Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

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

View through CrossRef
<p>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.</p><p>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.</p>
Title: Assessment of the IRI-2016 and modified IRI 2016 models in China: Comparison with GNSS-TEC and ionosonde data
Description:
<p>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.
</p><p>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.
</p>.

Related Results

GNSS reflectometry for land remote sensing applications
GNSS reflectometry for land remote sensing applications
Soil moisture and vegetation biomass are two essential parameters from a scienti c and economical point of view. On one hand, they are key for the understanding of the hydrological...
Comparison of quite time ionospheric total electron content from IRI-2016 model and GPS observations
Comparison of quite time ionospheric total electron content from IRI-2016 model and GPS observations
Abstract. Earth's ionosphere is an important medium of radio wave propagation in modern times. However, the effective use of ionosphere depends on the understanding of its spatio-t...
Total electron content driven data products of SIMuRG
Total electron content driven data products of SIMuRG
<p>System for the Ionosphere Monitoring and Researching from GNSS (SIMuRG, see <em>https://simurg.iszf.irk.ru</em>) has been developed in ...
Ionospheric total electron content anomaly possibly associated with the April 4, 2010 Mw7.2 Mexico earthquake
Ionospheric total electron content anomaly possibly associated with the April 4, 2010 Mw7.2 Mexico earthquake
Abstract. Identifying ionospheric disturbances potentially related to an earthquake is a challenging work. Based on the ionospheric total electron content (TEC) data from the madri...
Distinct and Overlapping Functions of TEC Kinase and BTK in B Cell Receptor Signaling
Distinct and Overlapping Functions of TEC Kinase and BTK in B Cell Receptor Signaling
Abstract The Tec tyrosine kinase is expressed in many cell types, including hematopoietic cells, and is a member of the Tec kinase family that also includes Btk. Alt...
GNSS-based orbit and geodetic parameter estimation by means of simulated GENESIS data
GNSS-based orbit and geodetic parameter estimation by means of simulated GENESIS data
The ESA GENESIS mission, which obtained green light at ESA's Council Meeting at Ministerial Level in November 2022 and which is expected to be launched in 2027, aims to significant...
Spatiotemporal Prediction of Ionospheric Total Electron Content Based on ED-ConvLSTM
Spatiotemporal Prediction of Ionospheric Total Electron Content Based on ED-ConvLSTM
Total electron content (TEC) is a vital parameter for describing the state of the ionosphere, and precise prediction of TEC is of great significance for improving the accuracy of t...

Back to Top