Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies

Knowledge on the ionospheric total electron content (TEC) and its prediction are of great practical importance and engineering relevance in many scientific disciplines. We investigate regular ionospheric anomalies and TEC prediction by applying the least squares harmonic estimation (LS-HE) technique...

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Main Authors: Mahmoud Rajabi, Alireza Amiri-Simkooei, Hossein Nahavandchi, Vahab Nafisi
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/6/936
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spelling doaj-0b9c2f94b11f4165a2465d980c3109932020-11-25T01:48:28ZengMDPI AGRemote Sensing2072-42922020-03-0112693610.3390/rs12060936rs12060936Modeling and Prediction of Regular Ionospheric Variations and Deterministic AnomaliesMahmoud Rajabi0Alireza Amiri-Simkooei1Hossein Nahavandchi2Vahab Nafisi3Department of Civil and Environmental Engineering, Norwegian University of Science and Technology NTNU, 7491 Trondheim, NorwayDepartment of Geomatics Engineering, University of Isfahan, Hezar-Jarib Avenue 81746, Isfahan 73441, IranDepartment of Civil and Environmental Engineering, Norwegian University of Science and Technology NTNU, 7491 Trondheim, NorwayDepartment of Geomatics Engineering, University of Isfahan, Hezar-Jarib Avenue 81746, Isfahan 73441, IranKnowledge on the ionospheric total electron content (TEC) and its prediction are of great practical importance and engineering relevance in many scientific disciplines. We investigate regular ionospheric anomalies and TEC prediction by applying the least squares harmonic estimation (LS-HE) technique to a 15 year time series of the vertical TEC (VTEC) from 1998 to 2014. We first detected a few new regular and modulated signals in the TEC time series. The multivariate analysis of the time series indicates that there are diurnal, annual, 11 year, and 27 day periodic signals, as well as their higher harmonics. We also found periods matching with the global positioning system (GPS) draconitic year in the TEC time series. The results from the modulated harmonic analysis indicate that there exists a set of peaks with periods of <inline-formula> <math display="inline"> <semantics> <mrow> <mn>1</mn> <mo>&#177;</mo> <mn>0.0027</mn> <mi>j</mi> </mrow> </semantics> </math> </inline-formula> (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mo>&#8230;</mo> <mo>,</mo> <mn>5</mn> </mrow> </semantics> </math> </inline-formula>) and <inline-formula> <math display="inline"> <semantics> <mrow> <mn>1</mn> <mo>&#177;</mo> <mn>0.00025</mn> <mi>j</mi> </mrow> </semantics> </math> </inline-formula> (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>3</mn> </mrow> </semantics> </math> </inline-formula>) days. The same situation holds also true for the harmonics higher than the diurnal signal. A model is then adopted based on the discovered periods. This model, which consists of pure and modulated harmonic functions, is shown to be appropriate for assessing the regular variations and ionospheric anomalies. There is a clear maximum TEC at around 22:00 h, which we called the &#8220;evening anomaly&#8221;. The evening anomaly occurs in the winter and autumn, and is dependent on the solar activities. Also, the Semiannual, Winter, and Equatorial anomalies were investigated. Finally, to investigate the performance of the derived model, the TEC values have been predicted monthly, and the results show that the modulated signals can significantly contribute to obtaining superior prediction results. Compared with the pure signals, the modulated signals can improve a yearly average root mean squared error (RMSE) value in the lower and higher solar activities by 20% and 15%, respectively.https://www.mdpi.com/2072-4292/12/6/936ionospheric anomaliesleast squares harmonic estimation (ls-he)tec predictiontec time-series
collection DOAJ
language English
format Article
sources DOAJ
author Mahmoud Rajabi
Alireza Amiri-Simkooei
Hossein Nahavandchi
Vahab Nafisi
spellingShingle Mahmoud Rajabi
Alireza Amiri-Simkooei
Hossein Nahavandchi
Vahab Nafisi
Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies
Remote Sensing
ionospheric anomalies
least squares harmonic estimation (ls-he)
tec prediction
tec time-series
author_facet Mahmoud Rajabi
Alireza Amiri-Simkooei
Hossein Nahavandchi
Vahab Nafisi
author_sort Mahmoud Rajabi
title Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies
title_short Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies
title_full Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies
title_fullStr Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies
title_full_unstemmed Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies
title_sort modeling and prediction of regular ionospheric variations and deterministic anomalies
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-03-01
description Knowledge on the ionospheric total electron content (TEC) and its prediction are of great practical importance and engineering relevance in many scientific disciplines. We investigate regular ionospheric anomalies and TEC prediction by applying the least squares harmonic estimation (LS-HE) technique to a 15 year time series of the vertical TEC (VTEC) from 1998 to 2014. We first detected a few new regular and modulated signals in the TEC time series. The multivariate analysis of the time series indicates that there are diurnal, annual, 11 year, and 27 day periodic signals, as well as their higher harmonics. We also found periods matching with the global positioning system (GPS) draconitic year in the TEC time series. The results from the modulated harmonic analysis indicate that there exists a set of peaks with periods of <inline-formula> <math display="inline"> <semantics> <mrow> <mn>1</mn> <mo>&#177;</mo> <mn>0.0027</mn> <mi>j</mi> </mrow> </semantics> </math> </inline-formula> (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mo>&#8230;</mo> <mo>,</mo> <mn>5</mn> </mrow> </semantics> </math> </inline-formula>) and <inline-formula> <math display="inline"> <semantics> <mrow> <mn>1</mn> <mo>&#177;</mo> <mn>0.00025</mn> <mi>j</mi> </mrow> </semantics> </math> </inline-formula> (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>3</mn> </mrow> </semantics> </math> </inline-formula>) days. The same situation holds also true for the harmonics higher than the diurnal signal. A model is then adopted based on the discovered periods. This model, which consists of pure and modulated harmonic functions, is shown to be appropriate for assessing the regular variations and ionospheric anomalies. There is a clear maximum TEC at around 22:00 h, which we called the &#8220;evening anomaly&#8221;. The evening anomaly occurs in the winter and autumn, and is dependent on the solar activities. Also, the Semiannual, Winter, and Equatorial anomalies were investigated. Finally, to investigate the performance of the derived model, the TEC values have been predicted monthly, and the results show that the modulated signals can significantly contribute to obtaining superior prediction results. Compared with the pure signals, the modulated signals can improve a yearly average root mean squared error (RMSE) value in the lower and higher solar activities by 20% and 15%, respectively.
topic ionospheric anomalies
least squares harmonic estimation (ls-he)
tec prediction
tec time-series
url https://www.mdpi.com/2072-4292/12/6/936
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AT hosseinnahavandchi modelingandpredictionofregularionosphericvariationsanddeterministicanomalies
AT vahabnafisi modelingandpredictionofregularionosphericvariationsanddeterministicanomalies
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