Chemistry contribution to stratospheric ozone depletion after the unprecedented water rich Hunga Tonga eruption
Bibliographic record
Abstract
Following the Hunga Tonga–Hunga Ha’apai (HTHH) eruption in January 2022, stratospheric ozone depletion was observed in the Southern Hemisphere mid-latitudes and Antarctica during the 2022 austral wintertime and springtime. This eruption injected sulfur dioxide and unprecedented amounts of water vapor into the stratosphere. This work examines and quantifies the chemistry contribution of the volcanic materials to the ozone depletion using chemistry-climate model simulations with nudged meteorology. Simulated 2022 ozone and nitrogen oxides (NOx) anomalies show a good agreement with satellite observations. We find that chemistry only contributes up to 6% and 20% ozone destruction at mid-latitudes wintertime and Antarctic springtime respectively. The majority of the ozone depletion is attributed to the internal variability and dynamical changes forced by the eruption. Both the simulation and observations show a significant NOx reduction associated with the HTHH aerosol plume, indicating the enhanced dinitrogen pentoxide hydrolysis on sulfate 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".