Birkeland Current Boundary Flows Associated With Field Line Resonances
Bibliographic record
Abstract
Abstract Strong zonal flows greater than 1,000 m/s have recently been identified by Swarm in the midnight sector of the winter hemisphere auroral zone. These flows are typically observed between upward and downward field aligned current pairs and therefore are referred to as Birkeland current boundary flows (BCBFs). The Swarm observations also identify ion heating and upflows associated with the fast zonal flows. BCBFs and the resulting ion heating and upflows play an important role in thermosphere‐ionosphere‐magnetosphere coupling given their high occurrence rate in the quiet time nightside auroral zone. This paper utilizes Super Dual Auroral Radar Network (SuperDARN) high‐resolution fits to line‐of‐sight data to investigate two known BCBF events. The large (>2,000 m/s) BCBFs observed with Swarm A and B are found to be collocated with the location of field line resonances (FLRs) with periods of approximately 20–30 min. The SuperDARN high‐resolution fits determine FLR peak flow velocities of 400–700 m/s. When the FLR velocities are superimposed upon the background ionospheric convection of 400–600 m/s, this yields total east‐west velocities of 800–1,300 m/s near the time and location of the BCBF events. The peak flows of the field line resonances are shown to be bounded by pairs of upward and downward field aligned current similar to the BCBFs. The observations suggest a causal relationship between BCBFs and FLRs.
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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".