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A new observational phenomenon, named Simultaneous Global Ionospheric Density Disturbance (SGD), is identified in GNSS total electron content (TEC) data during periods of three typical geospace disturbances: a Coronal Mass Ejection‐driven severe disturbance event, a high‐speed stream event, and a minor disturbance day with a maximum Kp of 4. SGDs occur frequently on dayside and dawn sectors, with a ∼1% TEC increase. Notably, SGDs can occur under minor solar‐geomagnetic disturbances. SGDs are likely caused by penetration electric fields (PEFs) of solar‐geomagnetic origin, as they are associated with Bz southward, increased auroral AL/AU, and solar wind pressure enhancements. These findings offer new insights into the nature of PEFs and their ionospheric impact while confirming some key earlier results obtained through alternative methods. Importantly, the accessibility of extensive GNSS networks, with at least 6,000 globally distributed receivers for ionospheric research, means that rich PEF information can be acquired, offering researchers numerous opportunities to investigate geospace electrodynamics. Plain Language Summary Electric fields of solar wind and geomagnetic disturbance origin can penetrate into the low latitude upper atmosphere, influencing the ionospheric dynamics and electron density variations. This study employs a new method that utilizes global and continuous GNSS total electron content (TEC) observations to investigate the electric field effects. The analysis focuses on three geospace disturbance events of different intensities and solar‐terrestrial conditions. The study identifies a novel phenomenon named Simultaneous Global Ionospheric Density Disturbance (SGD), primarily occurring on the sunlit portion of the Earth's ionosphere and also near dawn hours with 1% or larger amplitudes of the background TEC, or a few tenths of a TEC unit (1016 m3). The remarkable global extent of ionospheric responses to minor solar‐geomagnetic conditions is noteworthy. The solar wind magnetic field directed southward is highly correlated with most SGDs, lasting for up to 30 min. The findings present an effective approach for continuously monitoring electric field penetration and ionospheric impacts, leading to an improved understanding of space weather and its technological implications. Key Points Simultaneous global ionospheric disturbances (SGDs) are often observed even during minor solar and geomagnetic disturbances SGDs occur predominately on dayside and are related to penetration electric fields (PEFs) of solar wind and geomagnetic disturbance origin Global GNSS networks offer a novel and effective technique for continuous PEF monitoring, providing rich data sets for further study

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.

In recent years, deep learning has been extensively used for ionospheric total electron content (TEC) prediction, and many models can yield promising prediction results, particularly under quiet conditions. Owing to the ionosphere's intricate and dramatic changes during geomagnetic storms, the high‐reliable prediction of the storm‐time ionospheric TEC remains a challenging problem. In this study, we developed a new deep learning‐based multi‐model ensemble method (DLMEM) to forecast geomagnetic storm‐time ionospheric TEC that combines the Random Forest (RF) model, the Extreme Gradient Boosting (XGBoost) algorithm, and the Gated Recurrent Unit (GRU) network with the attention mechanism. Seven features in 170 geomagnetic storm events, including the three components Bx, By and Bz of interplanetary magnetic field (IMF), the Kp and Dst indices of geomagnetic activity data, the F10.7 index of solar activity data and global TEC data, were used for modeling. The test set results showed that the DLMEM model can reduce the root mean square errors (RMSE) by an average of 43.6% in comparison to our previously presented model Ion‐LSTM, especially during the recovery period of geomagnetic storms. Furthermore, compared to Ion‐LSTM, the RMSE values of the low‐, middle‐ and high‐latitude single‐station forecast TEC can be greatly decreased by 33%, 53% and 59%, respectively. It was shown that the new model allows for more precise short‐term global ionospheric forecasting during geomagnetic storms, enabling real‐time monitoring of ionospheric changes.

The thermospheric density response during geomagnetic storms has been extensively explored, but with limited studies on the density response in the Mesosphere and Lower Thermosphere (MLT) region. In this study, the density response in the MLT region at mid-to-high latitudes of the Northern Hemisphere during the intense geomagnetic storm in May 2024 is investigated using density data from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument aboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite. The results indicate that during the geomagnetic storm, the density response exhibits both significant decreases and increases; specifically, approximately 25.2% of the observation points show a notable reduction within a single day, with the maximum decrease exceeding −59.9% at 105 km. In contrast, around 16.5% of the observation points experience a significant increase over the same period, with the maximum increase surpassing 82.4% at 105 km. The distribution of density changes varies with altitudes. The magnitude of density increases diminishes with decreasing altitude, whereas the density decreases exhibit altitude-dependent intensity variations. Density decreases are primarily concentrated in high-latitude regions, especially in the polar cap, while density increases are mainly observed between 50°N and 70°N. The intensity of density response is generally stronger in the dusk sector than in the dawn sector. These results suggest that atmospheric expansion and uplift driven by temperature variations are the primary factors underlying the observed density change.

A thin and highly dense sporadic E layer, which can occasionally block the upper ionospheric layers, is called blanketing sporadic E (E.sub.sb). We present the statistical seasonal local time occurrence pattern of E.sub.sb at equatorial station Tirunelveli (8.7° N, 77.8° E, dip latitude 0.7° N) during the extended minimum of solar cycle 24 (2007-2009). In spite of nearly the same average solar activity during both 2007 and 2009, considerable differences are noticed in the seasonal occurrence of E.sub.sb during this period. The percentage of E.sub.sb occurrence is found to be the highest during the summer solstice ( 50%) for both 2007 and 2009, which is in general accordance with the earlier studies. The occurrences of E.sub.sb during the vernal equinox (~ 33%) and January-February (~ 28%) are substantial in 2009 as compared to those during the same seasons in 2007. We find that, during winter (January-February), ~ 75% of E.sub.sb occurred during or just after the period of sudden stratospheric warming (SSW). We suggest that enhanced E.sub.sb occurrence during winter (January-February) and the vernal equinox of 2009 could be associated with SSW-driven changes in the E region ambient conditions. Furthermore, the close association of E.sub.sb with counter equatorial electrojet (CEEJ) suggested by earlier studies is re-examined carefully using the scenario of E.sub.sb occurrence on non-CEEJ days. Such an exercise is crucial as we are unaware whether the physical mechanisms driving E.sub.sb and CEEJ are linked or not. We find that, of all the seasons, the association of E.sub.sb and CEEJ is strongest during winter (November-December).

Specification and forecast of ionospheric parameters, such as ionospheric electron density (Ne), have been an important topic in space weather and ionospheric research. Neural networks (NNs) emerge as a powerful modeling tool for Ne prediction. However, heavy manual adjustments are time consuming to determine the optimal NN structures. In this work, we propose to use neural architecture search (NAS), an automatic machine learning method, to mitigate this problem. NAS aims to find the optimal network structure through the alternate optimization of the hyperparameters and the corresponding network parameters within a pre‐defined hyperparameter search space. A total of 16‐year data from Millstone Hill incoherent scatter radar (ISR) are used for the NN models. One single‐layer NN (SLNN) model and one deep NN (DNN) model are both trained with NAS, namely SLNN‐NAS and DNN‐NAS, for Ne prediction and compared with their manually tuned counterparts (SLNN and DNN) based on previous studies. Our results show that SLNN‐NAS and DNN‐NAS outperformed SLNN and DNN, respectively. These NN predictions of Ne daily variation patterns reveal a 27‐day mid‐latitude topside Ne variation, which cannot be reasonably represented by traditional empirical models developed using monthly averages. DNN‐NAS yields the best prediction accuracy measured by quantitative metrics and rankings of daily pattern prediction, especially with an improvement in mean absolute error more than 10% compared to the SLNN model. The limited improvement of NAS is likely due to the network complexity and the limitation of fully connected NN without the time histories of input parameters.

During the main phase of geomagnetic storms, large positive ionospheric plasma density anomalies arise at middle and polar latitudes. A prominent example is the tongue of ionisation (TOI), which extends poleward from the dayside storm-enhanced density (SED) anomaly, often crossing the polar cap and streaming with the plasma convection flow into the nightside ionosphere. A fragmentation of the TOI anomaly contributes to the formation of polar plasma patches partially responsible for the scintillations of satellite positioning signals at high latitudes. To investigate this intense plasma anomaly, numerical simulations of plasma and neutral dynamics during the geomagnetic superstorm of 20 November 2003 are performed using the Thermosphere Ionosphere Electrodynamics Global Circulation Model (TIE-GCM) coupled with the statistical parameterisation of high-latitude plasma convection. The simulation results reproduce the TOI features consistently with observations of total electron content and with the results of ionospheric tomography, published previously by the authors. It is demonstrated that the fast plasma uplift, due to the electric plasma convection expanded to subauroral mid-latitudes, serves as a primary feeding mechanism for the TOI anomaly, while a complex interplay between electrodynamic and neutral wind transports is shown to contribute to the formation of a mid-latitude SED anomaly. This contrasts with published simulations of relatively smaller geomagnetic storms, where the impact of neutral dynamics on the TOI formation appears more pronounced. It is suggested that better representation of the high-latitude plasma convection during superstorms is needed. The results are discussed in the context of space weather modelling.

A severe meteorological storm system on the frontal border of cyclone Fabienne passing above central Europe was observed on 23–24 September 2018. Large meteorological systems are considered to be important sources of the wave-like variability visible/detectable through the atmosphere and even up to ionospheric heights. Significant departures from regular courses of atmospheric and ionospheric parameters were detected in all analyzed datasets through atmospheric heights. Above Europe, stratospheric temperature and wind significantly changed in coincidence with fast frontal transition (100–110 km h−1). Zonal wind at 1 and 0.1 hPa changes from the usual westward before the storm to eastward after the storm. With this change are connected changes in temperature where at 1 hPa the analyzed area is colder and at 0.1 hPa warmer. Within ionospheric parameters, we have detected significant wave-like activity occurring shortly after the cold front crossed the observational point. During the storm event, both by Digisonde DPS-4D and continuous Doppler sounding equipment, we have observed strong horizontal plasma flow shears and time-limited increase plasma flow in both the northern and western components of ionospheric drift. The vertical component of plasma flow during the storm event is smaller with respect to the corresponding values on preceding days. The analyzed event of an exceptionally fast cold front of cyclone Fabienne fell into the recovery phase of a minor–moderate geomagnetic storm observed as a negative ionospheric storm at European mid-latitudes. Hence, ionospheric observations consist both of disturbances induced by moderate geomagnetic storms and effects originating in convective activity in the troposphere. Nevertheless, taking into account a significant change in the global circulation pattern in the stratosphere, we conclude that most of the observed wave-like oscillations in the ionosphere during the night of 23–24 September can be directly attributed to the propagation of atmospheric waves launched on the frontal border (cold front) of cyclone Fabienne. The frontal system acted as an effective source of atmospheric waves propagating upward up to the ionosphere.

During minor to moderate geomagnetic storms, caused by corotating interaction regions (CIRs) at the leading edge of high-speed streams (HSSs), solar wind Alfvén waves modulated the magnetic reconnection at the dayside magnetopause. The Resolute Bay Incoherent Scatter Radars (RISR-C and RISR-N), measuring plasma parameters in the cusp and polar cap, observed ionospheric signatures of flux transfer events (FTEs) that resulted in the formation of polar cap patches. The patches were observed as they moved over the RISR, and the Canadian High-Arctic Ionospheric Network (CHAIN) ionosondes and GPS receivers. The coupling process modulated the ionospheric convection and the intensity of ionospheric currents, including the auroral electrojets. The horizontal equivalent ionospheric currents (EICs) are estimated from ground-based magnetometer data using an inversion technique. Pulses of ionospheric currents that are a source of Joule heating in the lower thermosphere launched atmospheric gravity waves, causing traveling ionospheric disturbances (TIDs) that propagated equatorward. The TIDs were observed in the SuperDual Auroral Radar Network (SuperDARN) high-frequency (HF) radar ground scatter and the detrended total electron content (TEC) measured by globally distributed Global Navigation Satellite System (GNSS) receivers.