Revisiting bulk heat transfer on Peyto Glacier, Alberta, Canada, in light of the OG parameterization
Bibliographic record
Abstract
Abstract A scheme for katabatic turbulent heat transfer proposed by Oerlemans and Grisogono (2002), here referred to as the OG parameterization, is compared with bulk heat-transfer estimates on Peyto Glacier, Alberta, Canada. Automatic weather stations (AWSs) provide off-glacier data to drive the parameterization and glacier data for bulk estimates. Micrometeorological datasets are used to assess two schemes that employ the Monin-Obukhov stability parameter, z/L , to modify logarithmic, or neutral, bulk heat-transfer equations to allow for stability. Both schemes fail at >1 m above the surface, where the AWS sensors are located, unless a modified approach is used in which the stability correction is constant for z/ L ≥1/3. Then the bulk sensible-heat-flux density falls to ≈0.93 of its neutral estimate at all measurement levels, thus providing a basis for comparison with the parameterization. The results of the comparison are very good, indicating that a one-to-one relationship between bulk and parameterized values can be achieved by optimizing the fit with a background exchange coefficient and, because there is only one off-glacier AWS, using a sinusoidal function to model the diurnal variation of the potential temperature lapse rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".