SCIAMACHY stratospheric aerosol extinction profile retrieval using the OMPS/LP algorithm
Bibliographic record
Abstract
Abstract. The Ozone Mapper and Profiler Suite, Limp Profiler (OMPS/LP) algorithm is used to retrieve ozone concentration and aerosol extinction profiles using a series of 120 SCIAMACHY limb measurements collocated with SAGE II solar occultation events. The primary goal of the study is to ascertain the capability of the OMPS/LP retrieval algorithm to accurately retrieve the vertical distribution of stratospheric aerosol extinction coefficient so as to better account for aerosol effects in the ozone profiling retrieval process. Using simulated radiances, we show that the aerosol extinction coefficient can be retrieved from limb scatter measurements within 5% and a standard deviation better than 15%, which is more than sufficient to improve the OMPS/LP ozone products to be used as Environmental Data Records. We also illustrate the ability of SCIAMACHY limb measurements to retrieve stratospheric aerosol extinction profiles with accuracy comparable to other instruments. The retrieved aerosol extinction profiles agree with collocated SAGE II measurements on average to within 25%, with a standard deviation of 35%.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".