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Record W4407385500 · doi:10.1080/07055900.2025.2459084

Evolution and Effects of Typhoon Rumbia (2018) after Recurvature and their Links to Northeast China Cold Vortex Anomaly

2024· article· en· W4407385500 on OpenAlexvenueno aff
Hejing Wang, Lina Zheng, Wenjing Jiang

Bibliographic record

VenueATMOSPHERE-OCEAN · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsnot available
FundersNatural Science Foundation of Shandong Province
KeywordsTyphoonChinaVortexAnomaly (physics)GeologyClimatologyGeographyMeteorologyPhysicsCondensed matter physics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.191
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueATMOSPHERE-OCEANSame topicTropical and Extratropical Cyclones ResearchFrench-language works237,207