Moisture Analysis of a Type I Cloud-Topped Boundary Layer from Doppler Radar and Rawinsonde Observations
Bibliographic record
Abstract
Moisture data from radar and rawinsonde observations during three lake-effect snow events are analyzed to determine entrainment rates. Type I convective boundary layers, which are those driven largely by surface heating, typically accompany these storms. Gathered during the winter of 1990, the data are a subset from the Lake Ontario Winter Storms (LOWS) Project, which deployed a mesoscale network of sensors. Doppler wind profiler signal-to-noise ratio (SNR) data are used to derive humidity structure function parameter (C2q) time–height series analysis, which are then compared to rawinsonde specific humidity (q) plots. Visual comparison of log(C2q) and q analysis indicated a strongly positive correlation. Radar-derived humidity analysis is used to estimate the depth of the Type I (driven by surface heating), cloud-topped boundary layer (CTBL), which corresponded well with results from LOWS rawinsonde data. Calculations of the contribution of (C2q) to the refractive index structure parameter (C2n) showed the humidity correction factor (α2r) to range from 1.02 to 1.04 within the CTBL, consistent with previous findings for Type II CTBLs. A comparison of entrainment rates, computed via two different methods, were in agreement.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".