This work extends the research on the global distribution of anomalies in the vertical total electron content (VTEC), studied in the authors' previous work. These anomalies, aside of general link with the geomagnetic field variations, revealed interim regional extrema concentrated over tectonic plate boundaries and resembled their shapes. However, three questions remained: the relation of VTEC anomalies with the earthquakes, their source and a potential link with the solar wind suspected due to their large sizes, and finally, a potential impact of solar wind on the seismicity. Previously analyzed small samples of global ionospheric maps (GIMs) are now extended to 8 years and compared with global seismic records and solar wind data by averaging in several-day windows. Additionally, local VTEC data from three selected stations are applied in the validation of GIM-based analysis. The use of data from half of the solar cycle revealed notable correlations between the analyzed quantities over time. The correlations are lost and return back at different times of different years, which proves the importance of unexplored factors contributing to the couplings. However, numerous coincidences between the averaged quantities provide substantial answers to the questions about the source of ionospheric anomalies, their link with the earthquakes, and the contribution of solar wind. (c) 2025 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Atmospheric responses to earthquakes or volcanic eruptions have become an interesting topic and can potentially contribute to future forecasting of these events. Extensive anomalies of the total electron content (TEC) are most often linked with geomagnetic storms or Earth-dependent phenomena, like earthquakes, volcanic eruptions, or nuclear explosions. This study extends rarely discussed, but very frequent, interactions between tectonic plate boundaries and the ionosphere. Our investigations focus on the very frequent occurrence of TEC enhancements not exclusively linked with individual seismic phenomena but located over tectonic plate boundaries. The objective of this study is to provide a review of the global spatiotemporal distribution of TEC anomalies, facilitating the discussion of their potential relations with tectonic activity. We apply a Kriging-based UPC-IonSAT quarter-of-an-hour time resolution rapid global ionospheric map (UQRG) from the Polytechnic University of Catalonia (UPC) IonSAT group for the detection of relative vertical TEC (VTEC) changes. Our study describes global relative and normalized VTEC variations, which have spatial and temporal behaviours strongly indicating their relationship both with geomagnetic changes and the tectonic plate system. The variations in geomagnetic fields, including the storms, disturb the ionosphere and amplify TEC variations persisting for several hours over tectonic plate boundaries, mostly over the diverging ones. The seismic origin of the selected parts of these TEC enhancements and depletions and their link with tectonic plate edges are suspected from their duration, shape, and location. The changes in TEC originating from both sources can be observed separately or together, and therefore, there is an open question about the directions of the energy transfers. However, the importance of geomagnetic field lines seems to be probable, due to the frequent common occurrence of both types of TEC anomalies. This research also proves that permanent observation of global lithosphere–atmosphere–ionosphere coupling (LAIC) is also important in time periods without strong earthquake or volcanic events. The occurrence of TEC variations over diverging tectonic plate boundaries, sometimes combined with travelling anomalies of geomagnetic origin, can add to the studies on earthquake precursors and forecasting.

Swarm electron density (Ne) observations from the Langmuir probe (LP) can detect ionospheric disturbances at the altitude of a satellite. Along-track satellite observations provide a large number of very short observations of different places in the ionosphere, where Ne is disturbed. Moreover, different perturbations occupy various Ne signal frequencies. Therefore, such short signals are more recognizable in two dimensions, where aside from their change in time, we can observe their diversity in the frequency domain. Spectral analysis is an essential tool applied here, as it enables signal decomposition and the recognition of composite patterns of Ne disturbances that occupy different frequencies. This study shows a high-resolution application of short-term Fourier transform (STFT) to Swarm Ne observations in the Papua New Guinea region in the vicinity of earthquakes, tsunamis, and related general seismic activity. The system of tectonic plate junctions, including the Pacific–Australian boundary, is located orthogonally to Swarm track footprints. The selected wavelengths of seismically induced ionospheric disturbances detected via Swarm are compared with the three sets of three-month records of seismic activity: in the winter solstice of 2016/2017, when seismic activity was highest, and in the summer solstice and vernal equinox of 2016, which were calmer. Moreover, more Swarm data records are analyzed at the same latitudes for validation purposes, in a place where there are no tectonic plate boundaries that are orthogonal to the Swarm orbital footprint. Additional validation is supplied through Swarm Ne observations from completely different latitudes, where the Swarm orbital footprint orthogonally crosses a different subducting plate boundary. Aside from the seismic energy, the solar radio flux (F10.7), equatorial plasma bubbles (EPBs), and geomagnetic ap and Dst indices are also reviewed here. Their influence on the ionospheric Ne is also found in Swarm observations. Finally, the Pearson correlation coefficient (PCC), applied to the pairs of 3-month time series created from Swarm Ne variations, seismic energy, ap, Dst, and F10.7, summarizes the graphical inspection of mutual correlations. It points to the predominant correlation of Swarm Ne disturbances with seismicity, especially during nighttime. We show that most of the Ne disturbances at a selected wavelength of 300 km correlate more with seismicity than with geomagnetic and solar indices. Therefore, Swarm LP can be assessed as being capable of observing the lithosphere–atmosphere–ionosphere coupling (LAIC) from the orbit.

In the last decades, advances in satellite technologies, data analysis techniques, and models, and a growing number of analysis centers allow modeling the ionospheric electron content with unprecedented accuracy. International GNSS Service (IGS) Ionosphere Associated Analysis Centers (IAAC) continuously provide global ionospheric maps (GIMs) based on processing GNSS data from the ground IGS network. It is a great advantage that these GIMs are often based on very different modeling techniques and thus, are also characterized by different accuracy levels. Due to the dynamic nature of the ionosphere, there is a permanent need to improve the modeling techniques of ionospheric key parameters such as the vertical total electron content (vTEC). In this presentation, we evaluate a new ionosphere model from DGFI-TUM denoted OTHG, which is a candidate for a new IGS IAAC product. The OTHG model is based on tensor products of trigonometric B-spline functions in longitude and polynomial B-spline functions in latitude for a global representation (Goss et al. 2019). Here, we complement our earlier investigations of the seven analysis center models (Wielgosz et al. 2021) with new results for the OTHG GIMs. For these investigations, we use our own validation methodology presented in Krypiak-Gregorczyk et al. (2017), which is based on GIM-derived slant TEC (sTEC) comparison with carrier phase geometry-free combination of GNSS signals. In the presented study, we use one year of GNSS data collected by 25 globally distributed stations. The overall yearly RMS value is calculated for each product based on all 365 days of continuous observations from all stations. The results show that the overall RMS of the tested GIMs ranges from 0.93 TECU to 1.29 TECU. The OTHG GIMs performed as one of the best. In addition, GIM vTEC comparisons to Jason-2 and Jason - 3 altimetry data are studied. In these analyses, the OTHG GIMs also showed a good performance. Therefore, it can be concluded that DGFI-TUM is a valuable ionospheric product for the research community. Goss A., Schmidt M., Erdogan E., Görres B., Seitz F. (2019) High-resolution vertical total electron content maps based on multi-scale B-spline representations. Annales Geophysicae, 37(4), 10.5194/angeo-37-699-2019 Krypiak-Gregorczyk A., Wielgosz P., Borkowski A. (2017) Ionosphere Model for European Region Based on Multi-GNSS Data and TPS Interpolation, Remote Sensing, 9(12), 1221, DOI:10.3390/rs9121221 Wielgosz P., Milanowska B., Krypiak-Gregorczyk A., Jarmołowski W. (2021) Validation of GNSS‑derived global ionosphere maps for different solar activity levels: case studies for years 2014 and 2018. GPS Solutions 25, 103. https://doi.org/10.1007/s10291-021-01142-x

The adverse effects of ionospheric delays limit the positioning accuracy of single-frequency GNSS users. To mitigate these effects, GNSS system providers make several ionospheric delays models available for their global users. For example, the GPS has offered the Klobuchar model from the beginning. More recently, Galileo users can use the NeQuick G model. In the meantime, several independent models available for real-time navigation have emerged. Recent examples are the NTCM (Neustrelitz Total Electron Content Model) correction model provided by the German Aerospace Center (DLR) and real-time global ionosphere maps (RT-GIMs) provided by the National Centre for Space Studies (CNES). In this contribution, we evaluate the performance of several global ionospheric delay correction models in SPP mode. We used single-frequency pseudorange data from 12 GNSS stations distributed globally, covering different latitudes for the evaluation. The test data includes GNSS observations from DOY 93/2020 to DOY 80/2021, covering almost one full year of increasing solar activity. We validated the performance of the NTCM-G model driven by the Galileo Az parameters against the Klobuchar, NeQuick 2, NeQuick G, and CNES RT GIMs models. Finally, we compared the results to reference solutions obtained with CODE GIM and also using the ionosphere-free linear combination. We showed that NTCM-G corrections presented accuracy comparable with the NeQuick G model and better than the Klobuchar one.

This paper addresses the long-term climatology (over two solar cycles) of total electron content (TEC) irregularities from a polar cap station (Thule) using the rate of change of the TEC index (ROTI). The climatology reveals variabilities over different time scales, i.e., solar cycle, seasonal, and diurnal variations. These variations in different time scales can be explained by different drivers/contributors. The solar activity (represented by the solar radiation index F10.7P) dominates the longest time scale variations. The seasonal variations are controlled by the interplay of the energy input into the polar cap ionosphere and the solar illumination that damps the amplitude of ionospheric irregularities. The diurnal variations (with respect to local time) are controlled by the relative location of the station with respect to the auroral oval. We further decompose the climatology of ionospheric irregularities using the empirical orthogonal function (EOF) method. The first four EOFs could reflect the majority (99.49%) of the total data variability. A climatological model of ionospheric irregularities is developed by fitting the EOF coefficients using three geophysical proxies (namely, F10.7P, Bt, and Dst). The data-model comparison shows satisfactory results with a high Pearson correlation coefficient and adequate errors. Additionally, we modeled the historical ROTI during the modern grand maximum dating back to 1965 and made the prediction during solar cycle 25. In such a way, we can directly compare the climatic variations of the ROTI activity across six solar cycles.

In this article, we show the capability of a global navigation satellite system (GNSS) precise orbit determination (POD) low Earth orbit (LEO) data to detect anomalous ionospheric disturbances in the spectral range of the signals associated with earthquakes and tsunamis, applied to two of these events in Papua New Guinea (PNG) and the Solomon Islands during 2016. This is achieved thanks to the new PIES approach (POD-GNSS LEO Detrended Ionospheric Electron Content Significant Deviations). The significance of such ionospheric signals above the swarm LEOs is confirmed with different types of independent data: in situ electron density measurements provided by the Langmuir Probe (LP) onboard swarm LEOs, DORIS, and ground-based GNSS colocated measurements, as it is described in this article. In this way, we conclude the possible detection of the tsunami-related ionospheric gravity wave in PNG 2016 event, consistent with the most-recent theory, which shows that a tsunami (which is localized in space and time) excites a spectrum of gravity waves, some of which have faster horizontal phase speeds than the tsunami. We believe that this work shows as well the feasibility of a future potential monitoring system of ionospheric disturbances, to be made possible by hundreds of CubeSats with POD GNSS receivers among other appropriate sensors, and supported for real-time or near real-time confirmation and characterization by thousands of worldwide existing ground GNSS receivers.

In the last decades, advances in satellite technologies, data analysis techniques, and models, and a growing number of analysis centers allow modeling the ionospheric electron content with unprecedented accuracy. International GNSS Service (IGS) Ionosphere Associated Analysis Centers (IAAC) continuously provide global ionospheric maps (GIMs) based on processing GNSS data from the ground IGS network. It is a great advantage that these GIMs are often based on very different modeling techniques and thus, are also characterized by different accuracy levels. Due to the dynamic nature of the ionosphere, there is a permanent need to improve the modeling techniques of ionospheric key parameters such as the vertical total electron content (vTEC). In this presentation, we evaluate a new ionosphere model from DGFI-TUM denoted OTHG, which is a candidate for a new IGS IAAC product. The OTHG model is based on tensor products of trigonometric B-spline functions in longitude and polynomial B-spline functions in latitude for a global representation (Goss et al. 2019). Here, we complement our earlier investigations of the seven analysis center models (Wielgosz et al. 2021) with new results for the OTHG GIMs. For these investigations, we use our own validation methodology presented in Krypiak-Gregorczyk et al. (2017), which is based on GIM-derived slant TEC (sTEC) comparison with carrier phase geometry-free combination of GNSS signals. In the presented study, we use one year of GNSS data collected by 25 globally distributed stations. The overall yearly RMS value is calculated for each product based on all 365 days of continuous observations from all stations. The results show that the overall RMS of the tested GIMs ranges from 0.93 TECU to 1.29 TECU. The OTHG GIMs performed as one of the best. In addition, GIM vTEC comparisons to Jason-2 and Jason - 3 altimetry data are studied. In these analyses, the OTHG GIMs also showed a good performance. Therefore, it can be concluded that DGFI-TUM is a valuable ionospheric product for the research community. Goss A., Schmidt M., Erdogan E., Görres B., Seitz F. (2019) High-resolution vertical total electron content maps based on multi-scale B-spline representations. Annales Geophysicae, 37(4), 10.5194/angeo-37-699-2019 Krypiak-Gregorczyk A., Wielgosz P., Borkowski A. (2017) Ionosphere Model for European Region Based on Multi-GNSS Data and TPS Interpolation, Remote Sensing, 9(12), 1221, DOI:10.3390/rs9121221 Wielgosz P., Milanowska B., Krypiak-Gregorczyk A., Jarmołowski W. (2021) Validation of GNSS‑derived global ionosphere maps for different solar activity levels: case studies for years 2014 and 2018. GPS Solutions 25, 103. https://doi.org/10.1007/s10291-021-01142-x

The objective of the work is to compare geomagnetic storm impact on the ionosphere parameters measured from ground-based GNSS permanent stations and Swarm satellites. The analyses compare the changes of vertical total electron content (VTEC) measured along the entire ionosphere cross-section to the variations of electron density (ED) on the orbit, at ~500 km altitude. The objective is how sensitive are the measures of electric field variations available on the Earth, with respect to those obtained from the satellite orbit. The study applies Swarm in-situ ED measured by Langmuir Probes (LP), topside TEC from onboard Swarm GNSS receivers and vertical TEC determined from ground-based GNSS stations available in the area of the Northern polar cap. Ground and satellite data were processed in different ways. Ground-based VTEC is available at number of stations providing heterogeneous but useful horizontal coverage. Therefore ROTI values were calculated from VTEC as gradient values capable to indicate the disturbances. These ROTI values were interpolated spatially to obtain maps. Swarm passes over the polar cap starting from 45° lasts for several minutes each, and repeat in this region approximately every 1.5 h. Such along-track collected small data samples are useless in horizontal correlation analysis. Therefore Swarm data disturbances, in this case, are extracted with the use of Fourier transform-based filtering and are also analyzed in the spectrograms based on short-term Fourier transform (STFT). The case study has used three geomagnetic storms, namely: the St. Patrick storm of March 17, 2015, the storm on June 22, 2015, and the storm on August 25-26, 2018. The results reveal differences in storm impact on VTEC measured by GNSS on the Earth, with respect to the storm influence on topside TEC and in-situ ED disturbances measured onboard the Swarm. The overall summary statistics provide some preliminary conclusions on different times of the reaction to the storm. Additionally, some interesting differences between FT filtering and a very popular moving average are shown, with respect to Swarm data. The research was done in the frame of the FORSWAR project (Forecasting Space Weather in the Arctic Region) funded by ESA.

We present the optical flow algorithm for forecasting the rate of total electron content index (OFROTI). It consists of a method for predicting maps of rapid fluctuations of ionospheric electron content in terms of global navigation satellite system (GNSS) dual-frequency phase measurements of the rate of change of total electron content index (ROTI). The forecast is made in space and time, at horizons up to more than 6 h. These forecast maps will consist of the ROTI spatial distribution in the northern hemisphere above 45° latitude. The prediction method models the ROTI spatial distribution as a pseudoconservative flux, i.e., exploiting the inertia of the flux of ROTI to determine the future position. This idea is implemented as a modification of the optical flow image processing technique. The algorithm has been modified to deal with the nonconservation of the ROTI quantity in time. We show that the method can predict both, the local value of ROTI and also the regions with ROTI above a given level, better than the prediction using the current map as forecast, i.e., predicting by a current map from horizons of 15 min up to 6 h. The method was tested on 11 representative active and calm days during 2015 and 2018 from the multi-GNSS (GPS, GLONASS, Galileo, and Beidou) multifrequency measurements of more than 250 multi-GNSS receivers above 45°N latitude, including the high rate (1 Hz) measurements of Greenland geodetic network (GNET) network among the International GNSS Service network.

There is a noticeable number of studies carried out on both the operational parameters of Global Navigation Satellite System (GNSS) and the satellite signal itself. Researchers look for, inter alia, proven sources of errors affecting the integrity of the satellite signal because this parameter determines the approval of the system’s operational use. It also seems of key importance that the atmospheric conditions, in any area of satellite signal usage, should not be underestimated due to their extensive impact. As the ionospheric refraction seriously limits the operational use of the satellite navigation signal, in this article, the authors attempted to quantify the effect of solar activity (expressed by sunspots) on the signal integrity using fuzzy logic. Fuzzy reasoning is used when information is inaccurate or incomplete and necessitates making decisions under conditions of uncertainty. Thanks to fuzzy sets, there are no obstacles to characterize the degree of intensity of a given phenomenon. In order to look at the problem more broadly, attention was also paid to the tropospheric conditions, and it was verified whether, against the background of cloudiness, precipitation, humidity, pressure and temperature, solar activity affects the integrity to the greatest extent. The integrity measurements from the EGNOS system (PRN120 and PRN126) collected at the monitoring station in Warsaw, Poland in 2014 were used.

Ionosphere Associate Analysis Centers (IAACs) of the International GNSS Service (IGS) independently produce global ionosphere maps (GIMs) of the total electron content (TEC). The GIMs are based on different modeling techniques, resulting in different TEC levels and accuracies. In this study, we evaluated the accuracy and consistency of the IAAC GIMs during high (2014) and low (2018) solar activity periods of the 24th solar cycle. In our study, we applied two different evaluation methods. First, we carried out a comparison of the GIM-derived slant TEC (STEC) with carrier phase geometry-free combination of GNSS signals obtained from 25 globally distributed stations. Second, vertical TEC (VTEC) from GIMs was compared to altimetry-derived VTEC obtained from the Jason-2 and Jason-3 satellites and complemented for plasmaspheric TEC. The analyzed GIMs obtained STEC RMS values reaching from 1.98 to 3.00 TECU and from 0.96 to 1.29 TECU during 2014 and 2018, respectively. The comparison to altimetry data resulted in VTEC STD values that varied from 3.61 to 5.97 TECU and from 1.92 to 2.78 TECU during 2014 and 2018, respectively. The results show that among the IAACs, the Center for Orbit Determination in Europe global maps performed best in low and high solar activity periods. However, the highest accuracy was obtained by a non-IGS product—UQRG GIMs provided by Universitat Politècnica de Catalunya. It was also shown that the best results were obtained using a modified single layer model mapping function and that the map time interval has a relatively small influence on the resulting map accuracy.

The study investigates Swarm data including in-situ electron density (ED) measured by Langmuir Probes (LP) and total electron content (TEC) from precise orbit determination (POD) GNSS receivers in time of Chile-Illapel earthquake (EQ) and tsunami in 2015. The research is based on the symbiosis of Swarm data, ground GNSS data and seismic records combined with the information on EQs and tsunamis. The FFT-based filtering and short-term Fourier transform (STFT) analysis are used in detection of seismic ionospheric disturbances (SID) in ED from LP and POD TEC data. The classification of the spectral characteristics of disturbing along-track signals is supported by their simultaneous search in ground GNSS observations, which gives an opportunity for the validation of the spectral recognition. Ground GNSS data, due to several tens of satellites and thousands of stations, provide the only full spatiotemporal view on SIDs and enable the inspection of their spatial shapes, spatial relations and speeds. The location of dense ground GNSS networks is however limited to selected places. Swarm and other LEO satellite data, in turn, are globally distributed, but they are dense only along the orbital tracks. Therefore, 1D nature of Swarm along-track observations, fast satellite movement and limited chance for spatiotemporal correlation due to the non-repeating orbits, strongly require spectral analysis for better recognition of the signals. The detection of SIDs from along-track Swarm data is also complicated due to the variety of disturbing signals occurring in the ionosphere, and the spectral analysis is also crucial there. STFT spectral approach to along-track Swarm data gives an opportunity for distinguishing the signals of different origin. The analyses of Swarm data provide interesting observations of ionospheric disturbances not only directly related with the largest EQ events and tsunami, but also occurring during entire periods of enhanced seismic activity and at larger distances from EQ epicenter. The disturbing signals triggered by the largest EQs and tsunami were also observed. However their amplitude in the ionosphere is not always such dominating as the amplitude of some other, associated disturbances on the neighboring days. This difference in scale can suggest that the electron disturbances in the ionosphere are rather more generally related to the crustal motion and seismic activity, than solely correlated with large EQs.

The study investigates ionospheric electric field responses to the earthquake (EQ) of magnitude 8.3, and the related seismic activity and tsunami triggered by the mainshock in Chile-Illapel region, at 22:54 UTC, in the evening of September 16, 2015. The work is a wider review of available ground and satellite data and techniques available to detect seismically induced traveling ionospheric disturbances (TID) and irregularities of smaller scale. The data used in the experiment includes several types of ground and satellite observations from low-Earth orbit (LEO) satellites. The number of techniques applied here is also extended and includes spectral analysis of LEO along-track data and composed analysis of ground GNSS data. The timeframe of the analyses is focused on September 16 and 17, 2015 but also extended to several adjacent days, where an enhanced seismic activity has been recorded. Several examples of seismically triggered TIDs are shown, as detected by combined observations from more than one source and applying different methods, including spectral analysis. These disturbances occur before the mainshock, just after, or in time following this large EQ, and can be found in close neighborhood of Chile-Illapel or far away from the epicenter. The objective of the work was to demonstrate an increasing number of available data and techniques, which can be limited when applied alone, but their combination can provide many advantages in the analysis of seismically disturbed ionosphere. The combination of LEO satellite data reaching all regions of the globe with local but dense ground-based GNSS data and ionospheric HF sounders looks promising, especially in view of the nearby availability of CubeSat constellations equipped with instruments for ionosphere sounding. An important conclusion coming from the study is a need for spectral analysis techniques in the processing of LEO along-track data and the requirement of the validation of LEO observations with separate LEO data or ground-based data. A general but key finding refers to the complementarities of different observations of the ionospheric electric field, which is critically important in the case of analyzing ionospheric irregularities in the extended and composed ionosphere, especially if not every sounding direction can successfully find it.

Global ionosphere maps (GIMs) representing ionospheric total electron content (TEC) are applicable in many scientific and engineering applications. However, the GIMs provided by seven Ionosphere Associated Analysis Centers (IAACs) are generated with different temporal resolutions and using different modeling techniques. In this study, we focused on the influence of map time interval on the empirical accuracy of these ionospheric products. We investigated performance of the high-resolution GIMs during high (2014) and low (2018) solar activity periods as well as under geomagnetic storms (19 February 2014 and 17 March 2015). In each of the analyzed periods, GIMs were also assessed over different geomagnetic latitudes. For the evaluation, we used direct comparison of GIM-derived slant TEC (STEC) with dual-frequency GNSS observations obtained from 18 globally distributed stations. In order to perform a comprehensive study, we also evaluated GIMs with respect to altimetry-derived vertical TEC (VTEC) obtained from the Jason-2 and Jason-3 satellites. The study confirmed the influence of GIMs time interval on the provided TEC accuracy, which was particularly evident during high solar activity, geomagnetic storms, and also at low latitudes. The results show that 120-min interval contributes significantly to the accuracy degradation, whereas 60-min one is sufficient to maintain TEC accuracy.

Since 1998 Ionosphere Associate Analysis Centers (IAAC) of the International GNSS Service (IGS) routinely provide global ionosphere maps (GIMs). They are used for a wide range of geophysical applications, including supporting precise positioning and improving space weather analysis. These GIMs are generated by different analysis centers with the use of different modelling techniques. Therefore they have different accuracy levels, which has already been evaluated in several studies. Until 2014 all GIMs were provided with 2-hour temporal resolution, and since 2015 some of the IAACs have started to provide their products with higher resolutions, up to 30 - 60 minutes. Since GIMs have different temporal resolutions, we investigated whether map interval affected their accuracies.In this study we carried out IAAC GIM accuracy analysis for years 2014 and 2018, corresponding to high and low solar activity periods, respectively. Since in 2014 IAAC GIMs had 2-hour resolution, we also evaluated UQRG maps supplied with 15-minute interval. For low solar activity period (2018) we evaluated 4 models: CASG, CODG, EMRG and UQRG. In addition, we studied ionosphere map performance during two selected geomagnetic storms: on 19 February 2014 and 17 March 2015. Our accuracy evaluation was based on GIM-TEC comparisons to differential STEC derived from GNSS data and VTEC derived from altimetry measurements.The results show that temporal interval has no significant impact on the overall, annual map RMS during both high and low solar activity periods. However, during geomagnetic storms, when reducing map interval, the map accuracy improves by almost 25%.