The paper presents statistical and modeling study of the response of high-latitude regional electron content (REC) to a weak isolated reference geomagnetic storm. The global ionospheric maps of the total electron content are used as observational data. The statistical study includes the following steps. The first step is to identify geomagnetic storms using the AE index. Second, we obtained the reference response by averaging the responses of isolated storms with using the superposed epoch technique. Finally, we obtained the averaged AE index storm time behavior (reference storm) by averaging the AE index using the same superposed epoch technique. The modeling study is based on the Global Self-Consistent Model of the Thermosphere, Ionosphere and Protonosphere (GSM TIP) with using the reference storm as input data. We identified essential seasonal dependence of high-latitude response to geomagnetic activity with significant positive disturbances in local winter. The UT effect of the high-latitude REC response to a geomagnetic storm determines the magnitude of disturbances, but does not affect the seasonal pattern of disturbances. GSM TIP results agree well with the reference response obtained with the superposed epoch technique. In this paper, the contributions of different height and latitudinal ranges to the high-latitude REC response were considered. A geomagnetic storm leads to positive disturbances of the protonospheric electron content at high latitudes in both hemispheres for any season. In addition, we showed that the positive high-latitude REC response to geomagnetic storm is associated with the electron heating (key mechanism) and storm-time equatorward wind. Changing the composition of the neutral atmosphere is a counteracting mechanism. The results of competition between positive and negative high-latitude regional electron content response strongly depend on season. Such dependence connected to seasonal dependence of background vertical profiles of electron density and interhemispheric asymmetry of neutral composition and thermospheric 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.

The paper presents an analysis of reference responses of regional electron content to strong geomagnetic events identified by the AE-index. As an ionospheric characteristic, we used the regional electron content (REC), which is the average total electron content (TEC) for five latitude zones in the corrected geomagnetic coordinate system: the mid-latitude zones in both hemispheres, the high-latitude zones in both hemispheres, and the equatorial zone. The relative (percentage) deviation of observed values from the 27-day running average REC was used to calculate disturbances of REC (ΔREC). The reference response was calculated by averaging ΔREC using the superimposed epoch method with key moments corresponding to the AE maximum for the winter, spring, summer and autumn storms. The paper discusses storm-time behavior, seasonal dependence and interhemispheric asymmetry of the REC responses to strong geomagnetic events.

On 18 November 2023, SpaceX launched the Starship, the tallest and the most powerful rocket ever built. The Super Heavy engine separated from the Starship spacecraft and exploded at 90 km of altitude, while the main core Starship continued to rise up to 149 km and exploded after similar to 8 min of flight. In this work, we used data from ground-based GNSS receivers and we analyzed total electron content (TEC) response to the Starship flight and the two explosions. For the first time, we observed large-distance northward propagation of intensive 2,000 km V-shaped ionospheric disturbances from the rocket trajectory. The observed perturbations, most likely, represent shock waves propagating with the cone angle of similar to 14 degrees on the North and similar to 7 degrees on the South against the flight track that corresponds to the Mach angle of the shock waves in the lower atmosphere. The Starship explosion also produced a non-chemical depletion in the ionospheric TEC. On 18 November 2023, SpaceX launched the Starship, the tallest and the most powerful rocket ever built. About 2 min and 40 s after the liftoff, the Super Heavy engine separated from the Starship spacecraft and exploded at an altitude of 90 km. The main core Starship continued to rise to 149 km and exploded as well. The rocket launch and explosion produced an unexpected response in the ionosphere-the ionized part of the Earth's atmosphere. The Starship flew at a velocity, exceeding the local sound speed, and generated cone-like atmospheric shock-acoustic waves. Most unexpectedly, the observed disturbances represented long and intensive multi-oscillation wave structures that propagated northward, which is unusual for disturbances driven by a rocket launch. The Starship explosion also generated a large-amplitude total electron content depletion that could have been reinforced by the impact of the spacecraft's fuel exhaust in the lower atmosphere. This study appears to be the first-time detection of a non-chemical ionospheric hole produced by a man-made explosion. The 18 November 2023 Starship flight and explosions generated large-scale multi-oscillation supersonic conic waves in the ionosphere The cone angle of the V-shaped ionospheric disturbances corresponds to the Mach angle of shock waves propagating in the lower ionosphere The shock waves from the Starship explosion caused a depletion in total electron content (TEC)

We presented the results of comparative analysis of geomagnetic events identified by various indices. A previously developed technique is used to identify magnetic storms by the Dst index. As a basis for identification, we chose the previously developed method for identifying geomagnetic storms based on the Dst index. A similar method was implemented to identify geomagnetic events by the ap and AE indices. Comparative analysis includes: (1) identification of common geomagnetic events identified by various indices; (2) identification of cases when an event is a strong geomagnetic disturbance by one of the indices (Dst, ap, AE) and is not a geomagnetic event by at least one of the two remaining indices; and (3) a comparative analysis of the diurnal and seasonal distribution of the number of geomagnetic events identified by different indices.

Results are presented from a comparative analysis of geomagnetic events identified according to different indices. A way of identifying geomagnetic storms developed earlier using the Dst index is selected as the basis for identification. A similar technique for identifying geomagnetic events is obtained on the basis of the ap and AE indices. A comparative analysis includes identifying common geomagnetic events according to different indices; cases where an event is a strong geomagnetic disturbance according to one index (Dst, ap, or AE) but not a geomagnetic event by at least one of the two remaining indices; and considering the daily and seasonal distributions of geomagnetic events identified according to different indices.

The paper considers an experimental complex of the Shared Research Facilities "The Angara" of ISTP SB RAS. Although the centre aims to study Near-Earth space, scientists could use some equipment for research in geodynamics. We mainly described the Siberian network of receivers of signals from global navigation satellite systems SibNet that currently includes ten receiving points. We also provide information on the fields where "non-geodynamic" equipment can be used for multidisciplinary studies of lithospheric processes.

In this work, we perform a joint analysis of the spatial-temporal dynamics of ionospheric and stratospheric variability (with scales characteristic of internal gravity waves) at different longitudes of midlatitudes of the Northern Hemisphere. We analyze the winter periods of 2012–2013 and 2018–2019 when strong midwinter sudden stratospheric warmings (SSWs) occurred. An increase in the variability in the stratosphere is shown to occur in a limited latitude interval 40°–60° N in the region of existence of a winter circumpolar vortex. Under SSW conditions, the generation of wave disturbances in the stratosphere ceases manifesting itself in a significant decrease in the stratospheric variability index. Similar behavior is noted in the spatial-temporal dynamics of the index of the total electron content variability. The level of ionospheric variability at midlatitudes decreases significantly after SSW peaks. The decrease in the ionospheric variability can be explained by a reduction in wave generation in the stratosphere, associated with the destruction of the circumpolar vortex during SSWs.

We have conducted ionosphere heating experiments using HF radiation of SURA facility in August of 2010 and in September of 2016. We analyzed GPS positioning accuracy during the experiments. Positioning errors were estimated for 14 GPS receivers located at various distance, from just at the facility up to more than 1000 km from the facility. Data show that there were no noticeable positioning errors for both precise point positioning (PPP) and standard single-frequency modes.

Global navigation satellite systems (GNSS), such as GPS, GLONASS, Galileo, and Bei-Dou/Compass are widely used for solving a variety of research and applied problems. This work considers the use of GNSS signals for monitoring of the ionosphere to provide an ionospheric error correction in radio-engineering systems in quasireal time. The problems arising in this case, among which the absolute ionospheric parameter estimation is the key problem, are discussed.

This study is aimed at statistically analyzing the ionospheric response to geomagnetic storms based on the data from the global ionospheric maps (GIMs). The global electron content and average zonal values of the total electron content for five latitudinal zones (equatorial zone, mid-latitude zones of the Northern and Southern Hemispheres, and high-latitude zones of the Northern and Southern Hemispheres) are selected as the ionospheric characteristics that are calculated from the global characteristics by using GIMs. The results of the statistical analysis are discussed in terms of the concept of an ionospheric/thermospheric storm, within which ionospheric disturbances are a consequence of the changes in the thermospheric parameters (neutral composition of the thermosphere and wind). The contradictions in the concept of a thermospheric/ionospheric storm are discussed from the standpoint of the methodological aspects of the statistical analysis and effects that are beyond this concept.

The global navigation satellite system accuracy and the possibility to actively affect it is quite a relevant problem. Based on two experimental campaigns (2010 and 2016), we analyzed the GPS positioning accuracy with forcing from the Sura high-power HF radiation. Analysis of the positioning error variations for 14 stations at different distances from the heater (directly near the latter and more than a thousand kilometers away from it) showed the absence of significant effects both in the precise point positioning (PPP) mode and in a standard iterative single-frequency positioning mode that is most frequently used.

AbstractNon‐linear Error Compensation Technique with Associative Restoration (NECTAR) is a novel approach to the assimilation of fragmentary sensor data to produce a global nowcast of the near‐Earth space weather. NECTAR restores missing information by iteratively transforming (“morphing”) an underlying global climatology model into agreement with currently available sensor data. The morphing procedure benefits from analysis of the inherent multiscale diurnal periodicity of the geosystems by processing 24‐hr time histories of the differences between measured and climate‐expected values at each sensor site. The 24‐hr deviation time series are used to compute and then globally interpolate the diurnal deviation harmonics. NECTAR therefore views the geosystem in terms of its periodic planetary‐scale basis to associate observed fragments of the activity with the grand‐scale weather processes of the matching variability scales. Such approach strengthens the restorative capability of the assimilation, specifically when only a limited number of observatories is available for the weather nowcast. Scenarios where the NECTAR concept works best are common in planetary‐scale near‐Earth weather applications, especially where sensor instrumentation is complex, expensive, and therefore scarce. To conduct the assimilation process, NECTAR employs a Hopfield feedback recurrent neural network commonly used in the associative memory architectures. Associative memories mimic human capability to restore full information from its initial fragments. When applied to the sparse spatial data, such a neural network becomes a nonlinear multiscale interpolator of missing information. Early tests of the NECTAR morphing reveal its enhanced capability to predict system dynamics over no‐data regions (spatial interpolation).

In the recent years, a significant amount of the measurements of the Earth's ionosphere state has been made by medium- and high-orbit global navigation satellite systems (GNSS) such as GLONASS, GPS, Galileo, Beidou, SBAS, etc. Currently, a number of services (such as IGS, UNAVCO, CHAIN, CORS, etc.) provide GNSS data in open access in the RINEX format. The databases start from early 1990s. Currently more than 5700 GNSS sites provide ~ 1.5 Gb daily which is 200 millions independent data points. The software tools to deal with such amount of data become necessary to do research effectively. We have developed System for the Ionosphere Monitoring and Researching from GNSS (SIMuRG) for organizing RINEX data and analyzing results from geophysical research view point. This paper describes approaches to create SIMURG, as well as the opportunities that the system can provide to the scientific community.

This study presents an analysis of geomagnetic disturbances and ionospheric electron density distribution during the 2015 St. Patrick's Day geomagnetic storm. To study those we have used the satellite-borne and ground-based observations. The St. Patrick's geomagnetic storm covers the interval of 15–23 March 2015, when solar eruptive phenomena (a long-enduring C9-class solar flare and associated CME's on 15 March) and a strong geomagnetic storm on 16–18 March (Dst dropped as strong as –228 nT) were reported. This geomagnetic storm is still the strongest one observed in the current solar cycle. The severe geomagnetic storm on 17-18 March 2015 led to complex effects on the ionosphere. We consider major features of the positive and negative ionospheric storms development at European mid- and high-latitudes. One of the interesting phenomena was observation of the positive ionospheric disturbances during the recovery phase. Using the Global Self-consistent Model of the Thermosphere, Ionosphere and Protonosphere (GSM TIP) we examined the main physical processes that played a major role in dramatic changes of the total electron content and the F2 layer peak electron density during this storm event.

In 2011, ISTP SB RAS began to deploy a routinely operating network of receivers of global navigation satellite system signals. To date, eight permanent and one temporal sites in the Siberian region are operating on a regular basis. These nine sites are equipped with 12 receivers. We use nine multi-frequency multi-system receivers of Javad manufacturer, and three specialized receivers NovAtel GPStation-6 designed to measure ionospheric phase and amplitude scintillations. The deployed network allows a wide range of ionospheric studies as well as studies of the navigation system positioning quality under various heliogeophysical conditions. This article presents general information about the network, its technical characteristics, and current state, as well as the main research problems that can be solved using data from the network.

The results of studies of longitudinal and LT variations in parameters of the ionosphere–plasmasphere system, obtained using the Global Self-Consistent Model of the Thermosphere, Ionosphere and Protonosphere (GSM TIP), assimilation ionospheric model IRI Real-Time Assimilation Mapping (IRTAM), and satellite and ground-based observational data are presented in the paper. The study of the main morphological features of longitudinal and LT variations in the critical frequency of the ionospheric F2 layer ( foF2 ) and total electron content ( TEC ) depending on latitude in the winter solstice during a solar-activity minimum (December 22, 2009) is carried out. It is shown that the variations in foF2 and TEC , on the whole, are identical, and so mutually substitutable, while creating empirical models of these parameters in quiet geomagnetic conditions. The longitudinal and LT variations in both foF2 and TEC are within an order of magnitude everywhere except for the equator anomaly region, where LT variation is larger by an order of magnitude than longitudinal variation. According to the results of the study, in the American longitudinal sector at all latitudes of the Southern (summer) Hemisphere, maxima of foF2 and TEC are formed. The near-equatorial and high-latitudinal maxima are separated out from these. The estimate of the contribution into the longitudinal variation in foF2 and TEC for various local time sectors and at various latitudes has been obtained for the first time. In the Southern (summer) Hemisphere, longitudinal variation in foF2 and TEC is formed in the nighttime.

Non-linear Error Compensation Technique for Associative Restoration (NECTAR) is a novel approach to the task of assimilating fragmentary sensor data into a global coverage model, in which an underlying model prediction is iteratively transformed (“morphed”) into a better agreement with the available sensor data. Similarly to the Kalman filter, NECTAR gleans the system nowcast from the observed mismatch of prediction and observations; however, each NECTAR update step trying to correct the observation-model disagreements is a non-linear recursive process of manipulating a large number of internal multiscale constituents of the underlying empirical model, both spatial and temporal. The NECTAR error compensation procedure is performed by the Hopfield feed-back neural network commonly used in associative memory architectures that restore full information from its fragments. When applied to the sparse spatial data from the contributing observatories, such neural network becomes an associative multiscale interpolator of missing information. To ensure the multiscale capability of NECTAR assimilation analysis in the time domain, the spatial interpolation is performed individually for each diurnal harmonic of the differences between observation and prediction computed for each sensor location. Early results of the NECTAR model morphing applied to the assimilation of measured data from the Global Ionosphere Radio Observatory (GIRO) into the International Reference Ionosphere (IRI) model reveal its intriguing capability to predict system dynamics over no-data areas (spatial interpolation) and in time (short-term forecast).