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Record W2703796628 · doi:10.1175/jcli-d-17-0027.1

Impact of the Montreal Protocol on Antarctic Surface Mass Balance and Implications for Global Sea Level Rise

2017· article· en· W2703796628 on OpenAlexaboutno aff
Michael Previdi, Lorenzo M. Polvani

Bibliographic record

VenueJournal of Climate · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersOffice of Polar Programs
KeywordsMontreal ProtocolOzone layerEnvironmental scienceClimatologyOzone depletionAntarctic treatyClimate changeAtmospheric sciencesAtmosphere (unit)Greenhouse gasMeteorologyStratosphereOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.326
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2017
Admission routes1
Has abstractyes

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