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Record W3115358974 · doi:10.7916/d8rj4vm9

Ozone hole and Southern Hemisphere climate change

2009· article· en· W3115358974 on OpenAlexaboutno aff
Seok‐Woo Son, Neil F. Tandon, L. M. Polvani, Darryn W. Waugh

Bibliographic record

VenueColumbia Academic Commons (Columbia University) · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeClimatologySouthern HemisphereOzone depletionEnvironmental scienceNorthern HemisphereMeteorologyGeographyOzoneGeologyOceanography

Abstract

fetched live from OpenAlex

Climate change in the Southern Hemisphere (SH) has been robustly documented in the last several years. It has altered the atmospheric circulation in a surprising number of ways: a rising global tropopause, a poleward intensification of the westerly jet, a poleward shift in storm tracks, a poleward expansion of the Hadley cell, and many others. While these changes have been extensively related with anthropogenic warming resulting from the increase in greenhouse gases, their potential link to stratospheric cooling resulting from ozone depletion has only recently been examined and a comprehensive picture is still lacking. Examining model output from the coupled climate models participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment (AR4), and grouping them depending on the stratospheric ozone forcing used, we here show that stratospheric ozone affects the entire atmospheric circulation in the SH, from the polar regions to the subtropics, and from the stratosphere to the surface. Furthermore, model projections suggest that the anticipated ozone recovery, resulting from the implementation of the Montreal Protocol, will likely decelerate future climate change resulting from increased greenhouse gases, although it might accelerate surface warming over Antarctica.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.184
Teacher spread0.174 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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