Linear interference and the initiation of extratropical stratosphere‐troposphere interactions
Bibliographic record
Abstract
Vertical fluxes of wave activity from the troposphere to the stratosphere correlate negatively with the Northern Annular Mode (NAM) index in the stratosphere and subsequently in the troposphere. Recent studies have shown that stratospheric NAM variability is also negatively correlated with the amplitude of the wave pattern coherent with the large‐scale climatological stationary wavefield; when the climatological stationary wavefield is amplified or attenuated, the stratospheric jet correspondingly weakens or strengthens. Here we quantify the importance of this linear interference effect in initiating stratosphere‐troposphere interactions by performing a decomposition of the vertical wave activity flux using reanalysis data. The interannual variability in vertical wave activity flux in both the Northern and Southern Hemisphere extratropics is dominated by linear interference of quasi‐stationary waves during the season of strongest stratosphere‐troposphere coupling. Composite analysis of anomalous vertical wave activity flux events reveals the significant role of linear interference and shows that “linear” and “nonlinear” events are essentially independent. Linear interference is the dominant contribution to the vertical wave activity flux anomalies preceding displacement stratospheric sudden warmings (SSWs) while split SSWs are preceded by nonlinear wave activity flux anomalies. Wave activity variability controls the timing of stratospheric final warmings, and this variability is shown to be dominated by linear interference, particularly in the Southern Hemisphere. The persistence of the linear interference component of the vertical wave activity flux, corresponding to persistent constructive or destructive interference between the wave‐1 component of climatological stationary wave and the wave anomaly, may help improve wintertime extratropical predictability.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".