Arctic Mixed-Phase Stratiform Cloud Properties from Multiple Years of Surface-Based Measurements at Two High-Latitude Locations
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Macro- and microphysical properties of single-layer stratiform mixed-phase clouds are derived from multiple years of lidar, radar, and radiosonde observations. Measurements were made as part of the Mixed-Phase Arctic Clouds Experiment (MPACE) and the Study of Environmental Arctic Change (SEARCH) in Barrow, Alaska, and Eureka, Nunavut, Canada, respectively. Single-layer mixed-phase clouds occurred between 4% and 26% of the total time observed, varying with season and location. They had mean cloud-base heights between ∼700 and 2100 m and thicknesses between ∼200 and 700 m. Seasonal mean cloud optical depths ranged from 2.2 up. The clouds existed at temperatures of ∼242–271 K and occurred under different wind conditions, depending on season. Utilizing retrievals from a combination of lidar, radar, and microwave radiometer, mean cloud microphysical properties were derived, with mean liquid effective diameters estimated from 16 to 49 μm, mean liquid number densities on the order of 104–105 L−1, and mean water contents estimated between 0.07 and 0.28 g m−3. Ice precipitation was shown to have mean ice effective diameters of 50–125 μm, mean ice number densities on the order of 10 L−1, and mean water contents estimated between 0.012 and 0.031 g m−3. Mean cloud liquid water paths ranged from 25 to 100 g m−2. All results are compared to previous studies, and potential retrieval errors are discussed. Additionally, seasonal variation in macro- and microphysical properties was highlighted. Finally, fraction of liquid water to ice mass was shown to decrease with decreasing temperature.
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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 | 0.001 |
| 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 it