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The present work analyzes results coming from global maps of ionospheric total electron content (TEC) obtained from observations and from different empirical models like the International Reference Ionosphere (IRI), the model family developed at Trieste and Graz (NeQuick, COSTprof, and NeUoG‐plas), and the GPS operational model (formulation by J. A. Klobuchar). Since they still appear in the context of assessment studies we have also included “old” models like the Bent model. The attention is focused on situations which occurred in the present period of high solar activity, pointing out features like the equatorial anomaly and polar regions, which are crucial test regions for ionospheric TEC models. Experimental estimates of slant TEC from International GPS Service (IGS) stations have been compared particularly with the predictions of the NeQuick and GPS models. A very simple picture of the ionosphere like the one given by the GPS operational model appears to be insufficient to reproduce the global complex behavior of the ionosphere, as it is needed for assessment studies or for modern operational real‐time corrections of transionospheric propagation errors. The IRI estimates of TEC still present serious problems, essentially owing to the topside under high solar activity conditions, and the model cannot be integrated to heights above 2000 km. With processing resources suitable for real‐time operation, it seems that the NeQuick model can give a more widely reliable picture of the TEC estimated from GPS measurements. Computing times for this model are considerably smaller than for more complex models like NeUoG‐plas.
18Mapping high spatial resolution ionospheric total electron content by integrating Time Series InSAR with International Reference Ionosphere model
Mapping high spatial resolution ionospheric total electron content by integrating Time Series InSAR with International Reference Ionosphere model
Read more2Temporal extrapolation of TEC using WNN during 2007–2018 and comparison against GIM, IRI2016 and Kriging
Temporal extrapolation of TEC using WNN during 2007–2018 and comparison against GIM, IRI2016 and Kriging
A sequential calibration technique to improve IRI using TEC estimates of the GNSS network in Europe
<p>The development of space-geodetic observation techniques has brought out a wide range of applications such as positioning and navigation, where the Global Navigation Satellite System (GNSS) is the main tools to provide surveying measurements in these applications. Though GNSS signals enable the calculation of receiver's position, some errors restrict their accuracy. Among these errors, the ionospheric delay is considered as an important error source in the Standard Point Positioning (SPP) applications. Empirical ionospheric models such as Klobuchar, International Reference Ionosphere (IRI), and NeQuick are often applied for computing the Total Electron Content (TEC) within ionosphere and its equivalent delays. However the simulation and forecasting skills of these models are limited due to the simplified model structures and model sensitivity to the calibration period. In this study, we present a novel sequential Calibration approach based on the Ensemble Kalman Filter (C-EnKF) to improve the performance of TEC estimations for SPP applications. To demonstrate the results, the IRI model is used as our basis and the TEC estimates from 56 IGS stations in Europe are applied as observation. The C-EnKF is applied to calibrate some selected model parameter so that IRI can be tuned over Europe. The numerical assessments are performed against the TEC estimates from dual frequency GNSS measurements and against the final IONEX products (that are available with 11 days delays). Based on the forecasting results (during September 2017), we show that the accuracy of TEC estimates from the C-EnKF is improved in the range of 3.7-64.87% compared to IRI. <strong>Keywords: </strong>Ionosphere, Sequential Calibration, Ensemble Kalman Filter (EnKF), IRI, Total Electron Content (TEC), Standard Point Positioning (SPP), GNSS</p>
Read more6Mapping of the Ionospheric Total Electron Content over the East African Low–Latitude Region
Mapping of the Ionospheric Total Electron Content over the East African Low–Latitude Region
6Comparing the IRI prediction with the observed equatorial anomaly in the Total Electron Content around 120° E longitude
Comparing the IRI prediction with the observed equatorial anomaly in the Total Electron Content around 120° E longitude
7Comparison of temporal fluctuations in the total electron content estimates from EISCAT and GPS along the same line of sight
Abstract. The impact of space weather events on satellite-based technologies (e.g. satellite navigation and precise positioning) is typically quantified on the basis of the total electron content (TEC) and temporal fluctuations associated with it. GNSS (global navigation satellite systems) TEC measurements are integrated over a long distance and thus may include contributions from different regions of the ionised atmosphere which may prevent the resolution of the mechanisms ultimately responsible for given observations. The purpose of the experiment presented here was to compare TEC estimates from EISCAT and GPS measurements. The EISCAT measurements were obtained along the same line of sight of a given GPS satellite observed from Tromsø. The present analyses focussed on the comparison of temporal fluctuations in the TEC between aligned GPS and EISCAT measurements. A reasonably good agreement was found between temporal fluctuations in TEC observed by EISCAT and those observed by a co-located GPS ionospheric monitor along the same line of sight, indicating a contribution from structures at E and F altitudes mainly to the total TEC in the presence of ionisation enhancements possibly caused by particle precipitation in the nighttime sector. The experiment suggests the great potential in the measurements to be performed by the future EISCAT_3D system, limited only in the localised geographic region to be covered.
Read more124Performance of different TEC models to provide GPS ionospheric corrections
Performance of different TEC models to provide GPS ionospheric corrections
9A quantitative analysis of latitudinal variation of ionospheric total electron content and comparison with IRI-2020 over China
A quantitative analysis of latitudinal variation of ionospheric total electron content and comparison with IRI-2020 over China
Read more4Regional and seasonal parametric probability density function estimation for Total Electron Content
In this study, within the hour parametric probability density functions are calculated by using TEC (Total Electron Content) estimates. TEC estimates are obtained from IONOLAB-TEC method by using TNPGN-Active GPS network. GPS stations are placed at intervals with an average range of 80–100 km distance, between the years 2009 and 2012, provided input for calculation of probability density functions. The IONOLAB-TEC values within-an-hour are grouped depending on latitude, longitude, region and season. PDF estimates of IONOLAB-TEC are obtained and grouped according to latitude and longitude variation. It is observed that TEC values have a strong hourly, seasonal and positional dependence On east-west direction, the growing trend shifts according to sunrise and sunset times. In this context, geography of Turkey is separated into regions which are in 2° in latitude and 3° in longitude. A representative GPS station is chosen within each region. Within-the-hour pdf estimates are grouped into ionospheric seasons as Winter, Summer, March equinox and September equinox. In winter and summer seasons, Lognormal distribution is observed. During equinox seasons Weibull distribution is observed more frequently. Pdf estimates of TEC of the ionosphere over Turkey will contribute to developing a regional and seasonal random field model.
Read more18Comparing vertical total electron content from GPS, Bent and IRI models with TOPEX-Poseidon
Comparing vertical total electron content from GPS, Bent and IRI models with TOPEX-Poseidon
74The International GPS Service (IGS) Ionosphere Working Group
The International GPS Service (IGS) Ionosphere Working Group
1Pattern of variation of TEC, hmF2 and foF2, and their correlation during the geomagnetic storm time conditions
Pattern of variation of TEC, hmF2 and foF2, and their correlation during the geomagnetic storm time conditions
2Ionospheric Effects on High Gain Antenna GNSS Measurements � TEC Estimation and Correction
The ionospheric delay of global navigation satellite systems (GNSS) signals typically is compensated by adding a single correction value to the pseudorange measurement of a GNSS receiver. Yet, this neglects the dispersive nature of the ionosphere. In this context we analyze the ionospheric signal distortion beyond a constant delay. These effects become increasingly significant with the signal bandwidth and hence more important for new broadband navigation signals. Using measurements of the Galileo E5 signal, captured with a high gain antenna, we verify that the expected influence can indeed be observed and compensated. A new method to estimate the total electron content (TEC) from a single frequency high gain antenna measurement of a broadband GNSS signal is proposed and described in detail. The received signal is de facto unaffected by multi-path and interference because of the narrow aperture angle of the used antenna which should reduce the error source of the result in general. We would like to point out that such measurements are independent of code correlation, like in standard receiver applications. It is therefore also usable without knowledge of the signal coding. Results of the TEC estimation process are shown and discussed comparing to common TEC products like TEC maps and dual frequency receiver estimates.
Read more18Global TEC Map Fusion Through a Hybrid Deep Learning Model: RFGAN
Timely, reliable and comprehensive global observation information is essential for space weather research. However, limited observation technology hinders the consecutive global coverage of observation data. For the integrity and continuity of the global observation data, deep learning can obtain a global Ionospheric total electron content (TEC) map by fusing multi‐source TEC maps. Different from the previous methods, in the study, a deep learning hybrid model (RFGAN) based on Dual‐Discriminator Conditional Generative Adversarial Network (DDcGAN) and Free‐Form Image Inpainting with Gated Convolution (Deepfill v2) is proposed to fuse the Massachusetts Institute of Technology (MIT)—TEC, International Global Navigation Satellite System TEC (IGS‐TEC) and altimetry satellite TEC. Throughout the RFGAN structure, we use an autoencoder model with gated convolution to inpaint the missing parts of MIT‐TEC and altimetry satellite TEC. Meanwhile, DDcGAN fuses the inpainted MIT‐TEC (MIT'‐TEC) and IGS‐TEC to get a global TEC map with high accuracy. To a certain extent, we inpainted the ocean area of MIT‐TEC through RFGAN. At the same time, RFGAN keeps the consistency of RFGAN‐TEC and MIT‐TEC in the continent area. Our proposed deep learning hybrid model can be easily extended and widely applied to other fields of space science, especially in addressing observational data loss and multi‐source data fusion.
Read moreAssessment of performance of two ionospheric models: NeQuick 2 and IRI-2016 over Equatorial, Low-Latitude, and High-Latitude regions for low solar activity year 2008 of Solar Cycle 23
This work evaluates the performance of two standard models for specifying Earth's ionospheric parameters, the International Reference Ionosphere (IRI) and the NeQuick model.The performance of these models has been validated for Antarctica (ANT) (High latitude; Geographic: 70.46 S, 11.13 E; Geomagnetic: 62.45 S), Trivandrum (TRV) (Equatorial, Geographic: 8.524 N, 76.936 E; Geomagnetic:0.3N) and Delhi (DEL) (Low latitude, Geographic: 28.637 N, 77.174 E; Geomagnetic:22.4N).For this, the Total Electron Content (TEC) values estimated from these models for the locations are compared with the TEC values derived from the Global Ionospheric Scintillation and TEC Monitoring (GISTM) Systems present at the respective locations for the year 2008 which was at the descending phase of Solar Cycle 23.The results show that the equatorial TEC exhibits semi-annual, annual, and seasonal variations with maximum values appearing during equinoctial months and minimum during solstitial months.The low latitude TEC also exhibits similar variations but at times delayed.Generally, the TEC values produced by the IRI and NeQuick 2 models agree with the observed TEC for TRV and DEL but the models significantly underestimate the TEC at ANT at all times.For Diurnal variation, both the models show a good correlation during the noon time for the equatorial and low latitude stations but not for the high latitude station.For post-sunset and post-midnight periods, quite a disagreement is seen between the models and observed TEC for all three stations.So, it can be said that both IRI and NeQuick 2 models can predict TEC with good correlation in most cases for the Equatorial and Low Latitude stations but are incapable for high latitude regions.
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