Empirical Modeling of Ionospheric Current Using Empirical Orthogonal Function Analysis and Artificial Neural Network

Charles Owolabi, Haibing Ruan, Yosuke Yamazaki, Jinfeng Li, Jiahao Zhong, A. V. Eyelade, Shishir Priyadarshi, Akimasa Yoshikawa

Research output: Contribution to journalArticlepeer-review

6 Citations (SciVal)

Abstract

Given the potential importance of solar quiet (Sq) ionospheric current in geomagnetic field modeling, it is vital to obtain accurate parameters characterizing its variations, particularly the spatial and temporal variations. In this paper, we derived the Sq current function based on the spherical harmonic analysis (SHA) technique using a 14-year (2006–2019) quiet geomagnetic field record over the American sector. The empirical orthogonal function (EOF) analysis was then applied to deduce temporal and spatial variations of the Sq current. It is observed that the first EOF mode of the Sq current function is dominated by solar activity, while the second and third EOF modes exhibit annual and semiannual variations, respectively. Also, the artificial neural network (ANN) model of Sq current function was constructed to validate the EOF model predictions. While the Sq current intensity predicted by the ANN model is underestimated by 2.83%, the EOF model underpredicted the Sq current intensity by 1.92% relative to the observation. The root mean square error (RMSE) of the EOF model is 0.64 kA. This RMSE is about 79% smaller than that of the ANN model. In addition, both the EOF and ANN models capture the variation of the total Sq current (Jtotal) intensity with respect to solar activity. In principle, the EOF model had an optimal performance at nearly 98% accuracy, with the ANN model exhibiting almost the same degree of accuracy, which appears to be a reference point for ionospheric conditions when looking for space weather applications.

Original languageEnglish
Article numbere2021SW002831
JournalSpace Weather
Volume19
Issue number11
Early online date23 Oct 2021
DOIs
Publication statusPublished - 30 Nov 2021
Externally publishedYes

Bibliographical note

Funding Information:
The first author is indebted to Prof. Jiuhou Lei for his guidance over the years in the pursuit of understanding the ionospheric electrodynamics and to Prof. Yufeng Lin for his support and encouragement during this work. This work was in part supported by the National Natural Science Foundation (NSF) of China (Grant Numbers: 41804151, 42074186 and 41804150), Natural Science Foundation of Jiangsu Province (Grant Number: BK20211036), and the Guangdong Basic and Applied Basic Research Foundation (Grant Number: 2021A1515011216). The authors are thankful to the INTERMAGNET, LISN, MAGDAS/CPMN, AUTUMNX, CARISMA, EMBRACE, WDC and SAMBA members for providing the geomagnetic data used in this study. The LISN is a project led by Boston College in collaboration with the Geophysical Institute of Peru, and other institutions that provide information for the benefit of the scientific community. The MAGDAS/CPMN network is operated by the International Center for Space Weather Science and Education, Kyushu University, Fukuoka, Japan and funded by the Japan Society for the Promotion of Science (JSPS). The CARISMA network is operated by the University of Alberta, funded by the Canadian Space Agency. The AUTUMNX is funded through the Canadian Space Agency/Geospace Observatories (GO) Canada Program. The AMBER is operated by Boston College and funded by NASA and AFOSR. The SAMBA is also operated by UCLA and funded by NSF. We are appreciative to IAGA for providing a quasi‐dipole geomagnetic coordinate calculator. We are grateful to SPDF/GSFC for providing records of F10.7 flux indices used in the present study. We thank the Helmholtz Center Potsdam, German Research Center for Geosciences GFZ for providing records of the IQDs. We thank the two anonymous reviewers for their helpful criticism that helped us improve the paper.

Funding Information:
The first author is indebted to Prof. Jiuhou Lei for his guidance over the years in the pursuit of understanding the ionospheric electrodynamics and to Prof. Yufeng Lin for his support and encouragement during this work. This work was in part supported by the National Natural Science Foundation (NSF) of China (Grant Numbers: 41804151, 42074186 and 41804150), Natural Science Foundation of Jiangsu Province (Grant Number: BK20211036), and the Guangdong Basic and Applied Basic Research Foundation (Grant Number: 2021A1515011216). The authors are thankful to the INTERMAGNET, LISN, MAGDAS/CPMN, AUTUMNX, CARISMA, EMBRACE, WDC and SAMBA members for providing the geomagnetic data used in this study. The LISN is a project led by Boston College in collaboration with the Geophysical Institute of Peru, and other institutions that provide information for the benefit of the scientific community. The MAGDAS/CPMN network is operated by the International Center for Space Weather Science and Education, Kyushu University, Fukuoka, Japan and funded by the Japan Society for the Promotion of Science (JSPS). The CARISMA network is operated by the University of Alberta, funded by the Canadian Space Agency. The AUTUMNX is funded through the Canadian Space Agency/Geospace Observatories (GO) Canada Program. The AMBER is operated by Boston College and funded by NASA and AFOSR. The SAMBA is also operated by UCLA and funded by NSF. We are appreciative to IAGA for providing a quasi-dipole geomagnetic coordinate calculator. We are grateful to SPDF/GSFC for providing records of F10.7 flux indices used in the present study. We thank the Helmholtz Center Potsdam, German Research Center for Geosciences GFZ for providing records of the IQDs. We thank the two anonymous reviewers for their helpful criticism that helped us improve the paper.

Keywords

  • artificial neural network
  • empirical orthogonal function analysis
  • spherical harmonic analysis
  • Sq current

ASJC Scopus subject areas

  • Atmospheric Science

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