Ka‐band rain attenuation estimation using weather radar
Bibliographic record
Abstract
Weather radars have been routinely used for investigating propagation phenomena which affect satellite communication links. Weather radar returns can be used to estimate both attenuation and depolarization produced by hydrometeors. Some of the early radar measurements resulted in the discovery of high altitude ice particles as a potential source for depolarization and the development of models for the melting layer or the radar bright band. The radar return from precipitation particles is proportional to the number density of particles in the radar pulse volume. The reflectivity can be converted to an equivalent rain rate or signal attenuation through appropriate assumptions on the particle size distribution. If the radar is capable of measuring reflectivity in two orthogonal polarizations, the difference between the two reflectivity measurements is a direct estimate of the anisotropy of the particulate medium. Differential reflectivity can be used to detect regions containing highly non‐spherical particles such as the melting layer and high altitude ice particles. Results of an experiment involving a dual polarized radar to estimate Ka‐band path attenuation at a tropical location are presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".