Data from a flume experiment of passive scalar diffusion within vegetation canopies using laser-induced fluorescence

Ghannam, Khaled; Poggi, Davide; Katul, Gabriel; Bou-Zeid, Elie
Issue date: 22 April 2020
Cite as:
Ghannam, Khaled, Poggi, Davide, Katul, Gabriel, & Bou-Zeid, Elie. (2020). Data from a flume experiment of passive scalar diffusion within vegetation canopies using laser-induced fluorescence [Data set]. Princeton University. https://doi.org/10.34770/7hyr-rf67
@electronic{ghannam_khaled_2020,
  author      = {Ghannam, Khaled and
                Poggi, Davide and
                Katul, Gabriel and
                Bou-Zeid, Elie},
  title       = {{Data from a flume experiment of passive
                scalar diffusion within vegetation canop
                ies using laser-induced fluorescence}},
  publisher   = {{Princeton University}},
  year        = 2020,
  url         = {https://doi.org/10.34770/7hyr-rf67}
}
Abstract:

This dataset is a sequence of laser-induced fluorescence images of a dye injected in a channel flow with canopy-like stainless steel rods simulating a vegetation canopy stand. The data is acquired close to the channel bottom at z/h=0.2, where z is the height referenced to the channel bed and h is the canopy height. The dataset provides spatial distribution of scalar concentration in a plane parallel to the channel bed. The data has been used (but the data itself has not been published or available to the public) in previous work. The references are: Ghannam, K., Poggi, D., Porporato, A., & Katul, G. (2015). The spatio-temporal statistical structure and ergodic behaviour of scalar turbulence within a rod canopy. Boundary-Layer Meteorology,157(3), 447–460. Ghannam, K, Poggi, D., Bou-Zeid, E., Katul, G. (2020). Inverse cascade evidenced by information entropy of passive scalars in submerged canopy flows. Geophysical Research Letters (accepted).

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Description:

The attached readme.txt file explains the data attributes

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# Filename Description Filesize
1 readme.txt 1.3 KB
2 Concentration.tar 358 MB