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Record W4402087609 · doi:10.1029/2024gl110069

Synergistic Forcing of the Troposphere and Stratosphere on Explosively Developing Cyclones Over the North Pacific During Cold Season

2024· article· en· W4402087609 on OpenAlexfundno aff
Shengyi Qian, Haibo Hu, Kevin I. Hodges, Xiu‐Qun Yang, Tangxuan Song

Bibliographic record

VenueGeophysical Research Letters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNatural Environment Research CouncilQueen's UniversityChina Meteorological AdministrationNational Natural Science Foundation of ChinaSight Research UKGovernment of Jiangsu ProvinceUniversity of BernMassachusetts Institute of Technology
KeywordsStratosphereTroposphereClimatologyForcing (mathematics)Environmental scienceAtmospheric sciencesCyclone (programming language)MeteorologyGeologyGeography

Abstract

fetched live from OpenAlex

Abstract The mid‐latitude extreme weather disasters are often associated with explosively developing cyclones (ECs). Based on different vertical development characteristics, 4,608 ECs identified over the North Pacific in the cold season of 44 years of NCEP‐CFSR reanalyzes are divided into four types of upward development and four types of downward development categories. ECs with vertical upward (downward) development follow a northeastward (nearly eastward) path, mainly explosively developing over the Northwest Pacific (Asia continent and Pacific). Furthermore, utilizing the piecewise potential vorticity inversion method reveals the synergetic forcing of the turbulent heat transport and baroclinicity in the lower troposphere, the latent heat release in the middle levels, the upper‐level jet stream, and the downward intrusion of stratospheric potential vorticity on the ECs. Different configurations of these influences from the troposphere to the stratosphere result in the occurrences of eight types of ECs in the cold season over the North Pacific.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.274
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2024
Admission routes1
Has abstractyes

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