Validation of Aura Microwave Limb Sounder stratospheric ozone measurements
Bibliographic record
Abstract
The Earth Observing System (EOS) Microwave Limb Sounder (MLS) aboard the Aura satellite has provided essentially daily global measurements of ozone (O3) profiles from the upper troposphere to the upper mesosphere since August of 2004. This paper focuses on validation of the MLS stratospheric standard ozone product and its uncertainties, as obtained from the 240 GHz radiometer measurements, with a few results concerning mesospheric ozone. We compare average differences and scatter from matched MLS version 2.2 profiles and coincident ozone profiles from other satellite instruments, as well as from aircraft lidar measurements taken during Aura Validation Experiment (AVE) campaigns. Ozone comparisons are also made between MLS and balloon‐borne remote and in situ sensors. We provide a detailed characterization of random and systematic uncertainties for MLS ozone. We typically find better agreement in the comparisons using MLS version 2.2 ozone than the version 1.5 data. The agreement and the MLS uncertainty estimates in the stratosphere are often of the order of 5%, with values closer to 10% (and occasionally 20%) at the lowest stratospheric altitudes, where small positive MLS biases can be found. There is very good agreement in the latitudinal distributions obtained from MLS and from coincident profiles from other satellite instruments, as well as from aircraft lidar data along the MLS track.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".