Because of the whitening of data as a preprocessing step in rICA, the ordering of the components cannot be determined directly. To resolve this, we estimated the ordering using a ratio following (38), which characterized the contribution of the ith IC to the observed unfiltered motions (X)Embedded Image(2)

The importance (H) of each IC (i = 1,…,4) was estimated at each station (k), as the ratio of the observed motions (X) with time (t), with the predicted motion Embedded Image due to the ith IC at that station. For each IC, we then estimated the median of the ratios across all stations to find the relative contribution that each component made to the overall network, with lower values indicating higher importance. As discussed in text S1, the IC we associated with CME was found to have the lowest median H value (that is, the most important), consistent with the PCA that found that the same CME component had the largest eigenvalue.

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