4 resultados para Numerical weather prediction

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Several reefs of the world have undergone changes in community due to sedimentation processes. It has been suggested that Abrolhos reefs (Brazil/South-West Atlantic) are subjected to a steady coastal influence, although there is still little information regarding this assumption. In this work, we have analyzed a set of environmental parameters concerning sedimentation characteristics at the Abrolhos reefs, near 18 degrees S-39 degrees W. The analysis included remote sensing, model and in situ data to provide a three-dimensional quantitative description of the processes that influence sediment apportionment to the reefs. Mineralogy and natural radioactivity of sediment trapped at three reef sites in a transect perpendicular to the coastline were used in conjunction with numerical weather prediction model and remote sensing databases. We have observed an increase of around 100% of sediment flux during the summer compared to the winter season. A comparison of regional rainfall regime, sediment plume dynamics and a year-around monitoring of polar fronts trajectories and surface wind showed that the wind-driven resedimentation due to polar front activity is the major contributor to the intensification of sedimentation processes at the offshore area of Abrolhos reefs, despite river runoff from mainland. (C) 2007 Elsevier Ltd. All rights reserved.

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Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown. (C) 2012 Elsevier B.V. All rights reserved.

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The assimilation of satellite estimated precipitation data can be used as an efficient tool to improve the analysis of rainfall generated by numerical models of weather forecast. The system of data assimilation used in this study is cumulus parameterization inversion based on the Kuo scheme. Reanalysis were performed using the field experiment data of the LBA Project (WETAMC and DRYtoWET-AMC), where it was possible to verify an improvement in the simulations results, since the data assimilation corrects the position and the intensity of rainfall in the numerical model. (C) 2012 Elsevier B.V. All rights reserved.

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Computational fluid dynamics, CFD, is becoming an essential tool in the prediction of the hydrodynamic efforts and flow characteristics of underwater vehicles for manoeuvring studies. However, when applied to the manoeuvrability of autonomous underwater vehicles, AUVs, most studies have focused on the de- termination of static coefficients without considering the effects of the vehicle control surface deflection. This paper analyses the hydrodynamic efforts generated on an AUV considering the combined effects of the control surface deflection and the angle of attack using CFD software based on the Reynolds-averaged Navier–Stokes formulations. The CFD simulations are also independently conducted for the AUV bare hull and control surface to better identify their individual and interference efforts and to validate the simulations by comparing the experimental results obtained in a towing tank. Several simulations of the bare hull case were conducted to select the k –ω SST turbulent model with the viscosity approach that best predicts its hydrodynamic efforts. Mesh sensitivity analyses were conducted for all simulations. For the flow around the control surfaces, the CFD results were analysed according to two different methodologies, standard and nonlinear. The nonlinear regression methodology provides better results than the standard methodology does for predicting the stall at the control surface. The flow simulations have shown that the occurrence of the control surface stall depends on a linear relationship between the angle of attack and the control surface deflection. This type of information can be used in designing the vehicle’s autopilot system.