Mechanism of Interannual Cross‐Equatorial Overturning Anomalies in the Pacific Ocean
Bibliographic record
Abstract
Abstract The meridional overturning circulation (MOC) transports heat and mass between the tropics and the extratropics. Recent research has shown that the variability of the Indo‐Pacific MOC dominates the variability of the global MOC on interannual timescales, and this variability is characterized by a prominent cross‐equatorial cell (CEC) spanning the tropics. This CEC is a potentially important influence on interannual climate variability, but the mechanism responsible for the CEC is not understood. This study seeks to elucidate the mechanism of the CEC using two observational estimates of the ocean. Our analysis shows that the CEC can be explained by the following mechanistic chain: (a) Anomalies in the atmospheric circulation and hydrological cycle produce equatorially antisymmetric density anomalies in the upper Pacific Ocean (above approximately 500 m); (b) these density anomalies generate equatorially antisymmetric anomalies of sea surface height (SSH); (c) these SSH anomalies generate a cross‐equatorial flow above approximately 1,000 m; and (d) this anomalous cross‐equatorial flow drives compensating flow below approximately 1,000 m. This mechanism contrasts with that responsible for anomalous cross‐equatorial overturning on seasonal timescales, which is primarily the Ekman response to equatorially antisymmetric anomalies of zonal wind stress. On interannual timescales, the zonal wind stress anomalies associated with the CEC are equatorially symmetric, and steric SSH variations are the dominant driver of the CEC. These insights may lead to improved understanding and prediction of interannual climate 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".