A Parameterization of the Microphysical Processes Forming Many Types of Winter Precipitation
Bibliographic record
Abstract
Abstract Several types of precipitation, such as freezing rain, ice pellets, and wet snow, are commonly observed during winter storms. The objective of this study is to better understand the formation of these winter precipitation types. To address this issue, detailed melting and refreezing of precipitation was added onto an existing bulk microphysics scheme. These modifications allow the formation of mixed-phase particles and these particles in turn lead to, or affect, the formation of many of the other types of precipitation. The precipitation type characteristics, such as the mass content, liquid fraction, and threshold diameters formed during a storm over St John’s, Newfoundland, Canada, are studied and compared with observations. Many of these features were reproduced by the model. Sensitivity experiments with the model were carried out to examine the dependence of precipitation characteristics in this event on thresholds of particle evolution in the new parameterization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".