Sub-seasonal Forecast Skill for Weekly Mean Atmospheric Variability over the Northern Hemisphere in Winter and its Relationship to Mid-Latitude Teleconnections
Bibliographic record
Abstract
This study assesses the sub-seasonal predictability of the weekly mean geopotential height anomaly at 500 hPa and its relationship to teleconnections over the Northern Hemisphere in winter. The skill over the North Pacific, Canada, and Greenland is higher than over other areas for week-3 and -4 forecasts. These peaks correspond to the centers of action for the Pacific–North American (PNA) pattern and the North Atlantic Oscillation (NAO). PNA (NAO phase) predictions are better for El Niño years at lead times of 4 weeks (2–4 weeks). The effects of La Niña forcing on PNA and NAO forecasts are small compared with the El Niño forcing. Numerical models tend to predict a negative PNA at lead times of 3–4 weeks in La Niña years. The improvement in the mid-latitude upper-level jet rather than in the atmospheric response to ENSO forcing in the tropics is important for better S2S prediction.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".