Prediction of Ionospheric TEC during the Annular and Total Solar Eclipses that Occurred over Indonesia by Using OKSM and FFNN

IF 0.6 4区 物理与天体物理 Q4 ASTRONOMY & ASTROPHYSICS
S. Kiruthiga, S. Mythili, R. Mukesh, Sarat C. Dass
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引用次数: 0

Abstract

People across the world have been fascinated by solar eclipses for thousands of years. Solar eclipses are not only fascinating to observe but also provide opportunities for scientific research. During a solar eclipse, the quantity of solar energy reaching the Earth’s surface is reduced as the Moon passes in front of the Sun. This reduction in solar energy can have an effect on the Total Electron Content of the Earth’s ionosphere. In this paper, prediction and analysis of TEC variations in the Ionosphere during the solar eclipses happened on 26.12.2019 between 04:51 to 7:34 hours (UTC) and 09.03.2016 between 12:18 to 1:02 hours (UTC) over the Indonesia region were done by using two models: Ordinary Kriging based Surrogate Model (OKSM) and Feed-Forward Neural Network (FFNN). During the eclipse period, the TEC values were predicted by the OKSM and FFNN models and it is validated using literature. For this study, the GPS data belonging to the BAKO station situated in Indonesia were collected from IONOLAB servers and the input parameters were collected from the OMNIWEB servers. Forty days prior TEC data and input parameters were used to predict the TEC values. The credibility of the predicted results is assessed using statistical factors such as RMSE, CC, MAE, MAPE, sMAPE and R-Square. The statistical results show OKSM has performed well when compared to the FFNN model over the annular and total solar eclipse period. The study suggests that combining multiple modelling methods, such as OKSM and FFNN can improve our understanding of ionospheric variability during solar eclipses and provide more accurate predictions of TEC variations. This has important implications for satellite communications and navigation systems that rely on accurate TEC measurements for positioning and timing.

Abstract Image

利用OKSM和FFNN预测印度尼西亚日全食和日环食期间电离层TEC
摘要几千年来,世界各地的人们都对日食着迷。日食不仅令人着迷,而且为科学研究提供了机会。在日食期间,到达地球表面的太阳能数量随着月球在太阳前面经过而减少。太阳能的减少会对地球电离层的总电子含量产生影响。本文采用基于普通克里格代理模型(OKSM)和前馈神经网络(FFNN)两种模型,对印度尼西亚地区2019年12月26日04:51 ~ 7:34 (UTC)和2016年3月9日12:18 ~ 1:02 (UTC)日食期间电离层TEC的变化进行了预测和分析。利用OKSM和FFNN模型预测了日食期间的TEC值,并进行了文献验证。在本研究中,来自印度尼西亚BAKO站的GPS数据来自IONOLAB服务器,输入参数来自OMNIWEB服务器。使用40天前的TEC数据和输入参数来预测TEC值。使用RMSE、CC、MAE、MAPE、sMAPE和R-Square等统计因子评估预测结果的可信度。统计结果表明,与FFNN模型相比,OKSM模型在日环食和日全食期间表现良好。该研究表明,结合OKSM和FFNN等多种模拟方法可以提高我们对日食期间电离层变化的认识,并提供更准确的TEC变化预测。这对依靠精确的TEC测量进行定位和授时的卫星通信和导航系统具有重要影响。
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来源期刊
Cosmic Research
Cosmic Research 地学天文-工程:宇航
CiteScore
1.10
自引率
33.30%
发文量
41
审稿时长
6-12 weeks
期刊介绍: Cosmic Research publishes scientific papers covering all subjects of space science and technology, including the following: ballistics, flight dynamics of the Earth’s artificial satellites and automatic interplanetary stations; problems of transatmospheric descent; design and structure of spacecraft and scientific research instrumentation; life support systems and radiation safety of manned spacecrafts; exploration of the Earth from Space; exploration of near space; exploration of the Sun, planets, secondary planets, and interplanetary medium; exploration of stars, nebulae, interstellar medium, galaxies, and quasars from spacecraft; and various astrophysical problems related to space exploration. A chronicle of scientific events and other notices concerning the main topics of the journal are also presented.
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