The predictability study of the two flavors of ENSO in the CESM model from 1881 to 2017
Bibliographic record
Abstract
Abstract In this study, we evaluated the predictability of the two flavors of the El Niño Southern Oscillation (ENSO) based on a long-term retrospective prediction from 1881 to 2017 with the Community Earth System Model. Specifically, the Central-Pacific (CP) ENSO has a more obvious Spring Predictability Barrier and lower deterministic prediction skill than the Eastern-Pacific (EP) ENSO. The potential predictability declines with lead time for both the two flavors of ENSO, and the EP ENSO has a higher upper limit of the prediction skill as compared with the CP ENSO. The predictability of the two flavors of ENSO shows distinct interdecadal variation for both actual skill and potential predictability; however, their trends in the predictability are not synchronized. The signal component controls the seasonal and interdecadal variations of predictability for the two flavors of ENSO, and has larger contribution to the CP ENSO than the EP ENSO. There is significant scope for improvement in predicting the two flavors of ENSO, especially for the CP ENSO.
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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 | 0.002 | 0.000 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".