Dependence of Ice Microphysical Properties On Environmental Parameters: Results from HAIC-HIWC Cayenne Field Campaign
Bibliographic record
Abstract
Abstract High Ice Water Content (HIWC) regions above tropical mesoscale convective systems are investigated using data from the second collaboration of the High Altitude Ice Crystals and High Ice Water Content projects (HAIC-HIWC) based in Cayenne, French Guiana in 2015. Observations from in-situ cloud probes on the French Falcon 20 determine the microphysical and thermodynamic properties of such regions. Data from a 2-D stereo probe and precipitation imaging probe show how statistical distributions of ice crystal mass median diameter ( MMD ), ice water content ( IWC ), and total number concentration ( N t ) for particles with maximum dimension ( D max ) > 55 μm vary with environmental conditions, temperature ( T ), and convective properties such as vertical velocity ( w ), MCS age, distance away from convective peak ( L ), and surface characteristics. IWC is significantly correlated with w , whereas MMD decreases and N t increases with decreasing T consistent with aggregation, sedimentation and vapor deposition processes at lower altitudes. MMD typically increases with IWC when IWC < 0.5 g m -3 , but decreases with IWC when IWC > 0.5 g m -3 for -15 °C ≤ T ≤ -5 °C. Trends also depend on environmental conditions, such as presence of convective updrafts that are the ice crystal source, MMD being larger in older MCSs consistent with aggregation and less injection of small crystals into anvils, and IWC s decrease with increasing L at lower T . The relationship between IWC and MMD depends on environmental conditions, with correlations decreasing with decreasing T . The strength of correlation between IWC and N t increases as T decreases.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".