Global ionospheric modeling based on multi-GNSS, satellite altimetry, and Formosat-3/COSMIC data

Yao, Yibin; Liu, Lei; Kong, Jian; Zhai, Changzhi

doi:10.1007/s10291-018-0770-6

Cited by 37 publications

(14 citation statements)

References 22 publications

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“…We have used the data of the geomagnetic observatories also shown on this map. From the literature (Yao et al, 2018), it is known that the electron flux distribution consistent with the geomagnetic coordinates. This fact is illustrated both in Fig.…”

Section: Methodsmentioning

confidence: 85%

“…The TEC mapping is a powerful instrument of visualization and studying the ionospheric processes. Global ionospheric maps for the last two decades are actively used in scientific practice (Yao et al, 2018, Hernández-Pajares et al, 2009. In a number of publications, the continental TEC maps are applied as indicators of response of an ionosphere to the powerful tropospheric processes, such as, for example, typhoons (Chou et al, 2016), to the wavelike disturbances caused by tsunami (Tang et al, 2015) or earthquakes (Tsugawa et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Relationship of variations of the total electron content of ionosphere in magnetically conjugated regions with precipitation of high-energy charged particles

Zanimonskiy¹,

Koloskov²,

Yampolski³

et al. 2020

UAJ

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Purpose. A qualitative and quantitative study of the correlation of space-time changes of the total electron content of the ionosphere with variations in the energetic electron flux during a significant increase of the solar wind density and velocity. Determination of the conditions when the increase of the intensity of the flux of energetic electrons can be accompanied by the appearance of large-scale inhomogeneities of the ionosphere observed in magnetically conjugated regions of the Northern and Southern hemispheres. Methods. The research methodology is based on the construction of the time sequence of electron fluxes spatial distributions and their subsequent comparison with the maps of the total electron content (TEC) over North America and the TEC diurnal variations in magnetically conjugated regions. The degree of similarity has been estimated in this paper, and the corresponding correlation coefficients have been obtained. The TEC was calculated from the ground-based Global Navigation Satellite System (GNSS) observations, and the electron fluxes in the ionosphere were obtained from the in situ measurements by the POES satellites. The map-making region was selected by the presence of a dense network of GNSS receivers and the presence of stations in the magnetically conjugated region of the Antarctica, as well as by the favorable configuration of spatial distribution of energetic particles at the orbital height of POES satellites. The study is based on the two geomagnetic disturbances of the St. Patrick's Days in March 2013 and 2015. Results. The satellite and ground-based data during geomagnetic disturbances were processed by using the developed technique. It is found that the consistency of changes in the total electron content of the ionosphere and electron fluxes in time and space coincide with the variation range increase of the horizontal component of the geomagnetic field that has been observed according to the data of ground-based magnetometers and indicates the existence of ionospheric currents in the geospace. According to the analysis of the two events, the assumption is made that the presence of ionospheric currents formed by protons and electrons precipitated from the magnetosphere is one of the conditions for the consistency of changes in the total electron content and electron flux. Conclusions. It is shown that during the geomagnetic disturbances the space-time changes of the ionospheric inhomogeneities are partially consistent with the variations of the fluxes of energetic electrons that allows the possibility of using these observations of TEC as indicators of precipitation.

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Section: Methodsmentioning

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Relationship of variations of the total electron content of ionosphere in magnetically conjugated regions with precipitation of high-energy charged particles

Zanimonskiy¹,

Koloskov²,

Yampolski³

et al. 2020

UAJ

View full text Add to dashboard Cite

show abstract

“…The ionospheric TEC along the ray path between the satellite and receiver can be derived by using dual frequency global navigation satellite system (GNSS) measurements, because of the dispersive characteristics of the ionosphere. For instance, the International GNSS Service (IGS) ionospheric working group, consisting of seven Ionospheric Associate Analysis Centers (IAACs), has started generating reliable global TEC maps based on worldwide GNSS data since 1998, which are widely used in the ionosphere monitoring (Hernández‐Pajares et al, 2009; Li et al, 2015; Schaer, 1999; Yao et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Forecasting Global Ionospheric TEC Using Deep Learning Approach

et al. 2020

Self Cite

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Global ionospheric total electron content (TEC) maps are widely utilized in research regarding ionospheric physics and the associated space weather impacts, so there is a great interest in the community in short‐term ionosphere TEC forecasting. In this study, the long short‐term memory (LSTM) neural network (NN) is applied to forecast the 256 spherical harmonic (SH) coefficients that are traditionally used to construct global ionospheric maps (GIM). Multiple input data, including historical time series of the SH coefficients, solar extreme ultraviolet (EUV) flux, disturbance storm time (Dst) index, and hour of the day, are used in the developed LSTM NN model. Different combinations of the above parameters have been used in constructing the LSTM NN model, and it is found that the model using all four parameters performs the best. Then the best performing LSTM model is used to forecast the SH coefficients, and the global hourly TEC maps are reproduced using the 256 predicted SH coefficients. A comprehensive evaluation is carried out with respect to the CODE GIM TEC. Results show that the first/second hour TEC root mean square error (RMSE) is 1.27/2.20 TECU during storm time and 0.86/1.51 TECU during quiet time, so the developed model performs well during both quiet and storm times. Moreover, typical ionospheric structures, such as equatorial ionization anomaly (EIA) and storm‐enhanced density (SED), are well reproduced in the predicted TEC maps during storm time. The developed model also shows competitive performance in predicting global TEC when compared to the persistence model and two empirical models (IRI‐2016 and NeQuick‐2).

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“…With the completion of Beidou, Galileo, and the establishment of many other regional navigation systems, the number of available navigation satellites will be larger than 120 in combination with Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS). This can provide more observations for ionospheric modeling than ever (Ren et al, ; Yao et al, ; Abdelazeem et al, ; Zhang et al, ). However, the performance of GNSS‐based ionospheric model still highly depends on the number of ground‐based stations and their distribution.…”

Section: Introductionmentioning

confidence: 99%

Performance of GNSS Global Ionospheric Modeling Augmented by LEO Constellation

Ren

Zhang

Schmidt³

et al. 2020

Earth and Space Science

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The Low-Earth-Orbiting (LEO) satellite has a fast motion and thus contributes to rapid changes in satellite geometric distribution, which can effectively mitigate multipath effects and offer more available observations. Recently, some studies have investigated LEO-augmented Global Navigation Satellite System (GNSS) positioning and navigation. However, the study of LEO-augmented global ionospheric modeling was not yet available. In this paper, we present the performance and accuracy of global ionospheric model augmented by LEO constellation for the first time. Based on the three kinds of designed LEO constellations with 60, 96, and 192 satellite simulation data, the results show that LEO observations can expand the coverage and increase the density of ionospheric pierce points (IPPs). Meanwhile, the density of IPPs becomes higher with an increasing number of LEO satellites. When the cutoff elevation is set to 40°, the IPP distribution of GNSS+LEO is still better than that of GNSS-only at 10°. This way the cutoff elevation angle of the GNSS measurements can be increased, since the mapping function error and the multipath effects are reduced. Furthermore, the performances of global ionosphere maps based on the observations of GNSS-only and GNSS+LEO scenarios are evaluated. Compared with GNSS-only, the minimum and maximum bias can be reduced from −18.1 to −7.0 total electron content unit and from 12.6 to 6.4 total electron content unit, respectively, and the root-mean-square values with LEO constellations of 60, 96, and 192 satellites improve by 35.9%, 46.5%, and 50%, respectively. Key Points:• LEO satellite was utilized for global ionosphere modeling • LEO satellite observations can fill the gap of missing spatial and temporal values in existing GNSS-based ionospheric modeling • By combining LEO constellation and Multi-GNSS simulated datasets, higher accuracy and higher spatial model can be achieved

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Global ionospheric modeling based on multi-GNSS, satellite altimetry, and Formosat-3/COSMIC data

Cited by 37 publications

References 22 publications

Relationship of variations of the total electron content of ionosphere in magnetically conjugated regions with precipitation of high-energy charged particles

Relationship of variations of the total electron content of ionosphere in magnetically conjugated regions with precipitation of high-energy charged particles

Forecasting Global Ionospheric TEC Using Deep Learning Approach

Performance of GNSS Global Ionospheric Modeling Augmented by LEO Constellation

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