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A novel ionospheric mapping function modeling at regional scale using empirical orthogonal functions and GNSS data

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Abstract

The ionospheric mapping function (MF) converts the line-of-sight slant total electron content (STEC) into the vertical total electron content (VTEC) and vice versa, and it is an important function in the creation and use of ionospheric models. Most of the existing MFs are only related to satellite elevation angle, the accuracy is low, and it is necessary to establish a MF with higher accuracy. Therefore, this paper considers the differences of MF for different local time (LT) and DOY (day of year), and uses the Global Navigation Satellite Systems (GNSS) STEC observation data from International GNSS Service (IGS) tracking stations in the northern hemisphere mid-latitude region in 2016–2020 to establish a novel MF model. First, we retrieve the mapping coefficient \(\alpha_{h}\) for different LT and DOY, where the results show significant correlation with LT and DOY, and other periodic variations. Then, we use the empirical orthogonal functions (EOF) to decompose the time series, and the first four order EOF components can describe 98.31% of the total variability. Finally, the periodic function is used to fit the time series of EOF, and a small number of model coefficients are obtained. This work employs the differential STEC of 28 IGS tracking stations in the mid-latitudes of the northern hemisphere in 2020 to verify the accuracy of the new MF and compare it with the widely used modified single-layer model (MSLM) MF. The results show that the accuracy of the new MF is higher than the existing MSLM MF when using JPLG (Jet Propulsion Laboratory’s final Global Ionospheric Maps) to convert VTEC to STEC. Compared with MSLM MF, the RMS of the new MF is reduced by 0.24 TECU on average, and the maximum reduction is close to 0.4 TECU (~ 25%). Among the 28 tracking stations that participated in the verification, the new MF is better than MSLM MF on most days, with 7 stations reaching 100% and 20 stations exceeding 95%. For nearly 60% of the days in 2020, the accuracy of the new MF for all tracking stations is better than that of MSLM MF.

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Data availability

The multi-GNSS observables data used in the paper are freely accessible via the CDDIS website https://cddis.nasa.gov/archive/gnss/data/campaign/mgex/, and the final GIMs “JPLG” provided by JPL are also available at the CDDIS website https://cddis.nasa.gov/archive/gnss/products/ionex/. The XUST’s DCBs data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors thank the IGS MGEX for providing the multi-GNSS data, the Jet Propulsion Laboratory (JPL) for providing the final GIMs “JPLG,” and XUST (Xi’an University of Science and Technology) for providing the satellite and receiver DCBs products. This work was supported in part by the National Natural Science Foundation of China under Grant 41404031, in part by the Outstanding Youth Science Fund of Xi’an University of Science and Technology under Grant 2018YQ2-10, and in part by Beijing Key Laboratory of Urban Spatial Information Engineering under Grant 20210206. Thanks to the reviewers for their valuable comments.

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Authors and Affiliations

  1. College of Geomatics, Xi’an University of Science and Technology, Xi’an, 710054, China

    Peng Chen, Rong Wang, Zhiyuan An & Zhihao Wang

  2. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing, 100045, China

    Peng Chen

  3. School of Geodesy and Geomatics, Wuhan University, Wuhan, 430079, China

    Yibin Yao

  4. Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, Wuhan, 430079, China

    Yibin Yao

Authors
  1. Peng Chen
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  2. Rong Wang
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  3. Yibin Yao
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  4. Zhiyuan An
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  5. Zhihao Wang
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Contributions

PC, RW and YBY provided the initial idea and designed the research; PC and RW processed data and wrote the manuscript; ZYA helped to accomplish some test; ZYA and ZHW helped with the writing. All authors provided critical feedback and helped to shape the analysis and manuscript.

Corresponding author

Correspondence to Peng Chen.

Appendix

Appendix

See Tables 4, 5, 6, 7, 8, 9, and 10.

Table 4 Coefficient of \(a_{i}^{(0)}\)
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Table 5 Coefficient of \(a_{i}^{(2k - 1)}\)
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Table 6 Coefficient of \(a_{i}^{(2k)}\)
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Table 7 Coefficient of \(b_{i}^{(0)}\)
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Table 8 Coefficient of \(b_{i}^{(2k - 1)}\)
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Table 9 Coefficient of \(b_{i}^{(2k)}\)
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Table 10 The geographic coordinates of the stations participating in the dSTEC verification
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Chen, P., Wang, R., Yao, Y. et al. A novel ionospheric mapping function modeling at regional scale using empirical orthogonal functions and GNSS data. J Geod 96, 34 (2022). https://doi.org/10.1007/s00190-022-01624-x

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