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Equatorial Ionospheric Irregularity Detection and Analysis Using 2-D ROTI Maps and VHF Radar Images During the Upcoming Solar Maximum
(2026-01-01)
Supnithi, P.
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Myint, L. M.M.
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Tongkasem, N.
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Thanakulketsarat, T.
;
Nishioka, M.
In this work, we analyze the ionospheric irregularities at Chumphon station, Thailand, using observational data from GNSS receivers as well as VHF radar and ionosonde at Chumphon station, Thailand. The ionospheric irregularity event on 20 March 2020 and the super solar storms during 8–12 May 2024 are studied. Both instruments show traces the irregularities and interesting daytime fluctuation in total electron content over Thailand area. The statistics of ionospheric irregularities from 2020 to 2024 show that as we enter the solar maximum of the 25<sup>th</sup> solar cycle, more occurrences of ionospheric irregularities are clearly seen.
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A Bootstrapping Convolutional Neural Network Technique for Optimizing Automated Detection of Equatorial Plasma Bubbles by Optical All-Sky Imagers
(2025-06-01)
Okoh, Daniel
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Cesaroni, Claudio
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Rabiu, Babatunde
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Shiokawa, Kazuo
;
Otsuka, Yuichi
Equatorial plasma bubbles (EPBs) disrupt satellite-based communication and navigation systems, particularly in equatorial regions. Reliable detection and classification of EPBs from all-sky imager (ASI) images are essential for accurate space weather monitoring and forecasting. This study presents a novel bootstrapping convolutional neural network (CNN) approach to optimize automated EPB detection on ASI images for operational space weather monitoring applications, and overcoming challenges related to image variability and imbalanced data sets. Data used for CNN training were obtained from the optical mesosphere thermosphere imagers ASI installed at the Space Environment Research Laboratory, National Space Research and Development Agency, Abuja during the period from 2015 to 2020. Our method involved training three sub-models, and aggregating their predictions. The CNN trainings were conducted on three sub-datasets of 3,000 images each, categorized as “EPB,” “Noisy/Cloudy” or “No EPB.” Three corresponding sub-models were developed from the CNN trainings. The three sub-model classifications independently gave prediction accuracies of 98.67%, 98.33%, and 95.83% on a reserved test data set of 600 images. Ensemble models further improved the model prediction accuracies to 99.17% and 99.33% for methods based on the mean of sub-model probabilities and the mode of sub-model classifications respectively. Our results indicate that the bootstrapping CNN technique enhanced the EPB detection accuracy, providing a powerful tool for real-time space weather monitoring applications, and implications for improving operational reliability of satellite-based navigation and communication in the equatorial region.
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Multi-Instrument Analysis of Ionospheric Equatorial Plasma Bubbles over the Indian and Southeast Asian Longitudes During the 19–20 April 2024 Geomagnetic Storm
(2025-03-01)
Panda, Sampad Kumar
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Rajana, Siva Sai Kumar
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Vivek, Chiranjeevi G.
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Dabbakuti, Jyothi Ravi Kiran Kumar
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Jamir, Wangshimenla
In this study, we explored the occurrence of near-sunrise equatorial plasma bubbles (EPBs) and inhibition of dusk-time EPBs during the geomagnetic storm (SYM-Hmin= −139 nT) of 19–20 April 2024 using multi-instrument observations over the Indian and Southeast Asian longitude sectors. The initial phase of this storm commenced around 0530 UT on 19 April 2024 and did not manifest any visible alterations in the ionospheric electric fields during the main phase of the storm, which corresponded to a period between post-sunset to midnight over the study region. However, during the recovery phase of the storm, the IMF Bz suddenly flipped northward and was associated with an overshielding of the penetrating electric fields, which triggered the formation of near-sunrise EPBs. Interestingly, the persistence of EPBs was also noticed for more than three hours after the sunrise terminator. Initially, sunrise EPBs were developed in the Southeast Asian region and later drifted toward the Indian longitude region, along with the sunrise terminator. Moreover, this study suggested that the occurrence of EPBs was suppressed due to the altered storm time electric fields at the dip equatorial region across the 70–90°E longitude sector in the recovery period. This study highlighted that even moderate geomagnetic storms can generate near-sunrise EPBs in a broader longitude sector due to penetrating electric fields in overshielding conditions, which can significantly affect trans-ionospheric signals.
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Classification of Equatorial Ionospheric Irregularities Using Unsupervised Machine Learning Based on Spatiotemporal ROTI Keograms
(2025-01-01)
Mutasov, Gleb
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Supnithi, Pornchai
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Budtho, Jirapoom
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Tongkasem, Napat
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Nishioka, Michi
Equatorial ionospheric irregularities, particularly those associated with equatorial plasma bubbles (EPB), can significantly disrupt satellite navigation and communication systems. As the demand for reliable Global Navigation Satellite System (GNSS) and communication services grows, the prediction of ionospheric irregularities becomes critical. A key step in the prediction process is to identify distinct spatiotemporal patterns of irregularities, including day-to-day, longitudinal, and seasonal variations. However, with large datasets, manually classification or identification of these irregularities is a complex and challenging task. In this work, we propose unsupervised machine learning techniques to recognize and group irregularity patterns in large, unlabeled Rate of Total Electron Content (TEC) Index (ROTI) keograms. Specifically, two machine learning models: Gaussian Mixture Model and k-means clustering are employed. The ROTI keograms are constructed using GNSS data from two low-latitude receiver stations in Thailand. To reduce redundancy in the keogram images, three feature extraction techniques are applied before the clustering process. A comparative analysis is performed to determine the optimal number of clusters using these models. Based on the results, the optimal combination of feature extraction and clustering technique is determined for the proposed clustering model. The resulting k-means model with contour extractor classifies five distinct patterns of ionospheric irregularity patterns, providing valuable insights for enhancing EPB prediction models and deepening our understanding of ionospheric dynamics. Furthermore, these five irregularity patterns are analyzed in relation to space weather parameters such as the solar radio flux index (F10.7), and the geomagnetic index (Kp). The findings contribute to the development of robust prediction models, improving the reliability of satellite-based communication and navigation systems.
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Multi-Instrument Observation of the Ionospheric Irregularities and Disturbances during the 23–24 March 2023 Geomagnetic Storm
(2024-05-01)
Tahir, Afnan
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Wu, Falin
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Shah, Munawar
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Amory-Mazaudier, Christine
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Jamjareegulgarn, Punyawi
This work investigates the ionospheric response to the March 2023 geomagnetic storm over American and Asian sectors from total electron content (TEC), rate of TEC index, ionospheric heights, Swarm plasma density, radio occultation profiles of Formosat-7/Cosmic-2 (F7/C2), Fabry-Perot interferometer driven neutral winds, and E region electric field. During the storm’s main phase, post-sunset equatorial plasma bubbles (EPBs) extend to higher latitudes in the western American longitudes, showing significant longitudinal differences in the American sector. Over the Indian longitudes, suppression of post-sunset irregularities is observed, attributed to the westward prompt penetration electric field (PPEF). At the early recovery phase, the presence of post-midnight/near-sunrise EPBs till post-sunrise hours in the American sector is associated with the disturbance of dynamo-electric fields (DDEF). Additionally, a strong consistency between F7/C2 derived amplitude scintillation (S4) ≥ 0.5 and EPB occurrences is observed. Furthermore, a strong eastward electric field induced an increase in daytime TEC beyond the equatorial ionization anomaly crest in the American region, which occurred during the storm’s main phase. Both the Asian and American sectors exhibit negative ionospheric storms and inhibition of ionospheric irregularities at the recovery phase, which is dominated by the disturbance dynamo effect due to equatorward neutral winds. A slight increase in TEC in the Asian sector during the recovery phase could be explained by the combined effect of DDEF and thermospheric composition change. Overall, storm-time ionospheric variations are controlled by the combined effects of PPEF and DDEF. This study may further contribute to understanding the ionospheric responses under the influence of storm-phase and LT-dependent electric fields.
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On the solar activity dependence of midnight equatorial plasma bubbles during June solstice periods
(2021-09-01)
Ajith, K. K.
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Ram, S. Tulasi
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Li, Guo Zhu
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Yamamoto, M.
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Hozumi, K.
The occurrence of midnight Equatorial Plasma Bubbles (EPBs) during the June solstice period of the ascending phase of solar cycle 24, from 2010 to 2014, was studied using data from the 47 MHz Equatorial Atmosphere Radar (EAR) at Kototabang, Indonesia. The analysis shows that the occurrence of midnight hour EPBs was at its maximum during the low solar activity year 2010 and monotonically decreased thereafter with increasing solar activity. Details of the dependence of midnight hour EPB occurrence on solar activity were investigated using SAMI2 model simulation with a realistic input of E × B drift velocity data obtained from the CINDI-IVM onboard the C/NOFS satellite. Results obtained from term-by-term analysis of the flux tube integrated linear growth rate of RT instability indicate that the formation of a high flux tube electron content height gradient (steep vertical gradient) region at higher altitudes, due to the elevated F layer, is the key factor enhancing the growth rate of RT instability during low solar activity June solstices. Other factors are discussed in light of the relatively weak westward zonal electric field in the presence of the equatorward neutral wind and north-to-south transequatorial wind around the midnight hours of low solar activity June solstices. Also discussed are the initial seeding of RT instability by MSTIDs and how the threshold height required for EPB development varies with solar activity.

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