University of Oulu

Alken, P., A. Maute, A. D. Richmond, H. Vanhamäki, and G. D. Egbert (2017), An application of principal component analysis to the interpretation of ionospheric current systems, J. Geophys. Res. Space Physics, 122, 5687–5708, doi:10.1002/2017JA024051

An application of principal component analysis to the interpretation of ionospheric current systems

Saved in:
Author: Alken, P.1; Maute, A.2; Richmond, A. D.2;
Organizations: 1University of Colorado Boulder, Boulder, Colorado, USA
2High Altitude Observatory, National Center for Atmospheric Research, Boulder, Colorado, USA
3University of Oulu, Oulu, Finland
4Oregon State University, Corvallis, Oregon, USA
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 7.3 MB)
Persistent link:
Language: English
Published: American Geophysical Union, 2017
Publish Date: 2017-11-23


Ionospheric currents are driven by several different physical processes and exhibit complex spatial and temporal structure. Magnetic field measurements of ionospheric sources are often spatially sparse, causing significant challenges in visualizing current flow at a specific time. Standard methods of fitting equivalent current models to magnetic observations, such as line currents, spherical harmonic analysis, spherical cap harmonic analysis, and spherical elementary current systems (SECS), are often unable to capture the full spatial complexity of the currents or require a large number of parameters which cannot be fully determined by the available data coverage. These methods rely on a set of generic basis functions which contain limited information about the geometries of the various ionospheric sources. In this study, we develop new basis functions for fitting ground and satellite measurements, which are derived from physics-based ionospheric modeling combined with principal component analysis (PCA). The physics-based modeling provides realistic current flow patterns for all of the primary ionospheric sources, including their daily and seasonal variability. The PCA technique extracts the most relevant spatial geometries of the currents from the model run into a small set of equivalent current modes. We fit these modes to magnetic measurements of the Swarm satellite mission at low and middle latitudes and compare the resulting model with independent measurements and with the SECS approach. We find that our PCA method accurately reproduces features of the equatorial electrojet and Sq current systems with only 10 modes and can predict ionospheric fields far from the data region.

see all

Series: Journal of geophysical research. Space physics
ISSN: 2169-9380
ISSN-E: 2169-9402
ISSN-L: 2169-9380
Volume: 122
Issue: 5
Pages: 5687 - 5708
DOI: 10.1002/2017JA024051
Type of Publication: A1 Journal article – refereed
Field of Science: 115 Astronomy and space science
Funding: This work was supported by National Science Foundation grants EAR-1447036 and AGS-1135446. The National Center for Atmospheric Research is sponsored by the National Science Foundation.
Dataset Reference: We gratefully acknowledge the European Space Agency for providing Swarm data, which is available from https://earth. following registration. The ground observatory data used in this study can be obtained from the Bureau Central de Magnétisme Terrestre (http:// and INTERMAGNET ( The TIEGCM runs used in this work are available upon request.
Copyright information: ©2017. American Geophysical Union. Published in this repository with the kind permission of the publisher.