Wintertime enhancements of sea salt aerosol in polar regions consistent with a sea ice source from blowing snow
Bibliographic record
Abstract
Abstract. Sea salt aerosols (SSA) are generated via air bubbles bursting at the ocean surface as well as by wind mobilization of saline snow and frost flowers over sea-ice-covered areas. The relative magnitude of these sources remains poorly constrained over polar regions, affecting our ability to predict their impact on halogen chemistry, cloud formation, and climate. We implement a blowing snow and a frost flower emission scheme in the GEOS-Chem global chemical transport model, which we validate against multiyear (2001–2008) in situ observations of SSA mass concentrations at three sites in the Arctic, two sites in coastal Antarctica, and from the 2008 ICEALOT cruise in the Arctic. A simulation including only open ocean emissions underestimates SSA mass concentrations by factors of 2–10 during winter–spring for all ground-based and ship-based observations. When blowing snow emissions are added, the model is able to reproduce observed wintertime SSA concentrations, with the model bias decreasing from a range of −80 to −34 % for the open ocean simulation to −2 to +9 % for the simulation with blowing snow emissions. We find that the frost flower parameterization cannot fully explain the high wintertime concentrations and displays a seasonal cycle decreasing too rapidly in early spring. Furthermore, the high day-to-day variability of observed SSA is better reproduced by the blowing snow parameterization. Over the Arctic (> 60° N) (Antarctic, > 60° S), we calculate that submicron SSA emissions from blowing snow account for 1.0 Tg yr−1 (2.5 Tg yr−1), while frost flower emissions lead to 0.21 Tg yr−1 (0.25 Tg yr−1) compared to 0.78 Tg yr−1 (1.0 Tg yr−1) from the open ocean. Blowing snow emissions are largest in regions where persistent strong winds occur over sea ice (east of Greenland, over the central Arctic, Beaufort Sea, and the Ross and Weddell seas). In contrast, frost flower emissions are largest where cold air temperatures and open leads are co-located (over the Canadian Arctic Archipelago, coastal regions of Siberia, and off the Ross and Ronne ice shelves). Overall, in situ observations of mass concentrations of SSA suggest that blowing snow is likely to be the dominant SSA source during winter, with frost flowers playing a much smaller role.
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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 | 0.000 | 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 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".