948 resultados para areal radar rainfall


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This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of São Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of São Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

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To contribute to the knowledge of lotic zooplankton from dammed and free stretches, we tested the hypothesis that the ecological attributes are different between these environments, which are subjected to several effects caused by different hydrological conditions. The study was carried out in the low Iguacu river, a large hydrographic basin in the south of Brasil. Two samplings were performed, one in the dry period (April/04) and the other in the atypical rainy period (July/04), in five stations downstream a large reservoir, and other 12 stations in four tributaries representing the upper, intermediate and low regions of each river. The observations suggest a clear spatial distribution of zooplankton in lotic stretches subjected or not to damming, mainly due to the effects of physical, chemical and biological variables. Furthermore, the atypical rainfall promoted alterations in community structure when compared to the dry period.

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Radar and satellite data from the Tropical Rainfall Measuring Mission-Large-Scale Biosphere-Atmosphere (TRMM-LBA) project have been examined to determine causes for convective storm initiation in the southwest Amazon region. The locations and times of storm initiation were based on the National Center for Atmospheric Research (NCAR) S-band dual-polarization Doppler radar (S-Pol). Both the radar and the Geostationary Operational Environmental Satellite-8 (GOES-8) visible data were used to identify cold pools produced by convective precipitation. These data along with high-resolution topographic data were used to determine possible convective storm triggering mechanisms. The terrain elevation varied from 100 to 600 m. Tropical forests cover the area with numerous clear-cut areas used for cattle grazing and farming. This paper presents the results from 5 February 1999. A total of 315 storms were initiated within 130 km of the S-Pol radar. This day was classified as a weak monsoon regime where convection developed in response to the diurnal cycle of solar heating. Scattered shallow cumulus during the morning developed into deep convection by early afternoon. Storm initiation began about 1100 LST and peaked around 1500-1600 LST. The causes of storm initiation were classified into four categories. The most common initiation mechanism was caused by forced lifting by a gust front (GF; 36%). Forcing by terrain (>300 m) without any other triggering mechanism accounted for 21% of the initiations and colliding GFs accounted for 16%. For the remaining 27% a triggering mechanism was not identified. Examination of all days during TRMM-LBA showed that this one detailed study day was representative of many days. A conceptual model of storm initiation and evolution is presented. The results of this study should have implications for other locations when synoptic-scale forcing mechanisms are at a minimum. These results should also have implications for very short-period forecasting techniques in any location where terrain, GFs, and colliding boundaries influence storm evolution.

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Three types of imagery were evaluated for mapping drainage patterns and vegetation in a 100 000 ha area of Sao Paulo State, Brazil. The drainage measurements were drainage density, frequency of channels and texture ratio, studied on circular samples of 10 km2 for panchromatic photography and 100 km2 for radar and satellite images. The vegetation types were forest, pasture, sugar cane and rice, studied on circular samples of 100 km2. Radar images were the most convenient method to study drainage patterns and the land forms of large areas, while Landsat imagery was most efficient for the study of vegetative cover, although panchromatic photographs were the most accurate method.-from Field Crop Abstracts

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Two stochastic models have been fitted to daily rainfall data for an interior station of Brazil. Of these two models, the results show a better fit to describe the data, by truncated negative probability model in comparison with Markov chain probability model. Kolmogorov-Smirnov test is applied for significance for these models. © 1983 Springer-Verlag.

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The objective of the present work was the improvement of the methodology for soil mapping through the drainage network with the aid of Landsat data. The drainage network of the area studied was delineated and the soils identified. The main problem of the method has been the characterization of the contact between soil units when it is not abrupt, and in this case field trips and the analysis of the relief has been used to solve doubts.-from English summary

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On 27 March 1991, an isolated thunderstorm passed between the two CSIR Doppler radars, spaced about 45km apart. Both radars simultaneously recorded Doppler data of the storm, and a detailed case study during an 11-min period is presented. Air motions synthesized from these data provide the first three-dimensional display of Doppler-derived wind fields within a multicell storm on the Transvaal Highveld. Regions of high divergence values (10 -2s -1) at low levels were found mostly in close proximity to reflectivity maxima (45-51 dBZ), which is consistent with findings from North America, that gravitational loading by the precipitation plays a key role in the initiation and maintenance of downdraughts. -from Authors

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Pearl millet (Penisetum glaucum) is an interesting species to be used as cover crop in tropical areas, showing a high ability in potassium uptake. Potassium (K) is not linked to organic compounds in the plant, and can easily be released from decaying straw becoming available for subsequent crops. This experiment evaluated K leaching from millet straw grown under potassium rates (0, 100, 200, and 300 mg dm-3), and submitted to five levels of simulated rain (5, 10, 20, 40, and 80 mm). Plants were grown in soil filled pots in a greenhouse. On the 50th day after emergence, the plants were desiccated with glyphosate. Artificial rain was applied over the straw. Potassium deficiency speeds up millet dehydration after herbicide application and increases lightly rain water retention in the straw. The amount of K leached right after plant desiccation is correlated with the residue nutrient content and can be as high as 64 kg ha-1 considering a mulch of 8 t ha -1. Although well-nourished millet plants release considerable amounts of K with the first rains, a large percentage of the nutrient is still retained in the straw. Copyright © Taylor & Francis, Inc.

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In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Este trabalho utilizou os dados de precipitação do período de janeiro de 2000 a setembro de 2007 da torre micrometeorológica localizada na Estação Científica Ferreira Pena (ECFP) em Caxiuanã e foram comparados com o algoritmo 3B42 que combina dados de satélites no canal de microoondas para ajustar aqueles do canal infravermelho. Adicionalmente foi feita uma análise da distribuição temporal e espacial da precipitação na Amazônia Oriental utilizando os dados de cinco algoritmos estimadores de precipitação: O Geostationary Environmental SalellitePrecipitation lndex (GPI); o 3B42; 3A12 e 3A25 que são os algoritmos provenientes dos sensores de microondas e do radar meteorológico à bordo do satélite Tropical Rainfall MeasuringMission (TRMM); e o Global Precipitation Climatology Center (GPCC) de janeiro de 1998 a dezembro de 2007. A comparação entre o algoritmo 3B42 com os dados do pluviógrafo da torre mostrou que o estimador 3B42 superestima a precipitação em relação aos dados da torre para todo o período de estudo. Os períodos mais chuvosos foram os trimestres de março-abril-maio (MAM) e dezembro-janeiro-feveireiro (DJF) e os períodos menos chuvosos foram setembro-outubro-novembro (SON) e junho-julho-agosto (JJA). Esta sazonalidade da precipitação se apresenta principalmente devido à influência da Zona de Convergência Intertropical (ZCIT), que contribui de maneira apreciável para a modulação da estação chuvosa na região. A comparação trimestral entre o algoritmo 3B42 e pluviógrafo da torre, mostra que o algoritmo 3B42 superestimou (subestimou) a precipitação em relação ao pluviógrafo em MAM e JJA (DJF e SON); e DJF é o trimestre que apresenta as estimativas de precipitação com valores mais aproximados a precipitação medida na torre micrometeorológica de Caxiuanã. Na média mensal o 3B42 subestima a precipitação de outubro a janeiro e superestima em relação as dados medidos na torre, de março a agosto. O algoritmo3B42 superestimou (subestimou) a precipitação noturna (matutina e vespertina) do ciclo diurno em relação ao pluviógrafo da torre, nas vizinhanças de Caxiuanã. No entanto ambos estimadores mostraram que em média o horário de maior precipitação é por volta das 1800hora local (HL). Além disso, as análises do ciclo diurno médio sazonal indicam que em DJF nos horários de 0900 HL, 1500 HL e 1800HL têm os valores de precipitação estimada pelo algoritmo3B42 mais aproximados aos valores da precipitação medida pontualmente em Caxiuanã. Os meses de novembro a fevereiro têm um máximo principal de precipitação no período vespertino, tanto na torre como no algoritmo 3B42. No período de maio à julho o horário os máximos diurnos de precipitação passam do período da tarde para os da noite e madrugada,modificando o ciclo diurno em comparação aos demais meses. A comparação entre os cinco algoritmos na Amazônia Oriental mostrou diferentes comportamentos entre os estimadores. O algoritmo GPI subestimou s precipitação em relação aos demais algoritmos na região costeira do Amapá e Guiana Francesa e superestimou na região central da Amazônia. Tanto o algoritmo 3A12 quanto o 3A25 apresentaram menor precipitação que os demais algoritmos. O algoritmo 3842, por ser uma combinação de várias estimativas baseadas no canal de microondas e infravermelho, apresenta padrões semelhantes a Figueroa e Nobre (1990). No entanto, o GPCC mostra menos detalhes na distribuição espacial de precipitação nos lugares onde não há pluviômetros como, por exemplo, no Noroeste do Pará. As diferenças entre os algoritmos aqui considerados podem estar relacionados com as características de cada algoritmo e/ou a metodologia empregada. As comparações pontuais de precipitação de um pluviômetro com a média numa área com dados provenientes de satélites podem ser a explicação para as diferenças entre os estimadores nos trimestres ou ciclo diurno. No entanto não se descartam que essas diferenças sejam devidas à diferente natureza da precipitação entre as subregiões, assim como a existência de diferentes sistemas que modulam o ciclo diurno da precipitação na Amazônia Oriental.

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Investigação pioneira aplicando Radar de Penetração no Solo (GPR) na área da Praia do Atalaia, norte do Brasil, nos permitiu caracterizar, pela primeira vez, fácies e estratigrafia dos depósitos conhecidos informalmente como Sedimentos Pós-Barreiras (Plioceno e mais recente). Esta sucessão sedimentar recobre discordantemente o embasamento miocênico, representado pelas formações Pirabas/Barreiras. Três unidades estratigráficas foram reconhecidas. A Unidade 1, inferior, consiste em um intervalo com 6 m de espessura média dominado por reflexões pobremente definidas e de baixa amplitude, e que intergradam com reflexões de média escala dos tipos tangencial, obliquo e hummocky. A Unidade 2, intermediária, possui cerca de 9 m de espessura e inclui, principalmente, reflexões oblíquas de larga escala, cujas configurações variam de paralela, tangencial, sigmoidal a sigmoidal-complexa. A Unidade 3, superior, corresponde a um intervalo entre 3,5 e 9 m de espessura, sendo dominada por reflexões hummocky, seguidas por reflexões de média escala dos tipos oblíquo, paralelo a sub-paralelo, e em corte-e-preenchimento. A análise da configuração das reflexões internas e geometria das reflexões nos leva a propor que a unidade correspondente aos Sedimentos Pós-Barreiras é mais variável faciologicamente que inicialmente imaginado, incluindo depósitos eólicos (dunas costeiras), bem como depósitos de cordão litorâneo, planície de maré, canal e mangue. Além disto, o mapeamento das três unidades descritas acima é importante para desvendar a complexidade de sedimentação versus erosão durante o Neógeno tardio no norte do Brasil.