Effects of the Representation of Rimed Ice in Bulk Microphysics Schemes on Polarimetric Signatures
Bibliographic record
Abstract
Abstract Many flavors of multicategory, multimoment bulk microphysics schemes (BMPs) have various treatments of rimed ice. In this study, we compare three two-moment schemes available in the WRF Model—Milbrandt–Yau (MY2), National Severe Storms Laboratory (NSSL), and the two-category configuration of the Predicted Particle Properties (P3) scheme—focusing on differences in rimed-ice representation and their impacts on surface rain and ice. Idealized supercell simulations are performed. A polarimetric radar data simulator is used to evaluate their ability to reproduce the Z DR arc and hail signature in the forward-flank downdraft, well-known supercell polarimetric signatures that are potentially sensitive to rimed-ice parameterization. Both the MY2 and NSSL schemes simulate enhanced surface Z DR bands, but neither scheme simulates a Z DR arc commonly identified in observation-based studies. Surface Z DR in the default P3 scheme is homogeneous in the supercell’s forward flank, and is due to the scheme’s restrictive minimum rain particle size distribution (PSD) slope bound preventing the presence of larger drops creating a Z DR arc. The NSSL scheme simulates the location of the hail signature in the forward-flank downdraft more consistent with observations than the other two schemes. Large hail in MY2 sediments well downstream of the updraft (atypically compared to observations) near the surface. The sedimentation of large ice in the default P3 scheme is limited by a restrictive maximum ice number-weighted mean diameter limit within the scheme, precluding the scheme’s ability to reduce Z DR (and ρ HV compared to the MY2 and NSSL schemes) near the surface.
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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 | 0.001 |
| 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".