Mid-latitude <i>E</i>-region bulk motions inferred from digital ionosonde and HF radar measurements
Bibliographic record
Abstract
Abstract. In the mid-latitude E-region there is now evidence suggesting that neutral winds play a significant role in driving the local plasma instabilities and electrodynamics inside sporadicE layers. Neutral winds can be inferred from coherent radar backscatter measurements of the range-/azimuth-time-intensity (RTI/ATI) striations of quasi-periodic (QP) echoes, or from radar interferometer/imaging observations. In addition, neutral winds in the E-region can be estimated from angle-of-arrival ionosonde measurements of sporadic-E layers. In the present paper we analyse concurrent ionosonde and HF coherent backscatter observations obtained when a Canadian Advanced Digital Ionosonde (CADI) was operated under a portion of the field-of-view of the Valensole high frequency (HF) radar. The Valensole radar, a mid-latitude radar located in the south of France with a large azimuthal scanning capability of 82° (24° E to 58° W), was used to deduce zonal bulk motions of QP echoing regions using ATI analysis. The CADI was used to measure angle-of-arrival information in two orthogonal horizontal directions and thus derive the motion of sporadic-E patches drifting with the neutral wind. This paper compares the neutral wind drifts of the unstable sporadic-E patches as determined by the two instruments. The CADI measurements show a predominantly westward aligned motion, but the measured zonal drifts are underestimated relative to those observed with the Valensole radar.
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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".