A Complete Three‐Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme
Bibliographic record
Abstract
Abstract A new, complete three‐moment bulk microphysics approach is proposed that includes the effects of all relevant microphysical processes on the evolution of ice particle size distribution (PSD) width. This extends the three‐moment approach that was originally implemented in the Predicted Particle Properties (P3) scheme that assumed sedimentation and advection dominate and neglected the effects of most microphysical processes on PSD width. The new approach (FULL) is tested in idealized one‐dimensional kinematic updraft and three‐dimensional supercell simulations and compared to results using the original approach (ORIG). Although tendencies of the gamma PSD width parameter ( μ ) from several microphysical processes using FULL are large in magnitude relative to the sedimentation and advection tendencies, they have only minor impacts on the overall spatiotemporal patterns of μ ; PSDs are narrower using FULL in regions with relatively narrow PSDs using ORIG and slightly wider in regions with relatively wide PSDs. The processes driving these impacts using FULL are ice‐rain collection near convective cores and sublimation in the far forward flank, both leading to PSD narrowing, and broadening from aggregation in the near forward flank. A general theoretical expression is derived to explain whether a process broadens or narrows PSDs based in part on the ice particle mass‐size relationship. However, the effects on bulk cloud and precipitation properties are limited, with only a 7%–8% decrease in mean surface precipitation using FULL compared to ORIG. Although overall impacts are modest in the tests conducted, the full approach improves physical realism with a negligible increase in computational cost.
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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".