Characterization of Arctic ice cloud properties observed during ISDAC
Bibliographic record
Abstract
Extensive measurements from ground‐based sites and satellite remote sensing (CloudSat and CALIPSO) reveal the existence of two types of ice clouds (TICs) in the Arctic during the polar night and early spring. The first type (TIC‐2A), being topped by a cover of nonprecipitating very small (radar unseen) ice crystals (TIC‐1), is found more frequently in pristine environment, whereas the second type (TIC‐2B), detected by both sensors, is associated preferentially with a high concentration of aerosols. To further investigate the microphysical properties of TIC‐1/2A and TIC‐2B, airborne in situ and satellite measurements of specific cases observed during Indirect and Semi‐Direct Aerosol Campaign (ISDAC) have been analyzed. For the first time, Arctic TIC‐1/2A and TIC‐2B microstructures are compared using in situ cloud observations. Results show that the differences between them are confined in the upper part of the clouds where ice nucleation occurs. TIC‐2B clouds are characterized by fewer (by more than 1 order of magnitude) and larger (by a factor of 2 to 3) ice crystals and a larger ice supersaturation (of 15–20%) compared to TIC‐1/2A. Ice crystal growth in TIC‐2B clouds seems explosive, whereas it seems more gradual in TIC‐1/2A. It is hypothesized that these differences are linked to the number concentration and the chemical composition of aerosols. The ice crystal growth rate in very cold conditions impinges on the precipitation efficiency, dehydration and radiation balance. These results represent an essential and important first step to relate previous modeling, remote sensing and laboratory studies with TICs cloud in situ observations.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".