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Record W1829353783 · doi:10.1002/grl.50500

Attribution of observed sea level pressure trends to greenhouse gas, aerosol, and ozone changes

2013· article· en· W1829353783 on OpenAlex
Nathan P. Gillett, John C. Fyfe, D. E. Parker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeophysical Research Letters · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
FundersBritish Antarctic SurveyClimate Program OfficeBiological and Environmental ResearchDepartment for Environment, Food and Rural Affairs, UK GovernmentOffice of ScienceNational Oceanic and Atmospheric AdministrationMet OfficeU.S. Department of Energy
KeywordsGreenhouse gasAerosolEnvironmental scienceOzoneAtmospheric sciencesClimatologyLatitudeClimate changeAtmospheric circulationGeneral Circulation ModelMeteorologyOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract Human influence on atmospheric sea level pressure (SLP) has previously been detected globally, but the contributions of greenhouse gas, aerosol, and ozone changes to the observed trends have not been separately identified. We use simulations from eight climate models to show that greenhouse gas, aerosol, and ozone changes each drive distinct seasonal and geographical patterns of trends, which are separately detectable in observed seasonal SLP trends over the 1951–2011 period. This detection is driven by significant low‐latitude SLP responses to greenhouse gas, aerosol, and ozone changes, as well as the more frequently‐studied high latitude responses. These results aid in understanding past atmospheric circulation changes, and have potential to improve projections of future circulation changes.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.995

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.124
GPT teacher head0.312
Teacher spread0.187 · 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