Detection of turbulent coherent motions in a forest canopy part II: Time-scales and conditional averages
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Turbulent exchanges between plant canopies and the atmosphere are known to be strongly affected by intermittent coherent motions, which appear on time traces of turbulent variables as periodic, large-amplitude excursions from the mean. Detecting these features requires objective and powerful signal analysis techniques. We investigate here the possibilities offered by the recently developedwavelet transform, presented in a companion paper. For this purpose, a set of data acquired in a 13.5 m high pine forest in southwestern France was used, which provided time series of wind velocities and air temperature recorded at two levels simultaneously, under moderately unstable conditions. Firstly, a duration scale of the active part of coherent motions was estimated from the wavelet variance. Then, we focused on the detection itself of large-scale features; several wavelet functions were tested, and the results compared with those obtained from more classical conditional sampling methods such as VITA and WAG. A mean time interval Δ=1.8h/u * (h being the canopy height andu * the friction velocity) between contiguous coherent motions was obtained. The features extracted from the various traces and ensemble-averaged over 30 min periods appeared very similar throughout the four hours of data studied. They provided a dynamic description of the ejection-sweep process, readily observable at both levels. An alternate Reynolds decomposition of the instantaneous turbulent fields, using the conditionally averaged signals, allowed the relative importance of large- and small-scale contributions to momentum and heat fluxes to be estimated. The results were found to be in good agreement with comparable studies.
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- Detection of turbulent coherent motions in a forest canopy part II: Time-scales and conditional averages
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