Multi-model assessment of the late-winter stratospheric response to El Niño and La Niña
Bibliographic record
Abstract
Abstract The impact of El Niño-Southern Oscillation (ENSO) on the late-winter extra-tropical stratosphere (January–March) is assessed in a multi-model framework. Three state-of-the-art atmospheric models are run with prescribed SST anomalies representative of a strong ENSO event, with symmetric patterns for El Niño and La Niña. The well-known temperature perturbation in the lower stratosphere during El Niño is captured by two models, in which the anomalous warming at polar latitudes is accompanied by a positive geopotential height anomaly that extends over the polar cap. In the third model, which shows a lack of temperature anomalies over the pole, the anomalous anticyclone is confined over Canada and does not expand to the polar cap. This anomalous center of action emerges from the large-scale tropospheric Rossby wave train forced by ENSO, and shrinking/stretching around the polar vortex is invoked to link it to the temperature response. No disagreement across models is found in the lower stratosphere for La Niña, whose teleconnection is opposite in sign but weaker. In the middle-upper stratosphere (above 50 hPa) the geopotential height anomalies project on a wavenumber-1 (WN1) pattern for both El Niño and, more weakly, La Niña, and show a westward tilt with height up to the stratopause. It is suggested that this WN1 pattern arises from the high-latitude lower-stratospheric anomalies, and that the ENSO teleconnection to the polar stratosphere can be interpreted in terms of upward propagation of the stationary Rossby wave train and quasi-geostrophic balance, instead of wave breaking.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".