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arxiv: 1709.06885 · v1 · pith:MD454OCOnew · submitted 2017-09-19 · ⚛️ physics.space-ph · astro-ph.SR

Principal component analysis of geomagnetic activity: New information on solar wind

classification ⚛️ physics.space-ph astro-ph.SR
keywords activitygeomagneticcomponentprincipalnetworkanalysisannualdistribution
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We use the principal component analysis (PCA) to study geomagnetic activity at annual resolution using a network of 26 magnetic stations in 1966-2015, and an extended network of 40 stations in 1980-2015. The first principal component (PC1) describes the long-term evolution of global geomagnetic activity, and has an excellent correlation with indices like the Kp/Ap index. The two networks give identical results for PC1. The second principal component (PC2) is highly correlated with the annual percentage of high-speed streams (HSS). The extended network has a slightly higher sensitivity to HSSs. We verify the non-trivial latitudinal distribution of the second empirical orthogonal function (EOF2). We find that the amplitude of the 22-year variation of geomagnetic activity has a closely similar latitudinal distribution as EOF2. This verifies that the 22-year variation of geomagnetic activity is related to HSSs. The most likely cause is the Russell-McPherron mechanism.

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