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Record W2108119518 · doi:10.1002/2014gl060313

Momentum balance of katabatic flow on steep slopes covered with short vegetation

2014· article· en· W2108119518 on OpenAlexaff
Holly J. Oldroyd, Gabriel G. Katul, Eric R. Pardyjak, M. B. Parlange

Bibliographic record

VenueGeophysical Research Letters · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsKatabatic windAtmospheric sciencesWind speedTerrainTurbulenceGeologyVegetation (pathology)Momentum (technical analysis)Environmental scienceJet (fluid)Flow (mathematics)Pressure gradientMeteorologyMechanicsPhysicsGeography

Abstract

fetched live from OpenAlex

Abstract Katabatic flows over alpine mountainous terrain differ from their forested or bare slope counterparts due to the presence of well‐ventilated, short vegetation. The impact of a grass canopy and larger‐scale pressure perturbations on the one‐dimensional mean momentum balance is explored via theory and field measurements. The model presented here reproduces the measured velocity jet shape and turbulent flux gradients. These two features imply that even when Monin‐Obuhkov similarity theory breaks down, its use for a stability adjusted mixing length remains effective to first order. Results reveal that outer layer pressure effects can be significant under low‐speed wind conditions at the top of the thin katabatic layer when larger variations in the wind direction are observed. An analytical expression to estimate the jet height, which can be utilized in large‐scale weather prediction models, shows the importance of including canopy effects for the thin katabatic flow region above the vegetation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.246
Teacher spread0.233 · 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 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

Citations34
Published2014
Admission routes1
Has abstractyes

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