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Record W2083458282 · doi:10.1175/2007jas2355.1

The Effect of Dynamics on Mixed-Phase Clouds: Theoretical Considerations

2008· article· en· W2083458282 on OpenAlexaff
Alexei Korolev, Paul R. Field

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsMechanicsLiquid water contentNon-equilibrium thermodynamicsOscillation (cell signaling)Cloud physicsTurbulenceSaturation (graph theory)Mixed phaseEnvironmental scienceCloud computingMeteorologyIce cloudPhase (matter)PhysicsAtmospheric sciencesGeologyThermodynamicsMathematicsChemistryComputer science

Abstract

fetched live from OpenAlex

Abstract A theoretical framework has been developed describing nonequilibrium formation and maintenance of mixed-phase clouds. The necessary and sufficient conditions required to activate liquid water within a preexisting ice cloud, and thus convert it to mixed phase, are considered for three scenarios: (i) uniform ascent, (ii) harmonic vertical oscillations, and (iii) turbulent fluctuations. The general conditions are the following:First necessary condition: The vertical velocity of an ice cloud parcel must exceed a threshold velocity to activate liquid water.Second necessary condition: The activation of liquid water within an ice cloud parcel, below water saturation, requires a vertical ascent above some threshold altitude to bring the vapor pressure of the parcel to water saturation. Only when the first and second conditions are true do these conditions become sufficient for the activation of liquid water in ice clouds. These required conditions for the generation of mixed-phase cloud are supported by parcel modeling results and analogous conditions for a harmonic oscillation concerning the amplitude and tangential velocity of the parcel motion are proposed. The authors do not assume steady-state conditions, but demonstrate that nonequilibrium evolution of cloud parcels can lead to long-term steady existence of mixed-phase cloud.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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 designTheoretical or conceptual
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

Citations141
Published2008
Admission routes1
Has abstractyes

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