Sensitivity of modelled sulfate aerosol and its radiative effect on climate to ocean DMS concentration and air–sea flux
Bibliographic record
Abstract
Abstract. Dimethylsulfide (DMS) is a well-known marine trace gas that is emitted from the ocean and subsequently oxidizes to sulfate in the atmosphere. Sulfate aerosols in the atmosphere have direct and indirect effects on the amount of solar radiation reaching the Earth's surface. Thus, as a potential source of sulfate, ocean efflux of DMS needs to be accounted for in climate studies. Seawater concentration of DMS is highly variable in space and time, which in turn leads to high spatial and temporal variability in ocean DMS emissions. Because of sparse sampling (in both space and time), large uncertainties remain regarding ocean DMS concentration. In this study, we use an atmospheric general circulation model with explicit aerosol chemistry (CanAM4.1) and several climatologies of surface ocean DMS concentration to assess uncertainties about the climate impact of ocean DMS efflux. Despite substantial variation in the spatial pattern and seasonal evolution of simulated DMS fluxes, the global-mean radiative effect of sulfate is approximately linearly proportional to the global-mean surface flux of DMS; the spatial and temporal distribution of ocean DMS efflux has only a minor effect on the global radiation budget. The effect of the spatial structure, however, generates statistically significant changes in the global-mean concentrations of some aerosol species. The effect of seasonality on the net radiative effect is larger than that of spatial distribution and is significant at global scale.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".