Comparison of OSIRIS stratospheric NO<sub>2</sub> and O<sub>3</sub> measurements with ground-based Fourier transform spectrometer measurements at the Toronto Atmospheric Observatory
Bibliographic record
Abstract
Stratospheric NO2 and O3 retrieved from measurements of limb-scattered sunlight made by the Optical Spectrograph and InfraRed Imager System (OSIRIS) are compared with like observations made by a ground-based infrared Fourier Transform Spectrometer at the Toronto Atmospheric Observatory (TAO-FTS). Two different versions of OSIRIS NO2 are compared (DOAS version 3.0 and MART version 2.0) with partial column concentrations retrieved from the TAO-FTS. Two OSIRIS O3 versions are also compared (Triplet version 3.0 and MART version 2.0) with O3 retrieved from the TAO-FTS. To accommodate the most coincidences, comparisons are based on monthly mean stratospheric partial columns covering 16–50 km. All coincident monthly means display high correlations: 0.82–0.97. The monthly mean NO2 at TAO compared with the monthly mean NO2 from OSIRIS shows an average difference of less than ~3% with standard deviations up to 6%. The OSIRIS NO2 observations show a multiplicative bias of ~0.8–0.9 and a systematic difference of 5–10% greater then those of the TAO-FTS. O3 differences are less than 5%, on average, with standard deviations ranging from 2% to 2.8%. There is a pronounced multiplicative bias of OSIRIS compared with the TAO-FTS ranging from 0.55 to 0.73. The systematic O3 differences are less than 5% larger for OSIRIS. These small differences meet the standards outlined in the Integrated Global Observing Strategy and confirm the quality of the OSIRIS data for studying stratospheric ozone and nitrogen chemistry.PACS{ 92.60.hd, 92.60.Ry, 92.70.Cp, 93.30.Hf
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".