Ship plume dispersion rates in convective boundary layers for chemistry models
Bibliographic record
Abstract
Abstract. Detailed ship plume simulations in various convective boundary layer situations have been performed using a Lagrangian Dispersion Model driven by a Large Eddy Simulation Model. The simulations focus on the early stage (1–2 h) of plume dispersion regime and take into account the effects of plume rise on dispersion. Results are presented in an attempt to provide to atmospheric chemistry modellers a realistic description of characteristic dispersion impact on exhaust ship plume chemistry. Plume dispersion simulations are used to derive analytical dilution rate functions. Even though results exhibit striking effects of plume rise parameter on dispersion patterns, it is shown that initial buoyancy fluxes at ship stack have a minor effect on plume dilution rate. After initial high dispersion regimes a simple characteristic dilution time scale can be used to parameterize the subgrid plume dilution effect in large-scale chemistry models. The results show that this parameter is directly related to the typical turn-over time scale of the convective boundary layer.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".