Impact of tropical cyclones over the eastern North Pacific on El Niño–Southern Oscillation intensity
Bibliographic record
Abstract
Most tropical cyclones (TCs) generated over the eastern North Pacific (ENP) do not make landfall. Consequently, TCs in this basin have received less attention, especially those that occur away from the mainland. Furthermore, there have been few studies of the climatic effects of ENP TCs. This study explores the feedback relationship between ENP TCs and the intensity of the El Niño–Southern Oscillation (ENSO), including El Niño and La Niña events, from the perspective of accumulated cyclone energy (ACE). Observational and modeling results indicate that the ENP ACE 3 months earlier can still affect the intensity of El Niño and La Niña events, although the SST persistence is main contributor. Thereinto, the impact of ENP TCs on El Niño appears to be approximately equal to that on La Niña. Moreover, this impact is independent of the persistence of the sea surface temperature (SST) in the Niño 3.4 region and the Madden–Julian Oscillation. Generally, the greater the ENP ACE, the stronger the El Niño, and the smaller the ENP ACE, the stronger the La Niña, this is especially the case for those TCs that develop over the July‒September period. In addition, results show that the ENP TCs modulate ENSO intensity by changing anomalous zonal wind at the low-level atmospheric layer. And the joint impacts of the low-level zonal wind anomalies on the Walker circulation and the east-west thermocline gradient lead to the time characteristics that ENP TCs lead ENSO intensity by about 3 months. This study proposes a cross-time-scale role for tropical cyclones in the development of ENSO, further expanding the theoretical framework for ENSO's development, and offering significant scientific relevance and practical value for its prediction.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".