7 resultados para Atmospheric modeling
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We describe and begin to evaluate a parameterization to include the vertical transport of hot gases and particles emitted from biomass burning in low resolution atmospheric-chemistry transport models. This sub-grid transport mechanism is simulated by embedding a 1-D cloud-resolving model with appropriate lower boundary conditions in each column of the 3-D host model. Through assimilation of remote sensing fire products, we recognize which columns have fires. Using a land use dataset appropriate fire properties are selected. The host model provides the environmental conditions, allowing the plume rise to be simulated explicitly. The derived height of the plume is then used in the source emission field of the host model to determine the effective injection height, releasing the material emitted during the flaming phase at this height. Model results are compared with CO aircraft profiles from an Amazon basin field campaign and with satellite data, showing the huge impact that this mechanism has on model performance. We also show the relative role of each main vertical transport mechanisms, shallow and deep moist convection and the pyro-convection (dry or moist) induced by vegetation fires, on the distribution of biomass burning CO emissions in the troposphere.
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Nowadays, with the implantation of GNSS (Global Navigation Satellite System) reference station networks, several positioning techniques have been developed and/or improved. Using such kind of network data it is possible to model the GNSS distance dependent errors and to compute correction terms for the network region. Several methods have been developed to formulate the corrections terms from network stations data. A method that has been received a great attention is the Virtual Reference Station (VRS). The idea is that the VRS data resemble as much as possible a real receiver data placed in the same local. Therefore, the user has the possibility of using the VRS as if it were a real reference station in your proximities, and to accomplish the relative positioning with a single frequency receiver. In this paper it is described a different methodology applied to implement the VRS concept, using atmospheric models developed by Brazilian researchers. Besides, experiments for evaluating the quality of generated VRS are presented, showing the efficiency of the proposed method.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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dIn this work, a perceptron neural-network technique is applied to estimate hourly values of the diffuse solar-radiation at the surface in São Paulo City, Brazil, using as input the global solar-radiation and other meteorological parameters measured from 1998 to 2001. The neural-network verification was performed using the hourly measurements of diffuse solar-radiation obtained during the year 2002. The neural network was developed based on both feature determination and pattern selection techniques. It was found that the inclusion of the atmospheric long-wave radiation as input improves the neural-network performance. on the other hand traditional meteorological parameters, like air temperature and atmospheric pressure, are not as important as long-wave radiation which acts as a surrogate for cloud-cover information on the regional scale. An objective evaluation has shown that the diffuse solar-radiation is better reproduced by neural network synthetic series than by a correlation model. (C) 2004 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)