Detection of turbulent coherent motions in a forest canopy part II: Time-scales and conditional averages

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.