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Experiments in Fluids

, 55:1737 | Cite as

Measurement of atmospheric boundary layer based on super-large-scale particle image velocimetry using natural snowfall

  • M. Toloui
  • S. Riley
  • J. Hong
  • K. Howard
  • L. P. Chamorro
  • M. Guala
  • J. Tucker
Research Article

Abstract

We present an implementation of super-large-scale particle image velocimetry (SLPIV) to characterize spatially the turbulent atmospheric boundary layer using natural snowfall as flow tracers. The SLPIV technique achieves a measurement area of ~22 m × 52 m, up to 56 m above the ground, with a spatial resolution of ~0.34 m. The traceability of snow particles is estimated based on their settling velocity obtained from the wall-normal component of SLPIV velocity measurements. The results are validated using coincident measurements from sonic anemometers on a meteorological tower situated in close proximity to the SLPIV sampling area. A contrast of the mean velocity and the streamwise Reynolds stress component obtained from the two techniques shows less than 3 and 12 % difference, respectively. Additionally, the turbulent energy spectra measured by SLPIV show a similar inertial subrange and trends when compared to those measured by the sonic anemometers.

Keywords

Particle Image Velocimetry Atmospheric Boundary Layer Settling Velocity Light Sheet Particle Image Velocimetry Measurement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by US Department of Energy (grant No: DE–EE0002980) and the resources provided by the University of Minnesota College of Science and Engineering, Department of Mechanical Engineering and St. Anthony Falls Laboratory as part of the start-up package of Jiarong Hong.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • M. Toloui
    • 1
    • 2
  • S. Riley
    • 1
    • 2
  • J. Hong
    • 1
    • 2
  • K. Howard
    • 1
    • 3
  • L. P. Chamorro
    • 1
    • 4
  • M. Guala
    • 1
    • 3
  • J. Tucker
    • 1
  1. 1.Saint Anthony Falls LaboratoryMinneapolisUSA
  2. 2.Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisUSA
  3. 3.Department of Civil EngineeringUniversity of MinnesotaMinneapolisUSA
  4. 4.Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA

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