Simulations of ice clouds during FIRE ACE using the CCCMA single‐column model
Bibliographic record
Abstract
The single‐column model (SCM) of the Canadian Centre for Climate Modelling and Analysis (CCCMA) solves prognostic equations for the number concentration and mass mixing ratios of ice crystals. Ice crystal formation is specified via different ice nucleation mechanisms. The CCCMA SCM was used to simulate the evolution of ice clouds for three different flights during the First ISCCP Regional Experiment Arctic Cloud Experiment (FIRE ACE) in April 1998, where measurements of cloud droplets, ice crystals, and aerosols >0.08 μm in radius were conducted. The CCCMA SCM in its original setup predicts larger ice crystal concentrations than measured with the 2DC probe. The agreement with observations of ice crystals detectable with the 2DC probe was improved if a condensation freezing parameterization depending on supersaturation with respect to ice was used. The best correlation between observed and simulated ice crystal number, which still showed a lot of scatter, was obtained if an empirical linear relationship between the number of aerosols and the number of ice crystals deduced from FIRE ACE was used.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".