Modeled and Observed Volcanic Aerosol Control on Stratospheric NO<sub>y</sub> and Cl<sub>y</sub>
Bibliographic record
Abstract
Abstract Decreases in stratospheric NOx associated with enhanced aerosol have been observed after large volcanic eruptions, for example, after the eruption of Mount Pinatubo in 1991. While the 1991 Mount Pinatubo eruption was the last large explosive eruption, recent studies have shed light on the impacts of moderate‐sized eruptions since the year 2000 on the global stratospheric aerosol budget. We use an ensemble of simulations from a coupled climate‐chemistry model to quantify and analyze changes in NO and NO2 (NOx), N2O5, HNO3, ClO, and ClONO2 during periods of increased stratospheric volcanic aerosol concentrations since 2000. By using an ensemble approach, we are able to distinguish forced responses from internal variability. We also compare the model ensemble results to satellite measurements of these changes in atmospheric composition, including measurements from the Optical Spectrograph and Infrared Imaging Spectrometer on the Odin satellite and the Aura Microwave Limb Sounder. We find decreases in stratospheric NOx concentrations up to 20 hPa, consistent with increases in stratospheric HNO3 concentrations. The HNO3 perturbations also extend higher, up to 5 hPa, associated with periods of increased volcanic aerosol concentrations in both model simulations and observations, though correlations with volcanic aerosol are considerably higher in the model simulations. The model simulates increases in ClO at altitudes and magnitudes similar to the NOx reductions, but this response is below the detectable limit in the available observations (100 pptv). We also demonstrate the value of accounting for transport‐related anomalies of atmospheric trace gases by regression onto N2O anomalies.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".