Impact of different types of La Niña development on the precipitation in the Maritime Continent
Bibliographic record
Abstract
In this study, the impacts of different types of La Niña development on the precipitation in the Maritime Continent are examined via observational and modelling analyses. The development processes of La Niña events primarily manifest in two types. One is El-To-La, originating from the transition of El Niño in the preceding winter, and the other is Non-El-To-La, evolving from a non-El Niño state in the previous winter. During La Niña developing summer, both types show a similar intensity of negative sea surface temperature (SST) anomalies over the central and eastern tropical Pacific (CETP), and the Maritime Continent (MC) exhibits positive precipitation anomalies. However, a notable difference occurs in the spatial pattern of MC precipitation response between these two types.For the El-To-La type, the local SST anomalies are positive in the entire MC region, which sets up a strong SST gradient between the warm MC and the cold CETP. The anomalous zonal Walker circulation associated with the zonal SST gradient causes uniform ascending anomalies over the MC region, promoting widespread positive precipitation. The local uniform warm SST anomalies contribute to positive specific humidity, further enhancing the precipitation anomaly. Therefore, positive precipitation anomalies span the entire MC region for the El-To-La type. Contrastingly, for the Non-El-To-La type, SST anomalies are only positive in the far eastern MC and negative in the western MC. Despite the establishment of large-scale Walker circulation between the MC and the CETP, the ascending branch of Walker circulation is positioned more to the east, resulting in increased precipitation over the eastern MC region. The local cold SST anomalies over the western MC hinder the moisture supply and are not favourable for precipitation enhancement. Therefore, the positive precipitation anomalies are only confined to the southeastern MC region for the Non-El-To-La type.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".