On the relationship between Arctic ice clouds and polluted air masses over the North Slope of Alaska in April 2008
Bibliographic record
Abstract
Abstract. Recently, two types of ice clouds (TICs) properties have been characterized using the Indirect and Semi-Direct Aerosol Campaign (ISDAC) airborne measurements (Alaska, April 2008). TIC-2B were characterized by fewer (< 10 L−1) and larger (> 110 μm) ice crystals, and a larger ice supersaturation (> 15%) compared to TIC-1/2A. It has been hypothesized that emissions of SO2 may reduce the ice nucleating properties of ice nuclei (IN) through acidification, resulting in a smaller concentration of larger ice crystals and leading to precipitation (e.g., cloud regime TIC-2B). Here, the origin of air masses forming the ISDAC TIC-1/2A (1 April 2008) and TIC-2B (15 April 2008) is investigated using trajectory tools and satellite data. Results show that the synoptic conditions favor air masses transport from three potential SO2 emission sources into Alaska: eastern China and Siberia where anthropogenic and biomass burning emissions, respectively, are produced, and the volcanic region of the Kamchatka/Aleutians. Weather conditions allow the accumulation of pollutants from eastern China and Siberia over Alaska, most probably with the contribution of acidic volcanic aerosol during the TIC-2B period. Observation Monitoring Instrument (OMI) satellite observations reveal that SO2 concentrations in air masses forming the TIC-2B were larger than in air masses forming the TIC-1/2A. Airborne measurements show high acidity near the TIC-2B flight where humidity was low. These results support the hypothesis that acidic coating on IN could be at the origin of the formation of TIC-2B.
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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) | 0.001 | 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 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".