A Modeling Study of an Atmospheric Bore Associated With a Nocturnal Convective System Over China
Bibliographic record
Abstract
Abstract Bores have been shown to play a role in the initiation and maintenance of mesoscale convective systems (MCSs), particularly during the night after the boundary layer stabilizes. To date, the generation, evolution, and structure of bores over China has received little attention. This study utilizes observations and simulations with the WRF‐ARW model to investigate the generation and evolution of an atmospheric bore observed over Yangtze‐Huai Plains of China. The bore was associated with a nocturnal MCS that first formed over elevated terrain. The bore was observed ahead of the MCS with a maximum lateral extension of ~100 km. The feature lasted for over 90 mins and propagated at a speed of ~13 m/s, slightly faster than the MCS. In the simulation, the bore evolved from the separating “head” of the convectively generated gravity current. The bore then continued to propagate ahead of the MCS, even after the dissipation of the feeder current, and took on the appearance of an undular bore. The bore lifted a layer of convectively unstable air above the nocturnal surface inversion, initiating new convection ahead of the MCS to help maintain the MCS. The Scorer parameter ahead of the bore revealed a low‐level wind profile with curvature of the vertical profile of horizontal wind, favoring the trapping of wave energy and the persistence of the bore. These results are generally consistent with the role of bores in the maintenance of nocturnal MCSs and emphasize the need for future studies into the relationship between bores and nocturnal MCSs over China.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".