Search Results (125)

Differing from previous work on ionospheric models only using a relative method, in this paper, stereoscopic ionospheric models are innovatively constructed utilizing both relative and absolute automatic plasma perturbations. Firstly, ionospheric perturbations are globally searched from electron density data measured for 10 years by Swarm-A/C satellites via automatic detection software. In total, 621,999 Swarm-A perturbations and 630,668 Swarm-C ones are obtained, respectively. Then, the variation for each perturbation is calculated in two ways: via the relative method and absolute method. To check possible discrepancy between ionospheric models under these two different calculations, seasonal ionospheric models have been globally established using relative and absolute perturbations for both satellites. The results show that both kinds of models for each satellite can comprehensively reveal the main ionospheric structures, like EIA, WSA/MSNA, the mid-latitude trough and the auroral anomaly zone. Relatively, the EIA always shows its significance in equinox under calculation methods due to strong ionospheric irregularities caused by seasonal variation, but it is more obvious under the absolute method than relative one because of its higher background density. Comparatively, the auroral anomaly zone is predominantly filled with relatively large perturbations and is particularly conspicuous, especially in winter, due to its low background density. By contrast, mid-latitude structures, such as WSA/MSNA and mid-latitude trough, are comparatively affected less under these dual methods. At the same time, the interhemispheric asymmetry of EIA phenomena, as well as latitudinal WN4/3, is also significantly distinguished by seasonal ionospheric models. The occurrence probabilities of perturbations as a function of various variation magnitudes are also examined and the results demonstrate that the percentages of all variation segments vary widely with seasonal changes but this uneven fluctuation is more pronounced in summer under relative calculation and in winter under absolute calculation. Small fluctuations with relative variation ΔVr < 10% or absolute ΔVa < 10⁴ m⁻³ always demonstrate significance in each group of seasonal perturbations while their percentage changes in different ways, decreasing in the order of summer, equinox and winter under the relative method and increasing under the absolute method. The measurements performed by Swarm-A/C demonstrate excellent consistency during the period considered. Full article

This study used Global Navigation Satellite System (GNSS) observations from the China Crustal Movement Observation Network (CMONOC) and the Kunming Continuously Operating Reference Station (KMCORS) network to investigate ionospheric response characteristics over China during the geomagnetic storm of 4–6 November 2023, and to assess their impacts on CORS-based real-time kinematic (RTK) positioning performance in the low-latitude Kunming region. A quantitative assessment was conducted by integrating regional two-dimensional dTEC (%) maps over China, BeiDou Navigation Satellite System (BDS) Geostationary Earth Orbit (GEO) total electron content (TEC), the rate of TEC index (ROTI), and RTK positioning solutions to evaluate ionospheric disturbances, irregularity activity, and associated degradation in positioning performance. Results indicate that, during geomagnetic storms, ionospheric responses over China exhibit pronounced phase-dependent and latitudinal variations. During the second geomagnetic storm on 5–6 November, positive responses were dominant at mid-to-high latitudes, whereas alternating positive and negative responses were observed at low latitudes. During the recovery phase, the Kunming region successively experienced a positive ionospheric storm lasting approximately 10 h, followed by a negative ionospheric storm lasting about 7 h, with relative TEC variations reaching a maximum of approximately 90%. The GEO TEC time series was consistent with the temporal evolution of the two-dimensional dTEC (%), while ROTI increased markedly during the disturbance enhancement period (21:00 UT on 5 November to 07:00 UT on 6 November 2023). During periods of enhanced ionospheric response and irregularities, RTK positioning performance was observed to deteriorate markedly. The fixed-solution rate at medium-to-long baseline stations decreased from nearly 100% to close to 0%, accompanied by an increase in vertical positioning errors to approximately 20 cm, whereas short-baseline stations were only minimally affected. These results indicate that ionospheric disturbances during geomagnetic storms exert a pronounced impact on CORS-based RTK positioning services in the Kunming region, with the magnitude of this impact being closely related to baseline length. Full article

Global Positioning System (GPS)-derived ionospheric electron concentration measurements provide a powerful observational framework for seismo-electromagnetic studies, enabling quantitative investigation of lithosphere–atmosphere–ionosphere coupling processes through statistically detectable perturbations in ionospheric electron concentration. We analyze GPS-derived Vertical Total Electron Content (VTEC) variations associated with the 14 August 2021 Haiti earthquake ($M_w$ 7.2) and the 11 January 2022 Cyprus earthquake ($M_w$ 6.6) using data from nearby International GNSS (Global Navigation Satellite System) Service (IGS) stations located within their respective earthquake preparation zones. VTEC time series spanning 45 days before and 7 days after each event are processed to remove the diurnal component, yielding residuals that isolate short-term ionospheric variability. Anomaly detection is performed using three statistical frameworks: a Gaussian mean, standard deviation model, a robust median/median absolute deviation (MAD) model, and a distribution-free quantile-based model. Daily “occurrence” and “energy” indices are constructed to quantify the frequency and cumulative strength of detected anomalies, respectively. While the indices exhibit similar temporal patterns across all methods, they indicate frequent anomaly detection, limiting statistical selectivity. To address this, both indices are normalized by their median values and filtered using a 95% quantile threshold, retaining only extreme deviations. This procedure substantially reduces background fluctuations and isolates a small number of statistically significant anomaly peaks. For both earthquakes, enhanced anomaly activity is identified in the weeks preceding the events, whereas post-event peaks coincide with periods of elevated meteorological and geomagnetic activity. The results demonstrate that normalization combined with robust statistical methods is essential for discriminating significant ionospheric TEC anomalies from background variability. Full article

Total Electron Content (TEC) maps allow the evaluation of the state of the ionosphere. There are many providers/sources of worldwide or regional TEC maps for the continuous monitoring of the ionosphere, which employ different GNSS monitoring networks for data acquisition, TEC calculation or interpolation methods for generating the maps, or different spatial and temporal resolutions and coverage. How reliable are TEC maps over Brazil? We employed TEC maps from four different providers for 2022–2024, in the growing phase of the current solar cycle 25. Seasonality is also taken into account. A systematic comparison of TEC maps over Brazil was performed using correlation and similarity analysis between maps of different sources. Significant differences were found. Even for the same source there are differences in the density of monitoring stations according to the region. An example of bubble signature in TEC maps is also analyzed. Ground truth validation of TEC is performed by comparing TEC point values extracted from the maps with values derived from a set of GNSS stations over Brazil. As a result, no TEC maps of these sources were deemed reliable, due to low spatial and/or temporal resolution, low monitoring station density, or inadequate interpolation scheme. Full article

A series of multi-parameter, multi-layer observations was conducted to study possible electromagnetic precursors associated with the M 6.7 earthquake that struck Iburi, Hokkaido, Japan, at 18:07:59 UT on 5 September 2018. The most significant observation is seismogenic lower-ionospheric perturbations in the propagation anomalies of sub-ionospheric VLF/LF signals recorded in Japan and Russia. Other substantial observations include the GIM-TEC irregularities, the intensification of stratospheric atmospheric gravity waves (AGWs), and the satellite and ground monitoring of air temperature (T), relative humidity (RH), atmospheric chemical potential (ACP), and surface latent heat flux (SLHF). We have found that there were very remarkable VLF/LF anomalies indicative of lower-ionospheric perturbations observed on 4 and 5 September just before the EQ date and even after it from the observations in Japan and Russia. In particular, the anomaly was detected for a particular propagation path from the JJY transmitter (Fukushima) to a VLF station at Wakkanai one day before the EQ, i.e., on 4 September, and is objectively confirmed by machine/deep learning analysis. An anomaly in TEC occurred only on 5 September, but it is unclear whether it is related to a pre-EQ effect or a minor geomagnetic storm. We attempted to determine whether any seismo-related atmospheric gravity wave (AGW) activity occurred in the stratosphere. Although numerous anomalies were detected, they are most likely associated with convective weather phenomena, including a typhoon. Finally, the Earth’s surface parameters based on satellite monitoring seem to indicate some anomalies from 29 August to 3, 4, and 5 September, a few days prior to EQ data, but the ground-based observation close to the EQ epicenter has indicated a clear T/RH and ACP on 2 September with fair weather, but no significant data on subsequent days because of severe meteorological activities. By integrating multi-layer observations, the LAIC (lithosphere–atmosphere–ionosphere coupling) process for the Hokkaido earthquake appears to follow a slow diffusion-type channel, where ionospheric perturbations arise a few days after ground thermal anomalies. This study also provides integrated evidence linking concurrent lower-ionospheric, atmospheric, and surface thermal anomalies, emphasizing the diagnostic value of such multi-parameter observations in understanding EQ-associated precursor signatures. Full article

BU–MIT whistler wave injection experiments, which were conducted at Arecibo Observatory, started with the joint US–USSR Active Space Plasma Program Experiment on 24 December 1989. In this experiment, a satellite-borne VLF transmitter injected radio waves at the frequency and power of 10 kHz and 10 kW. A series of controlled whistler wave experiments with the Arecibo HF heater were subsequently carried out during 1990–1998 until the HF heater was damaged by Hurricane Georges in 1998. In these ionospheric HF heating experiments, 28.5 kHz whistler waves were launched from the nearby naval transmitter (code-named NAU) located at Aguadilla, Puerto Rico. HF heater waves were used to create ionospheric ducts (in the form of parallel-plate waveguides) to facilitate the entry of NAU whistler waves from the neutral atmosphere into the ionosphere. Conjugate whistler wave propagation experiments were conducted between Arecibo, Puerto Rico and Trelew, Argentina in 1997. After 1999, whistler wave experiments in the absence of an HF heater had been conducted. Naturally-occurring large-scale ionospheric irregularities due to spread F or Traveling Ionospheric Disturbances (TIDs) were relied on to guide NAU launched 40.75 kHz whistler waves to propagate from the ionosphere further into the radiation belts, to cause 390 keV charged-particle precipitation. A train of TIDs, resulting from the 9.2 Mw earthquake off the west coast of Sumatra, Indonesia, was observed in our 26 December 2004 Arecibo experiments, about a day after the earthquake-launched tsunami waves traveled across the Indian Ocean, then into remote parts of the Atlantic Ocean. The author’s recent research efforts, motivated by Arecibo experiments, focus on Solar Powered Microwave Transmitting Systems, to simulate Solar Energy Harvesting via Solar Power Satellite (SPS) (also known as Space Based Solar Power (SBSP)) These experiments involved a large number of the author’s BU and MIT students working on theses and participating in the Undergraduate Research Opportunities Program (UROP), in collaboration with other colleagues at several universities and national laboratories. Full article

We present a comprehensive multi-parametric analysis of Lithosphere– Atmosphere–Ionosphere Coupling (LAIC) processes associated with the M = 8.8 earthquake that struck offshore Kamchatka, Russia, on 30 July 2025 (29 July 2015; 23:24:52 UTC). Thermal observations revealed coherent pre-seismic irregularities in near-surface air temperature, relative humidity, and atmospheric chemical potential (ACP), with maximum intensification occurring 1–2 days before the event, followed by rapid co-seismic dissipation and post-seismic recovery. Acoustic channel analysis revealed considerable enhancements in atmospheric gravity wave (AGW) potential energy, as computed from ERA5 reanalysis datasets, 3–5 days prior to the earthquake, with a co-seismic peak and weaker post-seismic irregularities at higher altitudes. Electromagnetic signatures manifested in both lower and upper ionospheric layers. Very-Low-Frequency (VLF) sub-ionospheric propagation from the NPM transmitter, continuously monitored at the PTK (Petropavlovsk-Kamchatsky) station in Kamchatka, Russia, exhibited both positive and negative deviations in amplitude and phase during the preparatory phase. VLF amplitude exhibited wavelike deviations consistent with AGW periods, peaking one day prior to the earthquake. Ionospheric Vertical Total electron content (VTEC) showed coherent pre-seismic maxima 2–3 days before the main shock. Together, these thermal, acoustic, and electromagnetic observations strongly suggest a consistent pre-seismic build-up, co-seismic dissipation, and post-seismic recovery, providing a robust multi-channel imprint of the Kamchatka earthquake and highlighting the importance of integrated multi-parameter approaches for understanding earthquake preparatory dynamics. Full article

The solar terminator, due to its unique characteristics, is a remarkable source of atmospheric disturbances. Due to its regularity and constancy, dependent solely on geometric factors, it can serve as a test source of disturbances, which can be used to test the response of the medium through which it passes and determine its state. However, our knowledge of the atmospheric phenomena generated by the terminator is far from complete. One clear indication of the terminator’s influence is geomagnetic disturbances manifested in the vertical and eastward components of the magnetic field measured at magnetic observatories. To determine the sources of geomagnetic disturbances from the solar terminator, which can be identified by the strict phase correlation of these disturbances with the moments of terminator passage, ionospheric irregularities arising during terminator passage were studied. Ionospheric irregularities extending along the boundary of the morning solar terminator were detected in total electron content data, based on measurements by GNSS receivers. Assumptions are made about the possible parameters of the ionospheric current structure that creates variations in the magnetic field associated with the passage of the solar terminator. Full article

The Hunga-Tonga volcanic eruption on 15 January 2022, produced significant atmospheric and ionospheric disturbances that may degrade global navigation satellite system (GNSS) and precise point positioning (PPP) accuracy. Using data from the GEONET GNSS network and Soratena barometric pressure sensors across Japan, we analyzed the eruption’s effects through the gradient ionospheric index (GIX) and the rate of TEC index (ROTI) to characterize the propagation and effects of these disturbances on ionospheric total electron content (TEC) gradients. Our analysis identified two separate ionospheric disturbance events. The first event, coinciding with the arrival of atmospheric Lamb waves, was characterized by wave-like pressure anomalies, differential TEC (dTEC) fluctuations, and modest horizontal gradients of vertical TEC (VTEC). In contrast, the second, more pronounced disturbance was driven by equatorial plasma bubbles (EPBs), which generated severe ionospheric irregularities and large TEC gradients. Further analysis revealed that these two disturbances had markedly different impacts on GNSS positioning accuracy. The Lamb wave–induced disturbance mainly caused moderate TEC fluctuations with limited effects on positioning accuracy, and mid-latitude stations maintained both average and 95th percentile positioning ($\mathrm{p}\mathrm{p}\mathrm{p},{\mathrm{P}}_{95}$) errors below 0.1 m throughout the event. In contrast, the EPB-driven disturbance had a substantial impact on low-latitude regions, where the average horizontal PPP error peaked at 0.5 m and the horizontal and vertical $\mathrm{p}\mathrm{p}\mathrm{p},{\mathrm{P}}_{95}$ errors exceeded 1 m. Our findings reveal two episodes of spatial-gradient enhancement and successfully estimate the propagation speed and direction of the Lamb waves, supporting the potential application of ionospheric gradient monitoring in forecasting GNSS performance degradation. Full article

Ionospheric scintillation represents a disturbance phenomenon induced by irregular electron density variations, predominantly occurring in equatorial, auroral, and polar regions, thereby posing significant threats to Global Navigation Satellite Systems (GNSS) performance. Polar regions in particular confront distinctive challenges, including the sparse deployment of dedicated ionospheric scintillation monitoring receiver (ISMR) equipment, the limited availability of strong scintillation samples, severely imbalanced training datasets, and the insufficient sensitivity of conventional Deep Neural Networks (DNNs) to intense scintillation events. To address these challenges, this study proposes a modeling framework that integrates residual neural networks (ResNet) with the Synthetic Minority Over-sampling Technique for Regression with Gaussian Noise (SMOGN). The proposed model incorporates multi-source disturbance features to accurately estimate phase scintillation indices (${\sigma }_{\phi }$) in polar regions. The methodology was implemented and validated across multiple polar observation stations in Canada. Shapley Additive Explanations (SHAP) interpretability analysis reveals that the rate of total electron content index (ROTI) features contribute up to 64.09% of the predictive weight. The experimental results demonstrate a substantial performance enhancement compared with conventional DNN models, with root mean square error (RMSE) values ranging from 0.0078 to 0.038 for daytime samples in 2024, and an average coefficient of determination (R²) consistently exceeding 0.89. The coefficient of determination for the Pseudo-Random Noise (PRN) path estimation results can reach 0.91. The model has good estimation results at different latitudes and is able to accurately capture the distribution characteristics of the local strong scintillation structures and their evolution patterns. Full article

We present new insights into post-sunrise ionospheric irregularities in Southeast Asia during the intense geomagnetic storm of 19–20 April 2024. By utilizing Total Electron Content (TEC) and Rate of TEC Change Index (ROTI) maps, along with ionosondes, we identified the emergence of post-sunset Equatorial Plasma Bubbles (EPBs)—plasma depletion structures and irregularities—in western Southeast Asia on 19 April. These EPBs moved eastward, and the irregularities dissipated before midnight after the EPBs covered approximately 10° of longitude. Interestingly, plasma density depletion structures persisted and turned westward after midnight until post-sunrise the following day. Concurrently, an increase in F-region height from midnight to sunrise, possibly induced by the storm’s electric field, facilitated the regeneration of irregularities in the residual plasma depletions during the post-sunrise period. The significant increase in F-region height was particularly pronounced in western Southeast Asia. As a result, post-sunrise irregularities expanded their latitudinal structure while propagating westward. These findings suggest that areas with decayed plasma depletion structures from post-sunset EPBs that last past midnight could be sites for creating post-sunrise irregularities during geomagnetic storms. The storm-induced electric fields produce EPBs and ionospheric irregularities at longitudes where the surviving plasma depletion structures of post-sunset EPBs are present. Full article

The present study analyzes the global ionospheric response to the intense geomagnetic storm of 10–11 October 2024 (SYM—H minimum of −346 nT), using observations from COSMIC—2 and Swarm satellites, GNSS TEC, and Digisondes. Significant uplift of the F-region was observed across both Hemispheres on the dayside, primarily driven by equatorward thermospheric winds and prompt penetration electric fields (PPEFs). However, this uplift did not correspond with increases in foF2 due to enhanced molecular nitrogen-promoting recombination in sunlit regions and the F2 peak rising beyond the COSMIC—2 detection range. In contrast, in the Southern Hemisphere nightside ionosphere exhibited pronounced Ne depletion and low hmF2 values, attributed to G-conditions and thermospheric composition changes caused by storm-time circulation. Strong vertical plasma drifts exceeding 100 m/s were observed during both the main and recovery phases, particularly over Ascension Island, driven initially by southward IMF—Bz-induced PPEFs and later by disturbance dynamo electric fields (DDEFs) as IMF—Bz turned northward. Swarm data revealed a poleward expansion of the Equatorial Ionization Anomaly (EIA), with more pronounced effects in the Southern Hemisphere due to seasonal and longitudinal variations in ionospheric conductivity. Additionally, the storm excited Large-Scale Travelling Ionospheric Disturbances (LSTIDs), triggered by thermospheric perturbations and electrodynamic drivers, including PPEFs and DDEFs. These disturbances, along with enhanced westward thermospheric wind and altered zonal electric fields, modulated ionospheric irregularity intensity and distribution. The emergence of anti-Sq current systems further disrupted quiet-time electrodynamics, promoting global LSTID activity. Furthermore, storm-induced equatorial plasma bubbles (EPBs) were observed over Southeast Asia, initiated by enhanced PPEFs during the main phase and suppressed during recovery, consistent with super EPB development mechanisms. Full article

While space weather indices (e.g., F10.7, Dst index) are commonly employed to characterize ionospheric activity levels, the Global Mean Electron Content (GMEC) provides a more direct and comprehensive indicator of the global ionospheric state. This metric demonstrates greater potential than space weather indices for calibrating empirical ionospheric models such as IRI-2020. The COSMIC-2 constellation enables continuous, all-weather global ionospheric monitoring via radio occultation, unimpeded by land–sea distribution constraints, with over 8000 daily occultation events suitable for GMEC modeling. This study developed two lightweight GMEC models using COSMIC-2 data: (1) a POD GMEC model based on slant TEC (STEC) extracted from Level 1b podTc2 products and (2) a PROF GMEC model derived from vertical TEC (VTEC) calculated from electron density profiles (EDPs) in Level 2 ionPrf products. Both backpropagation neural network (BPNN)-based models generate hourly GMEC outputs as global spatial averages. Critically, GMEC serves as an essential intermediate step that addresses the challenges of utilizing spatially irregular occultation data by compressing COSMIC-2’s ionospheric information into an integrated metric. Building on this compressed representation, we implemented a convolutional neural network (CNN) that incorporates GMEC as an auxiliary feature to calibrate IRI-2020’s global ionospheric maps. This approach enables computationally efficient correction of systemic IRI TEC errors. Experimental results demonstrate (i) 48.5% higher accuracy in POD/PROF GMEC relative to IRI-2020 GMEC estimates, and (ii) the calibrated global IRI TEC model (designated GCIRI TEC) reduces errors by 50.15% during geomagnetically quiet periods and 28.5% during geomagnetic storms compared to the original IRI model. Full article

Geomagnetic storms induce ionospheric disturbances, significantly affecting Global Navigation Satellite System (GNSS) positioning accuracy. This study investigates how geomagnetic storm-induced ionospheric irregularities influence GNSS Precise Point Positioning (PPP), using data from approximately 260 GNSS stations across China during 15 storm events between 1 January and 30 June 2015. We applied two indices—the Gradient Ionosphere Index (GIX), representing spatial gradients of vertical total electron content (VTEC), and the Rate of TEC Index (ROTI), describing temporal TEC variations. The analysis identified the St. Patrick’s Day geomagnetic storm (17 March 2015) as causing the most pronounced ionospheric disruptions, with significant east–west TEC gradients (|GIXx,P95| > 50 mTECU/km) consistently associated with substantial PPP errors (>0.5 m). Spatial analyses further indicated that significant 3D PPP errors (PPP, P₉₅ > 0.4 m) closely overlapped with regions experiencing intense east–west TEC gradients, predominantly in the 20–35°N latitude band. Further analysis indicated notable pre-storm ionospheric enhancements driven by zonal electric fields, distinct ionospheric suppression associated with westward disturbance dynamo electric fields (DDEFs) on 18 March, and re-intensification due to eastward penetration electric fields (PEFs) on 19 March. Full article

This paper investigates the effects of a Corotating Interaction Region (CIR)/High-Speed Stream (HSS)-driven geomagnetic storm from 13 to 23 October 2003, preceding the well-known Halloween storm. This moderate storm exhibited a prolonged recovery phase and persistent activity due to a High-Intensity Long-Duration Continuous AE Activity (HILDCAA) event. We focus on low-latitude ionospheric responses induced by Prompt Penetration Electric Fields (PPEFs) and Disturbance Dynamo Electric Fields (DDEFs). To assess these effects, we employed ground-based GNSS receivers, Digisonde data, and satellite observations from ACE, TIMED, and SOHO. An empirical model by Scherliess and Fejer (1999) was used to estimate equatorial plasma drifts and assess disturbed electric fields. Results show a ∼120 km uplift in hmF2 due to PPEF, expanding the Equatorial Ionization Anomaly (EIA) crest beyond 20° dip latitude. DDEF effects during HILDCAA induced sustained F-region oscillations (∼100 km). The storm also altered thermospheric composition, with [[O]/[N₂] enhancements coinciding with TEC increases. Plasma irregularities, inferred from the Rate of TEC Index (ROTI 0.5–1 TECU/min), extended from equatorial to South Atlantic Magnetic Anomaly (SAMA) latitudes. These results demonstrate prolonged ionospheric disturbances under CIR/HSS forcing and highlight the relevance of such events for understanding extended storm-time electrodynamics at low latitudes. Full article