Abstract
We utilise Principal Component Analysis to identify and quantify the
primary electric potential morphologies during geomagnetic storms.
Ordering data from the Super Dual Auroral Radar Network (SuperDARN) by
geomagnetic storm phase, we are able to discern changes that occur in
association with the development of the storm phases. Along with
information on the size of the patterns, the first 6 eigenvectors
provide over ~80% of the variability in the morphology,
providing us with a robust analysis tool to quantify the main changes in
the patterns. Studying the first 6 eigenvectors and their eigenvalues
with respect to storm phase shows that the primary changes in the
morphologies with respect to storm phase are the convection potential
enhancing and the dayside throat rotating from pointing towards the
early afternoon sector to being more sunward aligned during the main
phase of the storm. We find that the ionospheric electric potential
increases through the main phase and then decreases after the end of the
main phase is reached. The dayside convection throat points towards the
afternoon sector before the main phase and then as the potential
increases throughout the main phase, the dayside throat rotates towards
magnetic noon. Furthermore, we find that a two cell convection pattern
is dominant throughout and that the dusk cell is overall stronger than
the dawn cell.