Ozone depletion events in the Arctic spring of 2019: a new modeling approach to bromine emissions
Bibliographic record
Abstract
Ozone depletion events (ODEs) are a common occurrence in the boundary layer during Arctic spring. Ozone is depleted by bromine species, which are most likely emitted from snow, sea ice, or aerosols in an autocatalytic reaction cycle. Previous three-dimensional modeling studies of ODEs assumed an infinite bromine source at the ground. In the present study, an alternative emission scheme is presented in which a finite amount of bromide in the snow is tracked over time. For this purpose, a modified version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is used to study ODEs in the Arctic from February to May 2019. The model data are compared to in situ measurements, ozone sonde flights, and satellite data. A simulation of the ODEs in the Arctic spring of 2009 using the infinite-bromide assumption on first-year (FY) ice is transferred to the spring of 2019, which achieves good agreement with the observations; however, there is some disagreement in April 2009 and 2019 with respect to an overestimation concerning both the magnitude and the number of ODEs. New simulations using the finite-bromide assumption greatly improve agreement with in situ observations at Utqiaġvik, Alaska, Zeppelin Mountain, Svalbard, and Pallas, Finland, in April 2019, suggesting that bromide on the sea ice is depleted to an extent that reduces the bromine release. The new simulations also slightly improve the agreement with observations at these sites in February and March. A comparison to measurements near Eureka, Canada, and Station Nord, Greenland, shows that multi-year ice and possibly snow-covered land may be significant bromine sources. However, assuming higher releasable bromide near Eureka does not remove all disagreement with the observations. The numerical results are also compared to tropospheric-BrO vertical column densities generated with a new retrieval method from TROPOspheric Monitoring Instrument (TROPOMI) observations. BrO vertical column densities (VCDs) above 5×10 13 molec. cm −2 observed by the satellite agree well with the model results. However, the model also predicts BrO VCDs of around 3×10 13 molec. cm −2 throughout the Arctic and patches of BrO VCDs of around 10 14 molec. cm −2 not observed by the satellite, especially near Hudson Bay. This suggests that snow at Hudson Bay may be a weaker bromine source in late spring compared to snow in the north.
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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 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".