23/9 dimensional anisotropic scaling of passive admixtures using lidar data of aerosols
Bibliographic record
Abstract
In buoyancy-driven flows, another dimensional quantity appears in addition to the energy flux. Classically, this leads to the prediction that at large scales, isotropic Bolgiano-Obukhov (BO) scaling can dominate isotropic Kolmogorov scaling. We investigate this in the atmosphere by using state-of-the-art high-powered lidar data. We examine simultaneous horizontal and vertical sections of passive scalar surrogates over the ranges 100 m to 120 km and 3 m to 4.5 km , respectively. Overall, this spans the crucial "mesoscale" and involves nearly 1000 times more data than the largest relevant experiments to date. Rather than a transition from one isotropic regime to another, we find that the two regimes always coexist in an anisotropic Corrsin-Obukhov law with the Kolmogorov holding in the horizontal, and the BO holding in the vertical. The stratification is quantified by an elliptical dimension D(el) found to be equal to 2.55+/-0.02 . This anisotropic scaling is very close to that predicted by the 23/9 dimensional unified scaling model of the atmosphere and is consistent with observations of the horizontal wind.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".