Strengthened impact of boreal winter North Pacific Oscillation on ENSO development in warming climate
Bibliographic record
Abstract
Abstract The North Pacific Oscillation (NPO), an important mode of atmospheric variability, is a crucial trigger for the development of El Niño-Southern Oscillation (ENSO) via the seasonal footprinting mechanism. How the NPO effect on ENSO changes in response to greenhouse warming remains unclear, however. Here, using climate model simulations under high-emission scenarios, we show that greenhouse warming leads to an enhanced influence of NPO on ENSO as is manifested by enhanced responses of winter sea surface temperature (SST), precipitation and wind anomalies in the equatorial Pacific to the preceding winter NPO. The strengthened NPO impact is also reflected in an increased frequency of NPO events that are followed by ENSO events. Warmer background SST enhances the wind-evaporation-SST feedback over the subtropical North Pacific due to a nonlinear SST-evaporation relationship. This strengthens the NPO-generated surface zonal wind anomalies over the equatorial western-central Pacific, which trigger ENSO. Increased impact of winter NPO on ENSO could enable prediction of interannual variability at longer leads.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".