MétaCan
Menu
Back to cohort
Record W1967184305 · doi:10.1175/mwr-d-14-00254.1

Cloud Trails Past the Lesser Antilles

2014· article· en· W1967184305 on OpenAlexaff
Daniel J. Kirshbaum, Jonathan G. Fairman

Bibliographic record

VenueMonthly Weather Review · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsMcGill University
FundersNatural Environment Research CouncilSight Research UK
KeywordsRadiosondeWakeGeologyCloud heightMeteorologyTerrainDiurnal cycleWind shearWind speedInversion (geology)Atmospheric sciencesClimatologyEnvironmental scienceCloud computingGeographyCloud coverOceanographyPhysicsSeismology

Abstract

fetched live from OpenAlex

Abstract Observations and cloud-resolving simulations of elongated cloud plumes (or “cloud trails”) past the Lesser Antilles islands in the Caribbean Sea are presented. Analysis of one year of visible satellite images reveals that each island forms cloud trails on 30%–40% of days, typically in the afternoon in response to diurnal island heating. On around 10% of days the cloud bands are very well organized, with lengths of and durations of min. Radiosonde analysis suggests that the well-organized events are favored by moderate-to-strong trade winds (6–10 m s−1) and stronger trade inversions. The simulated cloud trails, which are consistent with observations in their morphology and diurnal cycle, are organized by quasi-linear bands of thermally forced convergence within the heated island wake. They are sensitive to overland surface fluxes, inversion strength and height, terrain height, and trade-wind speed. While surface fluxes control the strength of the wake thermal circulations, the inversion controls precipitation and the disruption of cloud trails by subcloud cold pools. The impacts of terrain height and wind speed are multifaceted, including control over (i) the mechanical flow regime, (ii) the intensity of wake turbulence, (iii) the cloud-trail length, (iv) the wake thermal anomaly, and (v) elevated-heating effects (which strengthen the thermal convergence). Dimensional analysis is used to develop empirical scalings for the wake thermal circulation, which describe the suite of numerical sensitivity tests reasonably well.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations16
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueMonthly Weather ReviewSame topicAtmospheric aerosols and cloudsFrench-language works237,207