976 resultados para Radar meteorology


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In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscattering coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, USA. Both the dry and the wet season SAR data showed exponential relationships with root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R² = 0.80), while the wet season SAR data have somewhat higher secondary variation (R² = 0.59). This lower correlation was probably provoked by the stronger influence of soil moisture, which may not be negligible in the wet season SAR data. We concluded that the single configuration C-band SAR data is useful to estimate surface roughness of rocky soils in a semiarid rangeland.

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Foram estudados nove perfis ao longo de uma toposseqüência sobre os sedimentos do Grupo Barreiras, na Fazenda Rio Negro, município de Entre Rios (BA), utilizando a prospecção eletromagnética por meio do Radar Penetrante no Solo - "Ground-penetrating radar - GPR", objetivando analisar a utilização dessa ferramenta na aquisição de informações sobre as feições que ocorrem no solo, mediante a comparação entre os radargramas obtidos e a descrição pedológica. O equipamento utilizado foi um Geophysical Survey System modelo GPR SR system-2, com antena de 80 MHz. A análise radargramétrica confirmou o aparecimento dos fragipãs e duripãs em profundidade, que ocorrem sempre acompanhados de um processo de transformação dos solos do tipo Latossolo Amarelo e Argissolo Amarelo em Espodossolo. Os padrões de reflexão mostram claramente os domínios dos solos argilosos e dos solos arenosos, com e sem a presença dos horizontes endurecidos.

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Investigations of solute transport in fractured rock aquifers often rely on tracer test data acquired at a limited number of observation points. Such data do not, by themselves, allow detailed assessments of the spreading of the injected tracer plume. To better understand the transport behavior in a granitic aquifer, we combine tracer test data with single-hole ground-penetrating radar (GPR) reflection monitoring data. Five successful tracer tests were performed under various experimental conditions between two boreholes 6 m apart. For each experiment, saline tracer was injected into a previously identified packed-off transmissive fracture while repeatedly acquiring single-hole GPR reflection profiles together with electrical conductivity logs in the pumping borehole. By analyzing depth-migrated GPR difference images together with tracer breakthrough curves and associated simplified flow and transport modeling, we estimate (1) the number, the connectivity, and the geometry of fractures that contribute to tracer transport, (2) the velocity and the mass of tracer that was carried along each flow path, and (3) the effective transport parameters of the identified flow paths. We find a qualitative agreement when comparing the time evolution of GPR reflectivity strengths at strategic locations in the formation with those arising from simulated transport. The discrepancies are on the same order as those between observed and simulated breakthrough curves at the outflow locations. The rather subtle and repeatable GPR signals provide useful and complementary information to tracer test data acquired at the outflow locations and may help us to characterize transport phenomena in fractured rock aquifers.

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Ground clutter caused by anomalous propagation (anaprop) can affect seriously radar rain rate estimates, particularly in fully automatic radar processing systems, and, if not filtered, can produce frequent false alarms. A statistical study of anomalous propagation detected from two operational C-band radars in the northern Italian region of Emilia Romagna is discussed, paying particular attention to its diurnal and seasonal variability. The analysis shows a high incidence of anaprop in summer, mainly in the morning and evening, due to the humid and hot summer climate of the Po Valley, particularly in the coastal zone. Thereafter, a comparison between different techniques and datasets to retrieve the vertical profile of the refractive index gradient in the boundary layer is also presented. In particular, their capability to detect anomalous propagation conditions is compared. Furthermore, beam path trajectories are simulated using a multilayer ray-tracing model and the influence of the propagation conditions on the beam trajectory and shape is examined. High resolution radiosounding data are identified as the best available dataset to reproduce accurately the local propagation conditions, while lower resolution standard TEMP data suffers from interpolation degradation and Numerical Weather Prediction model data (Lokal Model) are able to retrieve a tendency to superrefraction but not to detect ducting conditions. Observing the ray tracing of the centre, lower and upper limits of the radar antenna 3-dB half-power main beam lobe it is concluded that ducting layers produce a change in the measured volume and in the power distribution that can lead to an additional error in the reflectivity estimate and, subsequently, in the estimated rainfall rate.

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Contamination of weather radar echoes by anomalous propagation (anaprop) mechanisms remains a serious issue in quality control of radar precipitation estimates. Although significant progress has been made identifying clutter due to anaprop there is no unique method that solves the question of data reliability without removing genuine data. The work described here relates to the development of a software application that uses a numerical weather prediction (NWP) model to obtain the temperature, humidity and pressure fields to calculate the three dimensional structure of the atmospheric refractive index structure, from which a physically based prediction of the incidence of clutter can be made. This technique can be used in conjunction with existing methods for clutter removal by modifying parameters of detectors or filters according to the physical evidence for anomalous propagation conditions. The parabolic equation method (PEM) is a well established technique for solving the equations for beam propagation in a non-uniformly stratified atmosphere, but although intrinsically very efficient, is not sufficiently fast to be practicable for near real-time modelling of clutter over the entire area observed by a typical weather radar. We demonstrate a fast hybrid PEM technique that is capable of providing acceptable results in conjunction with a high-resolution terrain elevation model, using a standard desktop personal computer. We discuss the performance of the method and approaches for the improvement of the model profiles in the lowest levels of the troposphere.

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The current operational very short-term and short-term quantitative precipitation forecast (QPF) at the Meteorological Service of Catalonia (SMC) is made by three different methodologies: Advection of the radar reflectivity field (ADV), Identification, tracking and forecasting of convective structures (CST) and numerical weather prediction (NWP) models using observational data assimilation (radar, satellite, etc.). These precipitation forecasts have different characteristics, lead time and spatial resolutions. The objective of this study is to combine these methods in order to obtain a single and optimized QPF at each lead time. This combination (blending) of the radar forecast (ADV and CST) and precipitation forecast from NWP model is carried out by means of different methodologies according to the prediction horizon. Firstly, in order to take advantage of the rainfall location and intensity from radar observations, a phase correction technique is applied to the NWP output to derive an additional corrected forecast (MCO). To select the best precipitation estimation in the first and second hour (t+1 h and t+2 h), the information from radar advection (ADV) and the corrected outputs from the model (MCO) are mixed by using different weights, which vary dynamically, according to indexes that quantify the quality of these predictions. This procedure has the ability to integrate the skill of rainfall location and patterns that are given by the advection of radar reflectivity field with the capacity of generating new precipitation areas from the NWP models. From the third hour (t+3 h), as radar-based forecasting has generally low skills, only the quantitative precipitation forecast from model is used. This blending of different sources of prediction is verified for different types of episodes (convective, moderately convective and stratiform) to obtain a robust methodology for implementing it in an operational and dynamic way.

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Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.

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Ground-penetrating radar (GPR) and microgravimetric surveys have been conducted in the southern Jura mountains of western Switzerland in order to map subsurface karstic features. The study site, La Grande Rolaz cave, is an extensive system in which many portions have been mapped. By using small station spacing and careful processing for the geophysical data, and by modeling these data with topographic information from within the cave, accurate interpretations have been achieved. The constraints on the interpreted geologic models are better when combining the geophysical methods than when using only one of the methods, despite the general limitations of two-dimensional (2D) profiling. For example, microgravimetry can complement GPR methods for accurately delineating a shallow cave section approximately 10 X 10 mt in size. Conversely, GPR methods can be complementary in determining cavity depths and in verifying the presence of off-line features and numerous areas of small cavities and fractures, which may be difficult to resolve in microgravimetric data.

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O GPR utiliza técnica indireta para investigação das estruturas de subsuperfície, sendo caracterizado como método não-invasivo, o qual permite extrair informações ao longo do perfil de solo sem perfurar, sondar ou escavar. Este trabalho teve o objetivo de avaliar a utilização do GPR no estabelecimento de atributos físicos do solo em área de cultivo com cana-de-açúcar, além de estabelecer sua correlação com o método do cilindro volumétrico. A área de estudo está localizada no município de Bom Sucesso - PR, sendo utilizada com cultura da cana há mais de 20 anos. Foram obtidas amostras de solos indeformadas com cilindro volumétrico nas profundidades de 0-0,1, 0,1-0,2, 0,2-0,3, 0,3-0,4 e 0,4-0,5 m, ao longo de três transeptos paralelos, sendo o central referente à linha de plantio (transepto 2) e os outros dois correspondentes às entrelinhas laterais (transeptos 1 e 3). Os valores de densidade e porosidade total, obtidos por meio das amostras físicas, foram inicialmente interpretados para verificar o estado do solo nas linhas e nas entrelinhas de cana, nas cinco profundidades. Posteriormente, foram correlacionados com os valores das constantes dielétricas (K) adquiridos pelo georradar, porém apenas para a camada de 0,4-0,5 m, uma vez que as camadas superficiais até a profundidade de 0,4 m não puderam ser avaliadas devido às limitações técnicas do equipamento, aliadas às condições físicas e químicas do solo, que acabaram por prejudicar as reflexões. A densidade mostrou-se menor nas linhas, quando comparada às entrelinhas, para as camadas de 0-0,1 e 0,2-0,3 m. A porosidade total foi menor nas entrelinhas do que nas linhas na camada de 0-0,1 m. Os valores de K foram maiores nas linhas, onde a umidade e a porosidade total foram maiores, e menores nas entrelinhas, onde as densidades encontravam se próximas ao limite crítico. A correlação de K com a densidade e porosidade total não foi significativa. Pequenas modificações na porosidade do solo em função do aumento da densidade foram suficientes para diminuir o valor de K nas entrelinhas, devido à redução na quantidade de água nos poros. Esse fato pode ser confirmado pela correlação de K com a umidade. Assim, pode-se dizer que o georradar foi extremamente sensível à variação de umidade no solo, apresentando melhores resultados para esta variável do que para a densidade e porosidade total determinada por meio do cilindro volumétrico.

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When concrete deterioration begins to occur in highway pavement, repairs become necessary to assure the rider safety, extend its useful life and restore its riding qualities. One rehabilitation technique used to restore the pavement to acceptable highway standards is to apply a thin portland cement concrete (PCC) overlay to the existing pavement. First, any necessary repairs are made to the existing pavement, the surface is then prepared, and the PCC overlay is applied. Brice Petrides-Donohue, Inc. (Donohue) was retained by the Iowa Department of Transportation (IDOT) to evaluate the present condition with respect to debonding of the PCC overlay at fifteen sites on Interstate 80 and State Highway 141 throughout the State of Iowa. This was accomplished by conducting an infrared thermographic and ground penetrating radar survey of these sites which were selected by the Iowa Department of Transportation. The fifteen selected sites were all two lanes wide and one-tenth of a mile long, for a total of three lane miles or 190,080 square feet. The selected sites are as follows: On Interstate 80 Eastbound, from milepost 35.25 to 35.35, milepost 36.00 to 36.10, milepost 37.00 to 37.10, milepost 38.00 to 38.10 and milepost 39.00 to 39.10, on State Highway 141 from milepost 134.00 to 134.10, milepost 134.90 to milepost 135.00, milepost 135.90 to 136.00, milepost 137.00 to 137.10 and milepost 138.00 to 138.10, and on Interstate 80 Westbound from milepost 184.00 to 184.10, milepost 185.00 to 185.10, milepost 186.00 to 186.10, milepost 187.00 to 187.10, and from milepost 188.00 to 188.10.

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A major issue in the application of waveform inversion methods to crosshole georadar data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a time-domain waveform inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little-to-no trade-off between the wavelet estimation and the tomographic imaging procedures.

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Advances in Near-surface Seismology and Ground-penetrating Radar (SEG Geophysical Developments Series No. 15) is a collection of original papers by renowned and respected authors from around the world. Technologies used in the application of near-surface seismology and ground-penetrating radar have seen significant advances in the last several years. Both methods have benefited from new processing tools, increased computer speeds, and an expanded variety of applications. This book, divided into four sections ? ?Reviews,? ?Methodology,? ?Integrative Approaches,? and ?Case Studies? ? captures the most significant cutting-edge issues in active areas of research, unveiling truly pertinent studies that address fundamental applied problems. This collection of manuscripts grew from a core group of papers presented at a postconvention workshop, ?Advances in Near-surface Seismology and Ground-penetrating Radar,? held during the 2009 SEG Annual Meeting in Houston, Texas. This is the first cooperative publication effort between the near-surface communities of SEG, AGU, and EEGS. It will appeal to a large and diverse audience that includes researchers and practitioners inside and outside the near-surface geophysics community.

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A major issue in the application of waveform inversion methods to crosshole ground-penetrating radar (GPR) data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a recently published time-domain inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity of both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little to no trade-off between the wavelet estimation and the tomographic imaging procedures.