MétaCan
Menu
Back to cohort
Record W2898112020 · doi:10.3390/atmos9110416

Statistics on Nonmigrating Diurnal Tides Generated by Tide-Planetary Wave Interaction and Their Relationship to Sudden Stratospheric Warming

2018· article· en· W2898112020 on OpenAlexaboutno aff
Xiaojuan Niu, Jian Du, Xuwen Zhu

Bibliographic record

VenueAtmosphere · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsStratosphereMesopauseSudden stratospheric warmingAtmospheric sciencesPolar vortexEnvironmental scienceClimatologyWavenumberAtmosphere (unit)GeologyMeteorologyMesospherePhysics

Abstract

fetched live from OpenAlex

The nonmigrating diurnal tide, DW2, is known to have a source from the stationary planetary wave with wavenumber 1 (SPW1) and the migrating diurnal tide (DW1) interaction. Recent research has shown that DW2 time evolution in the equatorial mesopause tracks very well with SPW1 in the polar stratosphere for the winter of 2009–2010, which contains a sudden stratospheric warming (SSW) vortex split event. This paper extends previous research and investigates the relationship between these two waves for 31 winters from 1979 to 2010 with the extended Canadian Middle Atmosphere Model (eCMAM) through correlation and composite analysis. Significant correlations are present between the two waves in 20 out of 31 winters (65%). We separate the 31 winters into four categories: SSW-displacement, SSW-split, minor-SSW, and no-SSW. Our results show that there is no significant difference among the four categories in terms of correlations between the two waves. Although SPW1 is usually stronger during a SSW-D winter, this does not warrant a stronger interaction with DW2.

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 score0.295
Threshold uncertainty score0.998

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.230
Teacher spread0.210 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAtmosphereSame topicAtmospheric Ozone and ClimateFrench-language works237,207