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Record W2766056458 · doi:10.1002/2017gl075452

Joint Modulation of Intraseasonal Rainfall in Tropical Australia by the Madden‐Julian Oscillation and El Niño‐Southern Oscillation

2017· article· en· W2766056458 on OpenAlexaff
Roohi P. S. Ghelani, Eric C. J. Oliver, Neil J. Holbrook, Matthew C. Wheeler, Philip J. Klotzbach

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsDalhousie University
FundersMonash University
KeywordsMadden–Julian oscillationClimatologyEl Niño Southern OscillationPrecipitationWet seasonEnvironmental scienceDry seasonSouthern oscillationOscillation (cell signaling)Atmospheric sciencesGeographyGeologyConvectionMeteorology

Abstract

fetched live from OpenAlex

Abstract Rainfall in tropical Australia is a critical resource for the agricultural sector. However, its high variability implores improvements in our understanding of its variability. Australian tropical rainfall is influenced by both the Madden‐Julian Oscillation (MJO) on intraseasonal time scales and El Niño‐Southern Oscillation (ENSO) on interannual time scales. This study examines the joint relationship between the MJO, ENSO, and tropical Australian rainfall variability. We analyze daily precipitation data from stations across tropical Australia during the wet season (November to April). The wet season rainfall response to the MJO is found to be greater during El Niño than La Niña. We demonstrate that this relationship is not due to the statistical relationship between the MJO and ENSO indices but instead due to differences in how the MJO modulates the large‐scale circulation during El Niño versus during La Niña.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.069
GPT teacher head0.333
Teacher spread0.264 · 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 designSimulation or modeling
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
Published2017
Admission routes1
Has abstractyes

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