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Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
by
Yuan, Yunbin
, Zhang, Hongxing
, Zhang, Ting
, Liu, Yanwen
, Dai, Zelin
, Peng, Jing
, Wang, Yifan
in
Accuracy
/ Artificial satellites in remote sensing
/ COSMIC
/ Density profiles
/ Distribution
/ Electron density
/ Electron density profiles
/ Electrons
/ Environmental aspects
/ F2 layer peak electron density
/ Immunoglobulins
/ international reference ionospheric model
/ ionosonde
/ Ionosondes
/ Ionosphere
/ ionospheric electron density
/ Ionospheric models
/ Latitude
/ Optimization
/ Parameters
/ Radio signals
/ Remote sensing systems
/ Solar activity
/ Testing
2024
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Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
by
Yuan, Yunbin
, Zhang, Hongxing
, Zhang, Ting
, Liu, Yanwen
, Dai, Zelin
, Peng, Jing
, Wang, Yifan
in
Accuracy
/ Artificial satellites in remote sensing
/ COSMIC
/ Density profiles
/ Distribution
/ Electron density
/ Electron density profiles
/ Electrons
/ Environmental aspects
/ F2 layer peak electron density
/ Immunoglobulins
/ international reference ionospheric model
/ ionosonde
/ Ionosondes
/ Ionosphere
/ ionospheric electron density
/ Ionospheric models
/ Latitude
/ Optimization
/ Parameters
/ Radio signals
/ Remote sensing systems
/ Solar activity
/ Testing
2024
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Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
by
Yuan, Yunbin
, Zhang, Hongxing
, Zhang, Ting
, Liu, Yanwen
, Dai, Zelin
, Peng, Jing
, Wang, Yifan
in
Accuracy
/ Artificial satellites in remote sensing
/ COSMIC
/ Density profiles
/ Distribution
/ Electron density
/ Electron density profiles
/ Electrons
/ Environmental aspects
/ F2 layer peak electron density
/ Immunoglobulins
/ international reference ionospheric model
/ ionosonde
/ Ionosondes
/ Ionosphere
/ ionospheric electron density
/ Ionospheric models
/ Latitude
/ Optimization
/ Parameters
/ Radio signals
/ Remote sensing systems
/ Solar activity
/ Testing
2024
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Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
Journal Article
Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
2024
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Overview
The ionosphere is one of the important error sources that affect the communication of radio signals. The international reference ionosphere (IRI) model is a commonly used model to describe ionospheric parameters. The driving parameter IG12 of the IRI-2016 model was optimally updated based on GNSS-TEC data from 2015 and 2019. The electron density profiles and NmF2 calculated by the IRI-2016 model (upda-IRI-2016) driven by the updated IG12 value (IG-up) were evaluated for their accuracy using ionosonde observations and COSMIC inversion data. The experiments show that both the electron density profiles and NmF2 calculated by upda-IRI-2016 driven by IG-up show significant optimization effects, compared to the IRI-2016 model driven by IG12. For electron density, the precision improvement (PI) for both MAE and RMSE at the Beijing station exceed 31.2% in January 2015 and 16.0% in January 2019. While the PI of MAE and RMSE at the Wuhan station, which is located at a lower latitude, both exceed 32.5% in January 2015, both exceed 42.1% in January 2019, which is significantly higher than that of the Beijing station. In 2015, the PI of MAE and RMSE compared with COSMIC are both higher than 20%. For NmF2, the PI is greater for low solar activity years and low latitude stations, with the Wuhan station showing a PI of more than 11.7% in January 2019 compared to January 2015. The PI compared to COSMIC was higher than 17.2% in 2015.
Publisher
MDPI AG
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