Effect of volcanic aerosol on stratospheric NO <sub>2</sub> and N <sub>2</sub> O <sub>5</sub> from 2002–2014 as measured by Odin-OSIRIS and Envisat-MIPAS
Bibliographic record
Abstract
Abstract. Following the large volcanic eruptions of Pinatubo in 1991 and El Chichón in 1982, decreases in stratospheric NO2 associated with enhanced aerosol were observed. The Optical Spectrograph and Infrared Imaging Spectrometer (OSIRIS) measured the widespread enhancements of stratospheric aerosol following seven volcanic eruptions between 2002 and 2014, although the magnitudes of these eruptions were all much smaller than the Pinatubo and El Chichón eruptions. In order to isolate and quantify the relationship between volcanic aerosol and NO2, NO2 anomalies were calculated using measurements from OSIRIS and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). In the tropics, variability due to the quasi-biennial oscillation was subtracted from the time series. OSIRIS profile measurements indicate that the strongest anticorrelations between NO2 and volcanic aerosol extinction were for the 5 km layer starting ∼ 3 km above the climatological mean tropopause at the given latitude. OSIRIS stratospheric NO2 partial columns in this layer were found to be smaller than background NO2 levels during these aerosol enhancements by up to ∼ 60 % with typical Pearson correlation coefficients of R ∼ −0. 7. MIPAS also observed decreases in NO2 partial columns during periods affected by volcanic aerosol, with percent differences of up to ∼ 25 % relative to background levels. An even stronger anticorrelation was observed between OSIRIS aerosol optical depth and MIPAS N2O5 partial columns, with R ∼ −0. 9, although no link with MIPAS HNO3 was observed. The variation in OSIRIS NO2 with increasing aerosol was found to be consistent with simulations from a photochemical box model within the estimated model uncertainty.
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 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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".