Atmospheric precursors for intense summer rainfall over the United Kingdom
Bibliographic record
Abstract
Abstract Intense sub‐daily summer rainfall is linked to flooding impacts in the United Kingdom. Characterizing the atmospheric conditions prior to the rainfall event can improve understanding of the large‐scale mechanisms involved. The most intense sub‐daily rainfall intensity data generated from rain gauge records across the United Kingdom over the period 1979–2014 are combined with fields from the ERA Interim reanalysis to characterize atmospheric conditions prior to heavy rainfall events. The 200 most intense 3‐hourly events for six UK regions are associated with negative anomalies in sea level pressure (<−2 hPa) and 200 hPa geopotential height (<−60 m) to the west or south west of the United Kingdom 1 day earlier, with above average moisture, evaporation and dew point temperature over North West Europe. Atmospheric precursors are more intense but less coherent between regions for composites formed of the 25 heaviest rainfall events but all display substantial moisture transport from the south or south east prior to their occurrence. Composites for the heaviest events are characterized by a tripole geopotential anomaly pattern across the North Atlantic. Above average geopotential height and dew point temperature over Newfoundland and below average geopotential height but elevated evaporation in the North Atlantic are found to be weakly associated with an increased chance of the most intense sub‐daily rainfall events 5–9 days later.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".