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Record W1952214568 · doi:10.1029/2010gl044301

Has the ozone hole contributed to increased Antarctic sea ice extent?

2010· article· en· W1952214568 on OpenAlexaff
Michael Sigmond, John C. Fyfe

Bibliographic record

VenueGeophysical Research Letters · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Toronto
Fundersnot available
KeywordsOzone depletionSea iceSouthern HemisphereCryosphereOceanographyClimatologyEnvironmental scienceNorthern HemisphereAntarctic sea iceArctic ice packAtmospheric sciencesOzone layerEkman transportGeologyStratosphereUpwelling

Abstract

fetched live from OpenAlex

Since the 1970s sea ice extent has decreased dramatically in the Northern Hemisphere and increased slightly in the Southern Hemisphere, a difference that is potentially explained by ozone depletion in the Southern Hemisphere stratosphere. In this study we consider the impact of stratospheric ozone depletion on Antarctic sea ice extent using a climate model forced with observed stratospheric ozone depletion from 1979 to 2005. Contrary to expectations, our model simulates a year‐round decrease in Antarctic sea ice due to stratospheric ozone depletion. The largest percentage sea ice decrease in our model occurs in the austral summer near the coast of Antarctica, due to a mechanism involving offshore Ekman sea ice transport. The largest absolute decrease is simulated in the austral winter away from the coast of Antarctica, in response to an ocean warming that is consistent with a poleward shift of the large‐scale pattern of sea surface temperature. Our model results strongly suggest that processes not linked to stratospheric ozone depletion must be invoked to explain the observed increase in Antarctic sea ice extent.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.024
GPT teacher head0.271
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

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

Citations154
Published2010
Admission routes1
Has abstractyes

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