Verification of Substorm Onset From Intruding Flow Channels With High‐Resolution SuperDARN Radar Flow Maps
Bibliographic record
Abstract
Abstract Auroral observations were first to identify the substorm, and later used to propose that substorm onset is triggered in the inner plasma sheet (equatorward portion of the auroral oval) by an intrusion of low entropy plasma comprising plasma sheet flow channels. Longitudinal localization makes the intruding flow channels difficult to observe with spacecraft. However, they are detectable in the ionosphere via the broader, two‐dimensional coverage by radars. Line‐of‐sight radar flow measurements have provided considerable support for the onset proposal. Here we use two‐dimensional, ionospheric flow maps for further testing. Since these maps are derived without the smoothing from global fits typically used for global convection maps, their spatial resolution is significantly improved, allowing representation of localized spatial structures. These maps show channels of enhanced ionospheric flow intruding to the time and location of substorm onset. We also see evidence that these intruding flows enter the plasma sheet from the polar cap, and that azimuthal spread of the reduced entropy plasma in the inner plasma sheet contributes to azimuthal onset spreading after initial onset. Identified events with appropriate radar data remain limited, but we have found no exceptions to consistency with flow channel triggering. Thus, these analyses strongly support the proposal that substorm onset is due to the intrusion of new plasma to the onset region. The lower entropy of the new plasma likely changes the entropy distribution of inner plasma sheet, a change possibly important for the substorm onset instability seen via the growing waves that demarcate substorm auroral onset.
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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 | 0.001 |
| 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".