Improving precipitation estimates from dual-wavelength radars
Bibliographic record
Abstract
Dual-wavelength radars can, in principle, provide extra information to help in the estimation of precipitation. One method would be to use the differential attenuation measured between the two frequencies of the radar as an indication of the rain rate. Microwave attenuation is widely regarded as a good estimator of the intensity of precipitation. The theory of microwave attenuation is presented, as well as an estimation of the error sources involved in the measurement of attenuation with dual-wavelength radars. Two long-time datasets of disdrometer data are used to test the feasibility of tuning the radar Z - R relationship by measuring the relation between reflectivity and X-band attenuation. As an interesting fact, a surprising proportionality between these two variables is found for higher intensities of precipitation (Z > 40 dBZ). This finding limits the capabilities of dual-wavelength radars to use attenuation as a second parameter, since at higher reflectivities X-band attenuation is almost equivalent to reflectivity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".