Mixed‐phase clouds in a turbulent environment. Part 1: Large‐eddy simulation experiments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Mixed‐phase clouds are thermodynamically unstable, i.e. with no other forcing ice will grow at the expense of supercooled liquid water, eventually leading to complete glaciation of the cloud. In the presence of dynamic forcing, e.g. regular motions or turbulent fluctuations, liquid water can be generated in an ice cloud. Earlier theoretical considerations have identified two necessary conditions that had to be satisfied to produce liquid water in a pre‐existing ice cloud: (i) the vertical velocity of an ice cloud parcel must exceed a threshold velocity and (ii) the vertical displacement of an ice cloud parcel must be above a threshold altitude to achieve water saturation. This article uses a large‐eddy simulation (LES) model to investigate whether satisfying these conditions alone can be used as a predictive tool for the occurrence of mixed‐phase clouds in a turbulent environment. It is shown that, in general for a range of microphysical assumptions, ice concentrations and thermodynamic conditions, identifying points that satisfy these two dynamic conditions results in a good estimate of the domain liquid cloud fraction and the evolution of the liquid cloud fraction over time from the LES. When relatively large liquid water contents are present, theory underpredicts liquid cloud fraction. Further, when ice is permitted to sediment, theory overpredicts liquid cloud fraction. Two modifications to the theory are suggested, and it is demonstrated how these reduce the deviation of predicted liquid cloud fraction from simulated cloud fraction.
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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 | 0.000 |
| 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) | 0.003 | 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 it