Diferentes técnicas de condicionamento em séries temporais turbulentas

• Autor(a) principal: Zimermann, Hans Rogério
• Data de Publicação: 2005
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/0013000007x1d
• Texto Completo: http://repositorio.ufsm.br/handle/1/9211
• topic: Covariância dos vórtices; Turbulência; Micrometeorologia; Filtros digitais; Eddy covariance; Turbulence; Micrometeorology; Digital filtering; CNPQ::CIENCIAS EXATAS E DA TERRA::FISICA

The dynamics process of the atmosphere near Earth ground is controled by two main forcings, termical and machanics. These process are reponsible for the atmospheric flow variability in this layer, and this variability characterizes the atmospheric turbulence. The presence of turbulence phenomena drives to distinguish it from the rest of atmosphere, such layer is commom called Atmospheric Boundary Layer (ABL). So, the importance of studying ABL is the fact of that turbulence represents an effective transport process near the ground surface. Adequate treating of the experimental data gives more truthful so qualitative as quantitavie when we are interpreting and understading these transports. This is very impportant for suitable trustful charaterizing the turbulent fluxes. This dissertation shows an overview about some basics turbulent data treatment techics. The dataset, colected experimentaly and separed into 27 minutes window samples, were subjected to simple mean, running mean through digital recursive filter e and linear detrending. Our focus are the implications of applying this technics and how each of this acts in turbulent time series of temperature and vertical velocity of the wind data, showing and discussing about the results in the estimating fluxes of sensible heat by Eddy Covariance method and also spectral densities estimates of temperature and vertical wind velocity. The main goal of the study done in this dissertation, was identifying that applying corrections on fase lag, not considered in older digital recursive filter (FDR as proposed by McMillen 1988) and, present into the model (FFDR proposed by Franceschi e Zardi 2003) leads for trusties estimatives, mainly for turbulent temperature spectra, which are the hardest ones for minimizing the non statinarity effects. Clearly, observing the graphical results of temperature spectra, we see that those low frequencies were better removed than the others technics, giving to spectral shape the classics espected shape.