On the onset of the ice phase in boundary layer Arctic clouds
Bibliographic record
Abstract
Airborne measurements in slightly supercooled Arctic boundary layer stratocumulus have been carried out in Spitsbergen on 29 May during the ASTAR 2004 campaign. Cloud measurements have been performed in both warm and cold sectors of a cold front passing the observation area. The results show a north–south gradient in freezing properties and thus evidence of significant differences in the cloud microstructure. Ahead of the front line, in the warm sector (cloud top temperature at −4°C), no ice particles were detected. The cloud formed in clean air conditions (aerosol concentration of 300 cm−3) with subsequent large effective diameter (20–26 μm) and low concentration (50 cm−3) of cloud droplets. Therefore, the collision‐coalescence process was effective, favoring the drizzle formation with concentration up to 300 L−1 (D > 50 μm). In the cold sector behind the front, with a lower cloud top temperature (−6°C), ice crystals were observed in the entire cloud layer, and no droplets larger than about 50 μm (drizzle) were detected. The observations confirm high ice particle concentrations (up to 50 L−1) even with rather warm cloud top (−6°C) compared to previous studies in Arctic clouds. The shattering of isolated drops during freezing and the ice splinter production during riming appear to be the most likely processes to explain the observations of high ice concentration in the cold sector. Analysis of back trajectories did not reveal significant differences in the origin of the air masses in the warm and cold sectors that might have contributed to the differentiation of aerosol composition and thus cloud properties. A cloud top temperature colder than −4°C appears to be required for the onset of the ice phase in this slightly supercooled stratiform cloud.
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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 | 0.000 |
| 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) | 0.001 | 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".