scholarly journals Regional reference total electron content model over Japan based on neural network mapping techniques

2007 ◽  
Vol 25 (12) ◽  
pp. 2609-2614 ◽  
Author(s):  
T. Maruyama
Keyword(s):  
Neural Network ◽  
Solar Activity ◽  
Total Electron Content ◽  
Reference Model ◽  
Activity Period ◽  
Electron Content ◽  
Total Electron ◽  
Grid Points ◽  
Using Data ◽  
Regional Reference

Abstract. A regional reference model of total electron content (TEC) was constructed using data from the GPS Earth Observation Network (GEONET), which consists of more than 1000 Global Positioning System (GPS) satellite receivers distributed over Japan. The data covered almost one solar activity period from April 1997 to June 2007. First, TECs were determined for 32 grid points, expanding from 27 to 45° N in latitude and from 127 to 145° E in longitude at 15-min intervals. Secondly, the time-latitude variation averaged over three days was determined by using the surface harmonic functional expansion. The coefficients of the expansion were then modeled by using a neural network technique with input parameters of the season (day of the year) and solar activity (F10.7 index and sunspot number). Thus, two-dimensional TEC maps (time vs. latitude) can be obtained for any given set of solar activity and day of the year.

scholarly journals Neural network based model for global Total Electron Content forecasting

2020 ◽  
Vol 10 ◽  
pp. 11 ◽  
Author(s):  
Claudio Cesaroni ◽  
Luca Spogli ◽  
Angela Aragon-Angel ◽  
Michele Fiocca ◽  
Varuliator Dear ◽  
...  
Keyword(s):  
Neural Network ◽  
Total Electron Content ◽  
Geomagnetic Storms ◽  
Single Point ◽  
Global Scale ◽  
External Input ◽  
Electron Content ◽  
International Gnss Service ◽  
Total Electron ◽  
Grid Points

We introduce a novel empirical model to forecast, 24 h in advance, the Total Electron Content (TEC) at global scale. The technique leverages on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and applies a nonlinear autoregressive neural network with external input (NARX) to selected GIM grid points for the 24 h single-point TEC forecasting, taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a global scale, the technique makes use of the NeQuick2 Model fed by an effective sunspot number R12 (R12eff), estimated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same GIM grid points. The novel approach is able to reproduce the features of the ionosphere especially during disturbed periods. The performance of the forecasting approach is extensively tested under different geospatial conditions, against both TEC maps products by UPC (Universitat Politècnica de Catalunya) and independent TEC data from Jason-3 spacecraft. The testing results are very satisfactory in terms of RMSE, as it has been found to range between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-h forecasting technique even over the oceans. The validation of the forecasting during five geomagnetic storms reveals that the model performance is not deteriorated during disturbed periods. This 24-h empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to support different classes of GNSS users.

scholarly journals Variations of total electron content over Serbia during the increased solar activity period in 2013 and 2014

2016 ◽  
Vol 60 (04) ◽  
pp. 734-744
Author(s):  
Dragan Blagojevic ◽  
Miljana Todorovic Drakul ◽  
Oleg Odalovic ◽  
Sanja Grekulovic ◽  
Jovan Popovic ◽  
...  
Keyword(s):  
Solar Activity ◽  
Total Electron Content ◽  
Activity Period ◽  
Electron Content ◽  
Total Electron ◽  
Solar Activity Period

scholarly journals SCINDA-GPS derived TEC depletions and amplitude scintillations over Kisumu, Kenya during selected quiet and storm days of 2013 and 2014

2020 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Uluma Edward ◽  
Ndinya Boniface ◽  
Omondi George
Keyword(s):  
Total Electron Content ◽  
Equatorial Region ◽  
Activity Period ◽  
High Solar Activity ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Gps Receiver ◽  
Total Electron ◽  
Solar Intensity ◽  
Using Data

Total Electron Content (TEC) depletion and amplitude scintillation (S4) can be derived from, SCINDA-GPS receivers situated in various parts of the equatorial region. In this paper we present results of characterization of TEC depletions and amplitude scintillations over Kisumu, Kenya (Geomagnetic coordinates: 9.64o S, 108.59o E; Geographic coordinates: 0.02o S, 34.6o E) for both selected geomagnetically quiet and geomagnetically disturbed conditions between 1st January 2013 and 31st December 2014 using data derived from the Kisumu NovAtel GSV4004B SCINDA-GPS receiver situated at Maseno University. TEC depletions and amplitude scintillations affect Global Positioning System (GPS) signals in the ionosphere as they propagate from the satellite to the receiver. This study aims to investigate day to day variability of TEC depletions and amplitude scintillations over Kisumu, Kenya during both geomagnetically quiet and geomagnetically disturbed days of 2013 and 2014 which was a high solar activity period for Solar Cycle 24. Seasonal variability of TEC depletions and S4 index is also presented. The Receiver Independent Exchange (RINEX) data for the years 2013 and 2014 was retrieved from the Kisumu SCINDA-GPS receiver, processed to obtain Vertical Total Electron Content (VTEC), S4 and Universal Time (UT) and fed into MATLAB to generate VTEC and S4 plots against UT for each selected quiet and storm day within the 2013 and 2014 period. The obtained results showed a diurnal variation of TEC where TEC was minimum at pre-sunrise, maximum during daytime and minimum during nighttime. The minimum TEC during pre-sunrise and nighttime was attributed to reduced solar intensity while maximum TEC during daytime is attributed to increased solar intensity. Most of the selected quiet and storm days of the years 2013 and 2014 showed TEC depletions and TEC enhancements corresponding with enhanced amplitude scintillations between 1800UT and 20:00UT. This might be attributed to the rapid rise of the F-layer and the increase in the vertical E x B plasma drift due to the Pre-reversal Enhancement (PRE) of the eastward electric field. Post-midnight TEC depletions and amplitude scintillations were observed for some days and this was attributed to the effect of zonal winds which brought post-midnight enhancement of the E x B drift. The percentage occurrence of amplitude scintillations for the selected quiet and storm days exhibited a seasonal dependence with equinoctial months having higher occurrences than the solstitial months. The higher average S4 index during equinoctial months might be attributed to increased solar intensity resulting from the close alignment of the solar terminator and the geomagnetic meridian.  

scholarly journals Empirical models of Total Electron Content based on functional fitting over Taiwan during geomagnetic quiet condition

2009 ◽  
Vol 27 (8) ◽  
pp. 3321-3333 ◽  
Author(s):  
Y. Kakinami ◽  
C. H. Chen ◽  
J. Y. Liu ◽  
K.-I. Oyama ◽  
W. H. Yang ◽  
...  
Keyword(s):  
Solar Activity ◽  
Total Electron Content ◽  
Empirical Models ◽  
Electron Content ◽  
Total Electron ◽  
Quiet Condition ◽  
Functional Fitting ◽  
Using Data ◽  
First Time ◽  
Fitting Model

Abstract. Empirical models of Total Electron Content (TEC) based on functional fitting over Taiwan (120° E, 24° N) have been constructed using data of the Global Positioning System (GPS) from 1998 to 2007 during geomagnetically quiet condition (Dst>−30 nT). The models provide TEC as functions of local time (LT), day of year (DOY) and the solar activity (F), which are represented by 1–162 days mean of F10.7 and EUV. Other models based on median values have been also constructed and compared with the models based on the functional fitting. Under same values of F parameter, the models based on the functional fitting show better accuracy than those based on the median values in all cases. The functional fitting model using daily EUV is the most accurate with 9.2 TECu of root mean square error (RMS) than the 15-days running median with 10.4 TECu RMS and the model of International Reference Ionosphere 2007 (IRI2007) with 14.7 TECu RMS. IRI2007 overestimates TEC when the solar activity is low, and underestimates TEC when the solar activity is high. Though average of 81 days centered running mean of F10.7 and daily F10.7 is often used as indicator of EUV, our result suggests that average of F10.7 mean from 1 to 54 day prior and current day is better than the average of 81 days centered running mean for reproduction of TEC. This paper is for the first time comparing the median based model with the functional fitting model. Results indicate the functional fitting model yielding a better performance than the median based one. Meanwhile we find that the EUV radiation is essential to derive an optimal TEC.

scholarly journals A Neural Network-Based TEC Model Capable of Reproducing Nighttime Winter Anomaly

2021 ◽  
Vol 13 (22) ◽  
pp. 4559
Author(s):  
Marjolijn Adolfs ◽  
Mohammed Mainul Hoque
Keyword(s):  
Neural Network ◽  
Solar Activity ◽  
Geomagnetic Latitude ◽  
Machine Learning Techniques ◽  
High Solar Activity ◽  
Electron Content ◽  
Solar Cycles ◽  
Total Electron ◽  
The Neural Network ◽  
Winter Anomaly

With the availability of fast computing machines, as well as the advancement of machine learning techniques and Big Data algorithms, the development of a more sophisticated total electron content (TEC) model featuring the Nighttime Winter Anomaly (NWA) and other effects is possible and is presented here. The NWA is visible in the Northern Hemisphere for the American sector and in the Southern Hemisphere for the Asian longitude sector under solar minimum conditions. During the NWA, the mean ionization level is found to be higher in the winter nights compared to the summer nights. The approach proposed here is a fully connected neural network (NN) model trained with Global Ionosphere Maps (GIMs) data from the last two solar cycles. The day of year, universal time, geographic longitude, geomagnetic latitude, solar zenith angle, and solar activity proxy, F10.7, were used as the input parameters for the model. The model was tested with independent TEC datasets from the years 2015 and 2020, representing high solar activity (HSA) and low solar activity (LSA) conditions. Our investigation shows that the root mean squared (RMS) deviations are in the order of 6 and 2.5 TEC units during HSA and LSA period, respectively. Additionally, NN model results were compared with another model, the Neustrelitz TEC Model (NTCM). We found that the neural network model outperformed the NTCM by approximately 1 TEC unit. More importantly, the NN model can reproduce the evolution of the NWA effect during low solar activity, whereas the NTCM model cannot reproduce such effect in the TEC variation.

scholarly journals A New Global Total Electron Content Empirical Model

2019 ◽  
Vol 11 (6) ◽  
pp. 706 ◽  
Author(s):  
Jiandi Feng ◽  
Baomin Han ◽  
Zhenzhen Zhao ◽  
Zhengtao Wang
Keyword(s):  
Total Electron Content ◽  
Empirical Model ◽  
Single Point ◽  
Empirical Models ◽  
Electron Content ◽  
International Gnss Service ◽  
Prediction Ability ◽  
Total Electron ◽  
Grid Model ◽  
Grid Points

Research on total electron content (TEC) empirical models is one of the important topics in the field of space weather services. Global TEC empirical models based on Global Ionospheric Maps (GIMs) TEC data released by the International GNSS Service (IGS) have developed rapidly in recent years. However, the accuracy of such global empirical models has a crucial restriction arising from the non-uniform accuracy of IGS TEC data in the global scope. Specifically, IGS TEC data accuracy is higher on land and lower over the ocean due to the lack of stations in the latter. Using uneven precision GIMs TEC data as a whole for model fitting is unreasonable. Aiming at the limitation of global ionospheric TEC modelling, this paper proposes a new global ionospheric TEC empirical model named the TECM-GRID model. The model consists of 5183 sections, corresponding to 5183 grid points (longitude 5°, latitude 2.5°) of GIM. Two kinds of single point empirical TEC models, SSM-T1 and SSM-T2, are used for TECM-GRID. According to the locations of grid points, the SSM-T2 model is selected as the sub-model in the Mid-Latitude Summer Night Anomaly (MSNA) region, and SSM-T1 is selected as the sub-model in other regions. The fitting ability of the TECM-GRID model for modelling data was tested in accordance with root mean square (RMS) and relative RMS values. Then, the TECM-GRID model was validated and compared with the NTCM-GL model and Center for Orbit Determination in Europe (CODE) GIMs at time points other than modelling time. Results show that TECM-GRID can effectively describe the Equatorial Ionization Anomaly (EIA) and the MSNA phenomena of the ionosphere, which puts it in good agreement with CODE GIMs and means that it has better prediction ability than the NTCM-GL model.

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