Snowmelt Evolution Mapping Using an Energy Balance Approach over an Alpine Terrain
Bibliographic record
Abstract
A computer model simulating snowmelt evolution and the spatial snowmelt pattern using an energy balance approach over an alpine terrain was developed. With a digital elevation model (DEM), surface characteristics information and meteorological data as input, all radiation balance components, turbulent fluxes, precipitation, and finally snowmelt were modeled on a daily basis. Special emphasis was given to snow redistribution. The model was applied to an area of 35 km2 in the Schilthorn Massif (Bernese Oberland, Switzerland) for 1996–97. The model calculations are compared with a snowmelt evolution map, which was produced by combining seven scenes of aerial photographs taken in the Bernese Alps during the melting season 1997 (March–September). Both the temporal comparison of the snowmelt evolution and the spatial comparison of simulated and observed snowmelt patterns show a good accordance: at any of the compared dates, spatial coincidence is equal to or better than 78%. It can therefore be concluded that the model supplies a quite realistic reproduction of the energy exchange processes taking place at the ground snow-cover/atmosphere interface during winter and spring.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".