Studies for the Odin sub-millimetre radiometer. II. Retrieval methodology
Bibliographic record
Abstract
This paper presents the first algorithm developed to retrieve atmospheric vertical profiles of trace gases from calibrated spectra measured by the sub-millimetre radiometer (SMR) onboard the Odin satellite. An estimation of atmospheric profiles is obtained by means of an inversion of the spectra using the Optimal Estimation Method. Great attention is paid to the study of the simultaneous retrieval of several species and nonlinearity effects. The measurement response is defined to give the altitude domain of a good retrieval. Main sources of measurement and forward model errors are characterized and separated into two categories: the fixed errors and the variable errors. We define a standard retrieval strategy that can be applied to theoretically investigate any frequency band of any observing Odin mode. For each frequency band, two categories of species are defined: the target species, i.e., the main species to be retrieved, and the interfering species, i.e., molecules emitting an interfering radiance in the observed band. The standard code is based upon an inversion of spectra using a linearized forward model and simultaneously estimates target species and interfering species. As an example, inversions of synthetic noise-free spectra of ozone and chlorine monoxide within an autocorrelator band ranging from 501.18 to 501.58 GHz are shown to behave as expected in the middle stratosphere and in the lower mesosphere. The error analysis shows retrieval limitations in the lower stratosphere that are mainly induced by the high sensitivity of the retrieval to parameters such as tangent height, accuracy in the vertical profile of the interfering species, and spectral parameters of both target lines and interfering lines. PACS Nos.: 42.68Ay, 07.07Df, 07.57Kp
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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 | 0.000 |
| 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) | 0.000 | 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".