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

TL;DR

This study applies principal component analysis to long-term geomagnetic activity data, revealing correlations with solar wind features and confirming the 22-year variation's relation to high-speed streams and the Russell-McPherron mechanism.

Contribution

It introduces a PCA-based approach to analyze geomagnetic activity, linking principal components to solar wind phenomena and long-term variations.

Findings

PC1 correlates with global geomagnetic activity indices.

PC2 is linked to high-speed solar wind streams.

The 22-year variation aligns with EOF2 and HSS distribution.

Abstract

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.