Meridional Propagation of the 30- to 60-day Variability of Precipitation in the East Asian Subtropical Summer Monsoon Region: Monitoring and Prediction
Bibliographic record
Abstract
The meridional propagation of the 30- to 60-day intraseasonal variability (ISV) of precipitation in the East Asian subtropical summer monsoon (EASSM) region and its monitoring and prediction are investigated in the current study. Based on a multivariate empirical orthogonal function (MV-EOF) analysis of precipitation and relative vorticity at 700 hPa in East Asia, a bivariate index referred to as the EASSM-ISV index is designed using the two leading MV-EOF modes, with the objective of real-time monitoring of the 30- to 60-day variability of precipitation in the EASSM region. It is found that this index, with its eight phases, can explain the meridional propagation of the 30- to 60-day ISV in precipitation and circulation in the EASSM region. Based on a singular value decomposition technique, a statistical forecast model is developed in which the EASSM-ISV indices from the preceding five pentads are used to predict the indices in five pentads in the future. Meanwhile, the indices are used to predict the meridional propagation of the 30- to 60-day precipitation anomaly in the EASSM region. This model thus provides a useful tool for intraseasonal prediction of precipitation during the rainy season in China.
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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 | 0.000 |
| 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) | 0.000 | 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".