Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii
Bibliographic record
Abstract
Simultaneous sodium (Na) Doppler lidar and meteor radar measurements of horizontal winds in the mesopause region over Maui, Hawaii, were collected in July 2002 and October/November 2003. The coincident measurements span 96 hours and altitudes between 80 and 100 km. Statistical comparisons are carried out on radar/lidar winds with 1 hour and 4 km time and height resolution, respectively. The RMS radar/lidar wind component differences observed in this study are in the range 12–17 m/s at altitudes below 96 km. This is smaller than the RMS differences observed in a previous Na lidar and meteor radar comparison. Lidar wind component variances exceed radar variances, and radar/lidar covariance, is nearly equal to the radar variance. Excess variance observed by the lidar is consistent with the fact that the meteor radar cannot resolve wind perturbations with horizontal scales smaller than ∼200 km, whereas the lidar will respond to all horizontal scales. Close correspondence between the radar wind variance and radar/lidar covariance suggests that measurement errors associated with the radar winds are swamped by geophysical variation. Furthermore, the excess lidar variance exceeds lidar estimation errors by a large factor, indicating that the lidar measurement errors are also insignificant relative to geophysical variations. Together these observations suggest that the observed radar/lidar differences are a consequence of the different horizontal wave number filters associated with the techniques, and hence the differences are determined by the strength and shape of the horizontal wave number spectrum for wind perturbations at scales smaller than ∼200 km.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".