Chemistry Contribution to Stratospheric Ozone Depletion After the Unprecedented Water‐Rich Hunga Tonga Eruption
Bibliographic record
Abstract
Abstract Following the Hunga Tonga–Hunga Ha'apai (HTHH) eruption in January 2022, stratospheric ozone depletion was observed at Southern Hemisphere mid‐latitudes and over Antarctica during the 2022 austral wintertime and springtime, respectively. The eruption injected sulfur dioxide and unprecedented amounts of water vapor into the stratosphere. This work examines the chemistry contribution of the volcanic materials to ozone depletion using chemistry‐climate model simulations with nudged meteorology. Simulated 2022 ozone and nitrogen oxide (NO x = NO + NO 2 ) anomalies show good agreement with satellite observations. We find that chemistry yields up to 4% ozone destruction at mid‐latitudes near ∼70 hPa in August and up to 20% ozone destruction over Antarctica near ∼80 hPa in October. Most of the ozone depletion is attributed to internal variability and dynamical changes forced by the eruption. Both the modeling and observations show a significant NO x reduction associated with the HTHH aerosol plume, indicating enhanced dinitrogen pentoxide hydrolysis on sulfate aerosol.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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; both teacher heads agree on what is shown here.
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".