Microwave temperature and pressure measurements with the Odin satellite: II. Retrieval method
Bibliographic record
Abstract
The millimetre receiver on the Swedish satellite Odin, will be used for detection of the 118.750 GHz oxygen line. The temperature and pressure will be determined from the output of a three-channel filter bank measurement. One frequency bin is centred over the emission-line frequency while the other two cover parts of the line wing, where the opacity is less, providing a useful signal at lower altitudes. The bandwidth of each channel is 40 MHz. The signal in the frequency bin covering the line centre is modeled by a high-resolution model including the Zeeman effect, developed by the Observatoire de ParisMeudon. The other two 40 MHz bins are modeled using the much faster standard Odin forward model, developed at the Department of Meteorology at Stockholm University together with Chalmers University of Technology. The operational retrievals employ an iterative method that uses simulated signals from a reference atmosphere as a lookup table for the pressure. The temperature is then calculated from the equation of hydrostatic equilibrium, and a new lookup table computed. This process is repeated until a convergence criterion is reached. Simulations, including known error sources, show that the temperature can be retrieved with a root mean square (rms) around 3 K, in the altitude range ~ 2590 km using the operational temperature retrieval method (the filter bank method). A sub-millimetre receiver on board Odin will also be used to observe the oxygen line at 487.249 GHz. Both this line and the 118.750 GHz line can be observed in high resolution (150 kHz) for detailed studies of the Zeeman splitting. Retrievals from the high-resolution measurements are expected to give a precision of ± 2 K rms at that resolution. However, this kind of observation will occupy an entire spectrometer and will not be made on a regular basis. PACS Nos.: 07.57Yb, 94.10Dy, 95.75Rs
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".