Trends and Variability in Stratospheric NO<sub>x</sub> Derived From Merged SAGE II and OSIRIS Satellite Observations
Bibliographic record
Abstract
Abstract Nitrogen oxides (NO x ) in the stratosphere are produced from N 2 O, which is the dominant emission contributing to stratospheric ozone depletion in the 21st century and an important anthropogenic greenhouse gas. Decades worth of observations are required in order to quantify the variability and trends in stratospheric NO x so that we can better understand their impact on climate. Here we use the Stratospheric Aerosol and Gas Experiment (SAGE) II, a solar occultation instrument that measured NO 2 from 1984 to 2005, and the Optical Spectrograph and InfraRed Imager System (OSIRIS), a limb‐scattering instrument that began measuring NO 2 in 2001. By taking advantage of the 4‐year overlap between these instruments it was possible to produce a merged data set of stratospheric NO 2 , spanning over 34 years. In order to merge the data a photochemical correction was applied to account for the different times of day at which the instruments measure, and to convert the NO 2 to NO x . A linear regression model was applied to the merged, deseasonalized data set to identify variability associated with long‐term trends, the quasi‐biennial oscillation (QBO), and volcanic aerosols. High levels of aerosol associated with large volcanic eruptions were found to greatly influence the calculated trend; when volcanic periods are excluded the trend in NO x is around 10% per decade in the tropical lower stratosphere. In this case, the observed trends and variability from the satellite measurements show overall good agreement with simulations from the whole atmosphere community climate model (WACCM).
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".