in regions poorly observed by other techniques. Plain Language Summary A lightning strike generates an electromagnetic impulse that propagates within Earth's atmosphere and eventually leaks out into the ionosphere. As it propagates through the ionosphere toward low‐Earth orbiting (LEO) satellites, it gets converted into a so‐called whistler, with high frequencies arriving earlier than low frequencies. This frequency dispersion depends on the state of the ionosphere. Here, we analyse such whistler waves detected by magnetometers onboard the European Space Agency Swarm satellites to recover information about the state of the ionosphere below the satellites. We first introduce a new metric, the Total Root Electron Content (TREC), which quantifies the cumulative value of the square root of electron density along the path of the whistler. We next propose a method to recover the TREC from the analysis of the whistler dispersion. We finally validate this method by using independently derived ionospheric electron density profiles to infer expected TREC values. Our results show that whistlers detected by LEO satellites can be used to locally improve the widely used empirical International Reference Ionosphere model. Such whistler inferred TREC values could be used to sound the ionosphere above places difficult to sample with conventional measuring techniques, and help better model and understand the highly dynamic ionosphere. Key Points Total square‐Root Electron Content (TREC) is a new measure of the ionospheric electron content for electromagnetic signals in the ELF band A method to retrieve TREC from fractional‐hop whistlers in the ELF detected by the ESA Swarm mission is proposed The method is validated using TREC computed with independently constrained electron density profiles close to the Swarm whistler locations

In the context of the International GNSS Service (IGS), several IGS Ionosphere Associated Analysis Centers have developed different techniques to provide global ionospheric maps (GIMs) of vertical total electron content (VTEC) since 1998. In this paper we present a comparison of the performances of all the GIMs created in the frame of IGS. Indeed we compare the classical ones (for the ionospheric analysis centers CODE, ESA/ESOC, JPL and UPC) with the new ones (NRCAN, CAS, WHU). To assess the quality of them in fair and completely independent ways, two assessment methods are used: a direct comparison to altimeter data (VTEC-altimeter) and to the difference of slant total electron content (STEC) observed in independent ground reference stations (dSTEC-GPS). The main conclusion of this study, performed during one solar cycle, is the consistency of the results between so many different GIM techniques and implementations.

One of the most intense geomagnetic storms of recent times occurred on 10–11 May 2024. With a peak negative excursion of Sym‐H below −500 nT, this storm is the second largest of the space era. Solar wind energy transferred through radiation and mass coupling affected the entire Geospace. Our study revealed that the dayside magnetopause was compressed below the geostationary orbit (6.6 RE) for continuously ∼6 hr due to strong Solar Wind Dynamic Pressure (SWDP). Tremendous compression pushed the bow‐shock also to below the geostationary orbit for a few minutes. Magnetohydrodynamic models suggest that the magnetopause location could be as low as 3.3RE. We show that a unique combination of high SWDP (≥15 nPa) with an intense eastward interplanetary electric field (IEFY ≥ 2.5 mV/m) within a super‐dense Interplanetary Coronal Mass Ejection lasted for 409 min–is the key factor that led to the strong ring current at much closer to the Earth causing such an intense storm. Severe electrodynamic disturbances led to a strong positive ionospheric storm with more than 100% increase in dayside ionospheric Total Electron Content (TEC), affecting GPS positioning/navigation. Further, an HF radio blackout was found to occur in the 2–12 MHz frequency band due to strong D‐ and E‐region ionization resulting from a solar flare prior to this storm.

It is known that solar flares generate instantaneous ionization enhancement, referred to as sudden ionospheric disturbance (SID), that occurs simultaneously across the entire dayside. In this work, we use high‐rate 1‐s data of total electron content (TEC) to analyse ionospheric response to 13 solar flares that occurred in 2003–2023. For the first time, we demonstrate that the SID first appears at the subsolar point, and, within the next 20–25 s, expands toward dawn and dusk regions with an apparent horizontal expansion rate of 250–500 km/s, depending on the spectrum of the flare. The expansion is due to the solar zenith angle impacting the magnitude of the ionospheric response and, consequently, causing the time delay between the TEC increase detected at the subsolar point and in dawn/dusk regions. We performed high‐rate 10‐s Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) simulations that reproduced SID morphology and confirmed the flare enhancement expansion.