Seasonal and nightly variations of gravity-wave energy density in the middle atmosphere measured by the Purple Crow Lidar
Bibliographic record
Abstract
Abstract. The Purple Crow Lidar (PCL) is a large power-aperture product monostatic Rayleigh-Raman-Sodium-resonance-fluorescence lidar, which has been in operation at the Delaware Observatory (42.9° N, 81.4° W, 237 m elevation) near the campus of The University of Western Ontario since 1992. Kinetic-energy density has been calculated from the Rayleigh-scatter system measurements of density fluctuations at temporal-spatial scales relevant for gravity waves, e.g. soundings at 288 m height resolution and 9 min temporal resolution in the upper stratosphere and mesosphere. The seasonal averages from 10 years of measurements show in all seasons some loss of gravity-wave energy in the upper stratosphere. During the equinox periods and summer the measurements are consistent with gravity waves growing in height with little saturation, in agreement with the classic picture of the variations in the height at which gravity waves break given by Lindzen (1981). The mean values compare favourably to previous measurements when computed as nightly averages, but the high temporal-spatial resolution measurements show considerable day-to-day variability. The variability over a night is often extremely large, with typical RMS fluctuations of 50 to 100% at all heights and seasons common. These measurements imply that using a daily or nightly-averaged gravity-wave energy density in numerical models may be highly unrealistic.
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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".