Volcanic effects on climate: recent advances and future avenues
Bibliographic record
Abstract
Abstract Volcanic eruptions have long been studied for their wide range of climatic effects. Although global-scale climatic impacts following the formation of stratospheric sulfate aerosol are well understood, many aspects of the evolution of the early volcanic aerosol cloud and regional impacts are uncertain. In the last twenty years, several advances have been made, mainly due to improved satellite measurements and observations enabling the effects of small-magnitude eruptions to be quantified, new proxy reconstructions used to investigate the impact of past eruptions, and state-of-the-art aerosol-climate modelling that has led to new insights on how volcanic eruptions affect the climate. Looking to the future, knowledge gaps include the role of co-emissions in volcanic plumes, the impact of eruptions on tropical hydroclimate and Northern Hemisphere winter climate, and the role of eruptions in long-term climate change. Future model development, dedicated model intercomparison projects, interdisciplinary collaborations, and the application of advanced statistical techniques will facilitate more complex and detailed studies. Ensuring that the next large-magnitude explosive eruption is well observed will be critical in providing invaluable observations that will bridge remaining gaps in our understanding.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".