Cyclone-induced surface ozone and HDO depletion in the Arctic
Bibliographic record
Abstract
Abstract. Ground-based, satellite, and reanalysis datasets were used to identify two similar cyclone-induced surface ozone depletion events at Eureka, Canada (80.1° N, 86.4° W), in March 2007 and April 2011. These two events were coincident with observations of hydrogen deuterium oxide (HDO) depletion, indicating that condensation and sublimation occurred during the transport of the ozone-depleted air masses. Ice clouds (vapour and crystals) and aerosols were detected by lidar and radar when the ozone- and HDO-depleted air masses arrived over Eureka. For the 2007 event, an ice cloud layer was coincident with an aloft ozone depletion layer at 870 m altitude on 2–3 March, indicating this ice cloud layer contained bromine-enriched blowing-snow particles. Over the following 3 days, a shallow surface ozone depletion event (ODE) was observed at Eureka after the precipitation of bromine-enriched particles onto the local snowpack. A chemistry–climate model (UKCA) and a chemical transport model (pTOMCAT) were used to simulate the surface ozone depletion events. Incorporating the latest surface snow salinity data obtained for the Weddell Sea into the models resulted in improved agreement between the modelled and measured BrO concentrations above Eureka. MERRA-2 global reanalysis data and the FLEXPART particle dispersion model were used to study the link between the ozone and HDO depletion. In general, the modelled ozone and BrO showed good agreement with the ground-based observations; however, the modelled BrO and ozone in the near-surface layer are quite sensitive to the snow salinity. HDO depletion observed during these two blowing-snow ODEs was found to be weaker than pure Rayleigh fractionation. This work provides evidence of a blowing-snow sublimation process, which is a key step in producing bromine-enriched sea-salt aerosol.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".