Experimental translating downbursts immersed in the atmospheric boundary layer
Bibliographic record
Abstract
Thunderstorm winds are cold descending gravity currents whose impingement on the ground creates strong radial outflows with maximum wind speeds in the near-ground region. They represent one of the greatest hazards for natural and built environment as well as one of the deadliest phenomena all over the world. This study carries on the post-processing analyses of the downburst experimental campaign performed at the WindEEE Dome, at Western University in Canada, in the context of the ERC project THUNDERR. While a former study presented the interaction between downburst and atmospheric boundary layer (ABL) winds, here the focus is on the influence exerted by the thunderstorm cloud translation. This was experimentally replicated at large scale by means of impinging jet technique where the jet axis was inclined to a non-zero angle with respect to the vertical. Finally, the inclusion of background ABL wind allowed to reconstruct the complete three-dimensional and non-stationary nature of the phenomenon. The outflow radial symmetry is lost in case of inclined jet axis. This leads to an intensification of the front-wind side and weakening of the rear-wind side, where the entrainment of the counter-directed ABL wind, and consequent flow speed-up, are not as pronounced as in the vertical-axis case. The non-linearity of the complex interaction between downburst, ABL flow and cloud translation is proven and quantified. Vertical profiles of mean wind speed and turbulence intensity are discussed in relation to the mutual interaction among flow components.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".