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Post-Sunrise Ionospheric Irregularities in Southeast Asia During the Geomagnetic Storm on 19–20 April 2024
(2025-08-01)
Abadi, Prayitno
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Muafiry, Ihsan Naufal
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Pratama, Teguh Nugraha
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Putra, Angga Yolanda
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Faturahman, Agri
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.
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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
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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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Was the Unseasonal Development of Post-Sunset Equatorial Plasma Bubbles in Southeast Asia Driven by Quasi-2-Day Planetary Waves?
(2025-03-01)
Dai, Guofeng
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Li, Guozhu
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Otsuka, Yuichi
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Hu, Lianhuan
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Sun, Wenjie
Previous studies suggest that the planetary waves in mesosphere and low thermosphere (MLT) could modulate the occurrence of equatorial plasma bubbles (EPBs) via altering post-sunset F layer height. Using simultaneous observations by Global Navigation Satellite System receiver networks, two ionosondes separated by about 10° in longitude, high frequency and very high frequency radars, we investigated the day-to-day variations of post-sunset F layer height and EPB occurrence in southeast Asia during the quasi-2-day planetary wave (QTDW) event in July 2023. The results showed that the post-sunset F layer height over Bac Lieu (9.3°N, 105.7°E) and EPB occurrence had a quasi-2-day (QTD) variation. However, such a 2 day variation of F layer height was confined in a very limited longitude, that is contradictory to the planetary scale characteristics of QTDW. We suggest that the QTD variations of post-sunset F layer height and EPB occurrence over the specific location were not necessarily due to the QTDW in MLT. The local seeding source, as characterized by satellite traces in ionosonde ionograms, could drive the small-scale longitudinal structure of F layer height and play an important role in shaping the QTD variation of EPB. The results implicate that the connection between planetary waves and the EPB occurrence over a specific location should be interpreted carefully, even if the day-to-day variation of post-sunset F layer height shows periodic behavior with planetary wave scale.
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Assessing the potential of ionosonde for forecasting post-sunset equatorial spread F: an observational experiment in Southeast Asia
(2023-12-01)
Abadi, Prayitno
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Ali Ahmad, Umar
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Otsuka, Yuichi
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Jamjareegulgarn, Punyawi
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Almahi, Alif
The occurrence of equatorial spread F (ESF) has the potential to detrimentally impact space-based technological systems. This study investigates the utility of ionosondes in forecasting the incidence of post-sunset ESF in the zonal direction, utilizing observational data obtained from four ionosondes located near the magnetic Equator in Southeast Asia. Data were collected during the equinox seasons (March–April and September–October) between 2003 and 2020. To establish a relationship between the probability of post-sunset ESF occurrence and the evening vertical plasma drift (v), a logistic regression model was employed. Post-sunset ESF occurrence is defined as the presence of ESF during the time window between 19:00 and 21:00 LT, while v is derived from the average time derivative of virtual heights during the interval from 18:30 to 19:00 LT. Results indicate that the probability of post-sunset ESF occurrence approaches zero, signifying that ESF is unlikely to develop when v is negative. Conversely, when v exceeds 30 m/s, the probability of post-sunset ESF occurrence surpasses 0.87, indicating that ESF occurs almost invariably. The likelihood of post-sunset ESF occurrence reaches 1 when v equals or exceeds 40 m/s. Utilizing this model, the study determined that a single ionosonde positioned at the Equator can effectively forecast the incidence of post-sunset ESF up to a longitudinal distance of 30° from its location. The accuracy of ionosondes in predicting post-sunset ESF occurrence above their respective locations is approximately 0.80, with a 10% decrease in accuracy when forecasting ESF occurrence at longitudinal distances of 30°. In conclusion, this study enhances our understanding of the link between the evening vertical plasma drift and the manifestation of post-sunset ESF by leveraging ionosonde data. Furthermore, it provides valuable insights into the recommended coverage range of ionosondes for predicting post-sunset ESF occurrence in the zonal direction, which can be employed to fortify regional space weather services. Graphical Abstract: [Figure not available: see fulltext.].
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Modeling Post-Sunset Equatorial Spread-F Occurrence as a Function of Evening Upward Plasma Drift Using Logistic Regression, Deduced from Ionosondes in Southeast Asia
(2022-04-01)
Abadi, Prayitno
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Ahmad, Umar Ali
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Otsuka, Yuichi
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Jamjareegulgarn, Punyawi
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Martiningrum, Dyah Rahayu
The occurrence of post-sunset equatorial spread-F (ESF) could have detrimental effects on trans-ionospheric radio wave propagation used in modern communications systems. This problem calls for a simple but robust model that accurately predicts the occurrence of post-sunset ESF. Logistic regression was implemented to model the daily occurrence of post-sunset ESF as a function of the evening upward plasma drift (v). The use of logistic regression is formalized by ŷ = 1/[1 + exp(−z)], where ŷ represents the probability of post-sunset ESF occurrence, and z is a linear function containing v. The value of v is derived from the vertical motion of the bottom side of the F-region in the evening equatorial ionosphere, which is observed by the ionosondes in Southeast Asia. Data points (938) of v and post-sunset ESF occurrence were collected in the equinox seasons from 2003 to 2016. The training set used 70% of the dataset to derive z and ŷ and the remaining 30% was used to test the performance of ŷ. The expression z = −2.25 + 0.14v was obtained from the training set, and ŷ ≥ 0.5 (v ≥ ~16.1 m/s) and ŷ < 0.5 (v < ~16.1 m/s) represented the occurrence and non-occurrence of ESF, respectively, with an accuracy of ~0.8 and a true skill score (TSS) of ~0.6. Similarly, in the testing set, ŷ shows an accuracy of ~0.8 and a TSS of ~0.6. Further analysis suggested that the performance of the z-function can be reliable in the daily F<inf>10.7</inf> levels ranging from 60 to 140 solar flux units. The z-function implemented in the logistic regression (ŷ) found in this study is a novel technique to predict the post-sunset ESF occurrence. The performance consistency between the training set and the testing set concludes that the z-function and the ŷ values of the proposed model could be a simple and robust mathematical model for daily nowcasting the occurrence or non-occurrence of post-sunset ESFs.
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Detecting Equatorial Plasma Bubbles on All-Sky Imager Images Using Convolutional Neural Network
(2022-01-01)
Srisamoodkham, Worachai
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Shiokawa, Kazuo
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Otsuka, Yuichi
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Ansari, Kutubuddin
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Jamjareegulgarn, Punyawi
This paper proposes initially to apply convolutional neural network (CNN) for detecting the equatorial plasma bubbles on the ASI images. The considered CNN model is the YOLO v3 tiny model under a deep learning API (Keras), running on top of the machine learning platform (TensorFlow). Our program for EPB detection is written in Python that is extended easily to combine into a space weather web site for detecting and notifying EPBs in our next step. The results show that the YOLO v3-based CNN can detect the EPBs in ASI images with different intensities obtained from many countries. The threshold is tested and selected to be 0.40 suitably for detecting the anomaly (EPB existence). The maximum anomalous value is selected to decide the EPB occurrence.
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Total electron content observations by dense regional and worldwide international networks of GNSS
(2018-06-01)
Tsugawa, Takuya
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Nishioka, Michi
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Ishii, Mamoru
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Hozumi, Kornyanat
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Saito, Susumu
Two-dimensional ionospheric total electron content (TEC) maps have been derived from ground-based Global Navigation Satellite System (GNSS) receiver networks and applied to studies of various ionospheric disturbances since the mid-1990s. For the purpose of monitoring and researching ionospheric conditions and ionospheric space weather phenomena, we have developed TEC maps of areas over Japan using the dense GNSS network, GNSS Earth Observation NETwork (GEONET), which consists of about 1300 stations and is operated by the Geospatial Information Authority of Japan (GSI). Currently, we are providing high-resolution, two-dimensional maps of absolute TEC, detrended TEC, rate of TEC change index (ROTI), and loss-of-lock on GPS signal over Japan on a real-time basis. Such high-resolution TEC maps using dense GNSS receiver networks are one of the most effective ways to observe, on a scale of several 100 km to 1000 km, ionospheric variations caused by traveling ionospheric disturbances and/or equatorial plasma bubbles, which can degrade single-frequency and differential GNSS positioning/navigation. We have collected all the available GNSS receiver data in the world to expand the TEC observation area. Currently, however, dense GNSS receiver networks are available in only limited areas, such as Japan, North America, and Europe. To expand the two-dimensional TEC observation with high resolution, we have conducted the Dense Regional and Worldwide International GNSS TEC observation (DRAWING-TEC) project, which is engaged in three activities: (1) standardizing GNSS-TEC data, (2) developing a new high-resolution TEC mapping technique, and (3) sharing the standardized TEC data or the information of GNSS receiver network. We have developed a new standardized TEC format, GNSS-TEC EXchange (GTEX), which is included in the Formatted Tables of ITU-R SG 3 Data-banks related to Recommendation ITU-R P.311. Sharing the GTEX TEC data would be easier than sharing the GPS/GNSS data among those in the international ionospheric researcher community. The DRAWING-TEC project would promote studies of medium-scale ionospheric variations and their effect on GNSS.
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Detection of ruptures of Andaman fault segments in the 2004 great Sumatra earthquake with coseismic ionospheric disturbances
(2006-09-04)
Heki, Kosuke
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Otsuka, Yuichi
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Choosakul, Nithiwatthn
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Hemmakorn, Narong
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Komolmis, Tharadol
We Near-field coseismic perturbations of ionospheric total electron content (TEC), caused by direct acoustic waves from focal regions, can be observed with Global Positioning System (GPS). They appear 10-15 min after the earthquake with typical periods of ∼4-5 min and propagate as fast as ∼1 km/s toward directions allowed by ambient geomagnetic fields. Ionospheric disturbance, associated with the 2004 December 26 great Sumatra-Andaman earthquake, was recorded with nine continuous GPS receiving stations in Indonesia and Thailand. Here we explore the possibility to constrain the rupture process of the earthquake with the observed ionospheric disturbances. We assumed linearly distributed point sources along the zone of coseismic uplift extending ∼1300 km from Sumatra to the Andaman Islands that excited acoustic waves sequentially as the rupture propagate northward by 2.5 km/s. TEC variations for several satellite-receiver pairs were synthesized by simulating the propagation of acoustic waves from the ground to the ionosphere and by integrating the TEC perturbations at intersections of line of sights and the ray paths. The TEC perturbations from individual point sources were combined using realistic ratios, and the total disturbances were compared with the observed signals. Prescribed ratios based on geodeticatly inferred coseismic uplifts reproduced the observed signals fairly well. Similar calculation using a rupture propagation speed of 1.7 km/s degraded the fit. Suppression of acoustic waves from the segments north of the Nicobar Islands also resulted in a poor fit, which suggests that ruptures in the northern half of the fault were slow enough to be overlooked in short-period seismograms but fast enough to excite atmospheric acoustic waves. Coseismic ionospheric disturbance could serve as a new indicator of faulting sensitive to ruptures with timescale up to 4-5 min. Copyright 2006 by the American Geophysical Union.

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