A Look at Amazon Basin Seasonal Dynamics with the Biophysical ...
A Look at Amazon Basin Seasonal Dynamics with the Biophysical ... A Look at Amazon Basin Seasonal Dynamics with the Biophysical ...
Modeling the fine-scale turbulence within and above an Amazon forestusing Tsallis’ generalized thermostatistics. II. TemperatureFernando M. Ramos 2 , Leonardo D. A. Sá 1 , Maurício J. A. Bolzan 1,3 , Camilo RodriguesNeto 2 , Reinaldo R. Rosa 21. Laboratório Associado de Meteorologia e Oceanografia, Centro de Previsão de Tempo eEstudos Climáticos, Instituto Nacional de Pesquisas Espaciais, São José dos Campos,Brazil2. Laboratório Associado de Computação e Matemática Aplicada, Instituto Nacional dePesquisas Espaciais, São José dos Campos, Brazil3. Instituto de Pesquisa e Desenvolvimento, Universidade do Vale do Paraíba, São José dosCampos, BrazilAbstract: In this paper, we show that Tsallis generalized thermostatistics provides a simpleand accurate framework for modeling the statistical behavior of turbulent temperaturefluctuations. For this, we compared our theoretical framework to data measured during theLarge Scale Biosphere Atmosphere Experiment in Amazonia (LBA) wet-season campaign,in the southwestern part of Amazonia region. Measurements were made simultaneouslywith Campbell sonic thermometers at different heights in a 60 meters micrometeorologicaltower located in the Biological Reserve of Jaru (10 o 04´ S, 61 o 56´ W), Brazil. Thetheoretical results were found to be in good agreement with experiment through spatialscales spanning at least three orders of magnitude and for a range of up to 10 standarddeviations, including the rare fluctuations in the tails of the distribution. For scales largerthan approximately 10 m, a gradual transition to Gaussianity becomes evident in theexperimental histograms which is not captured by the present model. A generalization ofthis model is proposed to take this effect into account, assuring thus a smooth transition toGaussianity as the scale increases.____________________* Corresponding author.E-mail address: fernando@lac.inpe.br
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Modeling <strong>the</strong> fine-scale turbulence <strong>with</strong>in and above an <strong>Amazon</strong> forestusing Tsallis’ generalized <strong>the</strong>rmost<strong>at</strong>istics. II. Temper<strong>at</strong>ureFernando M. Ramos 2 , Leonardo D. A. Sá 1 , Maurício J. A. Bolzan 1,3 , Camilo RodriguesNeto 2 , Reinaldo R. Rosa 21. Labor<strong>at</strong>ório Associado de Meteorologia e Oceanografia, Centro de Previsão de Tempo eEstudos Climáticos, Instituto Nacional de Pesquisas Espaciais, São José dos Campos,Brazil2. Labor<strong>at</strong>ório Associado de Computação e M<strong>at</strong>emática Aplicada, Instituto Nacional dePesquisas Espaciais, São José dos Campos, Brazil3. Instituto de Pesquisa e Desenvolvimento, Universidade do Vale do Paraíba, São José dosCampos, BrazilAbstract: In this paper, we show th<strong>at</strong> Tsallis generalized <strong>the</strong>rmost<strong>at</strong>istics provides a simpleand accur<strong>at</strong>e framework for modeling <strong>the</strong> st<strong>at</strong>istical behavior of turbulent temper<strong>at</strong>urefluctu<strong>at</strong>ions. For this, we compared our <strong>the</strong>oretical framework to d<strong>at</strong>a measured during <strong>the</strong>Large Scale Biosphere Atmosphere Experiment in <strong>Amazon</strong>ia (LBA) wet-season campaign,in <strong>the</strong> southwestern part of <strong>Amazon</strong>ia region. Measurements were made simultaneously<strong>with</strong> Campbell sonic <strong>the</strong>rmometers <strong>at</strong> different heights in a 60 meters micrometeorologicaltower loc<strong>at</strong>ed in <strong>the</strong> Biological Reserve of Jaru (10 o 04´ S, 61 o 56´ W), Brazil. The<strong>the</strong>oretical results were found to be in good agreement <strong>with</strong> experiment through sp<strong>at</strong>ialscales spanning <strong>at</strong> least three orders of magnitude and for a range of up to 10 standarddevi<strong>at</strong>ions, including <strong>the</strong> rare fluctu<strong>at</strong>ions in <strong>the</strong> tails of <strong>the</strong> distribution. For scales largerthan approxim<strong>at</strong>ely 10 m, a gradual transition to Gaussianity becomes evident in <strong>the</strong>experimental histograms which is not captured by <strong>the</strong> present model. A generaliz<strong>at</strong>ion ofthis model is proposed to take this effect into account, assuring thus a smooth transition toGaussianity as <strong>the</strong> scale increases.____________________* Corresponding author.E-mail address: fernando@lac.inpe.br
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