Formation and Maintenance of the Tropical Cold-Point Tropopause in a Dry Dynamic-Core GCM
Bibliographic record
Abstract
Abstract The formation of the tropical cold-point tropopause (CPT) is examined using a dry primitive equation model driven by the Held–Suarez forcing. Without moist and realistic radiative processes, the dry model successfully reproduces the zonal-mean structure of the CPT. The modeled CPT is appreciably colder (~10 K) than the prescribed equilibrium temperature, and it is maintained by upwelling in the tropical upper troposphere and lower stratosphere (UTLS). A transient simulation starting from an axisymmetric steady state without the CPT shows that the evolution and maintenance of the CPT are closely related to the zonal-mean-flow response to wave driving in the stratosphere. The transformed Eulerian-mean analysis indicates that the wave driving is mostly due to convergence of synoptic-scale waves originating from the midlatitude troposphere and propagating into the subtropical UTLS in this model simulation. The modeled CPT also shows a large sensitivity to increased baroclinicity in the equilibrium temperature. Although planetary-scale waves are not considered in this simulation, the result confirms that wave-driven upwelling in the tropical UTLS is a crucial process for the formation and maintenance of the CPT. In addition, it also implies that synoptic-scale waves may play a nonnegligible role in this mechanism, particularly in the seasons when planetary-scale wave activity in the lower stratosphere is weak.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".