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Record W4255214081 · doi:10.1002/essoar.10503943.1

Quasi-10-day wave and semi-diurnal tide nonlinear interactions during the southern hemispheric SSW 2019 observed in the northern hemispheric mesosphere

2020· preprint· en· W4255214081 on OpenAlexaff
Maosheng He, Jorge L. Chau, J. M. Forbes, Denise Thorsen, Guozhu Li, Tarique Adnan Siddiqui, Yosuke Yamazaki, W. K. Hocking

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsWestern University
Fundersnot available
KeywordsMesosphereNorthern HemisphereAtmospheric sciencesPhysicsWavenumberGravity waveClimatologyGeologyStratosphereAstrophysicsOpticsGravitational wave

Abstract

fetched live from OpenAlex

Mesospheric winds from three longitudinal sectors at about 65$^\circ$N and 54$^\circ$N latitude are combined to diagnose the zonal wavenumbers ($m$) of high-frequency-resolved spectral wave signatures during the rare southern hemisphere sudden stratospheric warming (SSW) of 2019. Diagnosed are quasi-10- and 6-day planetary waves (Q10DW and Q6DW, $m$=1), solar semi-diurnal tides with $m$=1, 2, 3 (SW1, SW2, and SW3), lunar semi-diurnal tide, and the upper and lower sidebands (USB and LSB, $m$=1 and 3) of Q10DW-SW2 nonlinear interaction. We further present a 7-year composite analysis to distinguish SSW effects from climatological behaviors. Immediately before (after) the SSW onset, LSB (USB) enhances, accompanied by the enhancing (fading) Q10DW, and a weakening of climatological SW2 maximum. These behaviors are explained in terms of Manley-Rowe energy relation, i.e., the energy goes first from SW2 to Q10DW and LSB, and then from SW2 and Q10DW to USB.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2020
Admission routes1
Has abstractyes

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