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Author: search.filters.author.Li, GuozhuSubject: search.filters.subject.equatorial plasma bubble

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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
    ;
    Muafiry, Ihsan Naufal
    ;
    Pratama, Teguh Nugraha
    ;
    Putra, Angga Yolanda
    ;
    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 Novel Short-Term Prediction Model for Regional Equatorial Plasma Bubble Irregularities in East and Southeast Asia
    (2025-02-01)
    Zhao, Xiukuan
    ;
    Li, Guozhu
    ;
    Xie, Haiyong
    ;
    Hu, Lianhuan
    ;
    Sun, Wenjie
    Equatorial plasma bubble (EPB) irregularities can significantly impact satellite-based communication and navigation systems. Accurate prediction of EPB occurrence is essential for mitigating these impacts. Using the GNSS receiver network and ionosonde data from East and Southeast Asia during 2010–2021, and the rate of TEC change index to characterize the occurrence of EPB irregularities, we developed a novel Spatio-Temporal deep learning model for regional EPB irregularities short-term Prediction (STEP). The model integrates the convolutional neural network and long short-term memory (LSTM) network, together with attention mechanisms, to capture both spatial and temporal features of regional ionospheric irregularities. The results show that for 5-min forecast, the STEP model achieves a root mean square error (RMSE) of 0.062 TECU/min and an R<sup>2</sup> of 0.818, reducing RMSE by 19.48% compared to LSTM and 27.06% compared to gated recurrent unit model. For 60-min prediction, the STEP model can still achieve reasonable accuracy with an RMSE of 0.110 TECU/min and an R<sup>2</sup> of 0.482, showing significant improvement over traditional models. The equatorial F layer height and regional TEC fluctuations were identified as the most critical factors for predicting the generation and duration of EPB irregularities, respectively. The spatial and temporal distributions of EPB irregularities, including their latitudinal variation and delayed onset after sunset, and the occurrence across different days in East and Southeast Asia, were well predicted by the STEP. It is expected that the STEP model would provide a valuable tool for improving the resilience of GNSS against ionospheric scintillations induced by EPB irregularities.