The correlation of ULF waves and auroral intensity before, during and after substorm expansion phase onset
Bibliographic record
Abstract
We present case studies of the evolution of Ultra‐Low Frequency (ULF) magnetic wave amplitudes and auroral intensity through the late growth phase and the expansion phase of the substorm cycle. We present strong evidence that substorm‐related auroral enhancements are clearly and demonstrably linked to ULF wave amplitudes observed at the same location. In all three case studies presented, the correlation analysis shows that the ULF wave activity and auroral intensities are highly correlated at close to zero lag. We discuss four possible explanations that may be able to explain both the timing and the high correlations between these two phenomena, including a simple coincidence, an artifact of instrumental effects, the response of the ionosphere to magnetic waves and auroral particle precipitation, and finally, that ULF waves and auroral particle precipitation are physically linked at their source. We discount coincidence and instrumental effects since we present multiple events where instrumental effects have a negligible contribution, and we find that the ionospheric response to waves and precipitation can explain some, but not all, of the results contained within this paper. Specifically, the ionospheric response to substorm waves and auroral precipitation cannot explain the result backed up by previous studies that the onset of ULF wave activity and the onset of auroral particle precipitation occur at the same time and in the same location. This leaves the possibility that ULF waves and auroral particles are physically linked at their source. We therefore re‐emphasize the importance of ULF wave observations in fully understanding the mechanism or mechanisms responsible for rapid auroral brightenings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".