Statistics on Low-Lying Liquid and Liquid-Dominant Mixed-Phase Clouds over Ottawa
Bibliographic record
Abstract
The Communications Research Centre Canada (CRC) in Ottawa employs a multifrequency profiling radiometer to model the impact of clouds and water vapour on Earth-Space links. The profiling radiometer can retrieve vertical profiles of temperature, humidity and cloud liquid water every 30 seconds or every minute from the surface up to 10 km in height under clear sky and cloudy conditions. It is also capable of assessing the columnar cloud liquid water content (also known as the liquid water path L) and the water vapour path continuously, unlike what can be achieved with conventional radiosondes. The profiler also features an infrared thermometer that detects the cloud base temperature: the cloud base height of the lowest layer can thus be estimated using the contemporaneous temperature profile. Statistics on liquid water path, cloud base height and cloud top height for non-precipitating liquid-phase and mixed-phase stratus and stratocumulus clouds observed over CRC between April 2005 and April 2006 during the daytime are presented in this paper. According to the land cloud climatology of Hahn and Warren [1], these clouds are one of the most frequently occurring liquid-bearing types over a 5-degree by 5-degree box that includes the Ottawa area. Cloud top height has been assessed using CRC's cloud detection algorithm [2]. It is based on the Chernykh and Eskridge (CE) method that was originally designed to detect cloud layers and amounts from radiosonde profiles [3]. Our algorithm uses the CE method with retrieved vertical profiles of temperature and relative humidity, but also data not measured by radiosondes: the cloud base height estimated by the infrared thermometer, and the retrieved L. This extra set of conditions can be summarized as follows: a cloud contains liquid water whenever L exceeds a certain threshold value computed for each profile [2] and its cloud base height is lower than some maximum value (found to be 6 km in [2]). This cloud detection algorithm has been shown to significantly reduce the number of false positives compared to the application of the original CE method [2]. Daytime seasonal and annual averages will be compared, whenever possible, to the 6-year climatology of midlatitude low-level continental clouds from the United States ARM Southern Great Plains (SGP) Central Facility, Oklahoma, reported in [4]. To the best of the authors' knowledge, this 6-year cloud climatology is the only one available in the literature.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".