Wind comparisons between meteor radar and Doppler shifts in airglow emissions using field widened Michelson interferometers
Bibliographic record
Abstract
Abstract. Winds from two co-located two wind measuring instruments, a meteor radar and field widened Michelson interferometer at the Polar Environment Atmospheric Research Laboratory in Eureka, Nu, Canada (80° N, 86° W) are compared. The two instruments have very different temporal and spatial observational footprints. ERWIN provides airglow weighted winds from three nightglow emissions (O(1S) (oxygen green line, 557.7 nm), an O2 line (866 nm), and an OH line (843 nm)) on a ∼5 minute cadence for measurements at all three heights. As with Fabry-Perot airglow wind observations, these winds are airglow weighted winds from volumes of ∼8 km in height by ∼5 km radius. ERWIN’s higher accuracy (1–2 m/s for the O(1S) and OH emissions and ∼4 m/s for the O2 emissions) and higher cadence allows more detailed wind comparisons of airglow and radar winds than previously possible. The best correlation is achieved using Gaussian weighting of meteor radar winds with peak height and vertical width being optimally determined. Peak heights agree well with co-located SABER airglow observations. Offsets between the two instruments are ∼ 1–2 m/s for the O2 and O(1S) emissions and less than 0.3/s for the OH emission. Wind direction are highly correlated with a ∼ 1:1 correspondence. On average meteor radar wind magnitudes are ∼ 40 % larger than those from ERWIN. Gravity wave airglow brightness weighting of observations is discussed. Non-quadrature phase offsets between the airglow weighting and gravity wave associated wind and temperature perturbations will result in enhanced or reduced layer weighted wind amplitudes.
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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 | 0.001 |
| 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) | 0.001 | 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".