Calculation of Faraday Rotation Angle from SMOS Radiometric Data
Bibliographic record
Abstract
The Faraday Rotation (FR) consists of a rotation in the components of the electromagnetic field emitted by the Earth as it propagates through the ionosphere. It depends on the frequency, the geomagnetic field, and the Vertical Total Electron Content (VTEC) of the ionosphere. For the Soil Moisture and Ocean Salinity (SMOS) mission, which operates in the L-band, this effect is not negligible and must be compensated. This project is born from a methodology that consists of the estimation of the ionosphere VTEC of every SMOS overpass through an inversion procedure based on the measured FRA. However, there are some zones where the FRA and VTEC cannot be retrieved due to the presence of Radio Frequency Interferences (RFI) or in zones of dense forest or ice. In order to improve the maps of the recovered VTEC and FRA, these zones where they cannot be recovered have been analyzed. First, the brightness temperature (TB) maps have been reproduced and the FRA formula has been analyzed to observe in detail where the FRA cannot be recovered, focusing on Canada. It will be found that this happens because of an indetermination of the formula. Then, three approaches will be proposed, each one with a different methodology with the aim of improving the recovered VTEC maps. The VTEC cannot have negative values, but in the core methodology, some negative values appear which are then rejected when plotting them on the map, since they correspond to VTEC values that have not been correctly recovered. Therefore, the VTEC recovery maps will be improved by applying one of these approaches, although the statistic will worsen a bit. Finally, more suitable and optimal thresholds are going to be looked for in order to improve the statistics of the maps.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".