Assessment of Near 0 °C Temperature and Precipitation Characteristicsacross Canada
Bibliographic record
Abstract
Abstract. The 0 °C temperature threshold is critical to many meteorological and hydrological processes driven by melting and freezing in the atmosphere, surface and sub-surface and by the associated precipitation varying between rain, freezing rain, wet snow and snow. This threshold, linked with freeze-thaw, is especially important in cold regions such as Canada. This study develops a Canada-wide perspective on near 0 °C conditions with a particular focus on the occurrence of its associated precipitation. Since this analysis requires hourly values of surface temperature and precipitation type observations, it was limited to 92 stations over the 1981–2011 period. In addition, nine stations representative of various climatic regions are selected for further analysis. Near 0 °C conditions are defined as periods when the surface temperature is between −2 °C and 2 °C. Near 0 °C conditions occur often across all regions of the country although the annual number of days and hours and the duration of these events varies dramatically. Various forms of precipitation (including rain, freezing rain, wet snow and ice pellets) are sometimes linked with these temperatures with highest fractions tending to occur in Atlantic Canada. Trends of most temperature-based and precipitation-based indicators show little or no change despite a systematic warming in annual temperatures. Over the annual cycle, near 0 °C temperatures and precipitation often exhibit a pattern with short durations near summer driven by the diurnal cycle, while longer durations tend to occur more towards winter associated with storms. There is also a tendency for near 0 °C temperatures to occur more often than expected relative to other temperature windows; due at least in part to diabatic cooling and heating occurring with melting and freezing, respectively, in the atmosphere and at the surface.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".