scholarly journals Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies

2020 ◽  
Vol 12 (6) ◽  
pp. 936 ◽  
Author(s):  
Mahmoud Rajabi ◽  
Alireza Amiri-Simkooei ◽  
Hossein Nahavandchi ◽  
Vahab Nafisi
Keyword(s):  
Time Series ◽  
Mean Squared Error ◽  
Practical Importance ◽  
Electron Content ◽  
Total Electron ◽  
Scientific Disciplines ◽  
Yearly Average ◽  
Periodic Signals ◽  
Modulated Signals ◽  
Least Squares Harmonic Estimation

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 1 ± 0.0027 j ( j = 1 , … , 5 ) and 1 ± 0.00025 j ( j = 1 , 2 , 3 ) 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 “evening anomaly”. 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.

scholarly journals The comparative study of chaoticity and dynamical complexity of the low-latitude ionosphere, over Nigeria, during quiet and disturbed days

2014 ◽  
Vol 21 (1) ◽  
pp. 127-142 ◽  
Author(s):  
B. O. Ogunsua ◽  
J. A. Laoye ◽  
I. A. Fuwape ◽  
A. B. Rabiu
Keyword(s):  
Time Series ◽  
Lyapunov Exponents ◽  
Correlation Dimension ◽  
Chaotic Behavior ◽  
Surrogate Data ◽  
Tsallis Entropy ◽  
Electron Content ◽  
Total Electron ◽  
Dynamical Complexity ◽  
Definite Pattern

Abstract. The deterministic chaotic behavior and dynamical complexity of the space plasma dynamical system over Nigeria are analyzed in this study and characterized. The study was carried out using GPS (Global Positioning System) TEC (Total Electron Content) time series, measured in the year 2011 at three GPS receiver stations within Nigeria, which lies within the equatorial ionization anomaly region. The TEC time series for the five quietest and five most disturbed days of each month of the year were selected for the study. The nonlinear aspect of the TEC time series was obtained by detrending the data. The detrended TEC time series were subjected to various analyses for phase space reconstruction and to obtain the values of chaotic quantifiers like Lyapunov exponents, correlation dimension and also Tsallis entropy for the measurement of dynamical complexity. The observations made show positive Lyapunov exponents (LE) for both quiet and disturbed days, which indicates chaoticity, and for different days the chaoticity of the ionosphere exhibits no definite pattern for either quiet or disturbed days. However, values of LE were lower for the storm period compared with its nearest relative quiet periods for all the stations. The monthly averages of LE and entropy also show no definite pattern for the month of the year. The values of the correlation dimension computed range from 2.8 to 3.5, with the lowest values recorded at the storm period of October 2011. The surrogate data test shows a significance of difference greater than 2 for all the quantifiers. The entropy values remain relatively close, with slight changes in these values during storm periods. The values of Tsallis entropy show similar variation patterns to those of Lyapunov exponents, with a lot of agreement in their comparison, with all computed values of Lyapunov exponents correlating with values of Tsallis entropy within the range of 0.79 to 0.81. These results show that both quantifiers can be used together as indices in the study of the variation of the dynamical complexity of the ionosphere. The results also show a strong play between determinism and stochasticity. The behavior of the ionosphere during these storm and quiet periods for the seasons of the year are discussed based on the results obtained from the chaotic quantifiers.

Development and investigation of a deep learning based method for TEC map completion

2020 ◽  
Author(s):  
Mingwu Jin ◽  
Yang Pan ◽  
Shunrong Zhang ◽  
Yue Deng
Keyword(s):  
Solar Activity ◽  
Mean Squared Error ◽  
Image Inpainting ◽  
Science Research ◽  
High Solar Activity ◽  
Electron Content ◽  
International Gnss Service ◽  
Generative Adversarial Network ◽  
Total Electron ◽  
Adversarial Network

<p>Because of the limited coverage of receiver stations, current measurements of Total Electron Content (TEC) by ground-based GNSS receivers are not complete with large portions of data gaps. The processing to obtain complete TEC maps for space science research is time consuming and needs the collaboration of five International GNSS Service (IGS) Ionosphere Associate Analysis Centers (IAACs) to use different data processing and filling algorithms and to consolidate their results into final IGS completed TEC maps. In this work, we developed a Deep Convolutional Generative Adversarial Network (DCGAN) and Poisson blending model (DCGAN-PB) to learn IGS completion process for automatic completion of TEC maps. Using 10-fold cross validation of 20-year IGS TEC data, DCGAN-PB achieves the average root mean squared error (RMSE) about 4 absolute TEC units (TECu) of the high solar activity years and around 2 TECu for low solar activity years, which is about 50% reduction of RMSE for recovered TEC values compared to two conventional single-image inpainting methods. The developed DCGAN-PB model can lead to an efficient automatic completion tool for TEC maps.</p>

scholarly journals Modeling Total Electron Content derived from radio occultation measurements by COSMIC satellites over the African Region

2019 ◽  
Author(s):  
Patrick Mungufeni ◽  
Claudia Stolle ◽  
Sripathi Samireddipalle ◽  
Yenca Migoya-Orué ◽  
Yong Ha Kim
Keyword(s):  
Total Electron Content ◽  
Local Time ◽  
Radio Occultation ◽  
Mean Squared Error ◽  
Electron Content ◽  
Quiet Time ◽  
African Region ◽  
Total Electron ◽  
Flux Level ◽  
Binned Data

Abstract. This study developed a model of Total Electron Content (TEC) over the African region. The TEC data were derived from radio occultation measurements done by the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites. Geomagnetically quiet time (Kp  −20 nT) data during the years 2008–2011, and 2013–2017 were binned according to local time, seasons, solar flux level, geographic longitude, and dip latitude. Cubic B splines were fitted to the binned data to obtain the model. The model was validated using TEC data of the years 2012 and 2018. The validation exercise revealed that, approximation of observed TEC data by our model produces root mean squared error of 4.8 TECU. Moreover, the modeled TEC data correlated highly with the observed TEC data (r = 0.93). Our model is the first attempt to predict TECs over the entire African region by using extensive COSMIC TEC measurements. Due to the extensive input data and the good modeling technique, we were able to reproduce the well-known features such as local time, seasonal, solar activity, and spatial variations of TEC over the African region.

scholarly journals Brief communication "Further comments on the ionospheric precursor of the 1999 Hector Mine earthquake"

2013 ◽  
Vol 13 (1) ◽  
pp. 193-196 ◽  
Author(s):  
F. Masci
Keyword(s):  
Time Series ◽  
Total Electron Content ◽  
Seismic Activity ◽  
Seismic Event ◽  
Global Scale ◽  
Electron Content ◽  
Preparation Process ◽  
Total Electron ◽  
Mine Area ◽  
Ionospheric Total Electron Content

Abstract. Pulinets et al. (2007) document anomalous changes in the ionospheric total electron content (TEC) starting one week before the 16 October 1999 Hector Mine earthquake. The authors maintain that this TEC anomalous change is a precursor of the subsequent earthquake. In a previous paper, Afraimovich et al. (2004) excluded that TEC variations, which occurred before the Hector Mine earthquake, were induced by the preparation process of the seismic event. Thomas et al. (2012) reach similar conclusions by performing new analyses of the same TEC data which were investigated by Pulinets et al. (2007). They show that the TEC changes documented by Pulinets et al. (2007) are not anomalous but normal variations on global scale, and, therefore, these changes are not related to the localised seismic activity of the Hector Mine area. This paper confirms the results of Afraimovich et al. (2004) and Thomas et al. (2012). Through the use of geomagnetic indices time series it is shown that the presumed precursor of Pulinets et al. (2007) was a normal TEC variation induced by solar-terrestrial interaction.

scholarly journals Extreme Solar Events’ Impact on GPS Positioning Results

2021 ◽  
Vol 13 (18) ◽  
pp. 3624
Author(s):  
Janis Balodis ◽  
Madara Normand ◽  
Inese Varna
Keyword(s):  
Time Series ◽  
Space Weather ◽  
Geomagnetic Storms ◽  
Geomagnetic Latitude ◽  
Satellite System ◽  
Rate Of Change ◽  
Electron Content ◽  
Total Electron ◽  
Cycle Slips ◽  
Global Navigation Satellite

The main objective of the present study is to perform an analysis of the space weather impact on the Latvian CORS (Continuously Operating GNSS (Global Navigation Satellite System) Stations) GPS (Global Positioning System) observations, in situations of geomagnetic storms, sun flares and extreme TEC (Total Electron Content) and ROTI (Rate of change of TEC index) levels, by analyzing the results, i.e., 90-second kinematic post-processing solutions, obtained using Bernese GNSS Software v5.2. To complete this study, the 90-second kinematic time series of all the Latvian CORS for the period from 2007 to 2017 were analyzed, and a correlation between time series outliers (hereinafter referred to as faults) and extreme space weather events was sought. Over 36 million position determination solutions were examined, 0.6% of the solutions appear to be erroneous, 0.13% of the solutions have errors greater than 1 m, 0.05% have errors greater than 10 m, and 0.01% of the solutions show errors greater than 50 meters. The correlation between faulty results, TEC and ROTI levels and Bernese GNSS Software v5.2 detected cycle slips was computed. This also includes an analysis of fault distribution depending on the geomagnetic latitude as well as faults distribution simultaneously occurring in some stations, etc. This work is the statistical analysis of the Latvian CORS security, mainly focusing on geomagnetic extreme events and ionospheric scintillations in the region of Latvia, with a latitude around 57° N.

scholarly journals Modification of the solar activity indices in the International Reference Ionosphere IRI and IRI-Plas models due to recent revision of sunspot number time series

2016 ◽  
Vol 2 (3) ◽  
pp. 59-68 ◽  
Author(s):  
Тамара Гуляева ◽  
Tamara Gulyaeva
Keyword(s):  
Time Series ◽  
Solar Activity ◽  
Sunspot Number ◽  
International Reference Ionosphere ◽  
Electron Content ◽  
Prediction Errors ◽  
Solar Cycles ◽  
Total Electron ◽  
International Reference ◽  
Ionospheric Models

The International Reference Ionosphere (IRI) imports global effective ionospheric IG12 index based on ionosonde measurements of the critical frequency foF2 as a proxy of solar activity. Similarly, the global electron content (GEC), smoothed by the sliding 12-months window (GEC12), is used as a solar proxy in the ionospheric and plasmaspheric model IRI-Plas. GEC has been calculated from global ionospheric maps of total electron content (TEC) since 1998 whereas its productions for the preceding years and predictions for the future are made with the empirical model of the linear dependence of GEC on solar activity. At present there is a need to re-evaluate solar and ionospheric indices in the ionospheric models due to the recent revision of sunspot number (SSN2) time series, which has been conducted since 1st July, 2015 [Clette et al., 2014]. Implementation of SSN2 instead of the former SSN1 series with the ionospheric model could increase model prediction errors. A formula is proposed to transform the smoothed SSN212 series to the proxy of the former basic SSN112=R12 index, which is used by IRI and IRI-Plas models for long-term ionospheric predictions. Regression relationships are established between GEC12, the sunspot number R12, and the proxy solar index of 10.7 cm microwave radio flux, F10.712. Comparison of calculations by the IRI-Plas and IRI models with observations and predictions for Moscow during solar cycles 23 and 24 has shown the advantage of implementation of GEC12 index with the IRI-Plas model.

Modeling and Predicting Total Electron Content by Semi-Parametric Autoregressive (AR) Model

2012 ◽  
Vol 457-458 ◽  
pp. 705-709
Author(s):  
Xiu Hai Li
Keyword(s):  
Time Series ◽  
Total Electron Content ◽  
Stationary Time Series ◽  
Ar Model ◽  
Electron Content ◽  
Short Term ◽  
Total Electron ◽  
Modeling Methodology ◽  
Seasonal Time Series

Based on dynamic data system(DDS) modeling methodology, after transformed a seasonal time series for total electron content(TEC) of the ionosphere into a stationary time series by differencing technique, stationary TEC values are modeled by the autoregressive(AR) model. In order to correct model’s systematic errors, authors proposed that AR model is improved by non-parameters introduced to AR model and the ionospheric TEC is predicted using the improved AR model which is called semi-parametric AR model. Preliminary results show that the semi-parametric AR model has a good performance than one of the AR model for short-term TEC prediction while, for relatively long-term TEC prediction, the performance of the semi-parametric AR model is no less than one of AR model.

Traveling Ionospheric Disturbances Characteristics during the 2018 Typhoon Maria from GPS Observations

2020 ◽  
Vol 12 (4) ◽  
pp. 746 ◽  
Author(s):  
Yiduo Wen ◽  
Shuanggen Jin
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Ionospheric Disturbance ◽  
Electron Content ◽  
Ionospheric Disturbances ◽  
Dual Frequency ◽  
Total Electron ◽  
Traveling Ionospheric Disturbances ◽  
Gps Observations

Typhoons often occur and may cause huge loss of life and damage of infrastructures, but they are still difficult to precisely monitor and predict by traditional in-situ measurements. Nowadays, ionospheric disturbances at a large-scale following typhoons can be monitored using ground-based dual-frequency Global Positioning System (GPS) observations. In this paper the responses of ionospheric total electron content (TEC) to Typhoon Maria on 10 July 2018 are studied by using about 150 stations of the GPS network in Taiwan. The results show that two significant ionospheric disturbances on the southwest side of the typhoon eye were found between 10:00 and 12:00 UTC. This was the stage of severe typhoon and the ionospheric disturbances propagated at speeds of 118.09 and 186.17 m/s, respectively. Both traveling ionospheric disturbances reached up to 0.2 TECU and the amplitudes were slightly different. The change in the filtered TEC time series during the typhoon was further analyzed with the azimuth. It can be seen that the TEC disturbance anomalies were primarily concentrated in a range of between −0.2 and 0.2 TECU and mainly located at 135–300° in the azimuth, namely the southwest side of the typhoon eye. The corresponding frequency spectrum of the two TEC time series was about 1.6 mHz, which is consistent with the frequency of gravity waves. Therefore, the upward propagating gravity wave was the main cause of the traveling ionospheric disturbance during Typhoon Maria.

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