Nonlinear singular spectrum analysis of the tropical stratospheric wind
Bibliographic record
Abstract
Abstract The neural‐network‐based nonlinear singular spectrum analysis (NLSSA) is applied to the zonal winds in the 70–10 hPa region (roughly 20–30 km altitude) measured at near‐equatorial stations during 1956–2000. The data are pre‐filtered by the linear singular spectrum analysis (SSA), with the leading eight SSA principal components (PCs) used as inputs for the NLSSA. The NLSSA fits a curve to the data in the eight‐dimensional PC space. This NLSSA curve, when projected onto the two‐dimensional plane spanned by any two PCs, shows the relation between the two SSA PCs. As different SSA modes are associated with different time‐scales, the relations found by the NLSSA reveal the time‐scales between which there are interactions—interactions between the dominant quasi‐biennial oscillation (QBO) time‐scale of about 28 months and the first harmonic at 14 months, and between 28 months and 12 months are found. The anharmonic nature of the QBO is well represented by the NLSSA mode 1, but not by individual SSA modes. The NLSSA is also applied to the time series of the zonal‐wind acceleration. Copyright © 2003 Royal Meteorological Society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| 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 | 0.001 |
| 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 teacher head, 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".