Modeling of observed mineral dust aerosols in the arctic and the impact on winter season low‐level clouds
Bibliographic record
Abstract
Mineral dust aerosol is the main ice nucleus (IN) in the Arctic. Observed dust concentrations at Alert, Canada, are lowest in winter and summer and highest in spring and autumn. In this study, we simulate transport and deposition of dust in a global chemical transport model. The model predicts the spring maximum caused by natural dust from desert sources in Asia and Sahara but underestimates the observations in autumn. Both natural and pollution sources contribute to the wintertime dust burden, as suggested by previous measurements of elemental compositions. Cloud parcel model simulations were carried out to study the impact of dust aerosol on the formation of mixed‐phase and ice clouds in the Arctic lower troposphere. The liquid water path of low‐level cloud is most sensitive to dust aerosol concentration from winter to early spring when air temperature is at its lowest in the annual cycle. The global and parcel models together suggest that low concentrations and acid coating of dust particles are favorable conditions for occurrence of mixed‐phase clouds and that anthropogenic pollution can cause significant perturbations to Arctic IN and clouds in winter.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".