Estudo da variabilidade da energia cinética turbulenta acima da Floresta Amazônica com base em análises não lineares de séries temporais

Abstract

The Nocturnal Boundary Layer (NBL) emerges during the night when the Earth’s surface cools and interacts with the atmosphere above it. The dynamics and complexity of turbulent processes in this region play a crucial role in understand ing large-scale climatic and meteorological phenomena. Understanding the turbulent regimes in the NBL is essential to improve our comprehension of atmospheric interac tions and their implications, as well as the limitations of measuring fluxes through the eddy covariance method. The aim of this study was to identify patterns within these regimes using two nonlinear methods: Chaos Theory and Recurrence Plot (RP). In this study, analyses of micrometeorological time series collected during the GoAmazon 2014/15 campaign were conducted, based on the HOST theory, which classified atmo spheric turbulence into three regimes. A total of 18 time series were studied, with 6 series for each variable: velocity (V), Turbulent Kinetic Energy (TKE), and Tv (Virtual Temperature). For the variable V, the obtained results revealed attractor dimensions in the three turbulent regimes: in regime 2, with higher turbulence intensity, attractors with dimensions D2=4.36 and D2=3.71 were observed; in regime 3, with intermedi ate turbulence intensity, values of D2=3.20 and D2=3.31 were found; and in regime 1, dimensions of D2=3.20 and D2=3.02 were identified. These findings suggest the presence of low-dimensional attractors in all three turbulent regimes, whose values apparently correlate with the intensity of wind speed. The same pattern was observed for the Tv variable, indicating that the intensity of V and Tv is directly related to a higher fractal dimension of the attractor. This relationship, along with the analysis of autocorrelation function, suggests the occurrence of a gust event during the analyzed period. The non-stationarity of the analyzed time series was captured by the RPs, which showed variability around the line of instability (LOI). The results suggest greater stability in the time series of V when compared to the Tv variable. Turbulent regime 1, characterized by lower V values and higher Tv values, exhibited greater complexity in their RPs, leading to higher entropy values. This corresponds with the theory of turbulence, as the suppression of vertical mixing and turbulence dissipation results in more complex flow patterns near the surface.