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Range–Height Scans of Lidar Depolarization for Characterizing Properties and Phase of Clouds and Precipitation

2001· article· en· W2180100829 on OpenAlexaff
Luc Bissonnette, G. Roy, Frédéric Fabry

Bibliographic record

VenueJournal of Atmospheric and Oceanic Technology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsMcGill University
Fundersnot available
KeywordsLidarPrecipitationBackscatter (email)Elevation (ballistics)SnowScatteringDepolarizationPhase (matter)RangingOpticsMaterials scienceRemote sensingRange (aeronautics)Environmental scienceGeologyPhysicsMeteorologyGeodesy

Abstract

fetched live from OpenAlex

Backscatter and depolarization lidar measurements from clouds and precipitation are reported as functions of the elevation angle of the pointing lidar direction. The data were recorded by scanning the lidar beam (Nd:YAG) at a constant angular speed of ∼3.5° s−1 while operating at a repetition rate of 10 Hz. The scan results highlight known depolarization phenomena in clouds and precipitation, and contribute additional and often essential information for the unambiguous characterization of their liquid, solid, or mixed phase. Moreover, in rain and snow, there is an evident and at times spectacular dependence on the elevation angle. That dependence is very sensitive to crystal type and orientation, or raindrop shape. For the rain case, there is a definite need for calculations of the scattering phase matrix elements for slightly deformed and oscillating spheres because of the real potential for retrieving information on raindrop eccentricity from lidar depolarization scans.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

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 head0.013
GPT teacher head0.228
Teacher spread0.216 · 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

Citations31
Published2001
Admission routes1
Has abstractyes

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