Retrieval of ozone profiles from GOMOS limb scattered measurements
Bibliographic record
Abstract
Abstract. The GOMOS (Global Ozone Monitoring by Occultation of Stars) instrument on board the Envisat satellite measures the vertical composition of the atmosphere using the stellar occultation technique. While the night-time occultations of GOMOS have been proven to be of good quality, the daytime occultations are more challenging due to weaker signal-to-noise ratio. During daytime GOMOS measures limb scattered solar radiation in addition to stellar radiation. In this paper we introduce a retrieval method that determines ozone profiles between 20–60 km from GOMOS limb scattered solar radiances. GOMOS observations contain a considerable amount of stray light at high altitudes. We introduce a method for removing stray light and demonstrate its feasibility by comparing the corrected radiances against those measured by the OSIRIS (Optical Spectrograph & Infra Red Imaging System) instrument. For the retrieval of ozone profiles, a standard onion peeling method is used. The first comparisons with other data sets suggest that the retrieved ozone profiles in 22–50 km are within 10% compared with the GOMOS night-time occultations and within 15% compared with OSIRIS. GOMOS has measured about 350 000 daytime profiles since 2002. The retrieval method presented here makes this large amount of data available for scientific use.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".