Vertical distributions of sulfur species simulated by large scale atmospheric models in COSAM: Comparison with observations
Bibliographic record
Abstract
A comparison of large-scale models simulating atmospheric sulfate aerosols (COSAM) was conducted to increase our understanding of global distributions of sulfate aerosols and precursors. Earlier model comparisons focused on wet deposition measurements and sulfate aerosol concentrations in source regions at the surface. They found that different models simulated the observed sulfate surface concentrations mostly within a factor of two, but that the simulated column burdens and vertical profiles were very different amongst different models. In the COSAM exercise, one aspect is the comparison of sulfate aerosol and precursor gases above the surface. Vertical profiles of SO2, SO2−4, oxidants and cloud properties were measured by aircraft during the North Atlantic Regional Experiment (NARE) experiment in August/September 1993 off the coast of Nova Scotia and during the Second Eulerian Model Evaluation Field Study (EMEFSII), in central Ontario in March/April 1990. While no single model stands out as being best or worst, the general tendency is that those models simulating the full oxidant chemistry tend to agree best with observations although differences in transport and treatment of clouds are important as well.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".