Lagrangian Detection of Wind Shear for Landing Aircraft
Bibliographic record
Abstract
Abstract Recent studies have shown that aerial disturbances affecting landing aircraft have a coherent signature in the Lagrangian aerial particle dynamics inferred from ground-based lidar scans. Specifically, attracting Lagrangian coherent structures (LCSs) mark the intersection of localized material upwelling within the cone of the lidar scan. This study tests the detection power of LCSs on historical landing data and corresponding pilot reports of disturbances from Hong Kong International Airport. The results show that a specific LCS indicator, the gradient of the finite-time Lyapunov exponent (FTLE) field along the landing path, is a highly efficient marker of turbulent upwellings. In particular, in the spring season, projected FTLE gradients closely approach the efficiency of the wind shear alert system currently in operation at the airport, even though the latter system relies on multiple sources of data beyond those used in this study. This shows significant potential for the operational use of FTLE gradients in the real-time detection of aerial disturbances over airports.
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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) | 0.001 | 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".