Compensating atmospheric adjustments reduce the volcanic forcing from Hunga stratospheric water vapor enhancement
Bibliographic record
Abstract
The 2022 eruption of the Hunga submarine volcano injected an unprecedented volume of water vapor into the stratosphere, presenting a unique, natural experiment for ascertaining the influence of stratospheric water vapor within the global radiation budget. This study examines the radiative forcings of the Hunga stratospheric water vapor enhancement, comparing stratosphere-adjusted radiative forcing derived from offline methods to an effective radiative forcing derived from Earth System Model simulations. Assuming a uniform 2 parts per million mass mixing ratio increase of water vapor in the Southern Hemisphere stratosphere, we estimated the instantaneous, stratosphere-adjusted, and overall effective radiative forcing to be −0.04, 0.08, and 0.05 W m −2 , respectively. The lower magnitude of the positive volcanic stratospheric water vapor effective radiative forcing is due to compensating effects from atmospheric adjustments. Ensemble simulations of a coupled atmosphere-ocean model suggest a surface warming of 0.05 K, affirming a limited influence on global mean surface temperature from the volcanic stratospheric water vapor injection.
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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 | 0.000 |
| 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".