Interaction between the Tropical Atlantic and Pacific Oceans on an Interannual Time Scale
Bibliographic record
Abstract
Based on the fifth-generation reanalysis of the European Centre for Medium-range Weather Forecasts (ECMWF), the Hadley Centre sea surface temperature (SST) data, and the Global Precipitation Climatology Project (GPCP) precipitation data, the interaction between the tropical Atlantic and Pacific Oceans on an interannual time scale is investigated using correlation, regression, and composite analyses, and the quantitative estimates of the relative and collective contribution of the tropical North Atlantic (NTA) and equatorial Atlantic (ETA) SST anomalies to the El Niño–Southern Oscillation (ENSO) are presented. An El Niño or La Niña event can cause a same-sign SST anomaly in the NTA in the following boreal spring, accounting for 33% of the interannual variability of the NTA SST. The NTA SST anomaly may excite a same-sign SST anomaly of the ETA in boreal summer with an ETA SST anomaly of 0.44°C per 1°C NTA SST anomaly. Moreover, an SST anomaly in the NTA and ETA can cause an opposite-sign SST anomaly in the equatorial Pacific during the following winter. The NTA SST anomaly influences the central equatorial Pacific with a Niño 3.4 SST anomaly of −0.85°C per 1°C NTA SST anomaly, while the ETA SST anomaly exerts an impact on the central-eastern equatorial Pacific with a Niño 3.4 SST anomaly of −1.85°C per 1°C ETA SST anomaly based on a multiple regression analysis. The composite analyses based on Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) hindcasts show that the ETA SST anomaly in summer acts as a primary contributor to the interaction between the tropical Atlantic and Pacific Oceans. The ETA impact can relay and amplify the NTA SST anomaly such that it affects the equatorial Pacific. The collective impact of spring NTA and summer ETA SST anomalies can explain 33% of the total variance of the winter Niño 3.4 index. This study deepens our understanding of the interannual interaction between the tropical Atlantic and Pacific Oceans and highlights the role of the tropical Atlantic Ocean, especially the ETA region, in the pan-tropical air–sea interaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".