A Parameterization of cirrus cloud formation: Homogeneous freezing including effects of aerosol size
Bibliographic record
Abstract
In a previous study, we have derived an approximate, physically based parameterization of cirrus cloud formation by homogeneous freezing, applying to a wide class of supercooled aerosols in the upper troposphere and tropopause region. In this study, the parameterization scheme is extended to include the effects of aerosol size on the freezing process in adiabatically rising air parcels. Aerosol size effects become important when the timescale of the freezing event is fast compared to the timescale of depositional growth of the pristine ice particles. The generalized parameterization scheme is validated with parcel model simulations and can directly be applied in models that do not explicitly resolve the ice nucleation process, such as cloud‐resolving models, weather forecast models, and climate models. The relationship between aerosol and ice crystal number concentrations in cirrus clouds formed by homogeneous freezing is discussed. This relationship is much weaker than in liquid water clouds. It is shown that even freezing of enhanced levels of sulfate aerosol originating from strong volcanic eruptions is unlikely to exert a sensible influence on cirrus formation.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".