Application of a multi-layer artificial neural network in a 3-D global electron density model using the long-term observations of COSMIC, Fengyun-3C, and Digisonde

The ionosphere plays an important role in satellite navigation, radio communication, and space weather prediction. However, it is still a challenging mission to develop a model with high predictability that captures the horizontal-vertical features of ionospheric electrodynamics. In this study, mult...

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Bibliographic Details
Published in:Space Weather
Main Authors: Li, W. (Wang), Zhao, D. (Dongsheng), He, C. (Changyong), Shen, Y. (Yi), Hu, A. (Andong), Zhang, K. (Kefei)
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
COSMIC mission
Equatorial ionization anomaly
FY-3C
Ionospheric model
Neural network
Weddell
Weddell Sea
Online Access:https://ir.cwi.nl/pub/30718
https://doi.org/10.1029/2020SW002605
Description
Summary:The ionosphere plays an important role in satellite navigation, radio communication, and space weather prediction. However, it is still a challenging mission to develop a model with high predictability that captures the horizontal-vertical features of ionospheric electrodynamics. In this study, multiple observations during 2005\xe2\x80\x932019 from space-borne global navigation satellite system (GNSS) radio occultation (RO) systems (COSMIC and FY-3C) and the Digisonde Global Ionosphere Radio Observatory are utilized to develop a completely global ionospheric three-dimensional electron density model based on an artificial neural network, namely ANN-TDD. The correlation coefficients of the predicted profiles all exceed 0.96 for the training, validation and test datasets, and the minimum root-mean-square error of the predicted residuals is 7.8\xc2\xa0\xc3\x97\xc2\xa0104 el/cm3. Under quiet space weather, the predicted accuracy of the ANN-TDD is 30%\xe2\x80\x9360% higher than the IRI-2016 at the Millstone Hill and Jicamarca incoherent scatter radars. However, the ANN-TDD is less capable of predicting ionospheric dynamic evolution under severe geomagnetic storms compared to the IRI-2016 with the STORM option activated. Additionally, the ANN-TDD successfully reproduces the large-scale horizontal-vertical ionospheric electrodynamic features, including seasonal variation and hemispheric asymmetries. These features agree well with the structure revealed by the RO profiles derived from the FORMOSAT/COSMIC-2 mission. Furthermore, the ANN-TDD successfully captures the prominent regional ionospheric patterns, including the equatorial ionization anomaly, Weddell Sea anomaly and mid-latitude summer nighttime anomaly. The new model is expected to play an important role in the application of GNSS navigation and in the explanation of the physical mechanisms involved.

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