Assessment of the IRI-2016 and modified IRI 2016 models in China: Comparison with GNSS-TEC and ionosonde data

2020 ◽  
Author(s):  
wen zhang ◽  
xingliang Huo ◽  
haojie Liu
Keyword(s):  
Signal Propagation ◽  
Electron Density Profile ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Electron Densities ◽  
Iri Model ◽  
Total Electron ◽  
Observation Network ◽  
The Difference ◽  
Gnss Data

<p>Ionosphere is one of the main errors in the signal propagation of global navigation system satellite (GNSS), and it is also the key issue of space weather. The International Reference Ionosphere (IRI) is the most important empirical model described the ionospheric characteristics, and it provides the monthly averages of electron densities and vertical total electron content (VTEC) in the altitude range of 50km-2000km. The IRI-2016 model is the latest version. But some studies showed that the accuracy of the IRI model is not high enough in China due to the use of fewer data sources. This paper will assess the performance of IRI-2016 model in China, and a modified IRI 2016 model by adjusting the driving parameters IG and RZ index of IRI2016 model with GNSS TEC data are also investigated. In this contribution, GNSS data from the Crustal Movement Observation Network of China (CMONC) are used to estimate TEC values, and the ionosonde data from three stations are used as references for the ionospheric electron densities. Three ionosonde stations are located at Beijing (BP440, 40.3°N/116.2°E), Wuhan (WU430, 30.5°N/114.4°E) and Sanya (SA418, 18.3°N/ 109.6°E). The above data respectively cover a period of 6 days in the high year (2015) and low year (2019) of solar activity.</p><p>The study shows that the biggest reason for the difference (DTEC) between GPS-TEC and IRI2016-TEC in China is that the poor estimation of NmF2 and hmF2 by IRI model, and the driving parameters IG and RZ index of IRI2016 can be updated by constraining DTEC. Finally, the performance of the modified IRI-2016 model is improved by the updated IG and RZ indexes as the short-term driving values of ionospheric parameters. The analysis show that the modified IRI-2016 model is more accurate at estimating both the TEC and the electron density profile than the original model.</p>

scholarly journals Electron density profile modeling

1996 ◽  
Vol 39 (3) ◽  
Author(s):  
R. G. Ezquer ◽  
M. Mosert de Gonzalez ◽  
T. Heredia
Keyword(s):  
Electron Density ◽  
Characteristic Point ◽  
Base Point ◽  
Electron Density Profile ◽  
Electron Content ◽  
Total Electron ◽  
F Region ◽  
Bottom Side ◽  
The Difference ◽  
Good Agreement

The Base Point Model (BPM) is used to model the electron density (N) profile in the ionosphere, This model assumes two Chapman profile expressions one for the bottomside and one for the topside, and requires a characteristic point called "F region base point". The comparison among the modeled and experimental bottom-side N profiles obtained from Tucuman (26,9°S; 65.4°W) ionosonde shows that, in general, there is a very good agreement within 30 km below the height of the maximum N(hm). Cases with a very good agreement for the entire N-profile are observed. The study of the electron content below hm and the Total Electron Content (TEC) measured over Tucuman shows that, the difference among predicted and measured TEC is due to the disagreement in the topside N-profile more than that observed in the bottomside N-profile.

A systematic approach for modeling global VTEC using machine learning

2021 ◽  
Author(s):  
Karolina Kume ◽  
Irina Zhelavskaya ◽  
Yuri Shprits ◽  
Artem Smirnov ◽  
Ruggero Vasile ◽  
...  
Keyword(s):  
Geomagnetic Storms ◽  
Signal Propagation ◽  
Gradient Boosting ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Radio Communication ◽  
Total Electron ◽  
The Earth ◽  
Feature Importance ◽  
Time Histories

<p>Ionosphere is the ionized layer of the Earth’s upper atmosphere. Vertical total electron content (VTEC) is a highly descriptive measure of the ionosphere. Modeling and predicting VTEC is crucial, because its disturbances are indicative of severe effects in GPS signal propagation and radio communication. We present a new neural-network-based model of VTEC parametrized with geomagnetic indices, solar wind and their time histories. The model was extensively validated with nested cross-validation to ensure that it performs well during geomagnetic storms and quiet times. We applied a number of feature selection methods, namely gradient boosting, permutation feature importance, random forests and cross-correlation. We selected the best input parameters to the model. In addition to reducing dimensionality and avoiding overfitting, the proposed approach also allows to get physical insights into the dynamics of the ionosphere. </p>

Analysis of ionospheric vertical total electron content before the 1 April 2014 Mw 8.2 Chile earthquake

2017 ◽  
Vol 21 (6) ◽  
pp. 1599-1612 ◽  
Author(s):  
Weiping Jiang ◽  
Yifang Ma ◽  
Xiaohui Zhou ◽  
Zhao Li ◽  
Xiangdong An ◽  
...  
Keyword(s):  
Total Electron Content ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Total Electron ◽  
Chile Earthquake

scholarly journals New GGOS JWG3 on Improved understanding of space weather events and their monitoring

2020 ◽  
Author(s):  
Alberto Garcia-Rigo ◽  
Benedikt Soja
Keyword(s):  
Electron Density ◽  
Space Weather ◽  
International Association ◽  
Real Data ◽  
Weather Conditions ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Total Electron ◽  
Weather Events ◽  
Space Geodetic Techniques

<p>Multiple space geodetic techniques are capable of measuring effects caused by space weather events. In particular, space weather events can cause ionospheric disturbances correlated with variations in the vertical total electron content (VTEC) or the electron density (Ne) of the ionosphere.</p><p>In this regard and in the context of the new Focus Area on Geodetic Space Weather Research within IAG’s GGOS (International Association of Geodesy; Global Geodetic Observing System), the Joint Working Group 3 on Improved understanding of space weather events and their monitoring by satellite missions has been created as part of IAG Commission 4, Sub-Commission 4.3 to run for the next four years.</p><p>Within JWG3, we expect investigating different approaches to monitor space weather events using the data from different space geodetic techniques and, in particular, combinations thereof. Simulations will be beneficial to identify the contribution of different techniques and prepare for the analysis of real data. Different strategies for the combination of data will also be investigated, in particular, the weighting of estimates from different techniques in order to increase the performance and reliability of the combined estimates. Furthermore, existing algorithms for the detection and prediction of space weather events will be explored and improved to the extent possible. Furthermore, the geodetic measurement of the ionospheric electron density will be complemented by direct observations from the Sun gathered from existing spacecraft, such as SOHO, ACE, SDO, Parker Solar Probe, among others. The combination and joint evaluation of multiple datasets with the measurements of space geodetic observation techniques (e.g. geodetic VLBI) is still a great challenge. In addition, other indications for solar activity - such as the F10.7 index on solar radio flux, SOLERA as EUV proxy or rate of Global Electron Content (dGEC)-, provide additional opportunities for comparisons and validation.</p><p>Through these investigations, we will identify the key parameters useful to improve real-time/prediction of ionospheric/plasmaspheric VTEC, Ne estimates, as well as ionospheric perturbations, in case of extreme solar weather conditions. In general, we will gain a better understanding of space weather events and their effect on Earth’s atmosphere and near-Earth environment.</p>

scholarly journals Comparison of GPS TEC with IRI models of 2007, 2012, AND 1 2016 over Sukkur, Pakistan

2020 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Adil Hussain ◽  
Munawar Shah
Keyword(s):  
Global Positioning System ◽  
Electron Content ◽  
Iri Model ◽  
Low Latitude ◽  
Total Electron ◽  
Gps Tec ◽  
Global Positioning ◽  
Radio Signals ◽  
Ionospheric Scintillations ◽  
Latitude Region

The international reference ionosphere (IRI) models have been widely used for correcting the ionospheric scintillations at different altitude levels. An evaluation on the performance of VTEC correction from IRI models (version 2007, 2012 and 2016) over Sukkur, Pakistan (27.71º N, 68.85º E) is presented in this work. Total Electron Content (TEC) from IRI models and GPS in 2019 over Sukkur region are compared. The main aim of this comparative analysis is to improve the VTEC in low latitude Sukkur, Pakistan. Moreover, this study will also help us to identify the credible IRI model for the correction of Global Positioning System (GPS) signal in low latitude region in future. The development of more accurate TEC finds useful applications in enhancing the extent to which ionospheric influences on radio signals are corrected. VTEC from GPS and IRI models are collected between May 1, 2019 and May 3, 2019. Additionally, Dst and Kp data are also compared in this work to estimate the geomagnetic storm variations. This study shows a good correlation of 0.83 between VTEC of GPS and IRI 2016. Furthermore, a correlation of 0.82 and 0.78 is also recorded for IRI 2012 and IRI 2007 respectively, with VTEC of GPS. The IRI TEC predictions and GPS-TEC measurements for the studied days reveal the potential of IRI model as a good candidate over Pakistan.

Validating the impact of various ionosphere correction on mid to long baselines and point positioning using GPS dual-frequency receivers

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Alaa A. Elghazouly ◽  
Mohamed I. Doma ◽  
Ahmed A. Sedeek
Keyword(s):  
Geomagnetic Storms ◽  
Global Navigation Satellite Systems ◽  
Electron Content ◽  
Assessment Procedure ◽  
Vertical Total Electron Content ◽  
Dual Frequency ◽  
Total Electron ◽  
Satellite Systems ◽  
Point Positioning ◽  
The Impact

Abstract Due to the ionosphere delay, which has become the dominant GPS error source, it is crucial to remove the ionospheric effect before estimating point coordinates. Therefore, different agencies started to generate daily Global Ionosphere Maps (GIMs); the Vertical Total Electron Content (VTEC) values represented in GIMs produced by several providers can be used to remove the ionosphere error from observations. In this research, An analysis will be carried with three sources for VTEC maps produced by the Center for Orbit Determination in Europe (CODE), Regional TEC Mapping (RTM), and the International Reference Ionosphere (IRI). The evaluation is focused on the effects of a specific ionosphere GIM correction on the precise point positioning (PPP) solutions. Two networks were considered. The first network consists of seven Global Navigation Satellite Systems (GNSS) receivers from (IGS) global stations. The selected test days are six days, three of them quiet, and three other days are stormy to check the influence of geomagnetic storms on relative kinematic positioning solutions. The second network is a regional network in Egypt. The results show that the calculated coordinates using the three VTEC map sources are far from each other on stormy days rather than on quiet days. Also, the standard deviation values are large on stormy days compared to those on quiet days. Using CODE and RTM IONEX file produces the most precise coordinates after that the values of IRI. The elimination of ionospheric biases over the estimated lengths of many baselines up to 1000 km has resulted in positive findings, which show the feasibility of the suggested assessment procedure.

scholarly journals Evaluation of the IGS–Global Ionospheric Mapping model over Egypt

2018 ◽  
Author(s):  
Mostafa Rabah ◽  
Ahmed Sedeek
Keyword(s):  
North Africa ◽  
Evaluation Method ◽  
Daily Basis ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
International Gnss Service ◽  
Ionospheric Correction ◽  
Total Electron ◽  
The North ◽  
Using Data

Abstract. Global ionosphere maps (GIM) are generated on a daily basis at CODE using data from about 400 GPS/GLONASS sites of the IGS and other institutions. The vertical total electron content (VTEC) is modeled in a solar-geomagnetic reference frame using a Spherical Harmonics Expansion “SHE” up to degree and order 15. To cover the holes of the first GIM computation stage existing in the North Africa and over the Oceans resulting a shortage of GNSS station in North Africa, an optimum spatial-temporal interpolation technique was developed to cover these holes (Krankowski and Hernandez-Pajares, 2016). The current paper evaluates the ionospheric correction by Global Ionospheric Maps, GIM, provided in (IONEX) files produced by International GNSS Services “IGS”. The evaluation is performed based on investigating the effect of a given GIM ionospheric correction on kinematic relative positioning solutions. The evaluation was done using several baselines of different lengths in Egypt. The results show that there is no significant effect of the provided GIM values on the solution of kinematic processing. The results confirm that although there is a lack of International GNSS Service (IGS stations) over North Africa, GIMs have no effect in mitigating ionospheric error. A new value for the ionosphere correction VTEC values was obtained by a regional, developed algorithm based on zero-differenced phase ionospheric delay (ZDPID) (Tawfeek et al., 2018). These new values of VTEC were fed into GIMs for the specified stations data. A useful result was obtained for correcting the ionospheric error over kinematic solution of many baseline lengths up to 300 km which demonstrates validity of the proposed evaluation method.

scholarly journals Adaptive Modeling of the Global Ionosphere Vertical Total Electron Content

2020 ◽  
Vol 12 (11) ◽  
pp. 1822
Author(s):  
Eren Erdogan ◽  
Michael Schmidt ◽  
Andreas Goss ◽  
Barbara Görres ◽  
Florian Seitz
Keyword(s):  
Total Electron Content ◽  
Temporal Variations ◽  
Model Parameters ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Model Uncertainties ◽  
Data Set ◽  
Total Electron ◽  
B Spline ◽  
Run Time

The Kalman filter (KF) is widely applied in (ultra) rapid and (near) real-time ionosphere modeling to meet the demand on ionosphere products required in many applications extending from navigation and positioning to monitoring space weather events and naturals disasters. The requirement of a prior definition of the stochastic models attached to the measurements and the dynamic models of the KF is a drawback associated with its standard implementation since model uncertainties can exhibit temporal variations or the time span of a given test data set would not be large enough. Adaptive methods can mitigate these problems by tuning the stochastic model parameters during the filter run-time. Accordingly, one of the primary objectives of our study is to apply an adaptive KF based on variance component estimation to compute the global Vertical Total Electron Content (VTEC) of the ionosphere by assimilating different ionospheric GNSS measurements. Secondly, the derived VTEC representation is based on a series expansion in terms of compactly supported B-spline functions. We highlight the morphological similarity of the spatial distributions and the magnitudes between VTEC values and the corresponding estimated B-spline coefficients. This similarity allows for deducing physical interpretations from the coefficients. In this context, an empirical adaptive model to account for the dynamic model uncertainties, representing the temporal variations of VTEC errors, is developed in this work according to the structure of B-spline coefficients. For the validation, the differential slant total electron content (dSTEC) analysis and a comparison with Jason-2/3 altimetry data are performed. Assessments show that the quality of the VTEC products derived by the presented algorithm is in good agreement, or even more accurate, with the products provided by IGS ionosphere analysis centers within the selected periods in 2015 and 2017. Furthermore, we show that the presented approach can be applied to different ionosphere conditions ranging from very high to low solar activity without concerning time-variable model uncertainties, including measurement error and process noise of the KF because the associated covariance matrices are computed in a self-adaptive manner during run-time.

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