ENSO and NAO Linkage to Strong Volcanism and Associated Post-Volcanic High-latitude Winter Warming
Bibliographic record
Abstract
High-latitude winter warming was observed following strong tropical volcanism, which has long been believed to be due to the volcanic-induced positive NAO phase. However, recent works argue that this warming is caused by ENSO variability. Moreover, controversies exist about the sensitivity of ENSO to volcanism. Therefore, to better resolve the controversies related to post-volcanic ENSO and NAO sensitivity and associated high-latitude winter warming, we conducted ENSO-preconditioned volcanic experiments using GFDL-CM2.1 coupled model. Our simulations strongly suggest that the post-eruption Eurasian winter warming is caused by a post-eruption positive NAO phase and not by coexisting ENSO-preconditioned variability. Additionally, we find that the El Niño-preconditioned volcanic eruption enhances the El Niño phase; however, the neutral and La Niña-preconditioned volcanisms do not lead to ENSO–like response. These findings are helpful to better understand volcanic-induced circulation impacts and have important implications for the interpretation of model results and for post-volcanic 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".