Thermal characteristics of the cold‐point tropopause region in CMIP5 models
Bibliographic record
Abstract
The climatology, seasonality, and intraseasonal to interannual variability of the temperature field near the cold‐point tropopause (CPT) are examined using the state‐of‐the‐art climate models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both historical simulations and future projections based on the Representative Concentration Pathway (RCP) 8.5 scenario are used to evaluate model performance and to identify potential changes at the CPT focusing on the 100 hPa and zero‐lapse‐rate (ZLR) temperatures. It is found that historical simulations successfully reproduce the large‐scale spatial structure and seasonality of observed temperature and reasonably capture variability associated with El Niño‐Southern Oscillation and equatorial waves near the CPT. However, the models show nonnegligible biases in several aspects: (1) most models have a warm bias around the CPT, (2) large intermodel differences occur in the amplitude of the seasonal cycle in 100 hPa temperature, (3) several models overestimate lower stratospheric warming in response to volcanic aerosols, (4) temperature variability associated with the quasi‐biennial oscillation and Madden‐Julian oscillation is absent in most models, and (5) equatorial waves near the CPT exhibit a wide range of variations among the models. In the RCP 8.5 scenario, the models predict robust warming both at the 100 hPa and ZLR levels, but cooling at the 70 hPa level. A weakened seasonal cycle in the temperature is also predicted in most models at both the 100 and 70 hPa levels. These findings may have important implications for cross‐tropopause water vapor transport and related global climate change and variability.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".