Merged ozone profiles from four MIPAS processors
Bibliographic record
Abstract
Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was an infrared (IR) limb emission spectrometer on the Envisat platform. Currently, there are four MIPAS ozone data products, including the operational Level-2 ozone product processed at ESA, with the scientific prototype processor being operated at IFAC Florence, and three independent research products developed by the Istituto di Fisica Applicata Nello Carrara (ISAC-CNR)/University of Bologna, Oxford University, and the Karlsruhe Institute of Technology–Institute of Meteorology and Climate Research/Instituto de Astrofísica de Andalucía (KIT–IMK/IAA). Here we present a dataset of ozone vertical profiles obtained by merging ozone retrievals from four independent Level-2 MIPAS processors. We also discuss the advantages and the shortcomings of this merged product. As the four processors retrieve ozone in different parts of the spectra (microwindows), the source measurements can be considered as nearly independent with respect to measurement noise. Hence, the information content of the merged product is greater and the precision is better than those of any parent (source) dataset. The merging is performed on a profile per profile basis. Parent ozone profiles are weighted based on the corresponding error covariance matrices; the error correlations between different profile levels are taken into account. The intercorrelations between the processors' errors are evaluated statistically and are used in the merging. The height range of the merged product is 20–55 km, and error covariance matrices are provided as diagnostics. Validation of the merged dataset is performed by comparison with ozone profiles from ACE-FTS (Atmospheric Chemistry Experiment–Fourier Transform Spectrometer) and MLS (Microwave Limb Sounder). Even though the merging is not supposed to remove the biases of the parent datasets, around the ozone volume mixing ratio peak the merged product is found to have a smaller (up to 0.1 ppmv) bias with respect to ACE-FTS than any of the parent datasets. The bias with respect to MLS is of the order of 0.15 ppmv at 20–30 km height and up to 0.45 ppmv at larger altitudes. The agreement between the merged data MIPAS dataset with ACE-FTS is better than that with MLS. This is, however, the case for all parent processors as well.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".