SO <sub>2</sub> Retrieval from SCIAMACHY using the Weighting Function DOAS (WFDOAS) technique: comparison with Standard DOAS retrieval
Bibliographic record
Abstract
Abstract. Atmospheric SO2 can be measured by remote sensing of scattered sunlight from space, using its unique absorption features in the ultraviolet region. However, the sensitivity of the SO2 measurement depends critically on spectral interference, surface albedo and varies with wavelength as Rayleigh scattering increases at shorter wavelengths. The Weighting Function Differential Optical Absorption Spectroscopy (WFDOAS) method was used to pinpoint these problems and improve the retrieval. The Ring spectra included in the WFDOAS fit were determined as a function of total ozone column density, solar zenith angle, surface albedo, and effective scene altitude. The WFDOAS SO2 retrieval from SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) data onboard the ENVISAT satellite are presented here and compared to those of the Standard DOAS (SDOAS) method for cases of background conditions and volcanic eruption. The study demonstrates the problems in the SO2 retrieval with SDOAS, such as the positive offsets over remote (clean) regions and the negative offsets at high solar zenith angles and high ozone, could be attributed to imperfect correction for the varying ozone dependence of the Ring effect and could be solved by the WFDOAS approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".