EGU2020-16646
https://doi.org/10.5194/egusphere-egu2020-16646
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessment of the IRI-2016 and modified IRI 2016 models in China: Comparison with GNSS-TEC and ionosonde data

wen zhang, xingliang Huo, and haojie Liu
wen zhang et al.
  • University of Chinese Academy of Sciences, Institute of Geodesy and Geophysics, State Key Laboratory of Geodesy and geodynamics, China (zhangwen@apm.ac.cn)

Ionosphere is one of the main errors in the signal propagation of global navigation system satellite (GNSS), and it is also the key issue of space weather. The International Reference Ionosphere (IRI) is the most important empirical model described the ionospheric characteristics, and it provides the monthly averages of electron densities and vertical total electron content (VTEC) in the altitude range of 50km-2000km. The IRI-2016 model is the latest version. But some studies showed that the accuracy of the IRI model is not high enough in China due to the use of fewer data sources. This paper will assess the performance of IRI-2016 model in China, and a modified IRI 2016 model by adjusting the driving parameters IG and RZ index of IRI2016 model with GNSS TEC data are also investigated. In this contribution, GNSS data from the Crustal Movement Observation Network of China (CMONC) are used to estimate TEC values, and the ionosonde data from three stations are used as references for the ionospheric electron densities. Three ionosonde stations are located at Beijing (BP440, 40.3°N/116.2°E), Wuhan (WU430, 30.5°N/114.4°E) and Sanya (SA418, 18.3°N/ 109.6°E). The above data respectively cover a period of 6 days in the high year (2015) and low year (2019) of solar activity.

The study shows that the biggest reason for the difference (DTEC) between GPS-TEC and IRI2016-TEC in China is that the poor estimation of NmF2 and hmF2 by IRI model, and the driving parameters IG and RZ index of IRI2016 can be updated by constraining DTEC. Finally, the performance of the modified IRI-2016 model is improved by the updated IG and RZ indexes as the short-term driving values of ionospheric parameters. The analysis show that the modified IRI-2016 model is more accurate at estimating both the TEC and the electron density profile than the original model.

How to cite: zhang, W., Huo, X., and Liu, H.: Assessment of the IRI-2016 and modified IRI 2016 models in China: Comparison with GNSS-TEC and ionosonde data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16646, https://doi.org/10.5194/egusphere-egu2020-16646, 2020

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