Statistical Studies of Plasma Structuring in the Auroral Ionosphere by the Swarm Satellites
Bibliographic record
Abstract
Abstract This study uses over 2 years of 16 Hz density measurements, 50 Hz magnetic field data and ROTI data from the Swarm mission to perform long term statistics of plasma structuring in the polar ionosphere. The timeframe covers more than 2 years near the 24th solar cycle peak. We additionally use 3 years of data obtained from a timeframe close to solar minimum for discussion. We present power spectral densities (PSD) of electron density irregularities and magnetic field for 1‐min intervals. These PSD have been characterized by the probability of a slope steepening, and by integrating the power deposited within frequency intervals corresponding to kilometer scales. For the electron density, we observe seasonal dependencies for both the integrated power and slope characteristics. While the dual slope probability, especially within the polar cap, varies with solar EUV‐radiation, the integrated power is strongest around the equinoxes. Additionally, while we found similar results for the slope probability for both hemispheres, the integrated power exhibits strong hemispheric asymmetries with stronger enhancements within local summer in the southern hemisphere. The ROTI data shows a similar seasonal variability as the density PSD integrated power, in both seasonal dependency and interhemispheric variability. However, for the ROTI data the strongest fluctuations were found within the nightside auroral oval and the cusp. For the PSD of the magnetic field data, we obtain the strongest enhancements within the cusp for all seasons and all hemispheres. The fluctuations may indicate an increase in Alfvénic energy associated with a downward Poynting flux.
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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 | 0.001 | 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) | 0.000 | 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".