Evidence of Alfvenic Poynting Flux as the Primary Driver of Auroral Motion During a Geomagnetic Substorm
Bibliographic record
Abstract
Abstract Geomagnetic substorms are major energy transfer events where energy stored in the Earth's magnetotail is released into the ionosphere. Substorm phenomena, including auroral activities, earthward Poynting flux, magnetic field dipolarization, etc, have been extensively studied. However, the complex interplay among them is not fully understood. In a fortuitous event on June 7, 2013, the twin Van Allen Probes (separated by 0.4 h in local time) observed bursts of earthward Alfvenic Poynting flux in the vicinity of the plasma sheet boundary layer (PSBL). The Poynting flux bursts correlate with enhancements of auroral brightness around the footpoints of both spacecraft. This indicates a temporal and spatial correlation between the auroral brightening and Poynting flux bursts, and that the auroral motion is directly linked to the perpendicular expansion of the Alfven wave. These observations suggest that the Alfvenic Poynting flux is a primary driver for the auroral electron acceleration. Around the time of auroral brightening, a dipolarization was seen to propagate more than 4 h in local time during a 20 min period. The azimuthal phase speed of this dipolarization (2 deg/min) is too small to explain the azimuthal motion of the aurora (13.6 deg/min), but the dipolarization could be related to the generation of the Alfvenic Poynting flux through phase mixing at strong density gradients like those in the PSBL.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".