An Extreme Auroral Electrojet Spike During 2023 April 24th Storm
Bibliographic record
Abstract
Abstract Abrupt variations of auroral electrojets can induce geomagnetically induced currents, and the ability to model and forecast them is a pressing goal of space weather research. We report an auroral electrojet spike event that is extreme in magnitude, explosive in nature, and global in spatial extent that occurred on 24 April 2023. The event serves as a fundamental test of our understanding of the response of the geospace system to solar wind dynamics. Our results illustrate new and important characteristics that are drastically different from existing knowledge. Most important findings include (a) the event was only of ∼5‐min duration and was limited to a narrow (2°–3°) band of diffuse aurora; (b) the longitudinal span covered the entire nightside sector, possibly extending to the dayside; (c) the trigger seems to be a transient solar wind dynamic pressure pulse. In comparison, substorms usually last 1–2 hr and span almost the entire latitudinal width of the auroral oval. Magnetic perturbation events (MPEs) span hundreds km in radius. Both substorms and MPEs are mainly driven by disturbances in the magnetotail. A possible explanation is that the pressure pulse compresses the magnetosphere and enhances diffuse precipitation of electrons and protons from the inner plasma sheet, which elevates the ionospheric conductivity and intensifies the auroral electrojet. Therefore, the event exhibits a potentially new type of geomagnetic disturbance and highlights a solar wind driver that is enormously influential in driving extreme space weather events.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".