Aerosol‐driven increase in Arctic sea ice over the middle of the twentieth century
Bibliographic record
Abstract
Abstract Updated observational data sets without climatological infilling show that there was an increase in sea ice concentration in the eastern Arctic between 1950 and 1975, contrary to earlier climatology infilled observational data sets that show weak interannual variations during that time period. We here present climate model simulations showing that this observed sea ice concentration increase was primarily a consequence of cooling induced by increasing anthropogenic aerosols and natural forcing. Indeed, sulphur dioxide emissions, which lead to the formation of sulphate aerosols, peaked around 1980 causing a sharp increase in the burden of sulphate between the 1950s and 1970s; but since 1980, the burden has dropped. Our climate model simulations show that the cooling contribution of aerosols offset the warming effect of increasing greenhouse gases over the midtwentieth century resulting in the expansion of the Arctic sea ice cover. These results challenge the perception that Arctic sea ice extent was unperturbed by human influence until the 1970s, suggesting instead that it exhibited earlier forced multidecadal variations, with implications for our understanding of impacts and adaptation in human and natural Arctic systems.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".