CLIMATHUNDERR: Experimental database of buoyancy-driven downbursts
Bibliographic record
Abstract
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).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".