Abstract
Benefiting from global multi-frequency and multi-constellation GNSS measurements provided by the experimental International GNSS real-time service (IGS RTS), a predicting-plus-modeling approach employed by Chinese Academy of Sciences (CAS) for the routine generation of real-time global ionospheric maps (RT-GIM) is first reported. Along with RT-GIMs generated by Universitat Politècnica de Catalunya (UPC), the quality of CAS and UPC RT-GIMs in IONEX format is assessed during a low soar activity period from September 2017 to December 2019. The differential slant total electron contents (dSTEC) derived from 50 GPS stations of the IGS and Jason-3 vertical TECs (VTEC) over the ocean are used as references. In comparison with different reference TECs, CAS and UPC RT-GIMs are approximately 1.7–4.9% and 8.6–12.5% worse than the respective post-processed GIMs CASG and UQRG, respectively. Using RTCM ionospheric data streams from CAS, Centre National d’Etudes Spatiales (CNES) and UPC, the first experimental IGS combined RT-GIM is generated and validated in actual real-time conditions. Compared to Jason-3 VTEC measurements available during the period of common availability, from October 2018 to April 2019, RT-GIM discrepancies present similar relative RMS errors, which are 33, 36, 36 and 38% for CNES, combined one, UPC and CAS, respectively. Aside from a better understanding of the influence of working in the original IONEX versus RTCM ionospheric formats, the update to a new experimental adaptation of RT strategy is highlighted by UPC, and the computation of multi-layer RT-GIM is emphasized by CAS in view of the inadequacy of single-layer ionospheric assumption in the presence of large latitudinal gradients.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Data availability
CAS, CNES and UPC RT ionospheric data streams are routinely transmitted via the respective NTRIP caster. CAS RT-GIMs in IONEX format are publicly available from ftp://ftp.gipp.org.cn/product/ionex/.
References
Amiri-Simkooei A, Asgari J (2012) Harmonic analysis of total electron contents time series: methodology and results. GPS Solut 16(1):77–88
Azpilicueta F, Brunini C (2008) Analysis of the bias between TOPEX and GPS vTEC determinations. J Geod 83(2):121–127
Caissy M, Agrotis L, Weber G, Hernández-Pajares M, Hugentobler U (2012) Coming soon—the international GNSS real-time service. GPS World. http://gpsworld.com/gnss-systemaugmentation-assistanceinnovation-coming-soon-13044/
Ciraolo L, Azpilicueta F, Brunini C, Meza A, Radicella S (2007) Calibration errors on experimental slant total electron content (TEC) determined with GPS. J Geod 81(2):111–120
Dow JM, Neilan RE, Rizos C (2009) The international GNSS service in a changing landscape of global navigation satellite systems. J Geod 83(3–4):191–198
Feltens J, Angling M, Jackson-Booth N, Jakowski N, Hoque M, Hernández-Pajares M, Aragón-Àngel A, Orús R, Zandbergen R (2011) Comparative testing of four ionospheric models driven with GPS measurements. Radio Sci 46(6):1–11
García-Rigo A, Monte E, Hernández-Pajares M, Juan JM, Sanz J, Aragón-Angel A, Salazar D (2011) Global prediction of the vertical total electron content of the ionosphere based on GPS data. Radio Sci 46(6):1–3
García-Rigo A, Roma D, Hernández-Pajares M (2018) Towards RT assessment of ionospheric monitoring within IAG’s RTIM-WG. In: EGU General Assembly 2018, Apr 8–13, Vienna, Austria
Hernández-Pajares M, Roma-Dollase D (2017a) Examples of IGS real-time Ionospheric information benefits: space weather monitoring, precise farming and RT-GIMs. In: IGS workshop 2017, Jul 3–7, Paris, France
Hernández-Pajares M, Juan J, Sanz J (1999) New approaches in global ionospheric determination using ground gps data. J Atmos Sol Terr Phys 61(16):1237–1247
Hernández-Pajares M, Juan JM, Sanz J, Orus R, Garcia-Rigo A, Feltens J, Komjathy A, Schaer SC, Krankowski A (2009) The IGS VTEC maps: a reliable source of ionospheric information since 1998. J Geod 83(3–4):263–275
Hernández-Pajares M, Aragón-Ángel À, Defraigne P, Bergeot N, Prieto-Cerdeira R, García-Rigo A (2014) Distribution and mitigation of higher-order ionospheric effects on precise GNSS processing. J Geophys Res Solid Earth. https://doi.org/10.1002/2013JB010568
Hernández-Pajares M, Roma-Dollase D, Krankowski A, García-Rigo A, Orús-Pérez R (2017) Methodology and consistency of slant and vertical assessments for ionospheric electron content models. J Geod 91(12):1405–1414
Jakowski N, Hoque M, Mayer C (2011a) A new global TEC model for estimating transionospheric radio wave propagation errors. J Geod 85(12):965–974
Jakowski N, Mayer C, Hoque MM, Wilken V (2011b) Total electron content models and their use in ionosphere monitoring. Radio Sci. https://doi.org/10.1029/2010RS004620
Jee G, Lee HB, Solomon SC (2014) Global ionospheric total electron contents (TECs) during the last two solar minimum periods. J Geophys Res Space Phys 119(3):2090–2100
Juan JM, Rius A, Hernandez-Pajares M, Sanz J (1997) A two-layer model of the ionosphere using global positioning system data. Geophys Res Lett 24(4):393–396
Komjathy A, Sparks L, Wilson BD, Mannucci AJ (2005) Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms. Radio Sci. https://doi.org/10.1029/2005RS003279
Krankowski A, Hernandez-Pajares M, Cherniak I, Roma-Dollase D, Zakharenkova I, Ghoddousi-Fard R, Yuan Y, Li Z, Zhang H, Shi C, Feltens J, Komjathy A, Vergados P, Schaer S, Garcia-Rigo A, Gómez-Cama JM (2017) Ionosphere Working Group Technical Report 2016. In: Villiger A, Dach R (eds) IGS Technical Report 2016. Astronomical Institute University of Bern, pp 155–162
Laurichesse D, Blot A (2015) New CNES real time products including BeiDou. IGS Mail No. 7183, 10 Nov 2015
Li Z, Yuan Y, Wang N, Hernandez-Pajares M, Huo X (2015) SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions. J Geod 89(4):331–345
Li M, Yuan Y, Wang N, Li Z, Huo X (2018) Performance of various predicted GNSS global ionospheric maps relative to GPS and JASON TEC data. GPS Solut 22(2):55
Liu T, Zhang B, Yuan Y, Li M (2018) Real-time precise point positioning (RTPPP) with raw observations and its application in real-time regional ionospheric VTEC modeling. J Geod 92(11):1267–1283
Mannucci A, Wilson B, Yuan D, Ho C, Lindqwister U, Runge T (1998) A global mapping technique for GPS-derived ionospheric total electron content measurements. Radio Sci 33(3):565–582
Orús R, Hernández-Pajares M, Juan J, Sanz J (2005) Improvement of global ionospheric VTEC maps by using kriging interpolation technique. J Atmos Sol Terr Phys 67(16):1598–1609
Roma-Dollase D, Hernández-Pajares M, Krankowski A, Kotulak K, Ghoddousi-Fard R, Yuan Y, Li Z, Zhang H, Shi C, Wang C (2018a) Consistency of seven different GNSS global ionospheric mapping techniques during one solar cycle. J Geod 92(6):691–706
Roma-Dollase D, Hernández-Pajares M, García-Rigo A, Krankowski A (2018b) Looking for optimal ways to combine global ionospheric maps in real-time. In: IGS workshop 2018, Oct 29–Nov 2, Wuhan
Roma-Dollase D, Hernández-Pajares M, García-Rigo A, Krankowski A, Fron A, Laurichesse D, Blot A, Orus-Perez R (2018c) Assessment methodology for global ionospheric maps of electron content and potential adaptation to real-time. In: URSI AT-RASC meeting, Oct 29–Jun 1, Gran Canaria
RTCM-SC (2014) Proposal of new RTCM SSR messages, SSR Stage 2: Vertical TEC (VTEC) for RTCM Standard 10403.2 Differential GNSS (global navigation satellite system) Services—Version 3. RTCM Special Committee 104
RTCM-SC (2016) RTCM Standard 10403.3 Differential GNSS (Global Navigation Satellite System) Services—Version 3. RTCM Special Committee 104, Oct 7 2016
Sanz J, Juan JM, Rovira-Garcia A, González-Casado G (2017) GPS differential code biases determination: methodology and analysis. GPS Solut 21(4):1549–1561
Schaer S (1999) Mapping and predicting the earths ionosphere using the global positioning system. Ph.D. dissertation, University of Bern, Bern
Wang N, Li Z (2018) Benefits of IGS RTS for real time ionospheric space weather monitoring. In: IGS Workshop 2018, Oct 29–Nov 2, Wuhan
Wang N, Yuan Y, Li Z, Montenbruck O, Tan B (2016) Determination of differential code biases with multi-GNSS observations. J Geod 90(3):209–228
Wang N, Li Z, Montenbruck O, Tang C (2019) Quality assessment of GPS, Galileo and BeiDou-2/3 satellite broadcast group delays. Adv Space Res 64(9):1764–1779
Weber G, Mervart L, Lukes Z, Rocken C, Dousa J (2007) Real-time clock and orbit corrections for improved point positioning via NTRIP. In: Proceedings of the ION GNSS 2007. Institute of Navigation, pp 1992–1998
Yuan Y, Ou J (2002) Differential areas for differential stations (DADS): a new method of establishing grid ionospheric model. Chin Sci Bull 47(12):1033–1036
Yuan Y, Ou J (2004) A generalized trigonometric series function model for determining ionospheric delay. Prog Nat Sci 14(11):1010–1014
Zhang B (2016) Three methods to retrieve slant total electron content measurements from ground-based GPS receivers and performance assessment. Radio Sci 51(7):972–988
Acknowledgments
The authors acknowledge the IGS and other agencies for providing real-time GNSS data and products. This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA17010202), the National Natural Science Foundation of China (41674043, 41704038), the National Key Research Program of China (2017YFGH002206), and the Youth Innovation Promotion Association of the Chinese Academy of Sciences.
Author information
Authors and Affiliations
Contributions
ZL, NW and MH designed the research; ZL and NW performed the research and wrote the paper; ZL, NW, MH analyzed the data; AL, JZ AG and DR also contributed to the data analysis; YY, AK, HY, DL and AB gave helpful discussions on additional analyses and result interpretation.
Corresponding author
Rights and permissions
About this article
Cite this article
Li, Z., Wang, N., Hernández-Pajares, M. et al. IGS real-time service for global ionospheric total electron content modeling. J Geod 94, 32 (2020). https://doi.org/10.1007/s00190-020-01360-0
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00190-020-01360-0