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Record W2105485029 · doi:10.1002/2014jd022950

Observations of the variability of shallow trade wind cumulus cloudiness and mass flux

2015· article· en· W2105485029 on OpenAlexafffund
Katia Lamer, Pavlos Kollias, Louise Nuijens

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsCloud baseCloud fractionOutflowEnvironmental scienceMass fluxCloud coverAtmospheric sciencesFlux (metallurgy)Cloud computingCloud heightCloud topLiquid water contentWind profilerMeteorologyClimatologyGeologyRadarPhysicsMaterials science

Abstract

fetched live from OpenAlex

Abstract Two years of ground‐based remote sensing observations are used to study the vertical structure of marine cumulus near the island of Barbados, including their cloud fraction and mass flux profile. Daily radar derived cloud fraction profiles peak at different height levels depending on the depth of the cumuli and thus the extent to which they precipitate. Nonprecipitating cumuli have a peak cloud fraction of about 5% near mean cloud base (700 m), whereas precipitating cumuli tend to have a peak of only 2% near cloud base. Nineteen percent of the precipitating cumuli are accompanied by large cloud fractions near the detrainment level of cumulus tops (~1700 m). Day‐to‐day variations in cloud fraction near cloud base are modest (~3%). Nonprecipitating cumuli have their largest reflectivities near cloud top and an ascending core surrounded by a subsiding shell. Precipitating cumuli with enhanced elevated cloudiness (stratiform outflow) are deeper and contain larger vertical gradients in reflectivity and Doppler velocity than precipitating cumuli without such outflow. Bulk (3 h) statistics reveal that nonprecipitating shallow cumuli are active and organized. They contain on average 79% in‐cloud updrafts with 86% of them being organized in large coherent structures contributing to a maximum updraft mass flux of 8–36 gm −2 s −1 just above cloud base. Alternatively, downdrafts contribute insignificantly to the mass flux and show little vertical and temporal variability (0–7 gm −2 s −1 ). Complementary Raman lidar information suggests that updraft mass flux profile slope is inversely related to environmental relative humidity.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.063
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.310
Teacher spread0.249 · 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

Citations78
Published2015
Admission routes2
Has abstractyes

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