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Plasma blob is generally a low‐latitude phenomenon occurring at the poleward edge of equatorial plasma bubble (EPB) during post‐sunset periods. Here we report a case of midlatitude ionospheric plasma blob‐like structures occurring along with super EPBs over East Asia around sunrise during the May 2024 great geomagnetic storm. Interestingly, the blob‐like structures appeared at both the poleward and westward edges of EPBs, reached up to 40°N magnetic latitudes, and migrated westward several thousand kilometers together with the bubble. The total electron content (TEC) inside the blob‐like structures was enhanced by ∼50 TEC units relative to the ambient ionosphere. The blob‐like structure at the EPB poleward edge could be partly linked with field‐aligned plasma accumulation due to poleward development of bubble. For the blob‐like structure at the EPB west side, one possible mechanism is that it was formed and enhanced accompanying the bubble evolution and westward drift. Plain Language Summary: Accompanying the generation of equatorial plasma bubble (EPB), an extra structure with plasma density enhancement may occur. The density‐enhanced structure is known as plasma blob. Generally, plasma blobs mainly appear at the poleward edge of EPB, being low‐latitude phenomena occurring at 10–20° magnetic latitudes. Whereas previous simulations showed that plasma blobs could appear at the east/west side of EPBs, there were few observational evidences and the driving mechanism is unclear. In this study, midlatitude plasma blob‐like structures occurring up to 40°N magnetic latitude was observed along with super EPBs during magnetic storm. Different from most blobs appearing at the EPB poleward edge, the blob‐like structures in the present study appeared at both the EPB poleward and westward edges. By using ground‐based observations from GNSS receiver networks and in‐situ measurements onboard spacecraft, the morphology and evolution of the super plasma blob‐like structures are visualized. Potential mechanisms responsible for their generation are investigated. The results highlight the coexistence of large‐scale plasma depletion and blob structures and their complex evolution with longitude and latitude, and have implications for better understanding the sudden changes of plasma density in time and altitude observed by radar. Key Points: Super plasma blob‐like structures occurred up to 40°N MLat along with equatorial plasma bubbles near sunrise during storm timeThe blob‐like structures mainly occurred at the bubble poleward and westward edges and migrated westward along with the bubbleThe poleward development and evolution of the bubble could contribute to the formation of super blob‐like structures [ABSTRACT FROM AUTHOR]

This study investigated the latitudinal variations of post‐sunset enhancements in the ionospheric electron density during the geomagnetic quiet period in May 2021 with a combination of high‐precision ionospheric parameters obtained from four ionosondes, Beidou geostationary satellite (BD‐GEO) receiver network and Sanya incoherent scatter radar (SYISR). We identified four categories of post‐sunset enhancement phenomena (Types 1–4), each with unique spatial and temporal evolutions, yet uniformly accompanied by a decrease in hmF2. Measurements of plasma drift vector velocities from SYISR and hmF2 gradients across various latitudes provided pivotal insights, confirming that the ionospheric post‐sunset enhancements can result from downward plasma motion due to westward electric field, downward field‐aligned drift, or a combination of both. For Type 1, dominated by field‐aligned drift, plasma density enhancements not only intensify at low latitudes but may also extend to mid‐latitudes, exhibiting a distinct temporal delay with increasing latitude. In contrast, Type 4, primarily driven by the westward electric field, is characterized by modest increases in plasma density confined to localized low‐latitude regions, with no observable latitudinal time delay in the peak of enhancements. Types 2 and 3, which are subject to the combined influence of the westward electric field and field‐aligned drift, exhibit plasma density increases at certain low‐latitude areas, with Type 2 presenting a delayed pattern and Type 3 showing none with rising latitude. Meanwhile, neutral winds can partially account for the observed post‐sunset enhancement from low to middle latitudes. These findings offer new insights into the factors influencing ionospheric behavior after sunset. Key Points: Four types of distinctive latitudinal variations of post‐sunset enhancements were identified with multiple data sets during the quiet periodAccompanying the increase in the electron density at sunset, the decrease in hmF2 is favorable for the formation of post‐sunset enhancementDownward field‐aligned drift and westward electric field govern the spatial scale of post‐sunset enhancements at low and middle latitudes [ABSTRACT FROM AUTHOR]

The G‐condition (NmF2 ≤ NmF1) was observed by ground‐based ionosondes at Mohe and Beijing during the geomagnetic storm occurred on 23 and 24 April 2023. We studied exospheric temperature (Tex) responses during the G‐condition. Tex was derived from electron density (Ne) profiles (∼150–200 km) by the method proposed by Li et al. (2023, https://doi.org/10.1029/2022ja030988). The retrieved Tex showed obvious enhancements, with relative deviation of ∼10%–35% and ∼3%–20% at Mohe and Beijing, respectively. Additionally, chemical reaction rate increased by ∼15%–100% and ∼13%–30%, and O/N2 decreased by ∼17%–35% and ∼23%–30% at Mohe and Beijing, respectively. Under photochemical equilibrium assumption, peak Ne is inversely proportional to chemical reaction rate and proportional to O/N2. Increased chemical reaction rate and decreased O/N2 indicate a decrease in peak Ne. Compared to the increased Tex, the relative enhancement in Tex is more significantly associated with the G‐condition, with relative deviation above ∼10% during the G‐condition. Plain Language Summary: Normally, the peak Ne in the F2 layer (NmF2) is the largest in the full Ne profile. G‐conditions are special events in ionospheric observations, when NmF2 is smaller than or equal to NmF1 (i.e., NmF2 ≤ NmF1). Due to shielding effect of the F1 layer, no information above hmF1 can be obtained from ground‐based ionosondes, and Ne peak height is typically below 200 km. In previous works, incoherent scatter radar (ISR) observations are usually used to extract thermospheric parameters (Tex, neutral composition and thermospheric wind). In this paper, ground‐based ionosonde observations (∼150–200 km) at Mohe and Beijing prior to, during and after the G‐condition (from 22 to 26 April 2023) were selected to derive Tex using the method proposed by Li et al. (2023, https://doi.org/10.1029/2022ja030988). Furthermore, corresponding neutral temperature (Tn) and densities were further calculated by replacing the Tex module in the NRLMSISE‐00 model with the retrieved Tex. In our analysis, the retrieved Tex and chemical reaction rate showed significant enhancements and O/N2 showed obvious decrease compared to quiet reference days. This is consistent with the analysis of the mechanism of G‐conditions formation in previous studies. Key Points: The G‐condition (NmF2 ≤ NmF1) was observed by ground‐based ionosondes at Mohe and Beijing during the G4 storm on 24 April 2023Relative enhancements in Tex during the G‐condition were greater than that in other periods, with relative deviation above ∼10%Enhanced Tex with corresponding increased chemical reaction rate and decreased O/N2 collectively contributed to a decrease in Ne [ABSTRACT FROM AUTHOR]

Applying deep learning to high-precision ionospheric parameter prediction is a significant and growing field within the realm of space weather research. This paper proposes an improved model, Mixed Convolutional Neural Network (CNN)—Bidirectional Long Short-Term Memory (BiLSTM), for predicting the Total Electron Content (TEC) in China. This model was trained using the longest available Global Ionospheric Maps (GIM)-TEC from 1998 to 2023 in China, and underwent an interpretability analysis and accuracy evaluation. The results indicate that historical TEC maps play the most critical role, followed by Kp, ap, AE, F10.7, and time factor. The contributions of Dst and Disturbance Index (DI) to improving accuracy are relatively small but still essential. In long-term predictions, the contributions of the geomagnetic index, solar activity index, and time factor are higher. In addition, the model performs well in short-term predictions, accurately capturing the occurrence, evolution, and classification of ionospheric storms. However, as the predicted length increases, the accuracy gradually decreases, and some erroneous predictions may occur. The northeast region exhibits lower accuracy but a higher F1 score, which may be attributed to the frequency of ionospheric storm occurrences in different locations. Overall, the model effectively predicts the trends and evolution processes of ionospheric storms. [ABSTRACT FROM AUTHOR]

Low latitude ionosphere experiences complex dynamical and electrodynamical processes, which make the spatiotemporal variations of the corresponding electron density complicated and therefore influence trans‐ionosphere radio communications. The monitoring of low latitude dynamical drivers, such as neutral wind and ionospheric electric field, is essential for both dynamic mechanism investigations and applications. The Sanya Incoherent Scatter Radar Tristatic System (SYISR‐TS) was proposed with the main objective of low latitude ionospheric monitoring and investigation and has been successfully developed over the past decade. The system consists of the Sanya (18.3°N, 109.6°E) trans‐receiving main station with key parameters of ∼1,600 m2 antenna aperture, >4 MW peak power, <120 K system noise temperature, and ∼46 dBi normal gain, and Danzhou (19.5°N, 109.1°E) and Wenchang (19.6°N, 110.8°E) receiving only stations with key parameters of ∼790 m2 antenna aperture, <130 K system noise temperature, and ∼43 dBi normal gain. Three stations form a quasi‐equilateral triangle at Hainan Island and use Global Navigation Satellite System satellite common view technique to achieve the time synchronization with the uncertainty of the timing and time synchronization less than 50 and 10 ns, respectively. Initial collaborative satellite tracking and ionospheric common volume experiments among three stations have confirmed the detection ability of SYISR‐TS and the feasibility of achieving its scientific goals in the future. Plain Language Summary: Ionosphere is the ionized part (electrons and ions) of upper atmosphere around 60–1,000 km altitude. In the ionosphere, the generation and movement of electrons and ions are jointly determined by the solar radiation, photo‐chemistry, winds and electric fields. Monitoring the density of electrons, and winds and electric fields as well, is important for understanding and predicting the status of ionosphere. Among numerous ionospheric detection methods, Incoherent Scatter Radar (ISR) plays an important role due to its profiling multiple parameters capability. In this paper, we will describe the technical details and initial experiments of the newly built Sanya Incoherent Scatter Radar Tristatic System. It is also the world first tristatic ISR system using phased array technology, which can switch the beam direction quickly therefore increase the time resolution of measurements significantly. Key Points: Sanya Incoherent Scatter Radar Tristatic System (SYISR‐TS) is the world first completed phased array based tristatic ISR systemSYISR‐TS includes 1 trans‐receiving and 2 remote receiving stations and uses Global Navigation Satellite System satellite common view technique to achieve synchronizationInitial collaborative experiments among three stations have confirmed the detection ability of SYISR‐TS [ABSTRACT FROM AUTHOR]

In this study, we offer an extensive examination of the F‐region ionospheric disturbances during the May 2024 superstorm, focusing primarily on the middle‐low latitude regions of East Asia. Our analysis is grounded in a wealth of data sources including Total Electron Content (TEC), ionospheric parameters NmF2 and hmF2, Electron Density Profile (EDP) retrieved from Radio Occultation (RO) data, and ∑[O]/[N2] from the Global Ultraviolet Imager (GUVI), among others, complemented by model simulations. The observed negative ionospheric storm effect, characterized by a significant and long‐lasting reduction in electron density across the entire China, commenced immediately following the sudden storm commencement (SSC) on 10 May and continued through the main and early recovery phase of the storm on 11 May. On 11–12 May, positive ionospheric storm impacts were initially observed in a restricted geographical area from the post‐midnight to sunrise, first manifesting over the eastern regions of China and then shifting to the central regions. Subsequently, a pronounced negative storm effect persisted throughout the later stages of recovery phase. In contrast, the western regions of China experienced a positive storm effect on 12 May followed by a comparatively mild negative storm phase. This persistent extensive zonal gradient in electron density across the East Asian region resembles the scenarios depicted in prior superstorms attributed to the thermospheric circulation patterns. The disparity in the ionospheric response from east to west in this area is probably a common feature during superstorms, potentially resulting from an arch‐shaped structure of elevated ∑[O]/[N2]. Key Points: The superstorm in May 2024 led to a significant and persistent decrease in electron density at middle‐low latitude over Eastern ChinaPositive ionospheric effects spread from post‐midnight eastern China to central China, with western China seeing a weaker positive stormThe disparity in ionospheric response from east to west mainly arose from an arch‐shaped structure of elevated ∑[O]/[N2] [ABSTRACT FROM AUTHOR]

The application of deep learning in high‐precision ionospheric parameter prediction has become one of the focus in space weather research. In this study, an improved model called Mixed Convolutional Neural Networks (CNN)—Bi‐Long Short Term Memory is proposed for predicting future ionospheric Total Electron Content (TEC). The model is trained using the longest available (25 years) Global Ionospheric Maps‐TEC and evaluated the accuracy of ionospheric storm predictions. The results indicate that using historical TEC in the solar‐geographical reference frame as input driving data achieves higher prediction accuracy compared to that in the geocentric coordinate system. Additionally, by comparing different input parameters, it is found that incorporating the Kp, ap, and Dst indices as inputs to the model effectively improves its accuracy, especially in long‐term forecasting where R2 increased by 3.49% and Root Mean Square Error decreased by 13.48%. Compared with BiLSTM‐Deep Neural Networks (DNN) and CNN‐BiLSTM, the Mixed CNN‐BiLSTM model has the highest prediction accuracy. It suggests that the utilization of CNN modules for processing spatial information, along with the incorporation of DNN modules to incorporate geomagnetic indices for result correction. Moreover, in short‐term predictions, the model accurately forecasts the evolution process of ionospheric storms. When extending the predicted length, although there are cases of prediction errors, the model still captures the entire process of ionospheric storms. Furthermore, the predicted results are significantly influenced by longitude, magnetic latitude, and local time. Plain Language Summary: To address some limitations in the research on ionospheric storm prediction using deep learning, this paper developed a model called Mixed Convolutional Neural Networks ‐ Bi‐Long Short‐Term Memory that considers both temporal and spatial information to predict Total Electron Content (TEC). Subsequently, the predicted TEC is used to identify the evolution of ionospheric storms. The data set used spans from 1998 to 2023 and consists of global TEC measurements. The evaluation of the model's performance was conducted using selected data samples. The evaluation reveals that using data in the solar‐geographical reference frame, along with geomagnetic indices, enhances the prediction accuracy of the model. Additionally, the model exhibits higher prediction accuracy in low latitude and mid latitude regions compared to high latitude regions, and higher accuracy during daytime compared to nighttime. Meanwhile, the influence of geomagnetic index on long‐term prediction is more significant. Key Points: Development of an improved deep learning model for future Total Electron Content predictionThe model enhances accuracy in solar‐geographical reference frame by incorporating Kp, ap, Dst indicesThe evaluation confirmed accurate prediction of ionospheric storm occurrence, disturbance amplitude, and evolution process by the model [ABSTRACT FROM AUTHOR]

An unseasonal equatorial plasma bubble (EPB) event occurred in the East/Southeast Asian sector during the geomagnetic storm on 1 December 2023, causing strong amplitude scintillations from equatorial to middle latitudes. Based on the observations from multiple instruments over a large latitudinal and longitudinal region, the spatial features of the super EPB were investigated. The EPB developed vertically at a fast rising speed ∼470 m/s over the magnetic equator and extended to a very high middle latitude more than 40°N, despite that the storm intensity was not very strong with the minimum SYM‐H index −132 nT. In the zonal direction, the super EPB covered over a specific region ∼95–140°E, where the local sunset roughly coincided with southward turning of interplanetary magnetic field (IMF) Bz component. Before the onset of the super EPB, significant upward plasma drift up to ∼110 m/s was observed over the magnetic equator, which could amplify the growth rate of Rayleigh‐Taylor instability and lead to the generation of the super EPB. The significant drift was likely caused by eastward penetration electric field (PEF) due to sharp southward turning of IMF Bz. The local time of storm onset and duration of IMF Bz southward turning during the storm main phase may partly determine the onset region and zonal coverage of the EPB. Plain Language Summary: Previous studies have reported unexpected generation and development of equatorial plasma bubbles (EPBs) during geomagnetic storms, with different EPB morphology varied from case to case. It is important to figure out potential factors controlling the occurrence or absence of EPBs over a specific region during geomagnetic storms, their latitudinal and longitudinal development. In this study, super EPB extending to middle latitudes more than 40°N was observed over a limited zonal region ∼95–140°E during the main phase of the 1 December 2023 geomagnetic storm. Significant upward plasma drift was observed before the onset of the EPB, which coincided with sharp southward turning of interplanetary magnetic field (IMF) Bz that could induce remarkable penetration electric field. Based on the combination of multiple kinds of observations over a large region, the potential factors controlling the generation and development of the EPB over latitude and longitude were investigated. It was suggested that the onset time, duration and intensity of IMF Bz southward turning during the main phase of geomagnetic storm play an important role in controlling the EPB spatial features, including the onset region, zonal coverage and latitudinal extension. Key Points: Ionospheric super bubble with fast rising speed occurred during storm time, extended to more than 40°N and caused strong midlatitude scintillationThe super bubble occurred over a confined longitudinal sector ∼95–140°E where the local sunset roughly coincided with interplanetary magnetic field (IMF) Bz southward turningSignificant upward plasma drift due to penetration electric field (PEF) could be responsible for the generation of the super bubbles [ABSTRACT FROM AUTHOR]

In this study, multiple instrumental observations including Global Navigation Satellite System total electron content (TEC), plasma drift velocity measured by Sanya (18.3°N, 109.6°E, dip latitude 12.6°N) Incoherent Scatter Radar (SYISR) and F2‐layer peak electron density (NmF2) and peak height (hmF2) from ionosonde and SYISR have been used to investigate ionospheric responses during a minor yet highly geo‐effective geomagnetic storm on 26–27 May 2021. Our findings revealed a significant time delay in the post‐sunset plasma density enhancement peak across different latitudes over East Asia, that is, the lower the geographic latitude, the earlier the peak appeared. The plasma density enhancement was accompanied by a decrease in hmF2 prior to NmF2 peak around sunset. The newly built SYISR measurements around sunset verified that the field‐aligned drift decreased the ionosphere with a notable time delay at latitude, beneficial to electron density enhancements at lower altitudes within the 16–30°N latitudinal band but a small TEC change. While at 30–50°N, it is possible that the competition between storm‐induced equatorward winds and downward field‐aligned drift depressed hmF2 decline and the buildup increased both NmF2 and TEC. The ICON observations suggested that the meridional wind during this minor storm event modulated the direction of plasma transport near sunset, playing a dominant role in post‐sunset plasma density enhancement from low to middle latitudes. These results provide fresh insight into the electrodynamic mechanisms of post‐sunset enhancements at middle and low latitudes over East Asia, and also enhance our understanding of the intricate behaviors within the ionosphere‐thermosphere system in response to a minor storm. Key Points: The local time of post‐sunset plasma density enhancement peak had a notable time delay with increasing latitude during a minor stormThe plasma drift during postsunset hours observed by Sanya incoherent scatter radar exhibited strong response to the minor geomagnetic stormThe meridional winds changing from equatorward to poleward explained the post‐sunset enhancement from low to middle latitudes [ABSTRACT FROM AUTHOR]

Using Global Navigation Satellite Systems (GNSS) observation data for developing a high-precision ionospheric Total Electron Content (TEC) model is one of the essential subjects in ionospheric physics research and the application of satellite navigation correction. In this study, we integrate the Empirical Orthogonal Function (EOF) method with the TEC data provided by the Center for Orbit Determination in Europe (CODE), and observed by the dense GNSS receivers operated by the Crustal Movement Observation Network of China (CMONOC) to construct a regional ionospheric TEC model over China. The EOF analysis of CODE TEC in China from 1998 to 2010 shows that the first-order EOF component accounts for 90.3813% of the total variation of the ionospheric TEC in China. Meanwhile, the average value of CODE TEC is consistent with the spatial and temporal distribution characteristics of the first-order EOF base function, which mainly reflects the latitude and diurnal variations of TEC in China. The first-order coefficient after EOF decomposition shows an obvious 11-year period and semi-annual variations. The maximum amplitude of semi-annual variation mainly appears in March and October, which is closely associated with the variation in geographical longitude, the semi-annual change of the low-latitude electric field, and the ionospheric fountain effect. The second-order coefficient has an evident annual variation, the minimum amplitude mainly occurs in March, August, and September, and the amplitude values in the high solar activity years are more significant than those in the low solar activity years. The third-order coefficient mainly shows the characteristics of annual variation, and the fourth-order coefficient shows the noticeable semi-annual and annual variations. The third and fourth-order coefficients are both modulated by the solar activity index F10.7. The ionospheric TEC model in China, driven by CMONOC real-time GNSS observation data, can better reflect the latitude, local time and seasonal variation characteristics of ionospheric TEC over China. In particular, it can clearly show the spring and autumn asymmetry of ionospheric TEC in the low latitudes. The root mean square error of the absolute error between the model and the actual observation is mainly distributed around 2.45 TECU (1 TECU = 1016 electrons/m2). The values of the TEC model constructed in this study are closer to the actual observed values than those of the CODE TEC in China. [ABSTRACT FROM AUTHOR]