Characteristics of ripple structures revealed in OH airglow images
Bibliographic record
Abstract
Abstract Small‐scale ripple structures observed in OH airglow images are most likely induced by either dynamic instability due to large wind shear or convective instability due to superadiabatic lapse rate. Using the data set taken in the mesopause region with an OH all‐sky imager at Yucca Ridge Field Station, Colorado (40.7°N, 104.9°W), from September 2003 to December 2005, we study the characteristics and seasonal variations of ripple structures. By analyzing the simultaneous background wind and temperature observed by the nearby sodium temperature/wind lidar at Fort Collins, Colorado (40.6°N, 105°W), and a nearby medium‐frequency radar at Platteville, Colorado (40.2°N, 105.8°W), we are able to statistically study the possible relation between ripples and the background atmosphere conditions. Characteristics and seasonal variations of ripples are presented in detail in this study. The occurrence frequency of ripples exhibits clear seasonal variability, with peak in autumn. The occurrence of ripples shows a local time dependence, which is most likely associated with the solar tides. The lifetime and spatial scale of these ripples are typically 5–20 min and 5–10 km, respectively, and most of the ripples move preferentially either southward or northward. However, more than half of the observed ripples do not advect with background flow; they have higher Richardson numbers than those ripples that advect with background flow. It is possible that they are not instability features but wave structures that are hard to be distinguished from the real instability features.
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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 | 0.001 |
| 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".