Impact of Westerly Wind Bursts (WWBs) on ENSO based on a Hybrid Coupled Model: Part II – ENSO Prediction
Bibliographic record
Abstract
With a westerly wind burst (WWB) parameterization scheme introduced into a hybrid coupled model (HCM), we investigated in Part 1 of this study the impact of WWBs on El Nino – Southern Oscillation (ENSO) simulation features, including asymmetry, phase locking, and diversity. In the second part, we investigate the impact of WWBs on ENSO prediction skills. To achieve this, two ensemble experiments, one with WWBs and one without WWBs, are performed to evaluate the predictions of sea surface temperature (SST) anomalies.The results show that both experiments can predict the SST anomalies in the equatorial central and eastern Pacific up to lead times of 12 months. The correlation coefficient between the model and observations shows that the WWB experiment produces better prediction skills than the experiment without WWBs, especially at lead times longer than four months during El Niño events. This result is consistent with the expectation that the WWB parameterization scheme plays an important role in describing physical processes, which is indicated in Part 1. We also presented a predictability analysis for Central Pacific (CP) and Eastern Pacific (EP) El Niño events. The prediction of both types of El Niño events is also improved by the WWB parameterization scheme at long lead times.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".