Synoptic-Scale Characteristics and Precursors of Cool-Season Precipitation Events at St. John’s, Newfoundland, 1979–2005
Bibliographic record
Abstract
Abstract The issue of quantitative precipitation forecasting continues to be a significant challenge in operational forecasting, particularly in regions susceptible to frequent and extreme precipitation events. St. John’s, Newfoundland, Canada, is one location affected frequently by such events, particularly in the cool season (October–April). These events can include flooding rains, paralyzing snowfall, and damaging winds. A precipitation climatology is developed at St. John’s for 1979–2005, based on discrete precipitation events occurring over a time period of up to 48 h. Threshold amounts for three categories of precipitation events (extreme, moderate, and light) are statistically derived and utilized to categorize such events. Anomaly plots of sea level pressure (SLP), 500-hPa height, and precipitable water are produced for up to 3 days prior to the event. Results show that extreme events originate along the Gulf Coast of the United States, with the location of anomaly origin being farther to the north and west for consecutively weaker events, culminating in light events that originate from the upper Midwest of the United States and south-central Canada. In addition, upper-level precursor features are identified up to 3 days prior to the events and are mainly located over the west coast of North America. Finally, results of a wind climatology produced for St. John’s depict a gradual shift in the predominant wind direction (from easterly to southwesterly) of both the 925-hPa geostrophic wind and 10-m observed wind from extreme to light events, inclusively. In addition, extreme events are characterized by almost exclusively easterly winds.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".