A Review of Atmosphere–Ocean Forcings Outside the Tropical Pacific on the El Niño–Southern Oscillation Occurrence
Bibliographic record
Abstract
The El Niño–Southern Oscillation (ENSO) is the strongest interannual air–sea coupled variability mode in the tropics, and substantially impacts the global weather and climate. Hence, it is important to improve our understanding of the ENSO variability. Besides the well-known air–sea interaction process over the tropical Pacific, recent studies indicated that atmospheric and oceanic forcings outside the tropical Pacific also play important roles in impacting and modulating the ENSO occurrence. This paper reviews the impacts of the atmosphere–ocean variability outside the tropical Pacific on the ENSO variability, as well as their associated physical processes. The review begins with the contribution of the atmosphere–ocean forcings over the extratropical North Pacific, Atlantic, and Indian Ocean on the ENSO occurrence. Then, an overview of the extratropical atmospheric forcings over the Northern Hemisphere (including the Arctic Oscillation and the Asian monsoon systems) and the Southern Hemisphere (including the Antarctic Oscillation and the Pacific–South American teleconnection), on the ENSO occurrence, is presented. It is shown that the westerly (easterly) wind anomaly over the tropical western Pacific is essential for the occurrence of an El Niño (a La Niña) event. The wind anomalies over the tropical western Pacific also play a key role in relaying the impacts of the atmosphere–ocean forcings outside the tropical Pacific on the ENSO variability. Finally, some relevant questions, that remain to be explored, are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".