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Record W2915789632 · doi:10.1038/s41598-019-40034-6

On the emerging relationship between the stratospheric Quasi-Biennial oscillation and the Madden-Julian oscillation

2019· article· en· W2915789632 on OpenAlexafffund
Phil Klotzbach, S. Abhik, Harry H. Hendon, Michael M. Bell, Chris Lucas, Andrew G. Marshall, Eric C. J. Oliver

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsDalhousie University
FundersOffice of Naval ResearchU.S. Department of DefenseDepartment of Agriculture and Water Resources, Australian GovernmentAustralian GovernmentG. Unger Vetlesen FoundationNatural Sciences and Engineering Research Council of Canada
KeywordsOscillation (cell signaling)Madden–Julian oscillationQuasi-biennial oscillationClimatologyEnvironmental scienceMeteorologyAtmospheric sciencesGeographyBiologyGeologyStratosphere

Abstract

fetched live from OpenAlex

A strong relationship between the quasi-biennial oscillation (QBO) of equatorial stratospheric winds and the amplitude of the Madden-Julian oscillation (MJO) during the boreal winter has recently been uncovered using observational data from the mid-1970s to the present. When the QBO is in its easterly phase in the lower stratosphere, it favors stronger MJO activity during boreal winter, while the MJO tends to be weaker during the westerly phase of the QBO. Here we show using reconstructed indices of the MJO and QBO back to 1905 that the relationship between enhanced boreal winter MJO activity and the easterly phase of the QBO has only emerged since the early 1980s. The emergence of this relationship coincides with the recent cooling trend in the equatorial lower stratosphere and the warming trend in the equatorial upper troposphere, which appears to have sensitized MJO convective activity to QBO-induced changes in static stability near the tropopause. Climate change is thus suggested to have played a role in promoting coupling between the MJO and the QBO.

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)0.007
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 score0.269
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.023
GPT teacher head0.243
Teacher spread0.219 · 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

Citations69
Published2019
Admission routes2
Has abstractyes

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