| 14 May 2025
CLIMATHUNDERR: Experimental database of buoyancy-driven downbursts
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).
General comments
This manuscript presents an extensive and well-documented experimental database on downburst-like flows generated using buoyancy-driven and mechanically-assisted impinging jets in a large-scale thermal wind tunnel. The CLIMATHUNDERR project addresses an important, relevant and timely topic: the experimental replication of non-stationary thunderstorm downbursts under realistic thermodynamic conditions. The Authors propose a compelling contribution, succeeding in bridging a methodological gap between traditional gravity current and impinging jet techniques by reproducing buoyancy effects at large scales using only air as the working fluid. This work constitutes a notable advancement, and will influence the literature on this topic in the following years.
The experimental campaign is impressively ambitious, being definitely out of the current state-of-the-art. At the same time, the gathered database seems comprehensive. It combines advanced measurement techniques (large-scale PIV, distributed thermocouples), caused by a systematic variation of governing parameters (such as the variation of temperature, piston speed). It also includes the study of the problem on real-world orography. The processed datasets via Zenodo under open-access licensing will significantly enhances the paper’s value for the community.
The manuscript is well-organized, clearly written, and follows a logical structure. The physical modeling choices, instrumentation, and experimental design are well justified.
However, some aspects would benefit from further clarification and elaboration, and I will be pointing them in the following. In fact, clarifying them will help contextualize the scope and limitations of the dataset for future users. In particular, these will concern the scaling of the experiments with respect to real-world phenomena, as well as the uncertainties in the data estimation.
Overall, the manuscript makes a valuable contribution to the wind engineering and atmospheric science communities. It meets the ESSD criteria for scientific quality, transparency, and data reusability. I recommend its acceptance after minor revisions, as outlined below.
Specific Comments
Section 3.3: several quantities withing Eqs. (1) and (2) are not introduced, unless I am mistaken. wB may be immediately introduced as the expected vertical buoyant jet velocities, avoiding detailing that w is the vertical velocity of the jet; concerning z, it is not specified whether it is pointing upwards or downwards, if I am not mistaken. The terms “t” is not introduced, and neither are the nomenclatures “d/dt”, or the partial derivatives. Analogously, also several terms in Eq. (2) are not introduced. Besides, I would like to ask the Authors whether the hypothesis of non-varying reference density value could be verified.
Section 3.3: On the Richardson number, do the Authors think there is a variability in its estimation for full-scale downbursts? They refer to a specific case, but I am wondering whether it could vary across several full-scale records. Besides, I am wondering whether there is variability in the estimation of the Richardson number even in the experiments. Could the Authors provide more details about its variability with the other parameters of the tests ? I think it would make a very interesting point of the discussion.
Eq (5): It seems to me the Authors tried to estimate wIJ based on the flow rate conservation. Could this be instrumental to identify wGC (something that was discussed at Lines 244/245).
Line 274: could the Authors provide details on how they synchronized all the different measurements based on the louvers’ opening ?
Section 3.4.1: Do the simulated experimental phenomena “resemble” any of the full-scale events present in the database of the University of Genoa ? Specifically, the relative position of the orography model is allowing a touchdown point that may recall any full-scale event ? I believe comparison of wind velocity time-histories in specific points (i.e., anemometric stations in Genoa) will be a great point for future studies.
Do the Authors expect any end-effects induced by the boundary of the orography model that may cause some impact on the experimental measurements ? I am thinking how the orography model was installed within the surrounding environment in the laboratory. Was it flushing? I could not understand this piece of information from the manuscript. Perhaps an additional close-up picture would be beneficial.
Section 3,5 and in general: How do the Authors handle measurement uncertainties of the relevant instrumentation ? Which is the impact that the tolerance of the instrumentation may have on the results ? I am thinking, for example, to the different parameters included in Table 2 for the same “nominal” experiment. Could measurement uncertainty be important in this discrepancy? Still on this topic, the Authors note (p. 18–19) that the exact reproduction of experimental conditions (e.g., ∆T, piston speed) was challenging, and that each test is to be considered "unique." While this is understandable, some discussion is needed on how such variability might affect data interpretation, particularly in cross-test comparisons or model training/validation. Are users encouraged to use specific test subsets (e.g., most stable ∆T cases)?
Line 463- 466: as mentioned in the caption, the lines in Figure 9c is not a temperature timeseries, but it is the time-history of the percentage variation estimated from the thermocouples. I think this should be reflected in Line 465, replacing the terms “temperature timeseries” accordingly. This would also allow the Authors to modify the caption of Figure 9, avoiding the part “Temperature is actually the percentage …”.
Still on this Figure, I do not understand where are the surface thermocouples in Fig 9a-9b; could the Authors make them clearer ? Finally, I think that the legend voice “5.50 s” in Figure 9c may be replaced with “5.50 s + 0.5s”.
The paper meets the general principles of open data, but it would benefit from a brief discussion of metadata structure, variable names, and standard formats used. Are NetCDF, CSV, or other structured formats adopted? Is the dataset interoperable with common post-processing tools?
As final general conclusions, also to help with the next perspectives:
It is well-known the significant effects played by the Reynolds number in numerous aspects related to Fluid Mechanics and aerodynamics of bluff-bodies, which affect the design of wind tunnel studies of structures for Wind Engineering purpose. I am wondering if the Authors expect analogous effects in this study concerning thermal aspects because of significant scaling effects studied here (1:2000 scale). I think it would be an interesting aspect to deepen in future studies.
Still related to this aspect: In the introduction, it was mentioned that the models by Xhelaj et al. (2020, 2022, 2024) will be enhanced by incorporating the results from the current experiments to account for the thermal effects on downburst wind evolution. May I ask the Authors to detail how do they plan on doing that, also in light of scaling considerations ? What do they expect ?
Technical comments
Line 246: is the term “wGC=” needed within the parenthesis, or “wB” should suffice ?
Line 259: I think there is a missing “m” after ground level( 0.10 … below the nozzle).
Bibliography
The adopted bibliography is adequate; however, I note the following potential issues:
Some journals are cited with their full name (e.g., Journal of Wind Engineering and Industrial Aerodynamics), others are cited with abbreviations. Concerning the latter, there are some that are cited with a final dot (e.g., Mon. Wea. Rev.) and others without it (e.g., Environ Fluid Mech). I suggest the Authors to be consistent throughout, following ESSD's guidelines.
Canepa et al. (2025) is not in the bibliography; could the Authors add it ?
In the text, it is always mentioned Canepa (2024), but in actuality in the bibliography there are two (a and b); I suggest the Authors to modify the text accordingly.