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Record W2154033751 · doi:10.3189/172756405781813375

Solar forcing of the polar atmosphere

2005· article· en· W2154033751 on OpenAlexaboutno aff
Paul A. Mayewski, Kirk A. Maasch, Shichang Kang, E. A. Meyerson, Sharon B. Sneed, S. Kaspari, Daniel A. Dixon, E. C. Osterberg, Vin Morgan, T. D. van Ommen, Mark A. J. Curran

Bibliographic record

VenueAnnals of Glaciology · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersAustralian GovernmentNational Science Foundation
KeywordsPolar vortexClimatologyIce coreForcing (mathematics)GeologyNorthern HemisphereSolar variationAtmospheric circulationAtmospheric sciencesRadiative forcingProxy (statistics)PolarCryosphereSouthern HemisphereAtmosphere (unit)Environmental scienceClimate changeSea iceOceanographyGeographyStratosphereMeteorology

Abstract

fetched live from OpenAlex

Abstract We present highly resolved, annually dated, calibrated proxies for atmospheric circulation from several Antarctic ice cores (ITASE (International Trans-Antarctic Scientific Expedition), Siple Dome, Law Dome) that reveal decadal-scale associations with a South Pole ice-core 10 Be proxy for solar variability over the last 600 years and annual-scale associations with solar variability since AD 1720. We show that increased (decreased) solar irradiance is associated with increased (decreased) zonal wind strength near the edge of the Antarctic polar vortex. The association is particularly strong in the Indian and Pacific Oceans and as such may contribute to understanding climate forcing that controls drought in Australia and other Southern Hemisphere climate events. We also include evidence suggestive of solar forcing of atmospheric circulation near the edge of the Arctic polar vortex based on ice-core records from Mount Logan, Yukon Territory, Canada, and both central and south Greenland as enticement for future investigations. Our identification of solar forcing of the polar atmosphere and its impact on lower latitudes offers a mechanism for better understanding modern climate variability and potentially the initiation of abrupt climate-change events that operate on decadal and faster scales.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.287
Teacher spread0.245 · 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.

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

Citations43
Published2005
Admission routes1
Has abstractyes

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