The mechanisms and the predictability of the Arctic oscillation and the North Atlantic oscillation /
Bibliographic record
Abstract
The Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO) are the most pronounced modes of extratropical atmospheric wintertime variability in the Northern Hemisphere. This thesis investigates different aspects of the AO and NAO on the in traseasonal and seasonal time scales. First, the question of how the differences between the AO and NAO are influenced by the choice of the definitions of the NAO and to what extent the AO and NAO differ from each other is investigated using the daily NCEP/NCAR reanalysis data spanning 51 boreal winters. One AO index and four different NAO indices are used in this study. It is found that the AO and NAO are quite similar to each other when both are defined using pattern-based indices, while some notable differences are observed between them when the NAO is defined using a station/gridpoint-based index. Then the predictability of the AO and NAO is examined using a simple general circulation model (SGCM). Numerical experiments are performed to determine the sensitivity of the setup processes of the AO and NAO to the details of the initial conditions. The predictive skills for the AO and NAO are compared to each other. Finally, the potential role of tropical Pacific forcing in driving the seasonal variability of the AO is explored using both observations and the SGCM. The results indicate that a negative thermal forcing over the western tropical Pacific and a positive forcing north of the equatorial mid-Pacific play important roles in producing an AO-like atmospheric response.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".