Large-scale dynamical drivers associated with sub-daily extreme rainfall in Europe
Bibliographic record
Abstract
Short-duration (3hr) extreme rainfall events can cause significant socioeconomic and structural damage, alongside loss of life, due to their ability to generate dangerous flash floods, particularly in urban areas and small catchments. With the projected future increase in the frequency and intensity of these events due to global warming, it is imperative to improve our ability to provide warning to communities that may be impacted by these floods. Large-scale atmospheric dynamics play a role in generating the conditions conducive to the development of local-scale sub-daily extremes, but our current understanding of these processes is limited. Additionally, large-scale circulations are inherently more forecastable than small-scale features such as convection, therefore, this project focuses on finding connections between the large-scale dynamics and sub-daily extremes.This study uses the quality-controlled Global Sub-Daily Rainfall dataset to identify past extreme events in western Europe. The atmospheric circulation pattern present on the day of each event is extracted from the UK Met Office’s set of 30 weather patterns (WPs) based on mean sea level pressure. This information is then used to examine the intensity and frequency of extreme events under each WP, leading to analysis of the spatial connections between the WPs and sub-daily extremes.Results indicate just 5 of the 30 WPs account for 53% of recorded 3hr events above the 99.9th percentile in Europe in summer. The important WPs are a mixture of those showing a cyclonic system (cut-off low) close to or over western Europe and those representing a transitional environment. There are also distinct spatial patterns to the relationships in some cases, for example WP11 (isolated low pressure centred over the south-west UK), is associated with very high frequency of extremes over the UK and Portugal but much lower frequencies elsewhere in Europe. The identification of a select group of WPs as important for the generation of sub-daily extremes has implications for forecasting these events at longer lead times, as the large-scale WPs can be predicted further ahead than local conditions.The WP-based analysis is supplemented by investigation of the links between the sub-daily rainfall extremes and synoptic scale Rossby wave patterns. The Local Finite Amplitude Wave Activity (LWA) metric is used to identify regions of anomalous cyclonic or anticyclonic wave activity both prior to and during the extreme events. This analysis indicates anomalous cyclonic wave activity at certain locations, including over Alaska, to the west of the British Isles and over northern Siberia, is significantly correlated with extreme rainfall over Europe. It is also possible to trace the LWA in days leading up to the extreme events, enabling identification of wave patterns that evolve into conditions associated with the extremes.These results offer new evidence on the role of large-scale dynamics associated with sub-daily extreme rainfall, whilst also providing powerful information that could be used in the forecasting of these events.
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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 | 0.000 |
| 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".