Intercomparison of ozone profile measurements from ASUR, SCIAMACHY, MIPAS, OSIRIS, and SMR
Bibliographic record
Abstract
The airborne submillimeter radiometer (ASUR) was deployed onboard the Falcon research aircraft during the scanning imaging absorption spectrometer for atmospheric cartography (SCIAMACHY) validation and utilization experiment (SCIAVALUE) and the European polar stratospheric cloud and lee wave experiment (EuPLEx) campaigns. A large number of ozone profile measurements were performed over a latitude band spanning from 5°S to 80°N in September 2002 and February/March 2003 during the SCIAVALUE and around the northern polar latitudes in January/February 2003 during the EuPLEx. Both missions amassed an ample microwave ozone profile data set that is used to make quantitative comparisons with satellite measurements in order to assess the quality of the satellite retrievals. In this paper, the ASUR ozone profile measurements are compared with measurements from SCIAMACHY and Michelson interferometer for passive atmospheric sounding (MIPAS) on Environmental Satellite and optical spectrograph and infrared imager system (OSIRIS) and submillimeter radiometer (SMR) on the Odin satellite. The cross comparisons with the criterion that the ASUR measurements are performed within ±1000 km and ±6 hrs of the satellite observations show a good agreement with all the four satellite sensors. The differences in data values are the following: −4 to +8% for ASUR‐SCIAMACHY (operational product, v2.1), within ±15% for ASUR‐SCIAMACHY (scientific product, v1.62), up to +6% for ASUR‐MIPAS (operational product v4.61) and ASUR‐MIPAS (scientific product v1‐O3‐1), up to 17% for ASUR‐OSIRIS (v012), and −6 to 17% for ASUR‐SMR (v222) between the 20‐ and 40‐km altitude range depending on latitude. Thus, the intercomparisons provide important quantitative information about the quality of the satellite ozone profiles, which has to be considered when using the data for scientific analyses.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".