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Record W2163674098 · doi:10.1002/hyp.1227

Boundary‐layer integration approach to advection of sensible heat to a patchy snow cover

2002· article· en· W2163674098 on OpenAlexafffundabout
R. J. Granger, John W. Pomeroy, J. Parviainen

Bibliographic record

VenueHydrological Processes · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of CanadaLuonnontieteiden ja Tekniikan Tutkimuksen ToimikuntaNatural Environment Research CouncilCanadian Foundation for Climate and Atmospheric Sciences
KeywordsSnowAdvectionFetchBoundary layerEnvironmental scienceParametric statisticsBoundary (topology)MeteorologyGeologyAtmospheric sciencesMechanicsGeomorphologyMathematicsGeographyPhysics

Abstract

fetched live from OpenAlex

Abstract In the calculation of the melting of a patchy snow cover, the energy advected from the adjacent bare soil to the snow surface is an important consideration. The quantity or rate of energy advected depends on the fetches and sizes of snow and bare ground patches. Any successful method to estimate advection will necessarily require the incorporation of relationships describing the same. Complex boundary‐layer methods require detailed spatial knowledge of the patch sizes, wind direction and fetch distances, and are computationally intensive. A physically based approach that can be spatially applied using distributions of snow patch geometry is required. This paper presents a new approach, in which boundary‐layer integration is used to provide a means of calculating the amount of energy removed by the snow patch surface as warmer air moves over it. The method is reduced to a simple parametric form, and the relationships describing the coefficients required for its application are developed. The applicability of this new approach is discussed in light of the fractal nature of snow patches, the relationship between the individual patch length and area, and the distribution of patch sizes as they develop and disappear on the landscape. Copyright © 2002 Crown in the right of Canada. Published by John Wiley & Sons Ltd.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.229
Teacher spread0.180 · 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.

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

Citations45
Published2002
Admission routes3
Has abstractyes

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