Large-scale dynamical drivers associated with sub-daily extreme rainfall in Europe
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».