Significant summer rainfall in the Canadian Prairie Provinces: modes and mechanisms 2000–2004
Bibliographic record
Abstract
Abstract This study analysed nearly 1000 significant (≥10 mm in 24 h) summer rain events that occurred within the boundaries of the Canadian Prairie Provinces from 2000 to 2004. The objective of this examination was to identify the mode of each event (i.e. solely or partially convective versus non‐convective), and its primary forcing mechanism (i.e. source of lift). Daily rainfall and lightning maps revealed that most of the significant rain events (79%) were solely or partially convective (i.e. lightning was recorded during the event), while 88% of the total rain area, a measure of the impact of each event, was from events with moist deep convection. Average monthly percentages varied. In June, 74% of the events were solely or partially convective, in July 85%, and in August 79%. In June, 84% of the rain area was from events that were solely or partially convective, in July 93%, and in August 86%. For significant rain events with convection, the most frequent forcing mechanisms were meso‐scale processes (28%), surface low‐pressure centres (16%), surface troughs (14%), and warm and cold fronts (both 14%). While meso‐scale forcing mechanisms were responsible for 28% of the significant rain events with convection, they generated just 11% of the rain area with convection. Surface low‐pressure centres, responsible for just 16% of the events with convection, produced 25% of the rain area with convection. The most frequent forcing mechanisms for significant rain events without convection were surface low‐pressure centres (25%), surface troughs (22%), cold fronts (19%), and cold lows (12%). The portion of the significant rain area without convection attributed to each of the synoptic forcing mechanisms was generally consistent with its relative frequency of occurrence. Copyright © 2008 Royal Meteorological Society
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".