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Record W4286111132 · doi:10.1175/jcli-d-21-0945.1

Future Changes of East Asian Extratropical Cyclones in the CMIP5 Models

2022· article· en· W4286111132 on OpenAlexafffund
Jaeyoung Hwang, Seok‐Woo Son, John R. Gyakum

Bibliographic record

VenueJournal of Climate · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExtratropical cycloneClimatologyEast AsiaEnvironmental scienceCyclogenesisClimate modelCyclone (programming language)GeologyClimate changeGeographyChinaOceanography

Abstract

fetched live from OpenAlex

Abstract Future changes of extratropical cyclones (ETCs) over East Asia are investigated using the models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). To quantify ETC frequency, intensity, and genesis changes in a warming climate, the objective tracking algorithm is applied to nine CMIP5 models. These models provide 6-hourly wind data with no missing values in the high-terrain regions. The historical simulations reasonably well capture the spatial distribution of ETC properties, except for nonnegligible biases in and downstream of the high-terrain regions. Such biases are particularly pronounced in the models with a coarse spatial resolution and smooth topography, which weaken lee cyclogenesis. The best five models, which show better performance for historical simulations than other models, are used to evaluate the possible changes of East Asian ETCs under the RCP8.5 scenario. These models project a reduced cyclogenesis on the leeward side of the Tibetan Plateau, and over the East China Sea and western North Pacific in the late twenty-first century, resulting in a reduced ETC frequency from the east coast of China to the western North Pacific. The ETC intensity also shows a hint of weakening over the North Pacific. These ETC property changes are largely consistent with an enhanced static stability and a reduced vertical wind shear in a warming climate. This result indicates that the local baroclinicity, instead of increased moisture content, may play a critical role in determining the future changes of East Asian ETCs.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.246
Teacher spread0.224 · 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 designSimulation or modeling
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

Citations5
Published2022
Admission routes2
Has abstractyes

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