Measurements of Differential Reflectivity in Snowstorms and Warm Season Stratiform Systems
Bibliographic record
Abstract
Abstract The organized behavior of differential radar reflectivity (ZDR) is documented in the cold regions of a wide variety of stratiform precipitation types occurring in both winter and summer. The radar targets and attendant cloud microphysical conditions are interpreted within the context of measurements of ice crystal types in laboratory diffusion chambers in which humidity and temperature are both stringently controlled. The overriding operational interest here is in the identification of regions prone to icing hazards with long horizontal paths. Two predominant regimes are identified: category A, which is typified by moderate reflectivity (from 10 to 30 dB Z ) and modest +ZDR values (from 0 to +3 dB) in which both supercooled water and dendritic ice crystals (and oriented aggregates of ice crystals) are present at a mean temperature of −13°C, and category B, which is typified by small reflectivity (from −10 to +10 dB Z ) and the largest +ZDR values (from +3 to +7 dB), in which supercooled water is dilute or absent and both flat-plate and dendritic crystals are likely. The predominant positive values for ZDR in many case studies suggest that the role of an electric field on ice particle orientation is small in comparison with gravity. The absence of robust +ZDR signatures in the trailing stratiform regions of vigorous summer squall lines may be due both to the infusion of noncrystalline ice particles (i.e., graupel and rimed aggregates) from the leading deep convection and to the effects of the stronger electric fields expected in these situations. These polarimetric measurements and their interpretations underscore the need for the accurate calibration of ZDR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".