Multi‐Scale Kelvin‐Helmholtz Instability Dynamics Observed by PMC Turbo on 12 July 2018: 1. Secondary Instabilities and Billow Interactions
Bibliographic record
Abstract
Abstract The Polar Mesospheric Cloud (PMC) Turbulence experiment performed optical imaging and Rayleigh lidar PMC profiling during a 6‐day flight in July 2018. A mosaic of seven imagers provided sensitivity to spatial scales from ∼20 m to 100 km at a ∼2‐s cadence. Lidar backscatter measurements provided PMC brightness profiles and enabled definition of vertical displacements of larger‐scale gravity waves (GWs) and smaller‐scale instabilities of various types. These measurements captured an interval of strong, widespread Kelvin‐Helmholtz instabilities (KHI) occurring over northeastern Canada on July 12, 2018 during a period of significant GW activity. This paper addresses the evolution of the KHI field and the characteristics and roles of secondary instabilities within the KHI. Results include the imaging of secondary KHI in the middle atmosphere and multiple examples of KHI “tube and knot” (T&K) dynamics where two or more KH billows interact. Such dynamics have been identified clearly only once in the atmosphere previously. Results reveal that KHI T&K arise earlier and evolve more quickly than secondary instabilities of uniform KH billows. A companion paper by Fritts et al. (2022), https://doi.org/10.1029/2021JD035834 reveals that they also induce significantly larger energy dissipation rates than secondary instabilities of individual KH billows. The expected widespread occurrence of KHI T&K events may have important implications for enhanced turbulence and mixing influencing atmospheric structure and variability.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".