Colocated Observations of the <i>E</i> and <i>F</i> Region Thermosphere During a Substorm
Bibliographic record
Abstract
Abstract Two‐dimensional thermospheric wind fields, at both E and F region altitudes within a common vertical volume, were made using a Scanning Doppler Imager (SDI) at Poker Flat, Alaska, during a substorm event. Coinciding with these observations were F region plasma velocity measurements from the Super Dual Auroral Radar Network (SuperDARN) and estimations of the total downward and upward field‐aligned current density from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). This combination of instruments gives an excellent opportunity to examine the spatial characteristics of high‐latitude ionosphere‐thermosphere coupling and how a process which is triggered in the magnetosphere (the substorm) affects that coupling at different altitudes. We find that during the substorm growth phase, the F region thermospheric winds respond readily to an expanding ionospheric plasma convection pattern, while the E region winds appear to take a much longer period of time. The differing response timescales of the E and F region winds are likely due to differences in neutral density at those altitudes, resulting in E region neutrals being much more “sluggish” with regard to ion drag. We also observe increases in the F region neutral temperature, associated with neutral winds accelerating during both substorm growth and recovery phases.
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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 | 0.000 | 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".