Diferentes técnicas de condicionamento em séries temporais turbulentas

Detalhes bibliográficos
Autor(a) principal: Zimermann, Hans Rogério
Data de Publicação: 2005
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional Manancial UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/9211
Resumo: 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.
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spelling 2017-05-082017-05-082005-12-09ZIMERMANN, Hans Rogério. Diferentes técnicas de condicionamento em séries temporais turbulentas. 2005. 86 f. Dissertação (Mestrado em Física) - Universidade Federal de Santa Maria, Santa Maria, 2005.http://repositorio.ufsm.br/handle/1/9211The 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.A dinâmica da atmosfera próxima á superfície é regida por dois forçantes principais, um mecânico e outro térmico. Esses processos são responsáveis pela variabilidade dos escoamentos na baixa atmosfera e, é essa variabilidade que caracteriza a turbulência atmosférica. A presença do fenômeno de turbulência, permite distinguir uma camada do restante da atmosfera, esta é chamada de Camada Limite Atmosférica ( CLA). A importância de estudos nessa camada, está relacionada com o fato da turbulência representar um processo efetivo de transporte próximo à superfície. O tratamento adequado dos dados experimentais permite maior contabilidade, tanto qualitativa quanto quantitativas, na interpretação e entendimento desse transporte, ou seja, é necessário para uma adequada caracterização dos fluxos turbulentos. Nesta dissertação são investigadas algumas, das principais técnicas básicas, no tratamento de dados e condicionamento em séries temporais turbulentas. Os dados, experimentalmente coletados e separados em conjuntos de amostras com 27 minutos, são submetidos aos tratamentos com técnicas de média simples, média instantânea através de filtros digitais recursivos e remoção linear de tendência. Obeserva-se as implicações da aplicação destas técnicas, como cada uma delas age nas séries temporais turbulentas de temperatura e velocidade vertical do vento, apresentando e discutindo os resultados dessa aplicação, nas estimativas dos fluxos turbulentos de calor sensível através do método de Covariância dos Vórtices (MCV), e também das densidades espectrais de temperatura e velocidade vertical. Um dos grandes benefícios do estudo feito nessa dissertação, foi identificar que a correção do atraso de fase, que não era levada em consideração nos modelos de filtros digitais anteriores (FDR proposto por McMillen 1988) e, presente no modelo (FFDR Franceschi e Zardi 2003) conduz à estimativas satisfatórias, principalmente para espectros de temperatura turbulenta, que são os mais difíceis de se minimizar os efeitos de não estacionariedade. Ficou claro, observando nos resultados gráficos dos espectros, que a remoção de baixas freqüências nos espectros de temperatura, os deixou com o perfil típico de especros clássicamente esperados.Conselho Nacional de Desenvolvimento Científico e Tecnológicoapplication/pdfporUniversidade Federal de Santa MariaPrograma de Pós-Graduação em FísicaUFSMBRFísicaCovariância dos vórticesTurbulênciaMicrometeorologiaFiltros digitaisEddy covarianceTurbulenceMicrometeorologyDigital filteringCNPQ::CIENCIAS EXATAS E DA TERRA::FISICADiferentes técnicas de condicionamento em séries temporais turbulentasinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisMoraes, Osvaldo Luiz Leal dehttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4783106P7Goulart, Antonio Gledson de Oliveirahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4791371J5Acevedo, Otávio Costahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4796988J8http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4737776H0Zimermann, Hans Rogério100500000006400500500300500890f38b3-51f1-4071-8146-2205917ead15abded063-6692-4606-a204-f8905959dfc2d5d80d78-cf02-4c2c-9eaa-c869a704edacea185db5-1bdf-4651-9915-96f8102d7ee0info:eu-repo/semantics/openAccessreponame:Repositório Institucional Manancial UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALhans 1.pdfapplication/pdf1135781http://repositorio.ufsm.br/bitstream/1/9211/1/hans%201.pdfde49a5a1cc18613d781da136cdedde92MD51hans 2.pdfhans 2.pdfapplication/pdf2087825http://repositorio.ufsm.br/bitstream/1/9211/4/hans%202.pdf289d9952a4fee51b2f57b0f4770dfd89MD54hans 3.pdfhans 3.pdfapplication/pdf2092589http://repositorio.ufsm.br/bitstream/1/9211/5/hans%203.pdf2c8c9c9821bb18d23bc0bb5b1e276944MD55hans 4.pdfhans 4.pdfapplication/pdf1663813http://repositorio.ufsm.br/bitstream/1/9211/6/hans%204.pdf2a6d78d6e49e05e09231f3ceacab0d97MD56TEXThans 1.pdf.txthans 1.pdf.txtExtracted texttext/plain75560http://repositorio.ufsm.br/bitstream/1/9211/2/hans%201.pdf.txtb6470551224d1183370546a6266e702aMD52hans 2.pdf.txthans 2.pdf.txtExtracted texttext/plain2533http://repositorio.ufsm.br/bitstream/1/9211/7/hans%202.pdf.txt3bcf745f505a63460f623535ce9ef40cMD57hans 3.pdf.txthans 3.pdf.txtExtracted texttext/plain13410http://repositorio.ufsm.br/bitstream/1/9211/9/hans%203.pdf.txt0e40a37258aba59cbd407e84aef67badMD59hans 4.pdf.txthans 4.pdf.txtExtracted texttext/plain25825http://repositorio.ufsm.br/bitstream/1/9211/11/hans%204.pdf.txtad8ed858f52ee265e919f2678680b2c1MD511THUMBNAILhans 1.pdf.jpghans 1.pdf.jpgIM Thumbnailimage/jpeg4788http://repositorio.ufsm.br/bitstream/1/9211/3/hans%201.pdf.jpg3d23691ed3ce89c3d13f85867beac7b0MD53hans 2.pdf.jpghans 2.pdf.jpgIM Thumbnailimage/jpeg7919http://repositorio.ufsm.br/bitstream/1/9211/8/hans%202.pdf.jpgdec7e5d0aa3bf84e1b79e7b652a9cc33MD58hans 3.pdf.jpghans 3.pdf.jpgIM Thumbnailimage/jpeg7891http://repositorio.ufsm.br/bitstream/1/9211/10/hans%203.pdf.jpgfe003c16d4fb2d7c02205faf9c66d482MD510hans 4.pdf.jpghans 4.pdf.jpgIM Thumbnailimage/jpeg9088http://repositorio.ufsm.br/bitstream/1/9211/12/hans%204.pdf.jpgd7868c216e4d5429304e396998c3c2b5MD5121/92112017-07-25 11:52:22.403oai:repositorio.ufsm.br:1/9211Repositório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestouvidoria@ufsm.bropendoar:39132017-07-25T14:52:22Repositório Institucional Manancial UFSM - Universidade Federal de Santa Maria (UFSM)false
dc.title.por.fl_str_mv Diferentes técnicas de condicionamento em séries temporais turbulentas
title Diferentes técnicas de condicionamento em séries temporais turbulentas
spellingShingle Diferentes técnicas de condicionamento em séries temporais turbulentas
Zimermann, Hans Rogério
Covariância dos vórtices
Turbulência
Micrometeorologia
Filtros digitais
Eddy covariance
Turbulence
Micrometeorology
Digital filtering
CNPQ::CIENCIAS EXATAS E DA TERRA::FISICA
title_short Diferentes técnicas de condicionamento em séries temporais turbulentas
title_full Diferentes técnicas de condicionamento em séries temporais turbulentas
title_fullStr Diferentes técnicas de condicionamento em séries temporais turbulentas
title_full_unstemmed Diferentes técnicas de condicionamento em séries temporais turbulentas
title_sort Diferentes técnicas de condicionamento em séries temporais turbulentas
author Zimermann, Hans Rogério
author_facet Zimermann, Hans Rogério
author_role author
dc.contributor.advisor1.fl_str_mv Moraes, Osvaldo Luiz Leal de
dc.contributor.advisor1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4783106P7
dc.contributor.referee1.fl_str_mv Goulart, Antonio Gledson de Oliveira
dc.contributor.referee1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4791371J5
dc.contributor.referee2.fl_str_mv Acevedo, Otávio Costa
dc.contributor.referee2Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4796988J8
dc.contributor.authorLattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4737776H0
dc.contributor.author.fl_str_mv Zimermann, Hans Rogério
contributor_str_mv Moraes, Osvaldo Luiz Leal de
Goulart, Antonio Gledson de Oliveira
Acevedo, Otávio Costa
dc.subject.por.fl_str_mv Covariância dos vórtices
Turbulência
Micrometeorologia
Filtros digitais
topic Covariância dos vórtices
Turbulência
Micrometeorologia
Filtros digitais
Eddy covariance
Turbulence
Micrometeorology
Digital filtering
CNPQ::CIENCIAS EXATAS E DA TERRA::FISICA
dc.subject.eng.fl_str_mv Eddy covariance
Turbulence
Micrometeorology
Digital filtering
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS EXATAS E DA TERRA::FISICA
description 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.
publishDate 2005
dc.date.issued.fl_str_mv 2005-12-09
dc.date.accessioned.fl_str_mv 2017-05-08
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