The atmospheric response to North Atlantic SST anomalies in seasonal prediction experiments
Bibliographic record
Abstract
Seasonal forecasts performed over a 26 yr period as part of the Historical Seasonal Forecasting Project (HFP) are used to analyze the influence of North Atlantic sea surface temperature (SST) anomalies on the atmospheric circulation, its seasonality, and model dependence. The signals related to the El Nino events are first removed from both the SST and the atmospheric data. The North Atlantic SST and the ensemble mean forecast are then correlated over the 26 yr to identify the model response to the SST forcing. The signal-to-noise ratio shows that in spring there is a significant forecast signal that is related to the SST anomaly in the North Atlantic. In that season the two models used in the HFP yield responses to the SST anomaly that are both similar to each other and to the observed response. For the other seasons the agreement between the responses and the observed atmospheric anomalies is poor. In winter the response is very sensitive to the model used.
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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 | 0.002 |
| 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 | 0.000 | 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".