Bibliographic record
Abstract
This paper investigates the temporal properties of tropical precipitation in the Canadian Centre for Climate Modelling and Analysis (CCCma) third-generation atmospheric general circulation model (AGCM3). AGCM3 employs the penetrative mass-flux (PMF) scheme of Zhang and McFarlane (ZM) for the parameterization of deep cumulus convection. It is found that the temporal variability of the ZM scheme is sensitive to a number of its internal parameters as well to the use of a prognostic, rather than diagnostic, closure condition for the cloud-base mass flux. Sensitivity experiments suggest that the ZM scheme can produce realistic amounts of variability when compared to direct radar observations of deep cumulus convection in the Tropics. A central finding of this study is that the resolved large-scale stratiform precipitation (LSP) in the model can participate in the modeling of deep latent heating and so compete with the ZM scheme in the Tropics. In modeling deep latent heating the LSP is found to mimic the behavior of a moist-convective adjustment scheme. In AGCM3 it is found that typical parameter settings of the ZM scheme place it in a regime in which the temporal variability of tropical precipitation is dominated by this behavior of the LSP, while the temporal mean is dominated by the ZM scheme. In such circumstances it is the LSP, and not the ZM scheme, that provides the primary source of resolved tropical Kelvin and mixed Rossby–gravity waves in the GCM. Such competition between LSP and the parameterization of deep convection appears to be active in other modeling studies. Consequently, it has the potential to complicate efforts to understand the nature of resolved tropical waves in GCMs and their role in the forcing of the quasi-biennial and semiannual oscillations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".