The Influence of the Cloud Shell on Tracer Budget Measurements of LES Cloud Entrainment
Bibliographic record
Abstract
Abstract Direct measurements of rates of entrainment into and detrainment from cumulus cloud cores obtained from LES model cloud fields produce values twice as large as those produced from tracer budget calculations. This difference can be explained by two effects: the presence of a shell of air around the cloud cores that is moister than the mean environment and air at the edge of the cloud core that is drier than the mean core, and the tendency for the mean tracer values of the entrained fluid to be greater than the mean tracer values of the cloud shell. Preferential entrainment of shell air that is moving upward faster than the mean shell creates strong vertical momentum fluxes into the cumulus cloud core, thereby making the assumption that cumulus cloud cores entrain fluid with zero vertical momentum incorrect. Variability in the properties of the moist cloud shell has strong impacts on entrainment values inferred from tracer budget calculations. These results indicate that the dynamics of the cloud shell should be included in parameterization of cumulus clouds used in general circulation models.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".