Impact of the Montreal Protocol on Antarctic Surface Mass Balance and Implications for Global Sea Level Rise
Bibliographic record
Abstract
Abstract The Montreal Protocol on Substances that Deplete the Ozone Layer, adopted in 1987, is an international treaty designed to protect the ozone layer by phasing out emissions of chlorofluorocarbons and other ozone-depleting substances (ODSs). A growing body of scientific evidence now suggests that the implementation of the Montreal Protocol will have significant effects on climate over the next several decades, both by enabling stratospheric ozone recovery and by decreasing atmospheric concentrations of ODSs, which are greenhouse gases. Here, using a state-of-the-art chemistry–climate model, the Community Earth System Model (Whole Atmosphere Community Climate Model) [CESM(WACCM)], it is shown that the Montreal Protocol, through its impact on atmospheric ODS concentrations, leads to a substantial decrease in Antarctic surface mass balance (SMB) over the period 2006–65 relative to a hypothetical “World Avoided” scenario in which the Montreal Protocol has not been implemented. This SMB decrease produces an additional 25 mm of global sea level rise (GSLR) by the year 2065 relative to the present day. It is found, however, that the additional GSLR resulting from the relative decrease in Antarctic SMB is more than offset by a reduction in ocean thermal expansion, leading to a net mitigation of future GSLR due to the Montreal Protocol.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".