Modeling of the Melting Layer. Part III: The Density Effect
Bibliographic record
Abstract
Abstract A model of the melting snow and its radar reflectivity is presented here. The main addition to previous description of the melting layer is the explicit introduction of snow density as a variable. The model is validated with radar observations. Differences in brightband intensity for comparable precipitation rates are related here to the coexistence of supercooled cloud water (SCW) with snow above the melting level leading to riming and change in snow density. Cases where riming was suspected were selected according to the characteristics of the vertical profile of reflectivity flux above the melting layer and vertical Doppler velocities faster than expected from low-density snow. For stratiform precipitation with a melting layer, high snow-to-rain velocity ratio indicates high-density snow and consequently a small peak-to-rain reflectivity difference is expected. This relationship was computed from the model and confirmed with vertically pointing radar observations. In spite of the complexity of the physical processes present in the melting layer the model appears to capture the essential elements.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".