Atmospheric turbulence within and above an Amazon forest

Abstract

In this paper, we discuss the impact of a rain forest canopy on the statistical characteristics of atmospheric turbulence. This issue is of particular interest for understanding on how the Amazon terrestrial biosphere interact with the atmosphere. For this, we used a probability density function model of velocity and temperature differences based on Tsallis' non-extensive thermostatistics. We compared theoretical results with experimental data measured in a 66 m micrometeorological tower, during the wet-season campaign of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). Particularly, we investigated how the value of the entropic parameter is affected when one moves into the canopy, or when one passes from day/unstable to night/stable conditions. We show that this new approach provides interesting insights on turbulence in a complex environment such as the Amazon forest.

Application of Superstatistics to Atmospheric Turbulence

“…We show by means of a statistical analysis that we can describe this example of atmospheric turbulence by means of the nonextensive approach adopted in refs. 8,10,11,12,14,15 , within the more general superstatistics formalism introduced in ref. 13 .…”

Multifractal analysis of interplanetary magnetic field obtained during CME events

“…As the inhomogeneity involves the singular behavior of the energy distribution in physical space resulting in strong gradients, or intermittency in the timeseries of the energy related physical quantities of the system, e.g. velocity (Rodrigues Neto et al, 2001;Ramos et al, 2004), temperature (Bolzan et al, 2002) or magnetic fields (Kovács et al, 2001;Lui, 2002), an appropriate characterization of the IMF fluctuations is insured based on the multifractal spectra, τ (q), and singularity spectra, f (α), which quantifies the deviations of the observed singularities α from the expected value and gives a measurement of the intermittency level (Vörös, 2000). The underlying time scales involved in the intermittent level and their different types of τ (q) and f (α) spectra can characterize the fluctuation-driven mechanism, for example, involving coherent structures or intermittent interplanetary magnetic field responses from CME events influence.…”

Multifractal analysis of low-latitude geomagnetic fluctuations

“…Such strong variations constitute the intermittency pattern in the time-series, usually a measurement of the energy related to the physical quantities of the system, e.g. velocity (Ramos et al, 2004), temperature (Bolzan et al, 2002) or magnetic fields (Kovács et al, 2001;Lui, 2002). Thus, an appropriate characterization of the geomagnetic fluctuations is insured based on the so-called singularity spectra, f (α), which quantifies the deviations of the observed singularities α from the expected value and gives a measurement of the intermittency level (Vörös, 2000).…”