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An Updated Experimental Model of IG₁₂ Indices Over the Antarctic Region via the Assimilation of IRI2016 With GNSS TEC.
- Source :
- IEEE Transactions on Geoscience & Remote Sensing; Feb2021, Vol. 59 Issue 2, p1700-1717, 18p
- Publication Year :
- 2021
-
Abstract
- In order to improve the accuracy of the International Reference Ionosphere (IRI)-2016 model for application in the Antarctic region, total electron content (TEC) data from the Global Navigation Satellite Systems (GNSS) observation data in 2018 are assimilated into the IRI-2016 model by updating the effective ionospheric parameter, IG12 index on a daily basis. The functional relationship between the IG12 index and the longitude, latitude, and the day of year (DOY) is fitted by using the spherical crown harmonic function and the polynomial, and finally establish an updated experiential model of IG12 indices over the Antarctic region. Conclusions that were reached were: 1) the updated IG12 index varies greatly over different geographical locations and 2) it is also apparent that the accuracy of the IRI-2016 model is worse in the perpetual night than that in the perpetual day. In order to verify our method, the TEC calculated by the IRI-2016 model driven by the updated IG12 index and that calculated by the original IRI-2016 model are compared with the GNSS-TEC, and the results show that the updated IRI-2016 model has improved the accuracy of the BIAS and root mean square (RMS) of the TEC calculation by 97% and 87%, respectively, on the fitting moments, while 75% and 54% on the predicting moments. In addition, compared with the original IRI-2016 model, it is found that the updated IRI-2016 model improves the accuracy of the NmF2 calculation by approximately 23% on average for the fitting time and 8% for the predicting time. [ABSTRACT FROM AUTHOR]
- Subjects :
- GLOBAL Positioning System
ROOT-mean-squares
Subjects
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 59
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 148948808
- Full Text :
- https://doi.org/10.1109/TGRS.2020.2999132