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Record W2561023687 · doi:10.1002/2016gl072347

A model intercomparison of the tropical precipitation response to a CO<sub>2</sub> doubling in aquaplanet simulations

2016· article· en· W2561023687 on OpenAlexafffund
Jeongbin Seo, Sarah M. Kang, Timothy M. Merlis

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Science ICT and Future PlanningNational Research Foundation of Korea
KeywordsIntertropical Convergence ZoneEquatorHadley cellClimatologyAtmospheric sciencesEnvironmental sciencePrecipitationWalker circulationConvergence zoneEnergeticsLatitudeClimate modelTropical waveConvectionSea surface temperatureClimate changeGeologyPhysicsGeneral Circulation ModelMeteorologyTropical cycloneOceanographyThermodynamics

Abstract

fetched live from OpenAlex

Abstract In the present‐day climate, the mean Intertropical Convergence Zone (ITCZ) is north of the equator. We investigate changes in the ITCZ latitude under global warming, using multiple atmospheric models coupled to an aquaplanet slab ocean. The reference climate, with a warmer north from prescribed ocean heating, is perturbed by doubling CO2. Most models exhibit a northward ITCZ shift, but the shift cannot be accounted for by the response of energy flux equator where the atmospheric energy transport (FA) vanishes. The energetics of the simulated circulation shifts are subtle: changes in the efficiency with which the Hadley circulation transports energy, the total gross moist stability (Δm), dominate over mass flux changes in determining δFA. Even when δFA ≈ 0, the ITCZ can shift significantly due to changes in Δm, which have often been neglected previously. The dependence of ITCZ responses on δΔm calls for improved understanding of the physics determining the tropical Δm.

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 score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.066
GPT teacher head0.342
Teacher spread0.275 · 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

Citations25
Published2016
Admission routes2
Has abstractyes

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