Asymmetric influence of boreal spring Arctic Oscillation on subsequent ENSO
Bibliographic record
Abstract
Abstract Previous studies have suggested that the boreal spring Arctic Oscillation (AO) could exert a significant influence on the outbreak of El Niño–Southern Oscillation (ENSO) during the following winter. This study further reveals that the influence of the spring AO on the subsequent ENSO is asymmetric. When the spring AO is in its high phase, significant El Niño‐like sea surface temperature (SST) warming anomalies are observed over the tropical central eastern Pacific in the following winter. However, when the spring AO is in its low phase, negative SST anomalies over the tropical central eastern Pacific are weak and statistically insignificant. This asymmetric influence is attributed to the asymmetric features of both the atmospheric circulation anomalies in spring and atmospheric heating anomalies over the subtropical North Pacific from spring to summer. For the high AO phase composite, the anomalous cyclonic circulation over the subtropical western North Pacific and the related westerly wind anomalies to its south over the tropical western Pacific are strong and significant in spring. The tropical zonal wind anomalies would trigger ENSO events via the excitation of an eastward propagating Kelvin wave. Meanwhile, the atmospheric heating anomalies over the subtropical North Pacific play an important role in sustaining the westerly wind over the tropical western Pacific from spring to summer. In contrast, the counterparts in the low AO phase composite are weak and statistically insignificant. Our results indicate that the phase of spring AO should be taken into account when using spring AO as a predictor for ENSO.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".