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Record W2130575440 · doi:10.1175/jas3784.1

Relative Humidity in Liquid, Mixed-Phase, and Ice Clouds

2006· article· en· W2130575440 on OpenAlexfundno aff
Alexei Korolev, George A. Isaac

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
FundersGlenn Research CenterTransport CanadaLangley Research CenterNational Aeronautics and Space Administration
KeywordsRelative humidityIce cloudAtmospheric sciencesMesoscale meteorologyEnvironmental scienceSaturation (graph theory)HumidityIce nucleusLiquid water contentLiquid waterClimatologyMeteorologyGeologySatelliteGeographyThermodynamicsPhysicsCloud computing

Abstract

fetched live from OpenAlex

Abstract The results of in situ observations of the relative humidity in liquid, mixed, and ice clouds typically stratiform in nature and associated with mesoscale frontal systems at temperatures −45°C < Ta < −5°C are presented. The data were collected with the help of instrumentation deployed on the National Research Council (NRC) Convair-580. The length of sampled in-cloud space is approximately 23 × 103 km. The liquid sensor was calibrated in liquid clouds with the assumption that the air in liquid clouds is saturated with respect to water. It was found that the relative humidity in mixed-phase clouds is close to saturation over water in the temperature range from −5° to −35°C for an averaging scale of 100 m. In ice clouds the relative humidity over ice is not necessarily equal to 100%, and it may be either lower or higher than saturation over ice, but it is always lower than saturation over water. On average the relative humidity in ice clouds increases with a decrease of temperature. At −40°C the relative humidity over ice is midway between saturation over ice and liquid. A parameterization for the relative humidity in ice clouds is suggested. A large fraction of ice clouds was found to be undersaturated with respect to ice. The fraction of ice clouds undersaturated with respect to ice increases toward warmer temperatures.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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

Citations127
Published2006
Admission routes1
Has abstractyes

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