The Large‐Scale Circulation Patterns Responsible for Extreme Precipitation Over the North China Plain in Midsummer
Bibliographic record
Abstract
Abstract Extreme precipitation events over the North China Plain (NCP) in midsummer during 1979–2016 are classified into two types using objective cluster analysis: a northern pattern with heavy precipitation and a central–southern pattern with relatively moderate precipitation. The large‐scale circulation patterns responsible for the midsummer extreme precipitation are then determined. In the northern NCP type, extreme precipitation accompanies a zonal gradient between an anomalous low‐pressure system at high latitudes and the westward‐ and northward‐extended western North Pacific subtropical high (WNPSH). Anomalous southwesterlies flow is driven by a trough that extended from the high latitudes to the northern NCP, where it encounters southeasterly wind flow induced by an anomalously northward‐extended WNPSH and a southern low‐pressure anomaly at low latitudes. Anomalous amounts of moisture are mainly transported from the tropical western Pacific by southeasterlies. In the central–southern NCP type, remarkable anomalous low‐pressure systems control all of northern China with centers over the Sichuan Basin and northeast China. The westward‐extended WNPSH occupies further south than that of the northern NCP type. The southwesterly low‐level jet (LLJ) is more prevalent in the central–southern NCP type than in the northern NCP type. This southwesterly LLJ plays an important role in extreme precipitation over the central–southern NCP by transporting moisture primarily from the Bay of Bengal and the South China Sea and generating convergence. In addition, the upper‐level anomalous strong divergence that is anchored over the right entrance of the westerly jet makes a greater contribution to extreme precipitation in the northern type than in the central–southern type.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 teacher head, 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".