112 Characterizing Kelvin-Helmholtz Instabilities and von Kármán Vortices in Canopy Turbulence and Their Interrelationship

Wednesday, 22 June 2016
Alta-Deer Valley (Sheraton Salt Lake City Hotel)
Tirtha Banerjee, Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany; and F. De Roo and M. Mauder

Studying turbulence in vegetation canopies is important in the context of a number of micrometeorological and hydrological applications. While recent focus has shifted more towards exploring different kinds of canopy heterogeneities, there are still gaps in the existing knowledge on the multiple types of dynamics involved in the case of horizontally homogeneous canopies. For example, experimental studies have indicated that turbulence in the canopy sublayer (CSL) can be divided into three regimes. In the deep-zone, the flow-field is dominated by von Kármán vortex streets and interrupted by strong sweep events. The second zone near the canopy top is dominated by attached eddies and Kelvin-Helmholtz waves associated with the velocity inflection point in the mean longitudinal velocity profile. Above the canopy, the flow resembles classical boundary layer flow. In this study, these different kinds of dynamics are studied together by means of a large eddy simulation (LES). Two major questions are attempted to be answered: (1) since the Kelvin-Helmholtz waves and the von Kármán vortices are contained in two mutually perpendicular planes, how are these two motions related and what are their effect on momentum and energy flux? (2) With how much fidelity can one resolve these two motions in an LES since the canopy is parameterized by a distributed drag and leaf area density (LAD) instead of placing real solid obstacles? Different flow visualization methods are used to extract the coherent structures associated with the two motions. Spectra, co-spectra and correlations in time and space are also used to study the corresponding interrelationships. It can be stated that a better understanding of the rich dynamics associated with the simplest case of canopy turbulence can lead to more efficient simulations and more importantly improve the interpretation of more complex scenarios.
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