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Record W2083242238 · doi:10.5194/angeo-19-933-2001

The structure of turbulence in the middle and lower atmosphere seen by and deduced from MF, HF and VHF radar, with special emphasis on small-scale features and anisotropy

2001· article· en· W2083242238 on OpenAlexaff
W. K. Hocking, J. Röttger

Bibliographic record

VenueAnnales Geophysicae · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsWestern University
Fundersnot available
KeywordsRadarTurbulenceStratosphereAnisotropyAtmospheric sciencesMeteorologyTroposphereGeophysicsMesosphereAtmosphere (unit)GeologyPhysicsComputational physicsEnvironmental scienceOpticsAerospace engineering

Abstract

fetched live from OpenAlex

Abstract. An overview of the turbulent structures seen by MF, HF and VHF radars in the troposphere, stratosphere and mesosphere is presented, drawing on evidence from previous radar measurements, in situ studies, laboratory observations, observations at frequencies other than those under focus, and modelling studies. We are particularly interested in structures at scales less than one radar pulse length, and smaller than the beam width, and especially the degree of anisotropy of turbulence at these scales. Previous radar observations are especially important in regard to the degree of anisotropy, and we highlight the role that these studies have had in furthering our understanding in this area. The contrasts and similarities between the models of anisotropic turbulence and specular reflection are considered. The need for more intense studies of anisotropy at MF, HF and VHF is especially highlighted, since this is an area in which these radars can make important contributions to the understanding of atmospheric turbulence.Key words. Meteorology and atmospheric dynamics (turbulence) – Atmospheric composition and structure (instruments and techniques) – History of geophysics (atmospheric sciences)

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.558

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 head0.005
GPT teacher head0.186
Teacher spread0.182 · 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

Citations22
Published2001
Admission routes1
Has abstractyes

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