The Ross Sea Dipole – temperature, snow accumulation and sea ice variability in the Ross Sea region, Antarctica, over the past 2700 years
Bibliographic record
Abstract
Abstract. High-resolution, well-dated climate archives provide an opportunity to investigate the dynamic interactions of climate patterns relevant for future projections. Here, we present data from a new, annually-dated ice core record from the eastern Ross Sea. Comparison of the Roosevelt Island Climate Evolution (RICE) ice core records with climate reanalysis data for the 1979–2012 calibration period shows that RICE records reliably capture temperature and snow precipitation variability of the region. RICE is compared with data from West Antarctica (West Antarctic Ice Sheet Divide Ice Core) and the western (Talos Dome) and eastern (Siple Dome) Ross Sea. For most of the past 2,700 years, the eastern Ross Sea was warming with perhaps increased snow accumulation and decreased sea ice extent. However, West Antarctica cooled whereas the western Ross Sea showed no significant temperature trend. From the 17th Century onwards, this relationship changes. All three regions now show signs of warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea, but increasing in the western Ross Sea. Analysis of decadal to centennial-scale climate variability superimposed on the longer term trend reveal that periods characterised by opposing temperature trends between the Eastern and Western Ross Sea have occurred since the 3rd Century but are masked by longer-term trends. This pattern here is referred to as the Ross Sea Dipole, caused by a sensitive response of the region to dynamic interactions of the Southern Annual Mode and tropical forcings.
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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 | 0.001 |
| 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) | 0.000 | 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".