Observations of equatorial plasma bubbles using broadcast VHF radio waves

Nakata, Hiroaki; Nagashima, I.; Sakata, Kumiko; Otsuka, Yuichi; Akaike, Y.; Takano, Toshiaki; Shimakura, S.; Shiokawa, K.; Ogawa, T.

doi:10.1029/2005gl023243

Cited by 4 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…VHF radars operate in the VHF band between 30 and 300 MHz and they can observe ionospheric irregularities such as EPBs by transmitting a radar signal upward and receiving the signal after it has been scattered by the irregularities, Nakata et al (2005). The equatorial atmosphere radar, also known as the EAR, is a specialized type of VHF radar that was developed for the purpose of researching the equatorial ionosphere and has been put to extensive use in researching EPBs, Pavan et al (2017).…”

Section: Introductionmentioning

confidence: 99%

Classification of the equatorial plasma bubbles using convolutional neural network and support vector machine techniques

Thanakulketsarat,

Supnithi,

Myint

et al. 2023

Earth Planets Space

View full text Add to dashboard Cite

Equatorial plasma bubble (EPB) is a phenomenon characterized by depletions in ionospheric plasma density being formed during post-sunset hours. The ionospheric irregularities can lead to disruptions in trans-ionospheric radio systems, navigation systems and satellite communications. Real-time detection and classification of EPBs are crucial for the space weather community. Since 2020, the Prachomklao radar station, a very high frequency (VHF) radar station, has been installed at Chumphon station (Geographic: 10.72° N, 99.73° E and Geomagnetic: 1.33° N) and started to produce radar images ever since. In this work, we propose two real-time plasma bubble detection systems based on support vector machine techniques. Two designs are made with the convolutional neural network (CNN) and singular value decomposition (SVD) used for feature extraction, the connected to the support vector machine (SVM) for EPB classification. The proposed models are trained using quick look (QL) plot images from the VHF radar system at the Chumphon station, Thailand, in 2017. The experimental results show that the combined CNN-SVM model, using the RBF kernel, achieves the highest accuracy of 93.08% while the model using the polynomial kernel achieved an accuracy of 92.14%. On the other hand, the combined SVD-SVM models yield the accuracies of 88.37% and 85.00% for RBF and polynomial kernels of SVM, respectively. Graphical Abstract

show abstract

Section: Introductionmentioning

confidence: 99%

Classification of the equatorial plasma bubbles using convolutional neural network and support vector machine techniques

Thanakulketsarat,

Supnithi,

Myint

et al. 2023

Earth Planets Space

View full text Add to dashboard Cite

show abstract

Evolution of Equatorial Plasma Bubbles Group Simultaneously Observed by Multi-instruments over China

Wu¹,

Xu²,

Yuan³

2023

kjkxxb

View full text Add to dashboard Cite

Simultaneous observations of equatorial plasma bubbles with an all-sky airglow imager and a HF Doppler sounding system in Taiwan

Sejima,

Hosokawa,

Nakata

et al. 2023

Earth Planets Space

View full text Add to dashboard Cite

High-Frequency Doppler (HFD) sounders at low-latitudes often detect characteristic oblique spreading Doppler traces in the spectrogram, known as Oblique Spread Structure (OSS). OSS has been expected to be generated by the dispersion of radio wave reflection due to equatorial plasma bubbles (EPBs). However, it has not yet been confirmed whether OSS is surely a manifestation of EPB by conducting simultaneous observations of EPB and OSS with different observational techniques. Additionally, it remains unclear what kinds of properties of EPB are reflected in the fine structure of OSS. In this study, we investigated three cases of OSSs and EPBs simultaneously observed by a HFD sounding system and an all-sky airglow imager in Taiwan. For the three cases presented here, the timing of OSS occurrence in the HFD data well coincided with that of the EPB appearance in the airglow data. The frequency shift of OSS is quantitatively explained assuming a radio wave reflection at 250–300 km altitudes. These results strongly indicate that OSS is formed by electron density variations at F-region altitudes accompanying EPB; thus, OSS is a manifestation of EPB in the HFD observations. Furthermore, it was suggested that the fine structure of OSS reflected the branching structure of EPB when the multiple branches of EPB reached the intermediate reflection point of the HFD observation. The detection of EPB occurrence and its fine structure using HFD observation enables monitoring of EPB regardless of weather conditions, which will contribute to monitoring the space weather impact of EPBs, for example, on GNSS navigation, in a wide area. Graphical Abstract

show abstract

Observations of equatorial plasma bubbles using broadcast VHF radio waves

Cited by 4 publications

References 14 publications

Classification of the equatorial plasma bubbles using convolutional neural network and support vector machine techniques

Classification of the equatorial plasma bubbles using convolutional neural network and support vector machine techniques

Evolution of Equatorial Plasma Bubbles Group Simultaneously Observed by Multi-instruments over China

Simultaneous observations of equatorial plasma bubbles with an all-sky airglow imager and a HF Doppler sounding system in Taiwan

Contact Info

Product

Resources

About