12 resultados para Radar otico

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


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Foram analisadas características da precipitação estimada a partir de 145.194 campos de refletividade, de um total de 827 dias entre 1998 e 2003, obtidos do Radar Meteorológico de São Paulo (RSP). Os eventos foram classificados de acordo com intensidades de precipitação; em Convectivos (EC) e Estratiformes (EE). Quanto à morfologia, cinco tipos de sistemas foram identificados; Convecção Isolada (CI), Brisa Marítima (BM), Linhas de Instabilidade (LI), Bandas Dispersas (BD) e Frentes Frias (FF). Eventos convectivos dominam na primavera e verão e estratiformes no outono e inverno. A CI e a BM tiveram maiores picos de atuação entre outubro e março enquanto as FF de abril a setembro. BD atuam durante todo o ano e as LI só não foram observadas nos meses de junho e julho. Uma comparação pontual entre a precipitação medida pela telemetria e estimada com o radar foi realizada e, mostrou haver, na maioria dos casos, um viés positivo do RSP, para acumulações de 10, 30 e 60 minutos. Com o objetivo de integrar as estimativas de precipitação do radar com as medidas da rede telemétrica, por meio de uma análise objetiva estatística, foram obtidas dos campos de precipitação do radar as estruturas das correlações espaciais em função da distância para acumulações de chuva de 15, 30, 60 e 120 minutos para os cinco tipos de sistemas precipitantes que foram caracterizados. As curvas das correlações espaciais médias de todos os eventos de precipitação de cada sistema foram ajustadas por funções polinomiais de sexta ordem. Os resultados indicam diferenças significativas na estrutura espacial das correlações entre os sistemas precipitantes.

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É apresentado um estudo sobre sistemas convectivos linearmente organizados e observados por um radar meteorológico banda-C na região semi-árida do Nordeste do Brasil. São analisados três dias (27 a 29) de março de 1985, com ênfase na investigação do papel desempenhado por fatores locais e de grande escala no desenvolvimento dos sistemas. No cenário de grande escala, a área de cobertura do radar foi influenciada por um cavado de ar superior austral no dia 27 e por um vórtice ciclônico de altos níveis no dia 29. A convergência de umidade próxima à superfície favoreceu a atividade convectiva nos dias 27 e 29, enquanto que divergência de umidade próxima à superfície inibiu a atividade convectiva no dia 28. No cenário de mesoescala, foi observado que o aquecimento diurno é um fator importante para a formação de células convectivas, somando-se a ele o papel determinante da orografia na localização dos ecos. De maneira geral, as imagens de radar mostram os sistemas convectivos linearmente organizados em áreas elevadas e núcleos convectivos intensos envolvidos por uma área de precipitação estratiforme. Os resultados indicam que convergência do fluxo de umidade em grande escala e aquecimento radiativo, são fatores determinantes na evolução e desenvolvimento dos ecos na área de estudo.

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ABSTRACT Microphysical and thermodynamical features of two tropical systems, namely Hurricane Ivan and Typhoon Conson, and one sub-tropical, Catarina, have been analyzed based on space-born radar PR measurements available on the TRMM satellite. The procedure to classify the reflectivity profiles followed the Heymsfield et al (2000) and Steiner et al (1995) methodologies. The water and ice content have been calculated using a relationship obtained with data of the surface SPOL radar and PR in Rondonia State in Brazil. The diabatic heating rate due to latent heat release has been estimated using the methodology developed by Tao et al (1990). A more detailed analysis has been performed for Hurricane Catarina, the first of its kind in South Atlantic. High water content mean value has been found in Conson and Ivan at low levels and close to their centers. Results indicate that hurricane Catarina was shallower than the other two systems, with less water and the water was concentrated closer to its center. The mean ice content in Catarina was about 0.05 g kg-1 while in Conson it was 0.06 g kg-1 and in Ivan 0.08 g kg-1. Conson and Ivan had water content up to 0.3 g kg-1 above the 0ºC layer, while Catarina had less than 0.15 g kg-1. The latent heat released by Catarina showed to be very similar to the other two systems, except in the regions closer to the center.

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Este trabalho faz uma análise das estimativas de teores de umidade obtidas com o método Ground Penetrating Radar (GPR) comparativamente às determinadas com os métodos Time Domain Reflectometry (TDR) e gravimétrico. Os dados foram obtidos em dois experimentos diferentes: um experimento controlado em laboratório buscando reproduzir um meio homogêneo onde foram obtidas as medidas de umidade com GPR (antenas de 1 GHz) e TDR, e outro experimento de campo onde foram obtidos dados com GPR (antenas de 200 MHz) e de amostras de solos do local. Para a obtenção das estimativas a partir do método GPR foram analisados os eventos relativos à onda de transmissão direta entre as antenas, onda refratada criticamente e onda refletida em interfaces com diferentes propriedades elétricas.O GPR mostrou-se sensível às variações de umidades presentes nos dois experimentos e apresentou boa correlação com os dados obtidos com TDR (REQM de0,007 m³m-3) e das amostras (REQM de 0,039 m³m-3).

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This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

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Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region`s predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.

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Our objective was to develop a methodology to predict soil fertility using visible near-infrared (vis-NIR) diffuse reflectance spectra and terrain attributes derived from a digital elevation model (DEM). Specifically, our aims were to: (i) assemble a minimum data set to develop a soil fertility index for sugarcane (Sarcharum officinarum L.) (SFI-SC) for biofuel production in tropical soils; (ii) construct a model to predict the SFI-SC using soil vis-NIR spectra and terrain attributes; and (iii) produce a soil fertility map for our study area and assess it by comparing it with a green vegetation index (GVI). The study area was 185 ha located in sao Paulo State, Brazil. In total, 184 soil samples were collected and analyzed for a range of soil chemical and physical properties. Their vis-NIR spectra were collected from 400 to 2500 nm. The Shuttle Radar Topographic Mission 3-arcsec (90-m resolution) DEM of the area was used to derive 17 terrain attributes. A minimum data set of soil properties was selected to develop the SFI-SC. The SFI-SC consisted of three classes: Class 1, the highly fertile soils; Class 2, the fertile soils; and Class 3, the least fertile soils. It was derived heuristically with conditionals and using expert knowledge. The index was modeled with the spectra and terrain data using cross-validated decision trees. The cross-validation of the model correctly predicted Class 1 in 75% of cases, Class 2 in 61%, and Class 3 in 65%. A fertility map was derived for the study area and compared with a map of the GVI. Our approach offers a methodology that incorporates expert knowledge to derive the SFI-SC and uses a versatile spectro-spatial methodology that may be implemented for rapid and accurate determination of soil fertility and better exploration of areas suitable for production.

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Regional Climate Model version 3 (RegCM3) simulations of 17 summers (1988-2004) over part of South America south of 5 degrees S were evaluated to identify model systematic errors. Model results were compared to different rainfall data sets (Climate Research Unit (CRU), Climate Prediction Center (CPC), Global Precipitation Climatology Project (GPCP), and National Centers for Environmental Prediction (NCEP) reanalysis), including the five summers mean (1998-2002) precipitation diurnal cycle observed by the Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR). In spite of regional differences, the RegCM3 simulates the main observed aspects of summer climatology associated with the precipitation (northwest-southeast band of South Atlantic Convergence Zone (SACZ)) and air temperature (warmer air in the central part of the continent and colder in eastern Brazil and the Andes Mountains). At a regional scale, the main RegCM3 failures are the underestimation of the precipitation in the northern branch of the SACZ and some unrealistic intense precipitation around the Andes Mountains. However, the RegCM3 seasonal precipitation is closer to the fine-scale analyses (CPC, CRU, and TRMM-PR) than is the NCEP reanalysis, which presents an incorrect north-south orientation of SACZ and an overestimation of its intensity. The precipitation diurnal cycle observed by TRMM-PR shows pronounced contrasts between Tropics and Extratropics and land and ocean, where most of these features are simulated by RegCM3. The major similarities between the simulation and observation, especially the diurnal cycle phase, are found over the continental tropical and subtropical SACZ regions, which present afternoon maximum (1500-1800 UTC) and morning minimum (0900-1200 UTC). More specifically, over the core of SACZ, the phase and amplitude of the simulated precipitation diurnal cycle are very close to the TRMM-PR observations. Although there are amplitude differences, the RegCM3 simulates the observed nighttime rainfall in the eastern Andes Mountains, over the Atlantic Ocean, and also over northern Argentina. The main simulation deficiencies are found in the Atlantic Ocean and near the Andes Mountains. Over the Atlantic Ocean the convective scheme is not triggered; thus the rainfall arises from the grid-scale scheme and therefore differs from the TRMM-PR. Near the Andes, intense (nighttime and daytime) simulated precipitation could be a response of an incorrect circulation and topographic uplift. Finally, it is important to note that unlike most reported bias of global models, RegCM3 does not trigger the moist convection just after sunrise over the southern part of the Amazon.

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This study investigated the physical processes involved in the development of thunderstorms over southwestern Amazon by hypothesizing causalities for the observed cloud-to-ground lightning variability and the local environmental characteristics. Southwestern Amazon experiences every year a large variety of environmental factors, such as the gradual increase in atmospheric moisture, extremely high pollution due to biomass burning, and intense deforestation, which directly affects cloud development by differential surface energy partition. In the end of the dry period it was observed higher percentages of positive cloud-to-ground (+CG) lightning due to a relative increase in +CG dominated thunderstorms (positive thunderstorms). Positive (negative) thunderstorms initiated preferentially over deforested (forest) areas with higher (lower) cloud base heights, shallower (deeper) warm cloud depths, and higher (lower) convective potential available energy. These features characterized the positive (negative) thunderstorms as deeper (relatively shallower) clouds, stronger (relatively weaker) updrafts with enhanced (decreased) mixed and cold vertically integrated liquid. No significant difference between thunderstorms (negative and positive) and nonthunderstorms were observed in terms of atmospheric pollution, once the atmosphere was overwhelmed by pollution leading to an updraft-limited regime. However, in the wet season both negative and positive thunderstorms occurred during periods of relatively higher aerosol concentration and differentiated size distributions, suggesting an aerosol-limited regime where cloud electrification could be dependent on the aerosol concentration to suppress the warm and enhance the ice phase. The suggested causalities are consistent with the invoked hypotheses, but they are not observed facts; they are just hypotheses based on plausible physical mechanisms.

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Geophysics has been shown to be effective in identifying areas contaminated by waste disposal, contributing to the greater efficiency of soundings programs and the installation of monitoring wells. In the study area, four trenches were constructed with a total volume of about 25,000 m(3). They were almost totally filled with re-refined lubricating oil waste for approximately 25 years. No protection liners were used in the bottoms and laterals of the disposal trenches. The purpose of this work is to evaluate the potential of the resistivity and ground penetrating radar (GPR) methods in characterizing the contamination of this lubricant oil waste disposal area in Ribeiro Preto, SP, situated on the geological domain of the basalt spills of the Serra Geral Formation and the sandstones of the Botucatu Formation. Geophysical results were shown in 2D profiles. The geophysical methods used enabled the identification of geophysical anomalies, which characterized the contamination produced by the trenches filled with lubricant oil waste. Conductive anomalies (smaller than 185 Omega m) immediately below the trenches suggest the action of bacteria in the hydrocarbons, as has been observed in several sites contaminated by hydrocarbons in previously reported cases in the literature. It was also possible to define the geometry of the trenches, as evidenced by the GPR method. Direct sampling (chemical analysis of the soil and the water in the monitoring well) confirmed the contamination. In the soil analysis, low concentrations of several polycyclic aromatic hydrocarbons (PAHs) were found, mainly naphthalene and phenanthrene. In the water samples, an analysis verified contamination of the groundwater by lead (Pb). The geophysical methods used in the investigation provided an excellent tool for environmental characterization in this study of a lubricant oil waste disposal area, and could be applied in the study of similar areas.

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GPR (Ground Penetrating Radar) results are shown for perpendicular broadside and parallel broadside antenna orientations. Performance in detection and localization of concrete tubes and steel tanks is compared as a function of acquisition configuration. The comparison is done using 100 MHz and 200 MHz center frequency antennas. All tubes and tanks are buried at the geophysical test site of IAG/USP in Sao Paulo city, Brazil. The results show that the long steel pipe with a 38-mm diameter was well detected with the perpendicular broadside configuration. The concrete tubes were better detected with the parallel broadside configuration, clearly showing hyperbolic diffraction events from all targets up to 2-m depth. Steel tanks were detected with the two configurations. However, the parallel broadside configuration was generated to a much lesser extent an apparent hyperbolic reflection corresponding to constructive interference of diffraction hyperbolas of adjacent targets placed at the same depth. Vertical concrete tubes and steel tanks were better contained with parallel broadside antennas, where the apexes of the diffraction hyperbolas better corresponded to the horizontal location of the buried target disposition. The two configurations provide details about buried targets emphasizing how GPR multi-component configurations have the potential to improve the subsurface image quality as well as to discriminate different buried targets. It is judged that they hold some applicability in geotechnical and geoscientific studies. (C) 2009 Elsevier B.V. All rights reserved.

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The shuttle radar topography mission (SRTM), was flow on the space shuttle Endeavour in February 2000, with the objective of acquiring a digital elevation model of all land between 60 degrees north latitude and 56 degrees south latitude, using interferometric synthetic aperture radar (InSAR) techniques. The SRTM data are distributed at horizontal resolution of 1 arc-second (similar to 30m) for areas within the USA and at 3 arc-second (similar to 90m) resolution for the rest of the world. A resolution of 90m can be considered suitable for the small or medium-scale analysis, but it is too coarse for more detailed purposes. One alternative is to interpolate the SRTM data at a finer resolution; it will not increase the level of detail of the original digital elevation model (DEM), but it will lead to a surface where there is the coherence of angular properties (i.e. slope, aspect) between neighbouring pixels, which is an important characteristic when dealing with terrain analysis. This work intents to show how the proper adjustment of variogram and kriging parameters, namely the nugget effect and the maximum distance within which values are used in interpolation, can be set to achieve quality results on resampling SRTM data from 3"" to 1"". We present for a test area in western USA, which includes different adjustment schemes (changes in nugget effect value and in the interpolation radius) and comparisons with the original 1"" model of the area, with the national elevation dataset (NED) DEMs, and with other interpolation methods (splines and inverse distance weighted (IDW)). The basic concepts for using kriging to resample terrain data are: (i) working only with the immediate neighbourhood of the predicted point, due to the high spatial correlation of the topographic surface and omnidirectional behaviour of variogram in short distances; (ii) adding a very small random variation to the coordinates of the points prior to interpolation, to avoid punctual artifacts generated by predicted points with the same location than original data points and; (iii) using a small value of nugget effect, to avoid smoothing that can obliterate terrain features. Drainages derived from the surfaces interpolated by kriging and by splines have a good agreement with streams derived from the 1"" NED, with correct identification of watersheds, even though a few differences occur in the positions of some rivers in flat areas. Although the 1"" surfaces resampled by kriging and splines are very similar, we consider the results produced by kriging as superior, since the spline-interpolated surface still presented some noise and linear artifacts, which were removed by kriging.