Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hyp.6123 Boundary-layer growth over snow and soil patches: field observations
Bibliographic record
Abstract
Much of the snowmelt season is characterized by a patchy surface; differential heating of the snow and snow-free surfaces results in a significant horizontal transport of energy that affects and contributes to the snowmelt. The calculation of the rate of energy advection requires some knowledge of the behaviour of the thermal boundary layer over the patches of snow and snow-free surfaces. We present the results from a series of field observations of the rate of growth of the thermal boundary layer over snow and snow-free patches. The results confirm that the boundary-layer growth can be described by a power function of the distance from the leading edge of the patch. For the case of the thermal boundary layer over a snow patch within a bare field, the boundary-layer growth is affected by the upwind surface roughness; the thermal boundary layer over a snow patch within a ‘rough ’ field grows much more quickly than that in a ‘smooth ’ field. Relationships are derived and presented for the parameterization of the boundary-layer growth as a function of distance and upwind surface roughness. Copyright 2006 Crown in the right of Canada. Published by John Wiley & Sons, Ltd. KEY WORDS boundary layer; advection; snowmelt; sensible heat; snow patches
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.742 | 0.703 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".