The sensitivity of the El Niño–Southern Oscillation to volcanic aerosol spatial distribution in the MPI Grand Ensemble
Bibliographic record
Abstract
Abstract. Using the Max Planck Institute Grand Ensemble (MPI-GE) with 200 members for the historical simulation (1850–2005), we investigate the impact of the spatial distribution of volcanic aerosols on the El Niño–Southern Oscillation (ENSO) response. In particular, we select three eruptions (El Chichón, Agung and Pinatubo) in which the aerosol is respectively confined to the Northern Hemisphere, the Southern Hemisphere or equally distributed across the Equator. Our results show that relative ENSO anomalies start at the end of the year of the eruption and peak in the following one. We especially found that when the aerosol is located in the Northern Hemisphere or is symmetrically distributed, relative El Niño-like anomalies develop, while aerosol distribution confined to the Southern Hemisphere leads to a relative La Niña-like anomaly. Our results point to the volcanically induced displacement of the Intertropical Convergence Zone (ITCZ) as a key mechanism that drives the ENSO response, while suggesting that the other mechanisms (the ocean dynamical thermostat and the cooling of tropical northern Africa or the Maritime Continent) commonly invoked to explain the post-eruption ENSO response may be less important in our model.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".