Parametric studies of contrail ice particle formation in jet regime using one-dimensional microphysical modeling
Bibliographic record
Abstract
Abstract. Condensation trails (contrails) formed from water vapor emissions behind aircraft engines are the most uncertain components of the aviation impacts on climate change. To gain improved knowledge of contrail and contrail-induced cirrus cloud formation, understanding of contrail ice particle formation immediately after aircraft engines is needed. Despite many efforts spent in modeling the microphysics of ice crystal formation in jet regime (with a plume age <5 s), systematic understanding of parametric effects of variables affecting contrail ice particle formation is still limited. In this work, we apply a one-dimensional modeling approach to study contrail ice particle formation in near-field aircraft plumes up to 1000 m downstream of an aircraft engine in the soot-rich regime (soot number emission index >1×1015 (kg-fuel)−1) at cruise. The effects of ion-mediated nucleation, ambient relative humidity, fuel sulfur content, and initial soot emissions were investigated. Our simulation results suggest that ice particles are mainly formed by water condensation on emitted soot particles. The growth of ice coated soot particles is driven by water vapor emissions in the first 1000 m and by ambient relative humidity afterwards. The presence of chemi-ions does not significantly contribute to the formation of ice particles, and the effect of fuel sulfur content is small over the range typical of standard jet fuels. The initial properties of soot emissions play the most critical role, and our calculations suggest that higher number concentration and smaller size of contrail particle nuclei may be able to effectively suppress the formation of contrail ice particles, providing a possible approach for contrail mitigation.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".