Solid Precipitation and Visibility Measurements at the Centre for Atmospheric Research Experiments in Southern Ontario and Bratt’s Lake in Southern Saskatchewan
Bibliographic record
Abstract
Accurate measurement of solid precipitation (S) has a critical importance for proper understanding of the Earth’s hydrological cycle, validation of emerging technologies and weather prediction models, and developing parameterizations of severe weather elements such as visibility (Vis). However, measuring S is still a challenging problem, due mainly to wind effects. The wind effects are normally mitigated by using a Double-Fence Automated Reference (DFAR) system to reduce the wind speed (Ug). To contribute towards addressing some of these problems, we have analyzed datasets collected at two sites, Center for Atmospheric Research Experiments (CARE) and Bratt’s Lake, located in southern Ontario and southern Saskatchewan, Canada, respectively, using several instruments. The instruments at CARE include two Geonor gauges, one placed inside a DFAR (SDFAR) and the other inside a double Alter shield (DASG), a Pluvio2 gauge inside a single Alter shield (SASP), a HotPlate, a PARSIVEL2 disdrometer that measures S and fall velocity (V), and an FD12P senor that measures S and type and Vis. The instruments deployed in Bratt’s Lake includes a similar DFAR system and DAS Pluvio2 gauge. The results show that for the Ug observed in this study (Ug < 6 ms−1), both DASG and SASP have similar collection efficiency (CE) of near 70%. The transfer functions (TF) for DASG and SASP as a function of Ug and also Ug, and V were derived. The TF developed for the DASG that includes both Ug and V showed better agreement with observation than just Ug alone. The TF developed for DASG at CARE site was tested using the data collected in Bratt’s Lake and correlated well (R = 0.86), but slightly overestimated the S accumulation by about 12%. The S measured at CARE site using all the other instruments were correlated well with SDFAR (R = 0.9), but the PARSIVEL2 and FD12P overestimated and underestimated the snow amount, respectively, as compared the SDFAR. However, the HotPlate captured similar amount of S as the SDFAR. According to this study, the SDFAR showed good correlation with Vis.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".