Synoptic Typing and Precursors of Heavy Warm-Season Precipitation Events at Montreal, Québec
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A precipitation climatology is compiled for warm-season events at Montreal, Québec, Canada, using 6-h precipitation data. A total of 1663 events are recorded and partitioned into three intensity categories (heavy, moderate, and light), based on percentile ranges. Heavy (top 10%) precipitation events (n = 166) are partitioned into four types, using a unique manual synoptic typing based on the divergence of Q-vector components. Type A is related to cyclones and strong synoptic-scale quasigeostrophic (QG) forcing for ascent, with high-θe air being advected into the Montreal region from the south. Types B and C are dominated by frontogenesis (mesoscale QG forcing for ascent). Specifically, type B events are warm frontal and feature a near-surface temperature inversion, while type C events are cold frontal and associated with the largest-amplitude synoptic-scale precursors of any type. Finally, type D events are associated with little synoptic or mesoscale QG forcing for ascent and, thus, are deemed to be convective events triggered by weak shortwave vorticity maxima moving through a long-wave ridge environment, in the presence of an anomalously warm, humid, and unstable air mass that is conducive to convection. In general, types A and B feature the strongest dynamical forcing for ascent, while types C and D feature the lowest atmospheric stability. Systematic higher precipitation amounts are not preferential to any event type, although a handful of the largest warm-season precipitation events appear to be slow-moving type C (stationary front) cases.
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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 | 0.000 |
| 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) | 0.000 | 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 it