Joint Modulation of Intraseasonal Rainfall in Tropical Australia by the Madden‐Julian Oscillation and El Niño‐Southern Oscillation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".