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Record W2154183189 · doi:10.1175/jas-d-14-0013.1

Zonally Symmetric Adjustment in the Presence of Artificial Relaxation

2014· article· en· W2154183189 on OpenAlexfundno aff
Peter B. Hitchcock, Peter Haynes

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDiabaticStratosphereTroposphereBoundary layerAdiabatic processAtmospheric sciencesZonal and meridionalRelaxation (psychology)ClimatologyMechanicsEnvironmental sciencePhysicsGeologyMeteorologyThermodynamics

Abstract

fetched live from OpenAlex

Abstract Numerical experiments, presented in a companion paper, have been performed in which the zonal-mean state of the stratosphere in a comprehensive, stratosphere-resolving, general circulation model is strongly relaxed (or “nudged”) toward the evolution of a reference sudden warming event in order to investigate its influence on the freely evolving troposphere below. Similar approaches have been used in a number of other studies. This raises the question of whether such an artificial relaxation induces the adiabatic and diabatic adjustments expected below the region of nudging, even in the absence of the stratospheric wave driving responsible for the reference event. Motivated by this question, the zonally symmetric quasigeostrophic diabatic response to zonal forces (representing wave driving) in a system nudged to a time-dependent reference state is studied. In the presence of wave driving in the nudging region that differs from the reference state, the meridional mass circulation of the reference state is reproduced only in the region below the nudging up to a correction that is inversely proportional to the strength of the nudging. The anomalous circulation is confined because of an effective boundary condition at the interface of the nudging layer. The nudging also produces an artificial “sponge-layer feedback” immediately below the region of the nudging in response to differences in the tropospheric wave driving. The strength of this artificial feedback is closely related to the strength of the effective boundary condition; however, the time scale required for the sponge-layer feedback to be established is typically much longer than that required for the confinement.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.276
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.232
Teacher spread0.215 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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