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Record W4322209656 · doi:10.5194/egusphere-egu23-13881

Montreal Protocol's impact on the ozone layer and climate

2023· preprint· en· W4322209656 on OpenAlexaboutno aff
Jan Sedláčék, ‪Tatiana Egorova, Timofei Sukhodolov, Arseniy Karagodin‐Doyennel, Franziska Zilker, Eugene Rozanov

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal ProtocolOzone layerEnvironmental scienceRadiative forcingOzone depletionClimatologyOzoneAtmospheric sciencesClimate changeGlobal warmingClimate modelForcing (mathematics)Atmosphere (unit)PrecipitationMeteorologyAerosolGeographyOceanography

Abstract

fetched live from OpenAlex

It is now recognized and confirmed that the ozone layer shields the biosphere from dangerous solar UV radiation and is also important for the global atmosphere and climate. The observed massive ozone depletion forced the introduction of limitations on the production of halogen-containing ozone-depleting substances (hODS) by the Montreal Protocol and its Amendments and adjustments (MPA). Further research was aimed at analyzing the role played by the Montreal Protocol to increase public awareness of its necessity. In this study, we evaluate the benefits of the Montreal Protocol on climate and ozone evolution using the Earth system model (ESM) SOCOLv4.0 which includes dynamic ocean, sea ice, interactive ozone, and stratospheric aerosol modules. Here, we analyze the results of the numerical experiments performed with and without limitations on the ozone-depleting substances emissions. In the experiments, we have used CMIP6 SSP2-4.5 and SSP5-8.5 scenarios for future forcing behavior. We confirm previous results regarding catastrophic ozone layer depletion in the case without MPA limitations. The climate effects of MPA consist of additional global mean warming by up to 2.5 K in 2100 caused by the direct radiative effect of the hODS. We also obtained dramatic changes in several essential climate variables such as regional surface air temperature, sea-ice cover, and precipitation fields. The warming rate without the MPA under the SSP2-4.5 scenario is comparable to the warming rate of the SSP5-8.5 scenario with MPA. Our research updates and complements previous modeling studies on the quantifying of MPA benefits for the terrestrial atmosphere and climate.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.572
Threshold uncertainty score0.861

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.039
GPT teacher head0.288
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2023
Admission routes1
Has abstractyes

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