Cross–Seasonal Impact of SST Anomalies over the Tropical Central Pacific Ocean on the Antarctic Stratosphere
Bibliographic record
Abstract
Abstract. In this study we examine the cross–seasonal effects of boreal winter sea surface temperature (SST) anomalies over the central tropical Pacific (Niño4 region) on Antarctic stratospheric circulation and ozone transport during the subsequent austral winter using ERA5 reanalysis of 45 years (1980–2024). Our analyses show that warm (cold) SST anomalies in Niño4 region during December–February are associated with polar stratospheric warming (cooling), a weakened (strengthened) stratospheric polar vortex (SPV), and enhanced (suppressed) polar ozone concentrations during July–September of the subsequent year. This delayed response is mediated by a Pacific–South America (PSA) teleconnection, which excites planetary waves that propagate upward into stratosphere and modify the Brewer–Dobson circulation. In addition, as the influence of Niño4 SSTs on the PSA teleconnection pattern diminishes during July–September, surface heat feedback at mid and high latitudes becomes critically important for planetary waves. Specifically, persistent South Pacific SST warming and sea-ice loss over the Amundsen and Ross Seas reinforce planetary waves by releasing heat from ocean into atmosphere. A multivariate regression statistical model using predictors of boreal winter Niño4 SST, June PSA, June South Pacific SST, and May–June sea-ice concentration (SIC) indices explain approximately 35 % of the variance in austral winter stratospheric temperatures. These findings highlight a previously underexplored pathway through which tropical Pacific SST anomalies modulate Antarctic stratospheric dynamics and chemistry on seasonal timescales. This implies a new insight into tropical–polar coupling and provides a potential signal for extended–range forecasts of ozone depletion risk.
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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 | 0.001 |
| 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) | 0.002 | 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".