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Record W1990528643 · doi:10.1175/jas-d-11-0152.1

Multiscale Waves in an MJO Background and Convective Momentum Transport Feedback

2011· article· en· W1990528643 on OpenAlexafffund
Boualem Khouider, Ying Han, Andrew J. Majda, Samuel N. Stechmann

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Victoria
FundersOffice of Naval ResearchCanadian Foundation for Climate and Atmospheric SciencesDivision of Mathematical SciencesUniversity of Wisconsin-MadisonNational Science Foundation
KeywordsMadden–Julian oscillationKelvin waveSquall lineEquatorial wavesConvectionGeologyMesoscale meteorologyWind shearMesocycloneGeophysicsAtmospheric sciencesClimatologyPhysicsMeteorologyWind speedGeodesy

Abstract

fetched live from OpenAlex

Abstract The authors use linear analysis for a simple model to study the evolution of convectively coupled waves (CCWs) in a background shear and background moisture mimicking the observed structure of the Madden–Julian oscillation (MJO). This is motivated by the observation, in an idealized setting, of intraseasonal two-way interactions between CCWs and a background wind. It is found here that profiles with a bottom-heavy moisture content are more favorable to the development of mesoscale/squall line–like waves whereas synoptic-scale CCWs are typically more sensitive to the shear strength. The MJO envelope is thus divided into three regions, in terms of the types of CCWs that are favored: an onset region in front that is favorable to Kelvin waves, a mature or active region in the middle in which squall lines are prominent, and the stratiform and decay phase region in the back that is favorable to westward inertia–gravity (WIG) waves. A plausible convective momentum transport (CMT) feedback is then provided according to the results of the idealized two-way interaction model. The active region, in particular, coincides with the westerly wind burst where both Kelvin waves and squall lines are believed to play a significant role in both the deceleration of low-/high-level easterly/westerly winds and the acceleration of low-/high-level westerly/easterly winds. The WIG waves in the wake could be a precursor for a subsequent MJO event through the acceleration of low-/high-level easterly/westerly winds, which in turn favor Kelvin waves, and the cycle repeats. These results open interesting directions for future studies using observations and/or detailed numerical simulations using the full primitive equation.

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 score0.013
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.052
GPT teacher head0.261
Teacher spread0.209 · 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

Citations46
Published2011
Admission routes2
Has abstractyes

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