Freezing thresholds and cirrus cloud formation mechanisms inferred from in situ measurements of relative humidity
Bibliographic record
Abstract
Abstract. Factors controlling the microphysical link between distributions of relative humidity above ice saturation in the upper troposphere and lowermost stratosphere and cirrus clouds are examined with the help of microphysical trajectory simulations. Our findings are related to results from aircraft measurements and global model studies. We suggest that the relative humidities at which ice crystals form in the atmosphere can be inferred from in situ measurements of water vapor and temperature close to, but outside of, cirrus clouds. The comparison with concomitant measurements performed inside cirrus clouds provides a clue to freezing mechanisms active in cirrus. The analysis of field data taken at northern and southern midlatitudes in fall 2000 reveals distinct differences in cirrus cloud freezing thresholds. Homogeneous freezing is found to be the most likely mechanism by which cirrus form at southern hemisphere midlatitudes. The results provide evidence for the existence of heterogeneous freezing in cirrus in parts of the polluted northern hemisphere, but do not suggest that cirrus clouds in this region form exclusively on heterogeneous ice nuclei, thereby emphasizing the crucial importance of homogeneous freezing. The key features of distributions of upper tropospheric relative humidity simulated by a global climate model are shown to be in general agreement with both, microphysical simulations and field observations, delineating a feasible method to include and validate ice supersaturation in other large-scale atmospheric models, in particular chemistry-transport and weather forecast models.
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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) | 0.000 | 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".