Evolution and Effects of Typhoon Rumbia (2018) after Recurvature and their Links to Northeast China Cold Vortex Anomaly
Bibliographic record
Abstract
Typhoon Rumbia (2018) made landfall in Shanghai, China, immediately weakened and turned northward. According to the evolution of the middle tropospheric atmospheric circulation, Rumbia interacted with a cold vortex anomaly (CVA) split out of the Northeast China Cold Vortex (NCCV) before embedding in NCCV. It was found that Rumbia showed two enhancements at 500 hPa after recurvature. The first enhancement was related to the establishment and strengthening of upper-level jet stream, while the second was linked to the cold advection enhancement during the embedding period. When Rumbia approached the NCCV, it transferred energy to the CVA, aiding its development. Meanwhile, CVA continuously delivered cold advection to Rumbia, promoting the extratropical transformation of Rumbia. Furthermore, Rumbia brought severe precipitation after extratropical transformation, including direct precipitation and remote precipitation. The results indicated that severe direct precipitation was associated with the upper-level divergence zone. In contrast, heavy remote precipitation was attributed to the enhanced upward movement in the middle troposphere caused by the embedding process. This process was primarily convective precipitation, although it occurred under insufficient water vapour conditions.
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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) | 0.001 | 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".