Lynne Githio , Huixin Liu , Ayman A. Arafa , Ayman Mahrous
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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. 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引用次数: 0
摘要
赤道等离子体气泡(EPBs)是以等离子体密度波动为特征的区域,主要在日落后形成于低纬度电离层。它们使无线电信号受到振幅和相位变化的影响,从而影响利用全球导航卫星系统(GNSS)信号进行导航的技术系统的运行。因此,了解 EPB 的发生模式和形态特征对于减轻其影响至关重要。在这项工作中,我们利用两台全球导航卫星系统接收器和一台全天空成像仪(ASI)对巴西上空的 EPB 形态进行了同步观测。研究的主要目标是:(1)开发一个随机森林(RF)机器学习模型来估计和预测 EPB 的带状漂移速度;(2)将模型预测结果与从两个仪器推断出的实际 EPB 漂移以及从水平风模型(HWM-14)获得的带状中性风速进行比较。在模型开发过程中,我们利用了 2013 年至 2017 年期间在巴西地磁静止日进行的可靠 EPB 漂移测量。该模型根据年月日、全球时间、F2层临界频率(foF2)、太阳指数和星际指数等参数预测了风速。训练和验证的相关系数分别为 0.98 和 0.96,均方根误差值分别为 10.61 米/秒和 10.06 米/秒。我们评估了该模型在两个地磁静夜预测 EPB 漂移的准确性,得到的平均相关系数为 0.89,均方根误差为 15.74 m/s。预测的漂移、带状中性风速、GNSS 和 ASI 速度测量结果都被放在一起进行验证。总体而言,从 00 UT 到 05 UT 的速度相当,介于 ∼100 m/s 和 ∼30 m/s 之间。结果证实了模型的准确性和适用性,揭示了电离层-热层耦合在 F 区动力完全激活的情况下对 EPB 夜间传播的影响。
A machine learning approach for estimating the drift velocities of equatorial plasma bubbles based on All-Sky Imager and GNSS observations
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.
期刊介绍:
The COSPAR publication Advances in Space Research (ASR) is an open journal covering all areas of space research including: space studies of the Earth''s surface, meteorology, climate, the Earth-Moon system, planets and small bodies of the solar system, upper atmospheres, ionospheres and magnetospheres of the Earth and planets including reference atmospheres, space plasmas in the solar system, astrophysics from space, materials sciences in space, fundamental physics in space, space debris, space weather, Earth observations of space phenomena, etc.
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