A single column simulation-based decomposition of the tropical upper tropospheric warming
Bibliographic record
Abstract
Abstract An atmospheric global climate model (GCM) and its associated single-column model are used to study the tropical upper tropospheric warming and elucidate how different processes drive this warming. In this modeling framework, on average the direct radiative process accounts for 13% of the total warming. The radiation increases the atmospheric lapse rate and triggers more convection, which further produces 74% of the total warming. The rest 13% is attributable to the circulation adjustment. The relative importance of these processes differs in different regions. In the deep tropics, the radiative-convective adjustment produces the most significant warming and accounts for almost 100% of the total warming. In the subtropics, the radiative-convective adjustment accounts for 73% of the total warming and the circulation adjustment plays a more important role than in the deep tropics, especially at the levels above 200 hPa. When the lateral boundary conditions, i.e. the temperature and water vapor advections, are held fixed in single-column simulations, the tropospheric relative humidity significantly increases in the radiative-convective adjustment in response to the surface warming. This result, in contrast to the relative humidity conservation behavior in the GCM, highlights the importance of circulation adjustment in maintaining the constant relative humidity. The tropical upper tropospheric warming in both the full GCM and the single-column simulations is found to be less strong than the warming predicted by reference moist adiabats. This evidences that the sub-moist-adiabat warming occurs even without the dilution effect of the large-scale circulation adjustment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".