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, 22:104 | Cite as

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

  • Yibin YaoEmail author
  • Lei LiuEmail author
  • Jian Kong
  • Changzhi Zhai
Original Article

Abstract

Ionosphere total electron content (TEC) from global ionospheric maps (GIM) is widely applied in both ionospheric delay correction and research on space weather monitoring. Global ionospheric modeling based on multisource data is an effective method to improve conventional GIM accuracy and reliability. In this study, a global ionospheric model is constructed from multi-GNSS (here, GPS/GLONASS/BDS), satellite altimetry and Formosat-3/COSMIC (F3/C) observations using a spherical harmonic (SH) function. The results show that compared to the conventional GIM derived from GPS/GLONASS data, the combined GIM performance from multisource data improves significantly; the RMS versus external data decreases from [2, 5] to [2, 3] TECU, and the BIAS decreases from [− 3, 1] to [− 1, 1] TECU. Specifically, BDS observations improve the IPP distributions, especially over the region of Australia; compared with GPS-based ionospheric TEC. Our calculated GIM with BDS data has better performance than that without BDS data. By combining JASON 2 and GPS/GLONASS data, the residual distribution is more concentrated, and the RMS is improved effectively in mid-high latitudes of the southern hemisphere and in the equatorial region. F3/C TEC also exhibits relatively minor improvements on GIM; the standard deviation reduces from 2.89 to 1.92 TECU, and the BIAS regarding extra F3/C data decreases from − 2.02 to − 1.71 TECU.

Keywords

Global ionospheric maps (GIM) Total electron content (TEC) Multi-GNSS Satellite altimetry Formosat-3/COSMIC (F3/C) occultation 

Notes

Acknowledgements

This work was supported by the National Key Research and Development Program of China (No. 2016YFB0501803), the National Natural Science Foundation of China (No. 41574028), and the Natural Science Foundation for Distinguished Young Scholars of Hubei Province of China (No. 2015CFA036). The authors gratefully acknowledge the CDDIS for GNSS observations, NOAA for satellite altimetry data, and CDAAC for F3/C “ionPrf” products.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Geodesy and GeomaticsWuhan UniversityWuhanChina
  2. 2.Key Laboratory of Geospace Environment and Geodesy, Ministry of EducationWuhan UniversityWuhanChina
  3. 3.Collaborative Innovation Center for Geospatial TechnologyWuhanChina
  4. 4.Chinese Antarctic Center of Surveying and MappingWuhan UniversityWuhanChina

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