Estabilidade na camada limite atmosférica e intermitência nas pequenas escalas

Abstract

Although the understanding of turbulence is essential in many areas of science and technology, yet very little is known about its structure and its phenomenology. Since the first statistical models of decades of forty and sixty of the last century, few were really important contributions made to help qualitatively and quantitatively describe this phenomenon. The great complexity of turbulence is attributed to a characteristic phenomenon called intermittency, which is considered a "signature"of the turbulence and is associated with the variance of the rate of dissipation of energy distribution in different scales. The statistical parameter associated with this phenomenon is called the intermittency exponent (μ). The intermittency on small scales has been the main object of searches in turbulence over the past 46 years, so much effort has been applied in determining the parameter μ. The direct determination of the intermittency exponent with the use of experimental data is made by calculating the correlation of turbulent energy kinetic dissipation field (h(2(x + r)2(x)i ∼ r −μ ). Another method less accurate but also very popular, used to estimate indirectly μ is through the sixth order structure function (hu((x + r) − u(r)) 6 i ∼ r 2−μ ). However, to ensure a convergence statistics, these methods require long time series of high frequency and high quality provided by the hot wire anemometer, which require frequent calibrations. This type of anemometer are used mainly in the wind tunnel, where the experimental conditions are well controlled. Due to great the Atmospheric Boundary Layer (ABL) variations throughout the day, sonic anemometer are widely used in field experiments because they require much less frequently calibrations. However, the low sampling rate (∼ 10 a 30Hz) of sonic anemometer, plus the experimental difficulties results in a coarse and low resolution data series. In general, for a reliable direct estimation μ are needed tens of millions of points, which would require, in experiments in the CLA, a stationary signal of approximately 11 days (virtually impossible to acurr). Due to these implications, ( BASU; FOUFOULA-GEORGIOU; LASHERMES; ARNÉODO , 2007) proposed an alternative method for estimating the intermittency exponent for short and low frequency series using the Magnitude Cumulant Analysis together with the Surrogate Analysis. This methodology has been applied to ABL turbulent time series, which allowed us to estimate with good precision the intermittency exponent for these data. The results obtained through of the Magnitude Cumulantes Analysis are as precise as the values of μ estimated directly with wind tunnel data and ABL more elaborate experiments. The great importance to obtaining this exponent (μ) is that through of their behavior analysis in the presence of different conditions of atmospheric stability, was able to verify that the inertial range is affected by the large scale events, in this case, by different forcing generators of turbulence, contrary to classical idea where the inertial range is not influenced by large eddies anisotropy.