Microwave and submillimeter wave scattering of oriented ice particles
Bibliographic record
Abstract
Abstract. Microwave dual-polarization measurements above 100 GHz are so far sparse, but they consistently show that larger ice hydrometeors tend to deviate from the standard assumption of total random orientation. This conclusion has been derived by conceptual models, while the first detailed simulations, recreating the observed polarization patterns, are presented in this study. The ice particles are assumed to be azimuthally randomly oriented with a fixed but arbitrary tilt angle. The scattering data for azimuthal random orientation is much more complex than for total random orientation. The scattering data of azimuthally randomly oriented particles depends in general on the incidence angle and two scattering angles compared to one angle scattering for total random orientation. The additional tilt angle adds an additional dimension. The simulations are based on the discrete dipol approximation in combination with a self developed orientation averaging approach. Data for two particle habits (51 hexagonal plates and 18 plate aggregates) and 35 frequencies between 1 GHz and 864 GHz were produced. The data is publicly available from Zenodo (https://doi.org/10.5281/zenodo.3463003). This effort is also an essential part of preparing for the upcoming Ice Cloud Imager (ICI), that will perform polarized observations at 243 GHz and 664 GHz, which will deliver new insights about clouds.
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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 | 0.000 | 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) | 0.002 | 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".