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Title: Signals of Non-Turbulent Motions Caused by Stable Stratification in Near-Surface Sonic-Anemometer Data
Understanding the interactions between turbulent and non-turbulent motions has been a persistent challenge faced by the community studying stably stratified turbulent flows. For flows with high Reynolds number, high Rossby number, and stable stratifications, non-turbulent motions share a common characteristic to involve physical mechanisms acting against instability development. Because turbulence is generated through energy cascade via instability development, the presence of non-turbulent motions is expected to modify the energy distribution across scales compared to that of solely turbulent motions. The objective of this work is to identify statistical signals of non-turbulent motions caused by stable stratification. The need to resolve energy-containing motions in both space and time requires high-frequency time series of velocity fluctuations collected using arrays of sonic anemometers. The analysis is performed using data from the Canopy Horizontal Array Turbulence Study (CHATS), during which a total of 31 sonic anemometers were deployed on a horizontal array and on a 30-m tower. Compared to other field campaigns which were also equipped with arrays of sonic anemometers, CHATS took an important advantage of already published nighttime canopy-scale waves derived from aerosol backscatter lidar images. After precluding complexities caused by nonstationarity and horizontal heterogeneity, signals of non-turbulent motions caused by stable stratification are identified from spatial autocorrelations of time-block-averaged velocity fluctuations. These signals agree with existing understanding of turbulent canopy flows and two-dimensional Kelvin-Helmholtz instability development, which predicts a critical wavelength at which motions shift from free instability growth to internal gravity waves. The estimates of critical wavelengths and buoyancy periods agree well with the overall properties of nighttime canopy-scale waves derived from lidar images.  more » « less
Award ID(s):
2113854
PAR ID:
10654907
Author(s) / Creator(s):
; ;
Publisher / Repository:
Penn State Data Commons
Date Published:
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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