
We acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China,France, Italy, Japan, Norway, South Africa, United Kingdom, and the United States of America. We acknowledge the use of DMSP/SSUSI data provided by the Johns Hopkins University Applied Physics Laboratory (https://cdaweb.gsfc.nasa.gov). Additionally, the OMNI data set is available from the OMNIWeb service online of NASA/GSFC's Space Physics Data Facility' s(https://spdf.gsfc.nasa.gov/pub/data/omni/).The ground-based magnetic field measurements are accessible via the IMAGE Magnetometer network (https://space.fmi.fi/image/).We would like to thank N.A. Frissell for providing the complete code for the MUSIC (MUltiple SIgnal Classification) algorithm (https://github.com/HamSCI/pyDARNmusic).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
