Sensitivity of MOPITT observations to carbon monoxide in the lower troposphere
Bibliographic record
Abstract
The sensitivity of Measurements of Pollution in the Troposphere (MOPITT) observations to carbon monoxide (CO) concentrations in the lower troposphere (LT) varies widely as the result of variability in thermal contrast conditions. This effect is evident in both the MOPITT weighting functions and averaging kernels, particularly after these quantities are properly normalized to remove grid effects. Comparisons of simulated weighting functions and averaging kernels with operational data confirm the significance of thermal contrast effects. Retrieval sensitivity to LT CO is greatest in daytime observations over land, particularly in tropical and midlatitude regions exhibiting large diurnal variations in surface temperature. Nighttime observations over land typically exhibit poor sensitivity to LT CO. On the global scale, analysis of MOPITT averaging kernels for 1 month indicates that daytime MOPITT observations offer useful sensitivity to LT CO over large areas of most continents. Exceptions include tropical rainforests in Africa and South America, where thermal contrast conditions are relatively weak.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".