Recent breakdown of the seasonal linkage between the winter North Atlantic Oscillation/Northern Annular Mode and summer Northern Annular Mode
Bibliographic record
Abstract
The summer northern annular mode (NAM) and the winter North Atlantic Oscillation (NAO)/winter NAM have a positive correlation from the mid-1960s to the 1980s. Namely, when the winter NAO/NAM is in a positive phase, the following summer NAM tended to be in a positive phase. During the period from the mid-1960s to the 1980s, the NAO/NAM signals extended to the stratosphere in winter. Also, the lower-tropospheric warm anomaly over northern Eurasia in winter associated with the positive phase of NAO/NAM continued into spring. In summer, the annular anomalies in the temperature and 500-hPa height fields appeared, and the high-latitude westerly wind was enhanced following the winter positive NAO/NAM. However, after circa 1990, the seasonal linkage was broken (i.e., the winter-to-summer correlation became insignificant). The stratospheric signal in the winter NAO/NAM became weak and summer signals associated with the winter NAO/NAM almost disappeared. Seasonal evolutions of atmospheric circulation and sea surface temperature (SST) anomalies associated with the winter NAO are examined for an early good-linkage period and a recent poor-linkage period. We discuss the possible causes of the linkage breakdown such as stratospheric ozone, North Atlantic SST, and Atlantic multidecadal oscillation, besides chaotic internal variability in the climate system. Simulations with the Community Earth System Model suggest that the ocean and/or sea ice with interseasonal memories possibly cause the linkage, besides large internal variability through which the linkage can take place by chance.
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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 | 0.002 |
| 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 | 0.000 | 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".