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Record W2100427243 · doi:10.1175/jas-3361.1

Zonal Asymmetries, Teleconnections, and Annular Patterns in a GCM

2005· article· en· W2100427243 on OpenAlexaff
Benjamin A. Cash, Paul J. Kushner, Geoffrey K. Vallis

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAsymmetryEmpirical orthogonal functionsTeleconnectionClimatologyEddyGeologyAmplitudePhysicsAtmospheric sciencesMechanicsEl Niño Southern OscillationTurbulence

Abstract

fetched live from OpenAlex

Abstract The influence of zonally asymmetric boundary conditions on the leading modes of variability in a suite of atmospheric general circulation models is investigated. The set of experiments consists of nine model configurations, with varying degrees and types of zonal asymmetry in their boundary conditions. The structure of the leading EOF varies with the zonal asymmetry of the base state for each model configuration. In particular, a close relationship is found between the structure of the EOF and the model storm tracks. An approximately linear relationship is found to hold between the magnitude of the zonal asymmetry of the leading EOF and of the storm tracks in the models. It is shown that this linear relationship extends to the observations. One-point correlation maps centered on the regions where the EOFs reach their maximum amplitude show similar structures for all configurations. These structures consist of a north–south dipole, resembling the observed structure of the North Atlantic Oscillation (NAO). They are significantly more zonally localized than the leading EOF, but do resemble one-point correlation maps and sector EOFs calculated for a simulation with zonally symmetric boundary conditions. Thus, the leading EOF for each simulation appears to represent the longitudinal distribution of zonally localized NAO-like patterns. This longitudinal distribution appears to be tied to the distribution of high-frequency eddies, as represented by the storm tracks. A detailed momentum budget for each case confirms that high-frequency eddies play a crucial role in producing the NAO-like patterns. Other dynamical processes also play an important role, but vary with the details of the simulation.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

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

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 head0.229
Teacher spread0.218 · 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.

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

Citations32
Published2005
Admission routes1
Has abstractyes

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