The Tropical Tropopause Layer 1960–2100
Bibliographic record
Abstract
Abstract. The representation of the Tropical Tropopause Layer (TTL) in 13 different Chemistry Climate Models (CCMs) designed to represent the stratosphere is analyzed. Simulations for 1960–2005 and 1980–2100 are analyzed. Simulations for 1960–2005 are compared to reanalysis model output. CCMs are able to reproduce the basic structure of the TTL. There is a large (10 K) spread in annual mean tropical cold point tropopause temperatures. CCMs are able to reproduce historical trends in tropopause pressure obtained from reanalysis products. Simulated historical trends in cold point tropopause temperatures are not consistent across models or reanalyses. The pressure of both the tropical tropopause and the level of main convective outflow appear to have decreased (increased altitude) in historical runs as well as in reanalyses. Decreasing pressure trends in the tropical tropopause and level of main convective outflow are also seen in the future. Models consistently predict decreasing tropopause and convective outflow pressure, by several hPa/decade. Tropical cold point temperatures are projected to increase by 0.09 K/decade. Tropopause anomalies are highly correlated with tropical surface temperature anomalies and with tropopause level ozone anomalies, less so with stratospheric temperature anomalies. Simulated stratospheric water vapor at 90 hPa increases by up to 0.5–1 ppmv by 2100. The result is consistent with the simulated increase in temperature, highlighting the correlation of tropopause temperatures with stratospheric water vapor.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".