Will marine dimethylsulfide emissions amplify or alleviate global warming? A model study
Bibliographic record
Abstract
Dimethylsulfide (DMS) is the most abundant volatile sulfur compound at the sea surface and has a strong marine phytoplanktonic origin. Once outgased into the atmosphere, it contributes to the formation of sulfate aerosol particles that affect the radiative budget as precursors of cloud condensation nuclei (CCN). It has been postulated that climate may be partly modulated by variations in DMS production. We test this hypothesis in the context of anthro pogenic climate change and present here, modelled for the first time, an estimate of the radiative impact resulting from changes in DMS airsea fluxes caused by global warming. At 2× CO2, our model estimates a small increase (3%) in the global DMS flux to the atmosphere but with large spatial heterogeneities (from 15% to 30%). The radiative perturbation resulting from the DMS-induced change in cloud albedo is estimated to be 0.05 W·m2, which represents only a small negative climate feedback on global warming. However, there are large regional changes, such as a perturbation of up to 1.5 W·m2 in summer between 40°S and 50°S, that can impact the regional climate. In the Southern Ocean, the radiative impact resulting from changes in the DMS cycle may partly alleviate the radiative forcing resulting from anthropogenic CO2.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".