An Empirical Orthogonal Function Reanalysis of the Northern Polar External and Induced Magnetic Field During Solar Cycle 23. Issue 1 (9th January 2018)

• Record Type: Journal Article
• Authors: Shore, R. M.; Freeman, M. P.; Gjerloev, J. W.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 1(2018)
• Page Start: 781
• Page End: 795
• Publication Date: 2018-01-09
• Subjects: empirical orthogonal functions -- external magnetic field -- polar ionosphere -- decomposition of variability -- disturbance polar equivalent current systems -- graph theory; Magnetospheric physics -- Periodicals; Space environment -- Periodicals; Cosmic physics -- Periodicals; Planets -- Atmospheres -- Periodicals; Heliosphere (Astrophysics) -- Periodicals; Geophysics -- Periodicals; 523.01
• DOI: 10.1002/2017JA024420
• Languages: English
• ISSNs: 2169-9380

Abstract

Abstract: We apply the method of data‐interpolating empirical orthogonal functions (EOFs) to ground‐based magnetic vector data from the SuperMAG archive to produce a series of month length reanalyses of the surface external and induced magnetic field (SEIMF) in 110, 000 km 2 equal‐area bins over the entire northern polar region at 5 min cadence over solar cycle 23, from 1997.0 to 2009.0. Each EOF reanalysis also decomposes the measured SEIMF variation into a hierarchy of spatiotemporal patterns which are ordered by their contribution to the monthly magnetic field variance. We find that the leading EOF patterns can each be (subjectively) interpreted as well‐known SEIMF systems or their equivalent current systems. The relationship of the equivalent currents to the true current flow is not investigated. We track the leading SEIMF or equivalent current systems of similar type by intermonthly spatial correlation and apply graph theory to (objectively) group their appearance and relative importance throughout a solar cycle, revealing seasonal and solar cycle variation. In this way, we identify the spatiotemporal patterns that maximally contribute to SEIMF variability over a solar cycle. We propose this combination of EOF and graph theory as a powerful method for objectively defining and investigating the structure and variability of the SEIMF or their equivalent ionospheric currents for use in both geomagnetism and space weather applications. It is demonstrated here on solar cycle 23 but is extendable to any epoch with sufficient data coverage. Plain Language Summary: This study processes over a decade of ground‐based magnetometer data at 5 min resolution to arrive at a new model for the magnetic field external to the Earth's surface. The purpose of the model is threefold: (1) Infill the gaps in the available data using meteorological methods. These produce infill solutions that depend on the data alone, rather than on modeling assumptions, thus improving the infill accuracy. (2) Decompose the infilled data into independent spatial and temporal patterns, each of which describe the maximum possible data variance of any possible pattern. We need these because the structure of the patterns—which is unknown prior to doing the analysis—provides insight into the geomagnetic perturbations at ground level. For instance, we resolve spatiotemporal patterns that we interpret as well‐known ionospheric equivalent electrical current systems, thus we can describe the variation of these systems in time. (3) We wanted to approach the classification of the spatiotemporal patterns in a systematic manner, so we applied a cluster analysis to 12 years of monthly models. This provides a clear overview of geomagnetic variations spanning an 11 year solar cycle. Key Points: Eigenanalysis method infills missing magnetic field data and provides decomposition into spatial and temporal patterns of maximum variance Graph theory applied to eigenanalysis models to find clusters of spatially similar patterns in 12 years of monthly analyses (1997.0–2009.0) Combination of eigenanalysis and graph theory resolves seasonal and solar cycle variability in key equivalent ionospheric current systems