Wavelet analysis of the wind velocity and temperature variability in the Amazon Forest

Abstract

We studied the turbulent interactions among vertical wind velocity and temperature time-series measured in the Amazonian forest, during the wet season campaign of Large Biophere-Atmosphere Experiment in Amazonia (LBA) in 1999. The approach is based on the estimation of the correlation coefficient between the different scales in turbulent fields and Cross Wavelet Power (XWP). The results suggest that the correlations among scales of the vertical wind velocity are due to the Coherent Structures (CS), a large scale signature in the thermal profile. These coherent structures, kind of ramps, promoted an increase in the interaction among both variables, vertical wind velocity and temperature, and also depends on the atmospheric stability conditions. Furthermore, these coherent structures may explain the higher values of the correlation coefficient found in the large scales during the diurnal period compared with the nocturnal period, for the vertical wind velocity.

Global geomagnetic responses to the IMF <i>B</i><sub>z</sub> fluctuations during the September/October 2003 high-speed stream intervals

“…For more details of the first approach, see Bolzan et al (2009). For the second approach the following must be valid: if X(t) and Y (t) are time series and if W X (a, b), W Y (a, b) are their WT, the XWS analysis (Torrence and Compo, 1998;Bolzan and Vieira, 2006) is given by…”

“…The wavelet function used here was the Morlet function due to their special properties in geophysical time series (Torrence and Compo,1998;Bolzan and Vieira, 2006). The XWS indicates the scales of higher covariance between two time series (X, Y ).…”

“…Another important aspect is due to different wavelet functions which could compromise the identification of temporal variability of each periodicity found. Bolzan et al, 2006 observed that different wavelet functions may cause different behavior on the extraction of the coherent structures (CSs). Indeed, different wavelet functions cause different behavior on the white noise and red noise present in different time series.…”

Scale dependence of coherent structures' contribution to the daytime buoyancy heat flux over the Pantanal wetland, Brazil

“…This is obtained by using wavelet functions that are finite in time, as opposed to the infinite sines and cosines used in the Fourier analysis. This tool has been used in many geophysical studies and it is especially useful in the analysis of the turbulent motions over plant canopies, which are not always periodic and stationary (Farge, 1992;Collineau and Brunet, 1993b;Turner et al, 1994;Terradellas et al, 2001;Krusche and De Oliveira, 2004;Bolzan and Vieira, 2006). In this work, a package of Matlab scripts called Wavelab 2 was used to decompose the time series using orthogonal wavelets.…”

Horizontal and Vertical Turbulent Fluxes Forced by a Gravity Wave Event in the Nocturnal Atmospheric Surface Layer Over the Amazon Forest

“…It is generally used to analyse non-periodic features of geophysical signals (Farge 1992;Sá et al 1998), specially characteristics of the turbulent flow and organised motions (coherent structures) observed in the time series of scalars over vegetated surfaces (Collineau and Brunet 1993a,b;Lu and Fitzjarrald 1994;Katul and Vidakovic 1998;von Randow et al 2002;Thomas and Foken 2005;Bolzan and Vieira 2006). The wavelet decomposition is obtained by calculating the convolution between the discrete time series x n with scaled and translated versions of , a function called the wavelet mother.…”