5 resultados para Forecasts

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Parana, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

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In this study we present a climatology of the Amazon squall lines (ASLs), between the years 2000 and 2008, using satellite imagery and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses. The ASLs we are interested in are typically formed along the northern coast of Brazil and sometimes propagate for long distances inland. Results show that, on average, an ASL occurs every 2 days. ASLs are more frequent between April and June and less frequent between October and November. The years of 2005 and 2006 showed 25% more cases than the other years. This might be related to an increase of the Atlantic sea surface temperature. Of the total number of ASL cases, 54% propagated less than 170 km, 26% propagated between 170 and 400 km, and 20% propagated more than 400 km. We also studied the occurrence of low level jets (LLJs) associated with the coastal ASLs. Although LLJs are always present in the environment before the formation of the ASL and even on days without ASL cases, important differences were found, mainly related to the LLJ depths. (C) 2010 Elsevier B.V. All rights reserved.

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Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.

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This work models the carbon neutralization capacity of Brazil`s ethanol program since 1975. In addition to biofuel, we also assessed the mitigation potential of other energy products, such as, bioelectricity, and CO(2) emissions captured during fermentation of sugar cane`s juice. Finally, we projected the neutralization capacity of sugar cane`s bio-energy system over the next 32 years. The balance between several carbon stocks and flows was considered in the model, including the effects of land-use change. Our results show that the neutralization of the carbon released due to land-use change was attained only in 1992, and the maximum mitigation potential of the sugar cane sector was 128 tonnes Of CO(2) per ha in 2006. An ideal reconstitution of the deployment of the sugar cane sector, including the full exploitation of bio-electricity`s potential, plus the capture Of CO(2) released during fermentation, shows that the neutralization of land-use change emissions would have been achieved in 1988, and its mitigation potential would have been 390 tCO(2)/ha. Finally, forecasts of the sector up to 2039 shows that the mitigation potential in 2039 corresponds to 836 tCO(2)/ha, which corresponds to 5.51 kg Of CO(2) per liter of ethanol produced, or 55% above the negative emission level. (C) 2009 Elsevier Ltd. All rights reserved.

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The rate of high energy cosmic ray muons as measured underground is shown to be strongly correlated with upper-air temperatures during short-term atmospheric (10-day) events. The effects are seen by correlating data from the MINOS underground detector and temperatures from the European Centre for Medium Range Weather Forecasts during the winter periods from 2003-2007. This effect provides an independent technique for the measurement of meteorological conditions and presents a unique opportunity to measure both short and long-term changes in this important part of the atmosphere. Citation: Osprey, S., et al. (2009), Sudden stratospheric warmings seen in MINOS deep underground muon data, Geophys. Res. Lett., 36, L05809, doi: 10.1029/2008GL036359.