Validation of Measurements of Pollution in the Troposphere (MOPITT) CO retrievals with aircraft in situ profiles
Bibliographic record
Abstract
Validation of the Measurements of Pollution in the Troposphere (MOPITT) retrievals of carbon monoxide (CO) has been performed with a varied set of correlative data. These include in situ observations from a regular program of aircraft observations at five sites ranging from the Arctic to the tropical South Pacific Ocean. Additional in situ profiles are available from several short‐term research campaigns situated over North and South America, Africa, and the North and South Pacific Oceans. These correlative measurements are a crucial component of the validation of the retrieved CO profiles and columns from MOPITT. The current validation results indicate good quantitative agreement between MOPITT and in situ profiles, with an average bias less than 20 ppbv at all levels. Comparisons with measurements that were timed to sample profiles coincident with MOPITT overpasses show much less variability in the biases than those made by various groups as part of research field experiments. The validation results vary somewhat with location, as well as a change in the bias between the Phase 1 and Phase 2 retrievals (before and after a change in the instrument configuration due to a cooler failure). During Phase 1, a positive bias is found in the lower troposphere at cleaner locations, such as over the Pacific Ocean, with smaller biases at continental sites. However, the Phase 2 CO retrievals show a negative bias at the Pacific Ocean sites. These validation comparisons provide critical assessments of the retrievals and will be used, in conjunction with ongoing improvements to the retrieval algorithms, to further reduce the retrieval biases in future data versions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.000 | 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".