Quantization analysis of weather radar data with synthetic rainfall

Quantization is a process by where continuous signals are transformed into discrete values. It is an important part of the signal processing involved in using weather radar. Technological advances have made it easier to increase the number of quantization levels, as witnessed by the replacement of a 3 bit system by an 8 bit system by the UK Meteorological Office. Research has been conducted in the past demonstrating the error statistics of quantized rainfall, although these studies have used real radar data. The novelty of this study is in using synthetic rain, generated with a Poisson cluster model to represent hourly rainfall, and subsequently disaggregated using a fractal cascade to a fine 5 min time scale. The advantage of this approach is the length of time series that can be generated far outweighs the limited duration of historical rainfall series, especially at such fine time scales. This provides sufficient rainfall data, especially high intensity rainfall, to say something statistically significant about the error statistics. The models are parameterised for different months and also for a non-seasonal set. Rainfall is then generated for a summer case, a winter case, and for the non-seasonal case. It is discovered that the error distribution varies significantly as the parameters change for 3 bit rainfall. This error distribution is relatively constant for 8 bit data, within its working range (up to 126 mm/h). At a fine time scale, such high intensity events are not uncommon. This knowledge is useful when investigating historical radar data at lower quantization levels, for the purpose of flood frequency analysis, and remains relevant, especially, if as some studies have shown, the occurrence of high intensity storms is likely to increase.     

RAMAC／GPR探地雷达数据处理软件的自主开发与应用

分析研究了RAMAC／GPR探地雷达的数据结构,结合数据处理技术,利用Visual C＋＋编写了雷达数据处理软件,成图效果较好,为该类探地雷达数据的自主处理分析提供了高效率工具。     

探地雷达在多年冻土工程地质勘察中的应用效果研究

由于融土和冻土之间存在明显的电性差异,使探地雷达成为研究多年冻土的有效手段之一.本文结合工程实例,对探地雷达在青藏高原多年冻土工程地质勘察中的应用效果进行了现场试验研究.分析了探地雷达探测多年冻土的物理前提条件,总结了多年冻土主要地质要素的雷达图像特征和探地雷达在多年冻土工程地质勘察中的实际应用效果.研究表明融土与冻土的雷达图像特征存在明显差异:融土雷达反射波为低频强宽振幅的稀疏波,波形较杂乱;冻土反射波为高频低振幅细密波,波形较为规则;探地雷达可较为准确地划分地层、识别多年冻土上限、确定多年冻土分布范围,但尚不能有效确定多年冻土的含冰量;另外,探地雷达对细颗粒土的探测效果要明显好于粗颗粒土.文章还指出了现场探测和图像解译分析中需要注意的事项和下一步需要研究解决的问题,建议在开展现场探测工作之前先在有钻探资料或天然地质剖面处进行对比试验,搞清测区内主要地层的物性参数,掌握有效波和干扰波的分布规律,从而提高雷达探测结果的准确性和可靠性.     

Remigration of ground-penetrating radar data

Optimal electromagnetic wave propagation velocities and subsurface images for ground-penetrating radar (GPR) data can be specified by using an imaging scanning method. In addition to time-migrating the unmigrated GPR section, we remigrate the already time-migrated section by a one-step remigration operator using different velocities. This creates many time-migrated images for different constant migration velocities. In this way, the computation time for time-migration is very much reduced. Time-migrated reflector images `propagate' when the constant migration velocity is continuously changed. For this `propagation' there exists a wave-equation-type partial differential equation. Each time-migrated section can thus be viewed as a snapshot for a certain migration velocity. The time-migrated reflector images behave like `waves', called image waves. This is applied to real GPR data acquired over a concrete body within which a steel cable frame is buried. The method produces a quick velocity scan to find a reliable migration velocity leading to the best time-migrated image.     

浅层地震资料解释陷阱(英文)

高分辨率浅层地震方法是在近地表调查中使用最为广泛的方法。然而,在许多情况下,地震资料的解释经常会出现错误。在本文中,我们介绍了三个例子,分析了造成P波,SH波,多道的面波(MASW)地震资料解释的错误原因,大都是由于在表面或地下条件约束不确当引起的。第一个例子是P波反射剖面上的一个波的特征被解释为浅层断裂带,但后来证实它是由高水平的背景噪音引起的,因为采集测线通过了一个公路交叉口。第二个例子是SH波反射地震剖面上一个波特征被解释为是逆倾向滑断层,但有针对性的钻探表明,它是一个侵入到基岩面的一个深层局部侵蚀。最后,第三个例子,MASW调查剖面上,一个陡倾特征一开始被解释为基岩谷。然而,后来的钻探表明这是一个非常软的湖泊沉积物,后者严重损坏了应用面波频段。虽然最初的解释是不正确的,但这刺激地球物理学家和地质学家之间的讨论,并强调地球物理数据采集的时候,采集之前以及采集之后需要科学家之间有意义的合作与讨论。     

Parameterizing a physically based shallow landslide model in a data poor region

Shallow landslides and consequent debris flows are an increasing concern in the Western Ghats of Kerala, India. Their increased frequency has been associated with deforestation and unfavourable land‐use practices in cultivated areas. In order to evaluate the influence of vegetation on shallow slope failures a physically based, dynamic and distributed hydrological model (STARWARS) coupled with a probabilistic slope stability model (PROBSTAB) was applied to the upper Tikovil River basin (55·6 km²). It was tuned with the limited evidence of groundwater conditions during the monsoon season of 2005 and validated against observed landslide activity in the hydrological year 2001–2002. Given the data poor conditions in the region some modifications to the original model were in order, including the estimation of parameters on the basis of generalized information from secondary sources, pedo‐transfer functions, empirical equations and satellite remote sensing data. Despite the poor input, the model captured the general temporal and spatial pattern of instability in the area. Sensitivity analysis proved root cohesion, soil depth and angle of internal friction as the most dominant parameters influencing slope stability. The results indicate the importance of root cohesion in maintaining stability and the critical role of the management of rubber plantations in this. Interception and evapotranspiration showed little influence on the development of failure conditions. The study also highlights the importance of high resolution digital terrain models for the accurate mechanistic prediction of shallow landslide initiation. Copyright © 2009 John Wiley & Sons, Ltd.     

Ionospheric correction of space radar data

Radar is a critical tool for maintaining knowledge of the many objects in low Earth orbit and thus for maintaining confidence that societies around the world are secure against a variety of space-based threats. It is therefore important to raise awareness that LEO objects are embedded in the envelope of relatively dense plasma that co-rotates with the Earth (ionosphere-plasmasphere system) and thus accurate tracking must correct for the group delay and refraction caused by that system. This paper seeks to promote that awareness by reviewing those effects and high-lighting key issues: the need to customise correction to the altitude of the tracked object and prevailing space weather conditions, that ionospheric correction may be particularly important as an object approaches reentry. The paper outlines research approaches that should lead to better techniques for ionospheric correction and shows how these might be pursued in the context of the EURIPOS initiative.     

Integration of ground-penetrating radar and microgravimetric methods to map shallow caves

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 10×10 m² 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.     

MIDAS-W: a workstation-based incoherent scatter radar data acquisition system

The Millstone Hill Incoherent Scatter Data Acquisition System (MIDAS) is based on an abstract model of an incoherent scatter radar. This model is implemented in a hierarchical software system, which serves to isolate hardware and low-level software implementation details from higher levels of the system. Inherent in this is the idea that implementation details can easily be changed in response to technological advances. MIDAS is an evolutionary system, and the MIDAS hardware has, in fact, evolved while the basic software model has remained unchanged. From the earliest days of MIDAS, it was realized that some functions implemented in specialized hardware might eventually be implemented by software in a general-purpose computer. MIDAS-W is the realization of this concept. The core component of MIDAS-W is a Sun Microsystems UltraSparc 10 workstation equipped with an Ultrarad 1280 PCI bus analog to digital (A/D) converter board. In the current implementation, a 2.25 MHz intermediate frequency (IF) is bandpass sampled at 1 s intervals and these samples are multicast over a high-speed Ethernet which serves as a raw data bus. A second workstation receives the samples, converts them to filtered, decimated, complex baseband samples and computes the lag-profile matrix of the decimated samples. Overall performance is approximately ten times better than the previous MIDAS system, which utilizes a custom digital filtering module and array processor based correlator. A major advantage of MIDAS-W is its flexibility. A portable, single-workstation data acquisition system can be implemented by moving the software receiver and correlator programs to the workstation with the A/D converter. When the data samples are multicast, additional data processing systems, for example for raw data recording, can be implemented simply by adding another workstation with suitable software to the high-speed network. Testing of new data processing software is also greatly simplified, because a workstation with the new software can be added to the network without impacting the production system. MIDAS-W has been operated in parallel with the existing MIDAS-1 system to verify that incoherent scatter measurements by the two systems agree. MIDAS-W has also been used in a high-bandwidth mode to collect data on the November, 1999, Leonid meteor shower.     

小波分析在地震资料去噪中的应用

本文阐述了小波变换和去噪的基本原理,根据模拟信号和实际地震信号的频谱分析,讨论了如何选择小波基,及去噪中的阈值问题,从小波分解出发,利用多尺度分解对地震资进行分析,并基于MATLAB语言和小波工具箱,实现了对地震资料的去噪.     

远震层析成像在柴西狮子沟构造背景研究中的应用

利用2004——2007年在柴达木盆地西部狮子沟地区布设的地震台站的连续观测资料,挑选远震P波到时,采用远震体波走时层析成像方法进行反演处理,获得了该地区地下三维速度结构图象．反演结果表明,在研究观测地区西南侧存在一近北西走向的低速异常体,以较大倾角向北东方向插入;在该低速异常体的北部、东北部和东部环绕着相对高速的异常,其走向和分布范围基本与狮子沟背斜构造一致．      

AIC analysis of categorizing data for earthquakes and velocity structures in North China

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VHF radar observations of turbulent structures in the polar mesopause region

The mobile SOUSY VHF Radar was operated in the summer of 1987 during the MAC/SINE campaign in northern Norway to study the polar mesosphere summer echoes (PMSE). Measurements of the spectral width indicate that two types of structures occur. In general mesospheric layers are bifurcated exhibiting a narrow spectral width and a well-defined aspect sensitivity. However, for about 10% of the observation time cells of enhanced turbulence characterized by extremely broad spectral widths appear predominantly in the upper sublayer above 86 km. Identification and separation of beam and shear broadening allows a determination of the turbulence-induced component of the spectral width. This case study reveals that during several events these cloud-like structures of enhanced turbulence move with an apparent velocity of several tens of meters per second which is almost identical with the phase trace velocity of simultaneously observed waves. Since, at that time, the Richardson number was less than a quarter, it was concluded that these turbulent cells were generated by a Kelvin-Helmholtz mechanism. The horizontal extent of these structures was calculated to be less than 40 km. A general relation between spectral width and echo power was not detected. The turbulent component of the spectral width was used to calculate typical values of the energy dissipation rate at times where narrow spectral width dominates and during periods of enhanced turbulence. In addition, the outer scale of the inertial subrange (buoyancy scale) was estimated. For the first time the occurrence and motion of this type of structures of enhanced spectral width is analyzed and discussed in detail.     

Geoelectrical constraints on radar probing of shallow water-saturated zones within karstified carbonates in semi-arid environments

Shallow carbonates are of utmost importance as potential sources of groundwater in karstified semi-arid terrains. Ground-Penetrating Radar (GPR) is being increasingly used as a prominent mapping tool in such environments. However, its potential in exploring and identifying shallow water-saturated zones (WSZs) in carbonates is constrained by the geoelectrical properties of carbonate soils as a function of moisture content. We report results of a case study that includes laboratory geoelectrical characterization and their comparison to in situ GPR attenuation measurements performed on Cretaceous Edwards Formation rudist mounds in central Texas, which we hypothesize as analogs for water-bearing formations in semi-arid karstified carbonate terrains. Dielectric measurements on field-collected rock samples carried out in the laboratory under controlled conditions of moisture saturation suggest that real and imaginary parts of dielectric constants of rocks with higher porosity and/or permeability have steeper dependence on pore moisture content; they produce better dielectric contrasts but allow shallower penetration. Our analyses suggest that within carbonates, dielectric contrasts improve with decrease in sounding frequency and/or increase in moisture content; and the relationship between dielectric permittivity and moisture content may be represented by 3rd order polynomial equations. GPR surveys using a wide-band 400 MHz antenna reveal subsurface mound morphologies with heights of ～ 1–2 m and basal diameters of ～ 8–10 m resembling outcrop analogs. Each mound appears to be composed of smaller amalgamated lithounits that seem geoelectrically similar. Amplitudes decays of the backscattered radar signal correlate to moisture distribution. Measuring the differences in signal attenuation allows differentiation between saturated and non-saturated zones. Velocity analyses of GPR profiles enable estimation of moisture distribution in the vicinity of the mounds. Optimal delineation and production of high-resolution GPR data up to a depth of ～ 10 m were observed for a sounding frequency of ～ 250 MHz with moisture content of ～ 5% by weight. Below this moisture level, the dielectric contrast is insufficient to uniquely identify water-saturated zones from the surrounding geoelectrical context, and above it, the radar signal is substantially attenuated leading to a total inefficiency of the method.     

Recursive impedance inversion of ground-penetrating radar data in stochastic media

The travel time and amplitude of ground-penetrating radar (GPR) waves are closely related to medium parameters such as water content, porosity, and dielectric permittivity. However, conventional estimation methods, which are mostly based on wave velocity, are not suitable for real complex media because of limited resolution. Impedance inversion uses the reflection coefficient of radar waves to directly calculate GPR impedance and other parameters of subsurface media. We construct a 3D multiscale stochastic medium model and use the mixed Gaussian and exponential autocorrelation function to describe the distribution of parameters in real subsurface media. We introduce an elliptical Gaussian function to describe local random anomalies. The tapering function is also introduced to reduce calculation errors caused by the numerical simulation of discrete grids. We derive the impedance inversion workflow and test the calculation precision in complex media. Finally, we use impedance inversion to process GPR field data in a polluted site in Mongolia. The inversion results were constrained using borehole data and validated by resistivity data.     

Bayesian frequency-domain blind deconvolution of ground-penetrating radar data

Enhancing the resolution and accuracy of surface ground-penetrating radar (GPR) reflection data by inverse filtering to recover a zero-phased band-limited reflectivity image requires a deconvolution technique that takes the mixed-phase character of the embedded wavelet into account. In contrast, standard stochastic deconvolution techniques assume that the wavelet is minimum phase and, hence, often meet with limited success when applied to GPR data. We present a new general-purpose blind deconvolution algorithm for mixed-phase wavelet estimation and deconvolution that (1) uses the parametrization of a mixed-phase wavelet as the convolution of the wavelet's minimum-phase equivalent with a dispersive all-pass filter, (2) includes prior information about the wavelet to be estimated in a Bayesian framework, and (3) relies on the assumption of a sparse reflectivity. Solving the normal equations using the data autocorrelation function provides an inverse filter that optimally removes the minimum-phase equivalent of the wavelet from the data, which leaves traces with a balanced amplitude spectrum but distorted phase. To compensate for the remaining phase errors, we invert in the frequency domain for an all-pass filter thereby taking advantage of the fact that the action of the all-pass filter is exclusively contained in its phase spectrum. A key element of our algorithm and a novelty in blind deconvolution is the inclusion of prior information that allows resolving ambiguities in polarity and timing that cannot be resolved using the sparseness measure alone. We employ a global inversion approach for non-linear optimization to find the all-pass filter phase values for each signal frequency. We tested the robustness and reliability of our algorithm on synthetic data with different wavelets, 1-D reflectivity models of different complexity, varying levels of added noise, and different types of prior information. When applied to realistic synthetic 2-D data and 2-D field data, we obtain images with increased temporal resolution compared to the results of standard processing.     

Long-term diagnostics of precipitation estimates and the development of radar hardware monitoring within a radar product data quality management system

Abstract

Quality is key to ensuring that the potential offered by weather radar networks is realized. To achieve optimum quality, a comprehensive radar data quality management system, designed to monitor the end-to-end radar data processing chain and evaluate product quality, is being developed at the UK Met Office. Three contrasting elements of this system are described: monitoring of key radar hardware performance indicators; generation of long-term integrations of radar products; and monitoring of radar reflectivity factor using synthesized observations from numerical weather prediction model fields. Examples of each component are presented and ways in which the different types of monitoring information have been used to both identify issues with the radar product data quality and help formulate solutions are given.

Editor Z.W. Kundzewicz; Guest editor R.J. Moore

Citation Harrison, D., Georgiou, S., Gaussiat, N., and Curtis, A., 2013. Long-term diagnostics of precipitation estimates and the development of radar hardware monitoring within a radar product data quality management system. Hydrological Sciences Journal, 59 (7), 1327–1342. http://dx.doi.org/10.1080/02626667.2013.841316     

Application of third generation shallow water wave models in a tidal environment

Wave modeling was performed in the German Bight of the North Sea during November 2002, using the spectral wave models, namely the K-model and Simulating WAves Nearshore (SWAN), both developed for applications in environments of shallow water depths. These models mainly differ with respect to their dissipation source term expressions and in exclusion or inclusion of nonlinear wave–wave interactions. The K-model uses nonlinear dissipation and bottom dissipation, and neglects quadruplet wave–wave interaction whereas, SWAN includes, besides bottom dissipation, dissipation by white-capping and depth induced wave breaking and triad wave–wave interaction. The boundary spectra were extracted from the WAM model results of a North Sea hindcast of the HIPOCAS project, wind fields, tidal current and water level variations from the results of models used in the Belawatt project. The purpose of this study was to test the performance of both wave models to see whether they were able to predict near-shore wave conditions accurately. The runs were performed with and without tidal current and level variations to determine their effect on the waves. Comparisons of model results with buoy measurements show that taking into account tides and currents improve the spectral shape especially in areas of high current speeds. Whereas SWAN performed better in terms of spectral shape, especially in case of two peaked spectra, the K-model showed better results in terms of integrated parameters.Responsible Editor: Hans Burchard     

Mapping bathymetry using X-band marine radar data recorded from a moving vessel

Marine radars mounted on ships can provide remarkable insights into ocean behaviour from distances of several kilometres, placing other in situ observations and the environment around a ship into a wider oceanographic context. It has been known for some time that it is possible to map shallow water bathymetry and currents using radar image sequences recorded from shore based stations. However, a long standing question from military and hydrographic communities has been whether such techniques can be applied to radar data collected by moving vessels. If so, this presents the possibility of mapping large areas of shallow or coastal seas (albeit with a somewhat coarse horizontal resolution of 50–100 m) prior to the surveying vessel actually having to travel into potentially uncharted or dangerous shallow water areas. Trial sets of radar data were recorded by the Canadian Forces Auxiliary Vessel Quest using a Wamos radar digitiser connected to a Decca navigation radar during a number of deployments around Nova Scotia in 2008 and 2009. Georeferencing corrections derived from the existing ship navigation systems were sufficient to allow the application of the existing depth inversion analysis designed for static radar installations. This paper presents the results of bathymetry analyses of two datasets recorded from CFAV Quest while the vessel was travelling at speeds of up to 14 knots. The bathymetry derived from the radar data compare favourably with independent surveys and with the on-board echo sounder to depths of approximately 50 m.