Skip to main content
SpringerLink
Log in

Quality assessment of the ionospheric density profiles based on long-term COSMIC 1 and 2 radio occultation observations

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Abstract

The ionosphere is a part of the Earth’s atmosphere with complex temporal and spatial distribution and variation. Radio occultation can obtain the vertical distribution of ionosphere, effectively making up for the deficiencies of ground-based Global Navigation Satellite System (GNSS) and other ionospheric sounding technologies; however, the inversion results are subject to the hypothesis model and observation accuracy, making it important to conduct quality assessment. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) project started in 2006 and has been renewed since 2019. So far, a large amount of observation data has been accumulated. In this paper, we used the electron density profile data obtained by COSMIC-1 and COSMIC-2 to evaluate the quality. Four evaluation parameters, which only consider the profile’s self-characteristics, were used, and the spatiotemporal distribution characteristics of the data quality were analyzed. The experimental results show that the number of occultation electron density profiles of COSMIC-2 is significantly greater, which is about seven times greater than COSMIC-1. In terms of spatial distribution, the unqualified ratio of COSMIC-1 profiles is less than 25% in most mid-latitude areas and about 15% near the equator, while the unqualified ratio rises to 25–50% in high-latitude areas and reaches 65% or even higher in part of the polar region. The unqualified ratio of COSMIC-2 profiles is about 25% near the equator and about 15% in middle and low-latitude areas. In terms of seasonal distribution, the quality of profiles is the worst in winter, followed by summer, and best in spring and autumn. In terms of day–night distribution, the unqualified ratio is higher at night than daytime and changes significantly at the turn of day and night. The nmF2 and hmF2 of the qualified profiles are significantly higher near the magnetic equator than in other regions, exhibiting a double-peaked phenomenon. The case of a large geomagnetic storm shows that the qualified ratio of inversion results can still maintain about 70% during extremely severe magnetic storms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

References

  • Anthes R and Schreiner W 2019 Six new satellites watch the atmosphere over Earth’s equator; EoS 100, https://doi.org/10.1029/2019EO131779.

  • Bowhill S A 1974 Satellite transmission studies of spread-F produced by artificial heating of the ionosphere; Radio Sci. 9(11) 975–986.

    Article  Google Scholar 

  • Chen Y, Shao X, Cao C and Ho S 2021 Simultaneous radio occultation predictions for inter-satellite comparison of bending angle profiles from COSMIC-2 and GeoOptics; Remote Sens. 13(18) 3644.

    Article  Google Scholar 

  • Cherniak I, Zakharenkova I, Braun J, Wu Q, Pedatella N, Schreiner W, Weiss J and Hunt D 2021 Accuracy assessment of the quiet-time ionospheric F2 peak parameters as derived from COSMIC-2 multi-GNSS radio occultation measurements; J. Space Weather Space Clim. 11 18.

    Article  Google Scholar 

  • Cucurull L, Kuo Y, Barker D and Rizvi S 2006 Assessing the impact of simulated COSMIC GPS radio occultation data on weather analysis over the Antarctic: A case study; Mon. Wea. Rev. 134(11) 3283–3296.

    Article  Google Scholar 

  • Deng N, Bai W, Sun Y, Du Q, Xia J, Wang X, Liu C, Cai Y, Meng X, Yin C, Huang F, Hu P, Tan G and Liu X 2022 Evaluation of forward models for GNSS radio occultation data processing and assimilation; Remote Sens. 14(5) 1081.

    Article  Google Scholar 

  • Garcia-Fernandez M, Hernandez-Pajares M, Juan J M and Sanz J 2005 Performance of the improved Abel transform to estimate electron density profiles from GPS occultation data; GPS Solutions 9(2) 105–110.

    Article  Google Scholar 

  • Guo P, Xu X and Zhang G 2011 Analysis of the ionospheric equivalent slab thickness based on ground-based GPS/TEC and GPS/COSMIC RO measurements; J. Atmos. Sol.-Terr. Phys. 73(7–8) 839–846.

    Article  Google Scholar 

  • Hernández-Pajares M, Juan J, Sanz J, Aragón-Àngel À, García-Rigo A, Salazar D and Escudero M 2011 The ionosphere: Effects, GPS modeling and the benefits for space geodetic techniques; J. Geodesy 85 887–907.

    Article  Google Scholar 

  • Ho S, Anthes R A, Ao C O, Healy S, Horanyi A, Hunt D, Mannucci A J, Pedatella N, Randel W J, Simmons A, Steiner A, Xie F, Yue X and Zeng Z 2020 The COSMIC/FORMOSAT-3 radio occultation mission after 12 years: Accomplishments, remaining challenges, and potential impacts of COSMIC-2; Bull. Am. Meteorol. Soc. 101(7) E1107–E1136.

    Article  Google Scholar 

  • Horvath I and Lovell B 2010 Large-scale traveling ionospheric disturbances impacting equatorial ionization anomaly development in the local morning hours of the Halloween Superstorms on 29–30 October 2003; J. Geophys. Res.: Space Phys. 115(A4).

  • Jakowski N, Leitinger R and Angling M 2004 Radio occultation techniques for probing the ionosphere; Ann. Geophys. 47 1049–1066.

    Google Scholar 

  • Kakinami Y, Liu J, Tsai L C and Oyama K 2010 Ionospheric electron content anomalies detected by a FORMOSAT-3/COSMIC empirical model before and after the Wenchuan Earthquake; Int. J. Remote Sens. 31(13) 3571–3578.

    Article  Google Scholar 

  • Kelley M C, Wong V K, Aponte N, Coker C, Mannucci A and Komjathy A 2009 Comparison of COSMIC occultation-based electron density profiles and TIP observations with Arecibo incoherent scatter radar data; Radio Sci. 44(04) 1–13.

    Article  Google Scholar 

  • Krankowski A, Zakharenkova I, Krypiak-Greorczyk A, Shagimuratov I and Wielgosz P 2011 Ionospheric electron density observed by FORMOSAT-3/COSMIC over the European region and validated by ionsonde data; J. Geodesy 85(12) 949–964.

    Article  Google Scholar 

  • Kursinski E, Hajj G, Leroy S and Herman B 2000 The GPS radio occultation technique; TAO 11(1) 53–114.

    Article  Google Scholar 

  • Lanyi G and Roth T 1988 A comparison of mapped and measured total ionospheric electron content using global positioning system and beacon satellite observations; Radio Sci. 23(4) 483–492.

    Article  Google Scholar 

  • Lasota E 2021 Comparison of different machine learning approaches for tropospheric profiling based on COSMIC-2 data; Earth Planet. Space 73(1) 1–18.

    Article  Google Scholar 

  • Lei J, Syndergaard S, Burns A, Solomon S, Wang W, Zeng Z, Roble R, Wu Q, Kuo Y, Holt J, Zhang S, Hysell D, Rodrigues F and Lin C 2007 Comparison of COSMIC ionospheric measurements with ground-based observations and model predictions: Preliminary results; J. Geophys. Res.: Space Phys. 112(A07308) 1–10.

    Google Scholar 

  • Linty N, Farasin A, Favenza A and Dovis F 2019 Detection of GNSS ionospheric scintillations based on machine learning decision tree; IEEE Trans. Aerosp. Electron. Syst. 55(1) 303–317.

    Article  Google Scholar 

  • Liu Z, Skone S, Gao Y and Komjathy A 2005 Ionospheric modeling using GPS data; GPS Solutions 9 63–66.

    Article  Google Scholar 

  • Liu L, Zhao B, Wan W, Ning B, Zhang M and He M 2009 Seasonal variations of the ionospheric electron densities retrieved from Constellation Observing System for meteorology, ionosphere, and climate mission radio occultation; J. Geophys. Res. 114(1) A02302.

    Google Scholar 

  • Liu T, Lin C, Lin C, Lee I, Sun Y, Chen S, Chang F, Rajesh P, Hsu C, Matsuo T, Chen C and Tsai H 2022 Retrospect and prospect of ionospheric weather observed by FORMOSAT-3/COSMIC and FORMOSAT-7/COSMIC-2; Terr. Atmos. Ocean. Sci. 33(1) 20.

    Article  Google Scholar 

  • Matzka J, Stolle C, Yamazaki Y, Bronkalla O and Morschhauser A 2021 The geomagnetic Kp index and derived indices of geomagnetic activity; Space Weather 19(5) e2020SW002641.

    Article  Google Scholar 

  • Perevalova N, Romanova E and Tashchilin A 2020 Detection of high-latitude ionospheric structures using GNSS; J. Atmos. Sol.-Terr. Phys. 207 105335.

    Article  Google Scholar 

  • Potula B, Chu Y, Uma G, Hsia H and Wu K 2011 A global comparative study on the ionospheric measurements between COSMIC radio occultation technique and IRI model; J. Geophys. Res.: Space Phys. 116(A2).

  • Rishbeth H 1998 How the thermospheric circulation affects the ionosphere F2 layer; Atmos. Terr. Phys. 30 1385–1402.

    Article  Google Scholar 

  • Sai Gowtam V and Tulasi Ram S 2017 An artificial neural network-based ionospheric model to predict NmF2 and hmF2 using long-term data set of FORMOSAT-3/COSMIC radio occultation observations: Preliminary results; J. Geophys. Res.: Space Phys. 122(11) 11,743-11,755.

    Article  Google Scholar 

  • Sardon E, Rius A and Zarraoa N 1994 Estimation of transmitter and receiver differential biases and the ionospheric total electron content from global positioning system observations; Radio Sci. 29(3) 577–586.

    Article  Google Scholar 

  • Schreiner W, Sokolovskiy S, Rocken C and Hunt D 1999 Analysis and validation of GPS/MET radio occultation data in the ionosphere; Radio Sci. 34(4) 949–966.

    Article  Google Scholar 

  • Schreiner W, Rocken C, Sokolovskiy S and Hunt D 2007 Estimates of the precision of GPS radio occultations from COSMIC/FORMOSAT-3 mission; Geophys. Res. Lett. 34(4).

  • Schreiner W, Weiss J, Anthes R, Chu V, Fong J, Hunt D, Kuo Y, Meehan T, Serafino W, Sjoberg J, Sokolovskiy S, Talaat E, Wee T and Zeng Z 2020 COSMIC-2 radio occultation constellation: First results; Geophys. Res. Lett. 47(4) e2019GL086841.

    Article  Google Scholar 

  • Sokolovskiy S, Rocken C, Lenschow D, Kuo Y, Anthes A, Schreiner W and Hunt D 2007 Observing the moist troposphere with radio occultation signals from COSMIC; Geophys. Res. Lett. 34(18), https://doi.org/10.1029/2006GL030458.

  • Stolle C, Lühr H, Rother M and Balasis G 2006 Magnetic signatures of equatorial spread F as observed by the CHAMP satellite; J. Geophys. Res.: Space Phys. 111(A2).

  • Straus P, Schreiner W, Santiago J, Talaat E and Lin C 2020 FORMOSAT-7/COSMIC-2 TGRS space weather provisional data release 1; Technical Report, NOAA, USAF and NSP.

  • Uma G, Brahmanandam P and Chu Y 2016 A long-term study on the deletion criterion of questionable electron density profiles caused by ionospheric irregularities – COSMIC radio occultation technique; Adv. Space Res. 57(12) 2452–2463.

    Article  Google Scholar 

  • Ware R, Exner M, Feng D, Gorbunov M, Hardy K, Herman B, Kuo Y, Meehan T, Melbourne W, Rocken C, Schreiner W, Sokolovskiy S, Solheim F, Zou X, Anthes R, Businger S and Trenberth K 1996 GPS sounding of the atmosphere from low earth orbit: Preliminary results; Bull. Am. Meteorol. Soc. 77(1) 19–40.

    Article  Google Scholar 

  • Xu X, Li J, Luo J and Sun F 2018 Quality check of COSMIC occultation electron density profiles; J. Nat. Univ. Def. Technol. 40(05) 54–59 (in Chinese).

    Google Scholar 

  • Xu J, Wang Q, Ke F, Zhang B, Yan C and Zhang H 2021 Analysis of ionospheric parameters retrieved from Feng-Yun 3C and COSMIC radio occultation; Adv. Space Res. 68(1) 214–224.

    Article  Google Scholar 

  • Yang K, Chu Y, Su C, Ko H and Wang C 2009 An examination of FORMOSAT-3/COSMIC ionospheric electron density profile: Data quality criteria and comparisons with the IRI model; Terrestrial Atmospheric and Oceanic Sciences 20(1) 193–206.

    Article  Google Scholar 

  • Yue X, Schreiner W, Pedatella N, Richard A, Mannucci A, Straus P and Liu J 2014 Space Weather Observations by GNSS radio occultation: From FORMOSAT-3/COSMIC to FORMOSAT-7/COSMIC-2; Space Weather 12(11) 616–621.

    Article  Google Scholar 

Download references

Acknowledgements

Thanks for the COSMIC electron density profiles provided by UCAR. This research was supported by the National Natural Science Foundation of China (41604017), Guangdong Basic and Applied Basic Research Foundation (2019A1515011268) and the Guangzhou Science and Technology Plan Project (202102020380).

Author information

Authors and Affiliations

  1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou, 510642, China

    Na Fu, Rui Zhang, Qixin Pan, Shaoqiu Long & Chaolong Yao

  2. Guangdong Province Key Laboratory for Land Use and Consolidation, Guangzhou, 510642, China

    Rui Zhang, Shaoqiu Long & Chaolong Yao

  3. Key Laboratory of Construction Land Transformation, Ministry of Natural Resources, Guangzhou, 510642, China

    Rui Zhang, Shaoqiu Long & Chaolong Yao

  4. Geodetic Data Processing Center, Ministry of Natural Resources, Xi’an, 710054, China

    Xiaojing Tian

Authors
  1. Na Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rui Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qixin Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaojing Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shaoqiu Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Chaolong Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Rui Zhang and Na Fu contributed to the conception of the study; Rui Zhang contributed to analysis and manuscript preparation; Na Fu and Qixin Pan performed the experiment; Na Fu performed the data analyses and wrote the manuscript; Xiaojing Tian, Shaoqiu Long, and Chaolong Yao helped perform the analysis with constructive discussions.

Corresponding author

Correspondence to Rui Zhang.

Additional information

Communicated by T Narayana Rao

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fu, N., Zhang, R., Pan, Q. et al. Quality assessment of the ionospheric density profiles based on long-term COSMIC 1 and 2 radio occultation observations. J Earth Syst Sci 132, 175 (2023). https://doi.org/10.1007/s12040-023-02190-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12040-023-02190-2

Keywords

Search

Navigation