CLIMATHUNDERR: A Combined Impinging Jet and Gravity Current Technique to Investigate Thermal Effects on Downburst Winds
Bibliographic record
Abstract
Abstract A comprehensive experimental campaign was conducted as part of the ERIES-CLIMATHUNDERR project (CLIMAtic Investigation of THUNDERstorm Winds) at the Jules Verne Climatic Wind Tunnel, CSTB, Nantes, France. The study aimed to investigate the thermal effects driving downdraft winds from thunderstorm clouds and their influence on downburst outflow dynamics near the ground. Downbursts are typically simulated using two methods: (i) the gravity current (GC), which models jet formation through density instability between two fluids, and (ii) the impinging jet (IJ), which generates the downdraft mechanically using wind tunnel fans. While the IJ method is preferred in wind engineering for its scalability, it lacks the thermodynamic contributions intrinsic to GC-based simulations. For the first time, the CLIMATHUNDERR project combines these two techniques at large scale, leveraging varied temperature differentials between the jet and its surroundings to analyze the dynamic and geometric evolution of downburst outflows and associated vortex structures, particularly the leading primary vortex (PV). The experiments also include testing these reproduced flows over a scaled topographic model of the Polcevera Valley in Genoa, Italy, to assess real-world applications. Evolving flow and temperature fields are captured using state-of-the-art measurement techniques, including Large-Scale Particle Image Velocimetry (LS-PIV) and high-response thermocouples.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".