Modulation of wet‐season rainfall over Iran by the Madden–Julian Oscillation, Indian Ocean Dipole and El Niño–Southern Oscillation
Bibliographic record
Abstract
The intra‐seasonal variation of precipitation over Iran is examined in terms of the combined effects of the Madden–Julian Oscillation (MJO), Indian Ocean Dipole (IOD) and El Niño–Southern Oscillation (ENSO), using daily observations during the wet season (October–May) from 1961 to 2015. We have examined how the probability of daily rainfall above the upper tercile varies across MJO phases during positive and negative IOD and ENSO states. The results indicate that the response of Iran's wet‐season rainfall to the MJO is affected more by large‐scale atmospheric variations associated with the IOD than by ENSO. The negative (positive) IOD strengthens (suppresses) the MJO–rainfall relationship in the wet and dry MJO phases. The variation in the atmospheric variables (relative humidity and vertical velocity) indicates more (less) humidity and upwards (downwards) motion which increases (decreases) precipitation in wet (dry) MJO phases during the negative IOD. The rainfall relationship with the MJO during the negative IOD is statistically significant, while the relationship during the positive IOD is weak; and no significant relationship is found during either phase of ENSO.
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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 | 0.001 |
| 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".