Stratospheric aerosol particle size information in Odin-OSIRIS limb scatter spectra
Bibliographic record
Abstract
Abstract. The Optical Spectrograph and InfraRed Imaging System (OSIRIS) onboard the Odin satellite has now taken over a decade of limb scatter measurements that have been used to retrieve the version 5 stratospheric aerosol extinction product. This product is retrieved using a representative particle size distribution to calculate scattering cross sections and scattering phase functions for the forward model calculations. In this work the information content of OSIRIS measurements with respect to stratospheric aerosol is systematically examined for the purpose of retrieving particle size information along with the extinction coefficient. The benefit of using measurements at different wavelengths and scattering angles in the retrieval is studied, and it is found that incorporation of the 1530 nm radiance measurement is key for a robust retrieval of particle size information. It is also found that using OSIRIS measurements at the different solar geometries available on the Odin orbit simultaneously provides little additional benefit. Based on these results, an improved aerosol retrieval algorithm is developed that couples the retrieval of aerosol extinction and mode radius of a log-normal particle size distribution. Comparison of these results with coincident measurements from SAGE III shows agreement in retrieved extinction to within approximately 10% over the bulk of the aerosol layer, which is comparable to version 5. The retrieved particle size, when converted to Ångström coefficient, shows good qualitative agreement with SAGE II measurements made at somewhat shorter wavelengths.
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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 | 0.000 |
| 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".