Performance of the <scp>IPCC AR6</scp> models in simulating the relation of the western North Pacific subtropical high to the spring northern tropical Atlantic <scp>SST</scp>
Bibliographic record
Abstract
Abstract This study examines the relationship between the spring northern tropical Atlantic (NTA) sea surface temperature (SST) and its following summer western North Pacific subtropical high (WNPSH) in historical simulations of 20 coupled models of the IPCC AR6. These models well simulate the spring NTA SST, as well as the WNPSH‐related atmospheric and precipitation anomalies over the Asian monsoon region. Ensemble mean of these models reproduces the observed relation and processes linking the spring NTA SST to the summer WNPSH. In the ensemble mean, spring NTA SST warming persists to the following summer, and induces an anomalous Walker circulation with an ascent over the tropical Atlantic and a descent over the tropical central Pacific. The associated precipitation decrease over the tropical central Pacific induces an anomalous low‐level anticyclone over the WNP via a Rossby wave atmospheric response. Meanwhile, spring NTA SST warming leads to easterly wind anomalies over the Indian Ocean (IO) via a Kelvin wave atmospheric response and causes SST warming there via reducing wind speeds. Then, the precipitation anomalies induced by the IO SST warming result in an enhancement of the WNPSH. There exists a large diversity of the NTA SST‐WNPSH relationship among the models. This diversity is related to the difference in the climatological mean IO precipitation. The models with large mean IO precipitation provide a favourable condition for the IO SST warming to bring large local precipitation anomalies and trigger strong easterly wind anomalies over the tropical WNP, and thus exert a strong impact on the WNPSH.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".