Potential source regions and processes of aerosol in the summer Arctic
Bibliographic record
Abstract
Sub-micrometer particle size distributions measured during four summer cruises of the Swedish icebreaker Oden 1991, 1996, 2001, and 2008 were combined with dimethyl sulfide gas data, back trajectories, and daily maps of pack ice cover in order to investigate source areas and aerosol formation processes of the boundary layer aerosol in the central Arctic. With a clustering algorithm, potential aerosol source areas were explored. Clustering of particle size distributions together with back trajectories delineated five potential source regions and three different aerosol types that covered most of the Arctic Basin: marine, newly formed and aged particles over the pack ice. Most of the pack ice area with < 15% of open water under the trajectories exhibited the aged aerosol type with only one major mode around 40 nm. For newly formed particles to occur, two conditions had to be fulfilled over the pack ice: the air had spent 10 days while traveling over ever more contiguous ice and had traveled over less than 30% open water during the last 5 days. Additionally, the air had experienced more open water (at least twice as much as in the cases of aged aerosol) during the last 4 days before arrival in heavy ice conditions at Oden. Thus we hypothesize that these two conditions were essential factors for the formation of ultrafine particles over the central Arctic pack ice. In a comparison the Oden data with summer size distribution data from Alert, Nunavut, and Mt. Zeppelin, Spitsbergen, we confirmed the Oden findings with respect to particle sources over the central Arctic. Future more frequent broken-ice or open water patches in summer will spur biological activity in surface water promoting the formation of biological particles. Thereby low clouds and fogs and subsequently the surface energy balance and ice melt may be affected.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".