Reexamining the connection of <scp>El Niño and North American</scp> winter climate
Bibliographic record
Abstract
Abstract According to the ENSO amplitude and the zonal gradient in sea surface temperature anomaly (SSTA) between eastern and western Pacific, three types of El Niño are classified. The greater than average amplitude events are considered to be the strong El Niño (SEN), which commonly exhibits a salient zonal gradient over the Pacific and the surface warming in the Indian Ocean. The large‐scale atmospheric anomalies of SEN correspond to a typical Pacific‐North America teleconnection propagating along the great circle route over North Pacific‐North America (NP‐NA), resulting in a warm winter in northern NA but an opposite condition over southern NA. The less than average amplitude events are weak El Niños, which can be subdivided according to the zonal gradient of Pacific. The strong gradient weak El Niño shows an SEN‐like SSTA distribution within the Pacific, which induces an intensified Aleutian low and a negative North Atlantic Oscillation (NAO) anomaly. As a result, a cold (warm) T2m pattern is observed over southeastern NA (eastern Canada). The weak gradient weak El Niño, featuring a warmer than normal SST anomalies pattern along the equatorial Indian Ocean and central to eastern Pacific, generates an eastward propagating wave train from North Pacific to the eastern North American continent that results in a meridional seesaw T2m anomalies pattern over the NA continent. Interestingly, the T2m anomalies over NA for three types of El Niño correspond to the three leading modes of NA winter T2m variability. In addition, the above ENSO teleconnections can be reproduced through a series of numerical experiments.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".