Validation of the global distribution of CO<sub>2</sub> volume mixing ratio in the mesosphere and lower thermosphere from SABER
Bibliographic record
Abstract
Abstract The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on board the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite has been measuring the limb radiance in 10 broadband infrared channels over the altitude range from ~ 400 km to the Earth's surface since 2002. The kinetic temperatures and CO2 volume mixing ratios (VMRs) in the mesosphere and lower thermosphere have been simultaneously retrieved using SABER limb radiances at 15 and 4.3 µm under nonlocal thermodynamic equilibrium (non‐LTE) conditions. This paper presents results of a validation study of the SABER CO2 VMRs obtained with a two‐channel, self‐consistent temperature/CO2 retrieval algorithm. Results are based on comparisons with coincident CO2 measurements made by the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE‐FTS) and simulations using the Specified Dynamics version of the Whole Atmosphere Community Climate Model (SD‐WACCM). The SABER CO2 VMRs are in agreement with ACE‐FTS observations within reported systematic uncertainties from 65 to 110 km. The annual average SABER CO2 VMR falls off from a well‐mixed value above ~80 km. Latitudinal and seasonal variations of CO2 VMRs are substantial. SABER observations and the SD‐WACCM simulations are in overall agreement for CO2 seasonal variations, as well as global distributions in the mesosphere and lower thermosphere. Not surprisingly, the CO2 seasonal variation is shown to be driven by the general circulation, converging in the summer polar mesopause region and diverging in the winter polar mesopause region.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".