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Record W2026694017 · doi:10.1175/jas-d-14-0325.1

Thermally Forced Convection over a Mountainous Tropical Island

2015· article· en· W2026694017 on OpenAlexaff
Chun‐Chih Wang, Daniel J. Kirshbaum

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsMcGill University
Fundersnot available
KeywordsConvectionAtmospheric sciencesInflowClimatologyPrecipitationDiurnal cycleGeologyMass fluxForcing (mathematics)Environmental scienceFree convective layerRadiative coolingRidgeOrographyMeteorologyMechanicsPhysics

Abstract

fetched live from OpenAlex

Abstract Observations from the Dominica Experiment (DOMEX) and cloud-resolving numerical simulations are used to study a thermally forced convection event over the Caribbean island of Dominica on 18 April 2011. A clear diurnal cycle of island thermal forcing and cumulus convection was observed, with cumuli initiating over the southwestern flank of the ridge and deepening as they drifted eastward. Apart from errors in cloud fraction and (notably) precipitation, the simulations verified well against the observations, provided horizontal grid spacings of 500 m or less were used. The simulated flows developed an island-scale solenoidal circulation with an organized and intense updraft over the ridge that focused convective initiation. Sensitivity tests investigated the impacts of topographic forcing, subcloud winds, and cloud–radiative feedbacks on the island-scale horizontal inflow and cloud vertical mass flux. These experiments confirmed that thermal forcing drove the island convection and that the inflow and cloud mass flux were maximized under weak ambient cross-island winds. The simulations also indicated that cloud shading and precipitation each reduced the island inflow by ~20% while cloud latent heat release enhanced it by ~20%. However, precipitation caused a much smaller reduction in cloud mass flux (10%) than did cloud shading (50%) owing to effective secondary convective initiation by subcloud cold pools. Thermodynamic heat-engine theory provided accurate predictions of the simulated solenoidal updraft magnitudes in selected cases. It also provided a simple explanation for the weakening of the simulated thermal circulation in the presence of island orography: a shallower mixed layer reduced the efficiency of the thermal circulation.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.025
GPT teacher head0.253
Teacher spread0.229 · 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

Citations34
Published2015
Admission routes1
Has abstractyes

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