A machine learning approach for estimating the drift velocities of equatorial plasma bubbles based on All-Sky Imager and GNSS observations

被引:0
|
作者
Department of Space Environment, Institute of Basic and Applied Sciences, Egypt-Japan University of Science and Technology , New Borg El-Arab City, Alexandria [1 ]
21934, Egypt
不详 [2 ]
819-0395, Japan
不详 [3 ]
21934, Egypt
机构
来源
Adv. Space Res. | 2024年 / 11卷 / 6047-6064期
基金
美国海洋和大气管理局; 日本学术振兴会; 美国国家航空航天局;
关键词
Couplings - F region - Frequency estimation - Ionospheric measurement - Plasma density - Plasma diagnostics - Tropics;
D O I
10.1016/j.asr.2024.08.067
中图分类号
学科分类号
摘要
Equatorial Plasma Bubbles (EPBs) are zones characterized by fluctuations in plasma densities which form in the low-latitude ionosphere primarily during the post-sunset. They subject radio signals to amplitude and phase variabilities, affecting the functioning of technological systems that utilize the Global Navigation Satellite Systems (GNSS) signals for navigation. Thus, understanding EPB occurrence patterns and morphological features is vital for mitigating their effects. In this work, we employed two GNSS receivers and an All-Sky Imager (ASI) to conduct simultaneous observations on the morphology of EPBs over Brazil. The main objectives of the study were (1) to develop a Random Forest (RF) machine-learning model to estimate and predict the zonal drift velocities of EPBs, and (2) to compare the model predictions with actual EPB drifts inferred from the two instruments, as well as zonal neutral wind speeds obtained from the Horizontal Wind Model (HWM-14). In the model development, we utilized reliable EPB drift measurements made during geomagnetically quiet days between 2013 and 2017 in Brazil. The model predicted the velocities based on parameters including the day of the year, universal time, critical frequency of the F2 layer (foF2), solar and interplanetary indices. The correlation coefficients of 0.98 and 0.96 and RMSE values of 10.61 m/s and 10.06 m/s were obtained upon training and validation correspondingly. We evaluated the accuracy of the model in predicting EPB drifts on two geomagnetically quiet nights where an average correlation coefficient of 0.89 and an RMSE of 15.74 m/s were obtained. The predicted drifts, the zonal neutral wind velocities, and the GNSS and ASI velocity measurements were put into context for validation purposes. Overall, the velocities were comparable and ranged between ∼100 m/s and ∼30 m/s from the hours of 00 UT to 05 UT. The results confirmed the accuracy and applicability of the model, revealing the ionosphere-thermosphere coupling influence on the nocturnal propagation of EPBs under the full activation of the F region dynamo. © 2024 COSPAR
引用
收藏
页码:6047 / 6064
相关论文
共 46 条
  • [31] Comment on "Substorm triggering by new plasma intrusion: THEMIS all-sky imager observations" by Y. Nishimura et al.
    Frey, Harald U.
    JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS, 2010, 115
  • [32] Combining Deep Learning and Physical Models: A Benchmark Study on All-Sky Imager-Based Solar Nowcasting Systems
    Fabel, Yann
    Nouri, Bijan
    Wilbert, Stefan
    Blum, Niklas
    Schnaus, Dominik
    Triebel, Rudolph
    Zarzalejo, Luis F.
    Ugedo, Enrique
    Kowalski, Julia
    Pitz-Paal, Robert
    SOLAR RRL, 2024, 8 (04)
  • [33] Coordinated airglow observations between IMAP/VISI and a ground-based all-sky imager on concentric gravity wave in the mesopause
    Perwitasari, S.
    Sakanoi, T.
    Yamazaki, A.
    Otsuka, Y.
    Hozumi, Y.
    Akiya, Y.
    Saito, A.
    Shiokawa, K.
    Kawamura, S.
    JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS, 2015, 120 (11) : 9706 - 9721
  • [34] Coordinated THEMIS spacecraft and all-sky imager observations of interplanetary shock effects on plasma sheet flow bursts, poleward boundary intensifications, and streamers
    Yue, Chao
    Nishimura, Yukitoshi
    Lyons, Larry R.
    Angelopoulos, Vassilis
    Donovan, Eric F.
    Shi, Quanqi
    Yao, Zhonghua
    Bonnell, John W.
    JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS, 2013, 118 (06) : 3346 - 3356
  • [35] Estimating daytime vertical ExB drift velocities in the equatorial F-region using ground-based magnetometer observations
    Anderson, D
    Anghel, A
    Yumoto, K
    Ishitsuka, M
    Kudeki, E
    GEOPHYSICAL RESEARCH LETTERS, 2002, 29 (12) : 37 - 1
  • [36] A Machine Learning-Based Method for Downscaling All-Sky Downward Surface Shortwave Radiation Over Complex Terrain
    Lang, Qin
    Zhao, Wei
    Ma, Mingguo
    Wang, Wei
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20
  • [37] A Machine Learning-Based Method for Downscaling All-Sky Downward Surface Shortwave Radiation Over Complex Terrain
    Lang, Qin
    Zhao, Wei
    Ma, Mingguo
    Wang, Wei
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20
  • [38] All-Sky 1 km MODIS Land Surface Temperature Reconstruction Considering Cloud Effects Based on Machine Learning
    Cho, Dongjin
    Bae, Dukwon
    Yoo, Cheolhee
    Im, Jungho
    Lee, Yeonsu
    Lee, Siwoo
    REMOTE SENSING, 2022, 14 (08)
  • [39] Tracking the Region of High Correlation Between Pulsating Aurora and Chorus: Simultaneous Observations With Arase Satellite and Ground-Based All-Sky Imager in Russia
    Kawamura, S.
    Hosokawa, K.
    Kurita, S.
    Oyama, S.
    Miyoshi, Y.
    Kasahara, Y.
    Ozaki, M.
    Matsuda, S.
    Matsuoka, A.
    Kozelov, B.
    Kawamura, Y.
    Shinohara, I
    JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS, 2019, 124 (04) : 2769 - 2778
  • [40] Development of a Machine Learning Forecast Model for Global Horizontal Irradiation Adapted to Tibet Based on Visible All-Sky Imaging
    Wu, Lingxiao
    Chen, Tianlu
    Ciren, Nima
    Wang, Dui
    Meng, Huimei
    Li, Ming
    Zhao, Wei
    Luo, Jingxuan
    Hu, Xiaoru
    Jia, Shengjie
    Liao, Li
    Pan, Yubing
    Wang, Yinan
    REMOTE SENSING, 2023, 15 (09)