Multi-directional wave spectra from marine X-band radar

The signal measured by heave–pitch–roll directional wave buoys yields the first four coefficients of a Fourier series. Data adaptive methods must be employed to estimate a directional wave spectrum. Marine X-band radars (MRs) have the advantage over buoys that they can measure “model-free” two-dimensional (2D) wave spectra. This study presents the first comprehensive validation of MR-derived multi-directional wave characteristics. It is based on wave data from the 2010 Impact of Typhoons on the Ocean in the Pacific (ITOP) experiment in the Philippine Sea, namely MR measurements from R/V Roger Revelle, Extreme Air–Sea Interaction (EASI) buoy measurements, as well as WAVEWATCH-III (WW3) modeling results. Buoy measurements of mean direction and spreading as function of frequency, which do not require data adaptive methods, are used to validate the WW3 wave spectra. An advanced MR wave retrieval technique is introduced that addresses various shortcomings of existing methods. Spectral partitioning techniques, applied to MR and WW3 results, reveal that multimodal seas are frequently present. Both data sets are in excellent agreement, tracking the evolution of up to 4 simultaneous wave systems over extended time periods. This study demonstrates MR’s and WW3’s strength at measuring and predicting 2D wave spectra in swell-dominated seas.     

Ability of a dual polarized X-band radar to estimate rainfall

The aim of this study is to assess rainfall estimates by a dual polarized X-band radar. This study was part of the European project FRAMEA (Flood forecasting using Radar in Alpine and Mediterranean Areas). Two radars were set up near the small town of Collobrières in South Eastern France. The first radar was a dual polarized X-band radar (Hydrix^®) associated with a ZPHI^® algorithm while the second one was an S-band radar (Météo France). We compared radar rainfall data with measurements obtained by two rain gauge networks (Météo France and Cemagref). During the experiments from February 2006 to June 2007, four significant rainfall events occurred. The accuracy of the rain rate obtained with both S-band and X-band radars decreased significantly beyond 60 km, in particular for the X-band radar. At closer ranges, such as 30–60 km from the radars, the X-band and the S-band radar retrievals showed similar performance with Nash criteria around 0.80 for the X-band radar and 0.75 for the S-band radar. Furthermore, the X-band radar did not require calibration on rainfall records, which tends to make it a useful method to assess rainfall in areas without a rain gauge network.     

Multi-hydro hydrological modelling of a complex peri-urban catchment with storage basins comparing C-band and X-band radar rainfall data

ABSTRACT

The spread of impervious surfaces in urban areas combined with the rise in the intensity of rainfall events as a result of climate change has led to dangerous increases in storm water flows. This paper discusses a new implementation of the fully distributed hydrological model Multi-Hydro (developed at École des Ponts ParisTech), when operating storage basins, and its ability to deal with high-resolution radar rainfall data. The peri-urban area of Massy (south of Paris, France) was selected as a case study for having six of these drainage facilities, used extensively in flood control. Two radar rainfall datasets with different spatiotemporal resolutions were used: Météo-France’s PANTHER rainfall product (C-band) and ENPC’s X-band DPSRI. The rainfall spatiotemporal variability was analysed statistically using Universal Multifractals (UM). Finally, to validate the application, the water level simulations were compared with local measurements in the Cora storage basin located next to the catchment’s single outlet.     

Stochastic estimation of facies using ground penetrating radar data

Explicitly defining large-scale heterogeneity is a necessary step of groundwater model calibration if accurate estimates of flow and transport are to be made. In this work, neural networks are used to estimate radar facies probabilities from ground penetrating radar (GPR) images, yielding stochastic facies-based models that honour the large-scale architecture of the subsurface. For synthetic GPR images, a neural network was able to correctly identify radar facies with an accuracy of approximately 90%. Manual interpretation of a set of 450 MHz GPR field data from the Borden aquifer resulted in the identification of four radar facies. Of these, a neural network was able to identify two facies with an accuracy of near 80% and one with an accuracy of 44%. The neural network was not able to identify the fourth facies, likely due to the choice of defining facies characteristics. Sequential indicator simulation was used to generate facies realizations conditioned to the radar facies probabilities. Numerical simulations indicate that significant improvements in the prediction of solute transport are possible when GPR is used to constrain the facies model compared to using well data alone, especially when data are sparse.This work was supported by funding to R. Knight under Grant No. DE-FG07–00ER15118-A000, Environmental Management Science Program, Office of Science and Technology, Office of Environment Management, United States Department of Energy (DOE). However, any opinions, findings, conclusions, or recommendations expressed herein are those of the authors and do not necessarily reflect the views of DOE. Further support was provided by a Stanford Graduate Fellowship to S. Moysey. The authors would also like to thank James Irving for his assistance with processing of the radar data.     

The generation ofK indices from digitally recorded magnetic data

TheK index was developed by Bartels and is a measure of geomagnetic activity. The important feature of this index is that it is a measure of solar activity superimposed on the regular daily variation.It is the most used estimate of activity being of particular interest to researchers in ionospheric physics and telecommunications.In response to increased availability of digital data from magnetic observatories and their demand by the scientific community it becomes desireable to check whetherK indices produced from magnetograms plotted from digital data are consistent with those handscaled from La Cour charts.This paper presents results of these comparisons and also reports on several methods tested to produce theK index directly from the digital data.Handscaled indices from digital plots are suitable for producing theK index. Computations using digital data do not reproduceK as defined by Bartels precisely but do provide an equivalent index which is satisfactory for most user and research purposes.     

Studying the fine structure of coherent echo spectra using data from Irkutsk incoherent scatter radar

Studying the processes generating different-scale inhomogeneities is one of the challenging problems of ionospheric physics. Plasma instabilities are one of the physical mechanisms by which small-scale inhomogeneities are formed. The main forms of instability in the ionospheric E-layer are two-stream and gradient-drift ones. The inhomogeneities generated by them lead to an abnormally intense radio scattering of different wavelengths (known as coherent echo (CE) or radio aurora) in the E-layer. Therefore, the method of radiowave backscattering is among the widely used methods for studying such inhomogeneities. The CE phenomenon has been investigated most intensely at high and equatorial latitudes, where the conditions for the CE origination are formed rather regularly. For the last decade, CE has also been intensely studied at midlatitudes, where it is observed less frequently and its formation conditions are less known. In 1998–2006, the purposeful studies of the midlatitude CE peculiarities were performed at the Irkutsk incoherent scatter (IS) radar, with a particular emphasis on its coherent properties. It was for the first time found out that the spectra of some data sets had a fine comb-shaped structure, which generated well-known single-humped CE spectra as a result of statistical averaging. In the scope of this study, unique coherent methods for processing individual data sets of CE signals were developed, making it possible to reveal the peculiarities of unaveraged CE-signal spectra. To describe these peculiarities, we proposed a new model of the inhomogeneity spectrum, which is the superposition of the discrete set of spatial harmonics with close wave numbers. The model was shown to adequately describe the scattered signal characteristics observed experimentally.     

Isostatic response of the Laccadive Ridge from admittance analysis of gravity and bathymetry data

The Laccadive Ridge (L-R), trending roughly parallel to the west coast of India, is an intriguing segment of the northernmost Chagos-Laccadive Ridge (C-L-R) system. Although crustal nature and isostatic response of the southern C-L-R is well known, there are no similar studies on the L-R. In the present study, the isostatic response of the lithosphere beneath the L-R is estimated so as to characterize its crustal nature, total crustal as well as effective elastic plate thickness and mode of compensation. Twelve gravity and bathymetry profiles across the ridge were analyzed using linear transfer function and forward model techniques. The observed admittance function within the diagnostic waveband of 250 < λ > 80 km (0.025 < k > 0.080 km⁻¹) fits well with (i) the Airy model whose average crustal thickness (T_c) and density are 17 ± 2 km and 2.7 × 10³ kg m⁻³, respectively, and (ii) the thin plate flexure model of isostasy with an effective elastic plate thickness (T_e) of 2–3 km. The estimated average crustal thickness and density are in good agreement with published seismic refraction results over the ridge. The results of the present study support an Airy model of isostasy for the L-R. The low T_e value, in view of other published results in the study area, suggests stretched and loaded continental lithosphere of the L-R during the evolution of the western continental margin of India.     

Mapping of a major paleodrainage system in eastern Libya using orbital imaging radar: The Kufrah River

Over the last few decades, remote sensing has revealed buried river channels in a number of regions worldwide, in many cases providing evidence of dramatic paleoenvironmental changes over Cenozoic time scales. Using orbital radar satellite imagery, we mapped a major paleodrainage system in eastern Libya, that could have linked the Kufrah Basin to the Mediterranean coast through the Sirt Basin, possibly as far back as the middle Miocene. Synthetic Aperture Radar images from the PALSAR sensor clearly reveal a 900 km-long river system, which starts with three main tributaries (north-eastern Tibesti, northern Uweinat and western Gilf Kebir/Abu Ras) that connect in the Kufrah oasis region. The river system then flows north through the Jebel Dalmah, and forms a large alluvial fan in the Sarir Dalmah. The sand dunes of the Calanscio Sand Sea prevent deep orbital radar penetration and preclude detailed reconstruction of any possible connection to the Mediterranean Sea, but a 300 km-long link to the Gulf of Sirt through the Wadi Sahabi paleochannel is likely. If this connection is confirmed, and its Miocene antiquity is established, then the Kufrah River, comparable in length to the Egyptian Nile, will have important implications for the understanding of the past environments and climates of northern Africa from the middle Miocene to the Holocene.     

Determination of noise spectra from strong motion data recorded in Greece

A large number of strong ground motions inGreece have been recorded by analogaccelerographs. The processing of analogstrong motion recordings and conversion toa digital form introduces noise in thesignal, due to the digitization andprocessing whichsignificantly affects the record. In thepresent paper a unified processing anddetermination of digitization andprocessing noise for the Greek strongmotion records is presented. Moreover,appropriate relations are proposed for thelower cut-off frequency with respect tothe epicentral distance and earthquakemagnitude for record filtering.     

Extracting rotational components of earthquake ground motion using data recorded at multiple stations

Rotational components of earthquake ground motion have not been considered for seismic analysis, design and performance assessment because recordings of these components are unavailable. A number of procedures have been proposed to extract rotational components of ground motion from translational time series recorded at multiple, closely spaced recording stations. In this paper, a new procedure that is capable of capturing higher frequency content in rotational time‐series is presented. The frequencies at which numerical errors are introduced in the solution, which are a function of apparent wave velocity and array dimension, are identified. Results are presented for the proposed procedure, the widely accepted geodetic method, and a single‐station procedure developed by the authors, all using data recorded at the Lotung array in Taiwan. Copyright © 2012 John Wiley & Sons, Ltd.     

Spatial reconstruction of rainfall fields from rain gauge and radar data

Rainfall is a phenomenon difficult to model and predict, for the strong spatial and temporal heterogeneity and the presence of many zero values. We deal with hourly rainfall data provided by rain gauges, sparsely distributed on the ground, and radar data available on a fine grid of pixels. Radar data overcome the problem of sparseness of the rain gauge network, but are not reliable for the assessment of rain amounts. In this work we investigate how to calibrate radar measurements via rain gauge data and make spatial predictions for hourly rainfall, by means of Monte Carlo Markov Chain algorithms in a Bayesian hierarchical framework. We use zero-inflated distributions for taking zero-measurements into account. Several models are compared both in terms of data fitting and predictive performances on a set of validation sites. Finally, rainfall fields are reconstructed and standard error estimates at each prediction site are shown via easy-to-read spatial maps.     

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.     

Mapping hydraulic biotopes using terrestrial laser scan data of water surface properties

For more than a decade, habitat mapping using biotopes (in‐channel hydraulically‐defined habitats) has underpinned aquatic conservation in the UK through (a) providing baseline information on system complexity and (b) allowing environmental and ecological change to be monitored and evaluated. The traditional method used is the subjective river habitat or corridor survey. This has recently been revised to include the floodplain via GeoRHS, but issues still exist concerning development of a national database due to the labour intensive nature of the data collection, subjectivity issues between samplers, temporal changes, the fuzzy nature of perceived habitats and habitat boundaries. This paper takes an innovative approach to biotope definition using high resolution spatial data to define water surface roughness for two representative reaches of the River South Tyne, Cumbria, and the River Rede, Northumberland, UK. Data was collected using a terrestrial laser scanner (TLS) and hydraulic variability simply expressed through assigning a local standard deviation value to a set of adjacent water surface values. Statistical linkage of these data with biotope locations defined visually in the field allowed complete mapping of the surveyed reach defining habitat and biotope areas to the fine scale resolution of the TLS data. Despite issues of data loss due to absorption and transmission through the water, the reflected signal generated an extremely detailed and objective map of the water surface roughness, which may be compared with known biotope locations as defined by visual identification in the field. The TLS accuracy achieved in the present study is comparable with those obtained using hyperspectral imagery: with 84% of the pool/glide/marginal deadwater amalgamated biotope, 88% of riffles, 57% of runs and 50% of the amalgamated cascade/rapid biotope successfully plotted. It is clear from this exercise that biotope distribution is more complex than previously mapped using subjective techniques, and based upon the water surface roughness delimiters presented in this study, the amalgamation of pools with glides and marginal deadwaters, riffles with unbroken standing waves, and cascades with rapids, is proposed. Copyright © 2010 John Wiley & Sons, Ltd     

Origin and compensation of Chagos-Laccadive ridge, Indian ocean, from admittance analysis of gravity and bathymetry data

The Chagos-Laccadive ridge (CLR) is a prominent aseismic, volcanic ridge in the northern Indian ocean. The ridge, together with the Southern Mascarene plateau (SMP), to which it is genetically related, is considered as a volcanic trace of the Reunion hotspot. We have examined the isostatic compensation of the CLR through transfer function analysis of gravity and bathymetry data along seven profiles. The analysis suggests that the CLR is compensated locally, with an Airy crustal thickness (T_c) of 20 km. The rather low elastic plate thickness (T_e) of about 4 km implies that the volcanism of the ridge took place very near a spreading centre. The proximity of the Chagos fracture zone indicates that the emplacement was probably near a spreading centre-transform junction.     

Estimation of effective source signatures from marine VSP data1

We present a simple method for estimating an effective source wavelet from the first arrival in marine vertical seismic profiling (VSP) data. The method, which utilizes the free-space Green's function of the Helmholz equation, is simple and very computer efficient. We show examples from synthetic and real offset and walkaway VSP data. In the synthetic examples, we show that data modelled with the estimated wavelet give small residuals when subtracted from the reference data. In the real data examples, we show that when modelling with the wavelet estimated from the real data, in a smooth macromodel, we obtain a good fit between the first arrivals in the real and modelled data.     

利用K-SVD字典学习算法压制海洋大地电磁噪声

海洋大地电磁数据处理的结果会影响数据反演和解释的准确性.在浅水中, 由海浪引起的强电磁干扰和大地电磁场叠加在一起, 使得噪声所在频段内的视电阻率和相位曲线出现畸变.针对这种强干扰, 本文将K-SVD字典学习算法应用于海洋大地电磁信号处理中, 通过稀疏表示海浪感应磁噪声实现大地电磁磁场信号的重构, 并结合视电阻率信息进行相位校正.仿真数据和南黄海实测数据的处理结果表明, 该方法能够有效压制海浪感应磁噪声, 恢复后的视电阻率和相位曲线更加连续、光滑.

     

Evapotranspiration modelling from climatic data using a neural computing technique

Evapotranspiration is one of the basic components of the hydrologic cycle and essential for estimating irrigation water requirements. This paper investigates the modelling of evapotranspiration using the feed‐forward artificial neural network (ANN) technique with the Levenberg–Marquardt (LM) training algorithm. The LM algorithm has never been used in evapotranspiration estimation before. The LM is used for the optimization of network weights, since this algorithm is more powerful and faster than the conventional gradient descent. Various combinations of daily climatic data, i.e. wind speed, air temperature, relative humidity and solar radiation, from three stations in Los Angeles, USA, are used as inputs to the ANN so as to evaluate the degree of effect of each of these variables on evapotranspiration. A comparison is made between the estimates provided by the ANN and those of the following empirical models: Penman, Hargreaves, Turc. Mean square error, mean absolute error and determination coefficient statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it was found that the neural computing technique could be employed successfully in modelling evapotranspiration process from the available climatic data. The results also indicate that the Hargreaves method provides better performance than the Penman and Turc methods in estimation of the evapotranspiration. The accuracy of the ANN technique in evapotranspiration estimation using nearby station data was also investigated. Copyright © 2007 John Wiley & Sons, Ltd.     

Handling non-linearity in radar data assimilation using the non-linear least squares enhanced POD-4DVar

The Proper Orthogonal Decomposition(POD)-based ensemble four-dimensional variational(4DVar) assimilation method(POD4DEnVar) was proposed to combine the strengths of EnKF(i.e.,the ensemble Kalman filter) and 4DVar assimilation methods.Recently,a POD4DEnVar-based radar data assimilation scheme(PRAS) was built and its effectiveness was demonstrated.POD4 DEnVar is based on the assumption of a linear relationship between the model perturbations(MPs)and the observation perturbations(OPs);however,this assumption is likely to be destroyed by the highly non-linear forecast model or observation operator.To address this issue,using the Gauss-Newton iterative method,the nonlinear least squares enhanced POD4 DEnVar algorithm(referred to as NLS-4DVar) was proposed.Naturally,the PRAS was upgraded to form the NLS-4DVar-based radar data assimilation scheme(NRAS).To evaluate the performance of NRAS against PRAS,observing system simulation experiments(OSSEs) were conducted to assimilate reflectivity and radial velocity individually,with one,two,and three iterations.The results demonstrated that the NRAS outperformed PRAS in improving the initial condition and the forecasting of model variables and rainfall.The NRAS,with a smaller number of iterations,can yield a convergent result.In contrast to the situation when assimilating radial velocity,the advantages of NRAS over PRAS were more obvious when assimilating reflectivity.