On the low-frequency variability of wintertime Euro-Atlantic planetary wave-breaking
Bibliographic record
Abstract
Planetary wave-breaking can lead to large-scale atmospheric circulation anomalies and favour high-impact weather occurrences. For example, the simultaneous occurrence of anti-cyclonic wave-breaking to the south of the North Atlantic jet and cyclonic wave-breaking to the north, here termed double wave-breaking, has been linked to heightened frequencies of explosive cyclones in the Atlantic basin and destructive windstorms over Western and Continental Europe. The present study analyses the long-term temporal variability of wintertime cyclonic and anti-cyclonic wave-breaking, and the resulting double wave-breaking, in the North Atlantic. We use reanalysis data, proxy reconstructions of the North Atlantic Oscillation (NAO) and a 1000-year coupled global climate model equilibrium simulation under constant pre-industrial forcing. The wave-breaking wavelet spectra highlight a significant ultra-centennial variability in double wave-breaking frequency, which is largely mirrored in the variability of the NAO. However, we note that the NAO wavelet spectra in the different datasets display significant discrepancies. The low-frequency wave-breaking variability is reflected in long-term anomalies of the large-scale atmospheric circulation in the Euro-Atlantic sector. The 100-year periods with the most and least double wave-breaking occurrences display significant and opposite anomalies in both upper and lower-level wind, as well as in the frequency of extreme temperature events and in the magnitude of wind destructiveness over Europe. The latter broadly resembles the wind destructiveness anomalies associated with individual double wave-breaking instances in reanalysis data. The existence of low-frequency variability in an atmospheric pattern related to high-impact weather events has important implications for the study and interpretation of climate change projections and of possible future NAO changes.
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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) | 0.001 | 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".