CLIMATHUNDERR: Experimental database of buoyancy-driven downbursts
Notice bibliographique
Résumé
Abstract. Thunderstorm downbursts are windstorms due to intense negatively-buoyant flows produced beneath cumulonimbus clouds. Their study has recently attracted significant scientific and media attention due to the current and projected impacts of climate change. During their vertical descent phase (i.e., the downdraft), followed by a horizontal outflow, downbursts can cause severe damage to both natural ecosystems and built environments. Warm, humid air is lifted upward through natural or forced convective mechanisms, where it condenses into a cumulonimbus cloud. Inside the cloud, the air parcels – now colder and denser than the surrounding environment – sink due to buoyancy. Thermal and dynamic instabilities between the cold air jet and the environment generate a symmetrical vortex, known as the primary vortex (PV), which drives both the downdraft and the subsequent horizontal outflow at the surface. This vortex flow structure can have devastating effects on the ground. Building on these insights, a series of experiments was recently conducted as part of the CLIMATHUNDERR project – CLIMAtic Investigation of THUNDERstorm Winds – funded by the European Union through the European Research Infrastructures for European Synergies (ERIES) project. For the first time, the buoyancy effects that drive downdraft winds to the surface were reproduced at large fluid-dynamics geometric scales at the Jules Verne Climatic Wind Tunnel – Thermal Unit SC2 at the Centre Scientifique et Technique du Bâtiment (CSTB) in Nantes, France. This experimental campaign aimed to further explore thunderstorm wind phenomena, building on earlier research studies conducted at the WindEEE Dome in Canada under the European Research Council (ERC) Advanced Grant project THUNDERR. CLIMATHUNDERR extends this previous research by emphasizing thermal effects, which are key drivers in these wind events. In the experiments, downbursts were recreated using an upper plenum that simulates the thunderstorm cloud, innovatively combining two widely applied techniques: impinging jet and gravity current. Thermal effects were reproduced by controlling the temperature differential between the upper plenum and the air in the testing chamber. A mechanical piston controlled the outgoing flow velocity at the nozzle exit, simulating the contribution of a simple mechanical impinging jet. Benchmark experiments were performed with only the mechanical impinging jet, allowing the quantification of thermal effects at the interface between the jet and the calm surrounding air. The experimentally generated downburst-like flows were then tested against a scaled orography model of the Polcevera Valley in Genoa, Italy, to examine how it influences the dynamics and structure of the downburst vortices. Velocity measurements were performed using Particle Image Velocimetry (PIV), enabling a detailed reconstruction of the 2D vector flow field without the limitations of traditional anemometric instruments like multi-hole pressure probes, which struggle with low-velocity (i.e., < 2 m s-1) and reversal flows. Additionally, temperature profiles before and during downburst occurrence were measured with thermocouples distributed across the flow field. This project draws on a multi-disciplinary team of experts in thunderstorm phenomena, facilitating a comprehensive analysis of the collected data from various perspectives, including data interpretation, atmospheric and meteorological insights, numerical simulations, and analytical methods. The experimental data are openly available to the scientific community via the Zenodo repository at (Canepa et al., 2025).
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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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,003 |
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 ».