Bibliographic record
Abstract
The 2015/2016 El Niño was one of the strongest El Niño events in history, and this strong event was preceded by a weak El Niño in 2014. This study systematically analyzed the dynamical processes responsible for the genesis of these events. It was found that the weak 2014 El Niño had two warming phases, the spring-summer warming was produced by zonal advection and downwelling Kelvin waves driven by westerly wind bursts (WWBs), and the autumn-winter warming was produced by meridional advection, surface heating as well as downwelling Kelvin waves. The 2015/2016 extreme El Niño, on the other hand, was primarily a result of sustained zonal advection and downwelling Kelvin waves driven by a series of WWBs, with enhancement from the Bjerknes positive feedback. The vast difference between these two El Niño events mainly came from the different amount of WWBs in 2014 and 2015. As compared to the 1982/1983 and 1997/1998 extreme El Niño events, the 2015/2016 El Niño exhibited some distinctive characteristics in its genesis and spatial pattern. We need to include the effects of WWBs to the theoretical framework of El Niño to explain these characteristics, and to improve our understanding and prediction of El Niño.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.025 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.008 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".