Measuring and understanding turbulence in the atmosphere using natural snowfall for flow imaging


In the field of fluid mechanics, a turbulent boundary layer is the region of the fluid near to a surface where the fluid velocity, vortices, and other turbulent features are still affected by the presence of the surface. Perhaps the most ubiquitous example of a turbulent boundary layer is the atmospheric surface layer (ASL) formed by the wind over the earth’s surface. Understanding the behavior of the turbulent air within the ASL is of crucial importance for multiple industries. For instance, turbulence in the ASL determines the inflow conditions and fluctuating wind loading for wind turbines. Also, turbulence affects the exchange of heat and moisture between the earth’s surface and the atmosphere, thereby impacting weather and climate.

The standard technique for measuring turbulence in the atmosphere is to use anemometers mounted to meteorological towers. Anemometer measurements are limited to a time signal at the anemometer locations. In laboratory wind tunnels, studies of turbulent boundary layers can employ imaging techniques such as particle image velocimetry (PIV). PIV can measure the flow velocity in a two-dimensional plane as opposed to a single point, thus allowing the spatial organization of the fluid turbulence to be characterized. However, laboratory PIV findings may not extrapolate to the ASL where the boundary layer thickness and flow Reynolds number are orders of magnitude larger than in laboratory settings.

Recently, researchers from St Anthony Falls Laboratory at the University of Minnesota reported on new super-large-scale PIV (SLPIV) measurements at the field scale in the fully rough ASL. Dr. Jiarong Hong, one of the co-authors on the study, developed the SLPIV technique using natural snowfall during Minnesota winters to track the velocity of the turbulent wind. The new SLPIV measurements were used to investigate how velocity fluctuations are organized spatially in the so-called logarithmic region of the ASL with Reynolds number Reτ O(106). Their work is currently published in the research journal, Journal of Fluid Mechanics.

The authors, through visual and statistical methods, identified hallmark features of boundary layer turbulence in the ASL previously observed using PIV in lower Reynolds number laboratory flows. In particular, they observed instantaneous realizations of forward-inclined vortex structures having the same signature as hairpin vortex packets, as well as uniform momentum zones (UMZs). UMZs are regions of the flow having similar streamwise velocity, and are separated by relatively thin internal shear layers where a large jump in velocity occurs.

The researchers evaluated the zonal structure of the boundary layer by tracking UMZs and the shear interfaces between UMZs in space and time. Further analysis of the internal shear layers and UMZs revealed their dominant contribution to the overall velocity statistics such as the mean and variance. Additionally, through statistical evidence, the vortices were observed to concentrate in the proximity of the internal shear layers interfaces and had the same characteristic size as the interface thickness. In discussing the properties and scaling of the UMZs and internal shear layers, the authors ultimately provided new suggestions for the dynamic roles of these features in wall-bounded flows.

In summary, the study by the University of Minnesota researchers demonstrated new SLPIV measurements using snow particles as tracers in the atmospheric surface layer. The authors showed that SLPIV could provide reliable measurements of first- and second-order velocity statistics in the streamwise and wall-normal directions. Their results in the logarithmic region showed that the structural features identified in laboratory studies were similarly present in the atmosphere, and that uniform momentum zones are a key feature to understanding the spatial organization of high-Reynolds number turbulent flows. Altogether, their findings point out that the spatial structure of wall turbulence in the atmospheric surface layer is consistent with turbulent boundary layers at laboratory-scale Reynolds numbers.

Measuring and understanding turbulence in the atmosphere using natural snowfall for flow imaging - Advances in Engineering
Left: Example SLPIV image using snow in the atmosphere. Right: Example streamwise velocity signal (u) and the tracked interfaces (black lines) separating uniform momentum zones.

About the author

Michael Heisel, the primary author of the referenced work, is a PhD candidate in Civil Engineering at the University of Minnesota. He researches turbulence as it relates to renewable energy applications and flows in the environment. Along with his colleagues, Michael conducted the research at St. Anthony Falls Laboratory, an interdisciplinary fluid dynamics laboratory at the University of Minnesota. The co-authors include researchers from civil, mechanical, and aerospace engineering disciplines.


Michael Heisel, Teja Dasari, Yun Liu, Jiarong Hong, Filippo Coletti, Michele Guala. The spatial structure of the logarithmic region in very-high-Reynolds-number rough wall turbulent boundary layers. Journal of Fluid Mechanics (2018), volume 857, page 704–747.

Go To Journal of Fluid Mechanics

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