bluuebunny/crossref_metadata_2025 huggingface dataset:
Downstream and soaring interfaces and vortices in 2-D stratified wakes and their impact on transport of contaminants
Authors: Chashechkin Y. D. , Mitkin V. V. , Bardakov R. N.
Published: April 2010

Abstract. The flow of continuously stratified fluids past obstacles was studied analytically, numerically, and experimentally. The obstacles discussed here include a flat strip, aligned with the flow, inclined or transverse to the flow and a horizontal cylinder. In the flow pattern, transient and attached (lee) internal waves, downstream wakes with submerged interfaces and vortices, soaring singular interfaces, soaring vortices and vortex systems are distinguished. New components of laminar flow past a horizontally towed strip are presented. Fine transverse streaky structures on the strip in the downstream wake were visualized. Soaring isolated interfaces, which are internal boundary layers forming inside the downstream attached wave field past bluff bodies were observed. With increasing of the body velocity a vortex pair was formed directly at the leading edge of this interface.
Statistical characteristics of surrogate data based on geophysical measurements
Authors: Venema V. , Bachner S. , Rust H. W. , Simmer C.
Published: April 2010

Abstract. In this study, the statistical properties of a range of measurements are compared with those of their surrogate time series. Seven different records are studied, amongst others, historical time series of mean daily temperature, daily rain sums and runoff from two rivers, and cloud measurements. Seven different algorithms are used to generate the surrogate time series. The best-known method is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm, which is able to reproduce the measured distribution as well as the power spectrum. Using this setup, the measurements and their surrogates are compared with respect to their power spectrum, increment distribution, structure functions, annual percentiles and return values. It is found that the surrogates that reproduce the power spectrum and the distribution of the measurements are able to closely match the increment distributions and the structure functions of the measurements, but this often does not hold for surrogates that only mimic the power spectrum of the measurement. However, even the best performing surrogates do not have asymmetric increment distributions, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found deviations of the structure functions on small scales.
Characterisation of long-term climate change by dimension estimates of multivariate palaeoclimatic proxy data
Authors: Donner R. , Witt A.
Published: April 2010

Abstract. The problem of extracting climatically relevant information from multivariate geological records is tackled by characterising the eigenvalues of the temporarily varying correlation matrix. From these eigenvalues, a quantitative measure, the linear variance decay (LVD) dimension density, is derived. The LVD dimension density is shown to serve as a suitable estimate of the fractal dimension density. Its performance is evaluated by testing it for (i) systems with independent components and for (ii) subsystems of spatially extended linearly correlated systems. The LVD dimension density is applied to characterise two geological records which contain information about climate variability during the Oligocene and Miocene. These records consist of (a) abundances of different chemical trace elements and (b) grain-size distributions obtained from sediment cores offshore the East Antarctic coast. The presented analysis provides evidence that the major climate change associated with the Oligocene-Miocene transition is reflected in significant changes of the LVD dimension density. This is interpreted as a change of the interrelationships between different trace elements in the sediment and to a change of the provenance area of the deposited sediment.
Unstable periodic motion in turbulent flows
Authors: Kawahara G. , Kida S. , van Veen L.
Published: April 2010

Abstract. Recently found unstable time-periodic solutions to the incompressible Navier-Stokes equation are reviewed to discuss their relevance to plane Couette turbulence and isotropic turbulence. It is shown that the periodic motion embedded in the Couette turbulence exhibits a regeneration cycle of near-wall coherent structures, which consists of formation and breakdown of streamwise vortices and low-velocity streaks. In phase space a turbulent state wanders around the corresponding periodic orbit for most of the time, so that the root-mean-squares of velocity fluctuations of the Couette turbulence agree very well with the temporal averages of those along the periodic orbit. The Kolmogorov universal-range energy spectrum is observed for the periodic motion embedded in high-symmetric turbulence at the Taylor-microscale Reynolds number Reλ=67. A laminarization strategy inspired by investigation of the phase-space structure in the vicinity of the unstable periodic orbit is presented for the Couette turbulence.
On effect of precession-induced flows in the liquid core for early Earth's history
Authors: Shalimov S. L.
Published: April 2010

Abstract. Secondary and tertiary flow patterns seen in experiments simulating flow in the Earth's liquid core induced by luni-solar precession of the solid mantle (Vanyo et al., 1995) hint at the development of non-axisymmetric columnar periodic structures. A simple interpretation of the structure formation is presented in a hydrodynamic approach. It is suggested that if similar flow patterns can occur in the Earth's liquid core enclosed into precessing and rotating mantle then kinematic of the flows may be regarded as a possible geodynamo mechanism for early Earth's history (before the solid core formation).
An efficient nonlinear cardinal B-spline model for high tide forecasts at the Venice Lagoon
Authors: Wei H. L. , Billings S. A.
Published: April 2010

Abstract. An efficient class of nonlinear models, constructed using cardinal B-spline (CBS) basis functions, are proposed for high tide forecasts at the Venice lagoon. Accurate short term predictions of high tides in the lagoon can easily be calculated using the proposed CBS models.
Finite amplitudes helical waves on the surface of the conducting fluid earth core as an example of the self-exciting homopolar heterogeneous dynamo
Authors: Glazkov V. V. , Sinkevich O. A.
Published: April 2010

Abstract. Helical waves of the finite amplitude on a surface of the fluid conducting Earth core are examined for generation of the magnetic field. Estimates are made for the differentially rotating cylindrical conducting fluid body, with the helical surface wave structure on its top. This structure is similar to the self-exciting Faraday-disk homopolar heterogeneous dynamo. Estimations of angular velocity and magnetic field magnitude for a polar vortex on the surface of the Earth's liquid outer core gives reasonable numbers and proves this hypothesis to be of value for further detailed analysis. As magnetic field generation by the helical structure is a surface effect, it is possible to find connection between Earth magnetic field fluctuations and fast relief changes on the iron fluid core – the silicate mantle boundary of the Earth.
Synchronicity in predictive modelling: a new view of data assimilation
Authors: Duane G. S. , Tribbia J. J. , Weiss J. B.
Published: April 2010

Abstract. The problem of data assimilation can be viewed as one of synchronizing two dynamical systems, one representing "truth" and the other representing "model", with a unidirectional flow of information between the two. Synchronization of truth and model defines a general view of data assimilation, as machine perception, that is reminiscent of the Jung-Pauli notion of synchronicity between matter and mind. The dynamical systems paradigm of the synchronization of a pair of loosely coupled chaotic systems is expected to be useful because quasi-2D geophysical fluid models have been shown to synchronize when only medium-scale modes are coupled. The synchronization approach is equivalent to standard approaches based on least-squares optimization, including Kalman filtering, except in highly non-linear regions of state space where observational noise links regimes with qualitatively different dynamics. The synchronization approach is used to calculate covariance inflation factors from parameters describing the bimodality of a one-dimensional system. The factors agree in overall magnitude with those used in operational practice on an ad hoc basis. The calculation is robust against the introduction of stochastic model error arising from unresolved scales.
Large- and small-scale turbulent spectra in MHD and atmospheric flows
Authors: Chkhetiani O. G. , Eidelman A. , Golbraikh E.
Published: April 2010

Abstract. In the present review we discuss certain studies of large- and small-scale turbulent spectra in MHD and atmospheric flows performed by S. S. Moiseev and his co-authors during the last years of his life and continued by his co-authors after he passed away. It is shown that many ideas developed in these works have not lost their novelty and urgency until now, and can form the basis of future studies in this field.
Detecting unstable structures and controlling error growth by assimilation of standard and adaptive observations in a primitive equation ocean model
Authors: Uboldi F. , Trevisan A.
Published: April 2010

Abstract. Oceanic and atmospheric prediction is based on cyclic analysis-forecast systems that assimilate new observations as they become available. In such observationally forced systems, errors amplify depending on their components along the unstable directions; these can be estimated by Breeding on the Data Assimilation System (BDAS). Assimilation in the Unstable Subspace (AUS) uses the available observations to estimate the amplitude of the unstable structures (computed by BDAS), present in the forecast error field, in order to eliminate them and to control the error growth. For this purpose, it is crucial that the observational network can detect the unstable structures that are active in the system. These concepts are demonstrated here by twin experiments with a large state dimension, primitive equation ocean model and an observational network having a fixed and an adaptive component. The latter consists of observations taken each time at different locations, chosen to target the estimated instabilities, whose positions and features depend on the dynamical characteristics of the flow. The adaptive placement and the dynamically consistent assimilation of observations (both relying upon the estimate of the unstable directions of the data-forced system), allow to obtain a remarkable reduction of errors with respect to a non-adaptive setting. The space distribution of the positions chosen for the observations allows to characterize the evolution of instabilities, from deep layers in western boundary current regions, to near-surface layers in the eastward jet area.
Determining the verse of magnetic turbulent cascades in the Earth's magnetospheric cusp via transfer entropy analysis: preliminary results
Authors: Materassi M. , Wernik A. , Yordanova E.
Published: April 2010

Abstract. The inter-scale coupling in the dynamics of the magnetic field in the Earth's magnetospheric cusp is studied with the technique of transfer entropy. This is a non-linear data analysis technique conceived to determine which is the process that plays the role of the "dynamical driver" between two processes interacting. The time series of the magnetic field components measured along the trajectory of a spacecraft through the cusp are decomposed via continuous wavelets, so a time series of the square modulus of the wavelet coefficients may be associated to each scale ℓ considered. The coupling between to two nearby scales is studied, with the purpose of singling out turbulent cascade directions from large to small scales and viceversa. Preliminary physical conclusions are proposed.
Prediction of minimum temperatures in an alpine region by linear and non-linear post-processing of meteorological models
Authors: Eccel E. , Ghielmi L. , Granitto P. , Barbiero R. , Grazzini F. , Cesari D.
Published: April 2010

Abstract. Model Output Statistics (MOS) refers to a method of post-processing the direct outputs of numerical weather prediction (NWP) models in order to reduce the biases introduced by a coarse horizontal resolution. This technique is especially useful in orographically complex regions, where large differences can be found between the NWP elevation model and the true orography. This study carries out a comparison of linear and non-linear MOS methods, aimed at the prediction of minimum temperatures in a fruit-growing region of the Italian Alps, based on the output of two different NWPs (ECMWF T511–L60 and LAMI-3). Temperature, of course, is a particularly important NWP output; among other roles it drives the local frost forecast, which is of great interest to agriculture. The mechanisms of cold air drainage, a distinctive aspect of mountain environments, are often unsatisfactorily captured by global circulation models. The simplest post-processing technique applied in this work was a correction for the mean bias, assessed at individual model grid points. We also implemented a multivariate linear regression on the output at the grid points surrounding the target area, and two non-linear models based on machine learning techniques: Neural Networks and Random Forest. We compare the performance of all these techniques on four different NWP data sets. Downscaling the temperatures clearly improved the temperature forecasts with respect to the raw NWP output, and also with respect to the basic mean bias correction. Multivariate methods generally yielded better results, but the advantage of using non-linear algorithms was small if not negligible. RF, the best performing method, was implemented on ECMWF prognostic output at 06:00 UTC over the 9 grid points surrounding the target area. Mean absolute errors in the prediction of 2 m temperature at 06:00 UTC were approximately 1.2°C, close to the natural variability inside the area itself.
Magnetic holes in plasmas close to the mirror instability
Authors: Borgogno D. , Passot T. , Sulem P. L.
Published: April 2010

Abstract. Non-propagating magnetic hole solutions in anisotropic plasmas near the mirror instability threshold are investigated in numerical simulations of a fluid model that incorporates linear Landau damping and finite Larmor radius corrections calculated in the gyrokinetic approximation. This FLR-Landau fluid model reproduces the subcritical mirror bifurcation recently identified on the Vlasov-Maxwell system, both by theory and numerics. Stable magnetic hole solutions that display a polarization different from that of Hall-MHD solitons are indeed obtained slighlty below threshold, while magnetic patterns and spatio-temporal chaos emerge when the system is maintained in a mirror unstable regime.
Rényi dimensions and pedodiversity indices of the earth pedotaxa distribution
Authors: Caniego F. J. , Ibáñez J. J. , San José Martínez F.
Published: April 2010

Abstract. Pedodiversity, the study and measurement of soil diversity, may be considered as a framework to analyze spatial patterns. Recently, selfsimilar multifractal patterns have been recently reported in the pedotaxa-abundance distributions at the planetary scale. This is the result to be expected from the complexity of earth soil systems. When the state of soil is understood as the outcome of nonlinear chaotic dynamic, highly irregular patterns with so-called multifractal behavior should be common. This opens the opportunity to use parameters of fractal theory to characterize pedodiversity. We compute Rényi generalized dimensions for the abundance distribution of pedotaxa for the five landmasses and the whole World drawn from the most detailed available global dataset based on the second level of the FAO 1974 classification units. We explore the effective relationship between diversity indices and Rényi dimensions. We show how multifractal analysis unifies diversity indices and how they should be interpreted offering a coherent perspective with a single mathematical procedure to analyze spatial patterns of the pedosphere.
Numerical simulations of the charging of dust particles by contact with hot plasmas
Authors: Miloch W. J. , Pécseli H. L. , Trulsen J.
Published: April 2010

Abstract. Charging of individual dust particles in contact with hot plasmas is studied by numerical methods. The dust particle is treated as a rigid solid body, composed by either perfectly insulating or conducting material. The collisionless plasma, consisting of electrons and singly charged ions, is simulated by Particle-in-Cell methods in two spatial dimensions. It is demonstrated that the surface conditions, i.e. roughness, of the dust particles are significant for the charging. In a streaming plasma, a dust grain develops an electric dipole moment which varies systematically with the relative plasma flow. The strength and direction of this dipole moment depends critically on the material. We observe also Langmuir oscillations excited in the vicinity of the particles, and analyze the spatial variation of their spectral distribution.
Analysis of global geomagnetic variability
Authors: Anh V. , Yu Z.-G. , Wanliss J. A.
Published: April 2010

Abstract. The orthogonal field components from global INTERMAGNET magnetometer stations are studied via multifractal detrended fluctuation analysis to determine whether there are clear and consistent regional patterns in the behavior of the fluctuations. There are three distinct scaling regimes in the qth-order fluctuation function for each of the 24 stations studied covering Southwest North America, Northeast North America, Central Europe, Northern Europe, Australasia and Asia. There is a consistent break point at time scale around 23 h for all stations. The scaling exponents of the second-order fluctuation functions reflect the regional character of the stations, and can be used for station classification, and for possible regional models.
A comparison of the performance of 4D-Var in an explicit and implicit version of a nonlinear barotropic ocean model
Authors: Terwisscha van Scheltinga A. D. , Dijkstra H. A.
Published: April 2010

Abstract. A comparison is made of the performance of the four-dimensional variational data assimilation (4D-Var) method in an explicit and implicit version of a barotropic quasi-geostrophic model of the wind-driven double-gyre ocean circulation. As is well known, implicit methods have the advantage that relatively large time steps can be taken with respect to explicit methods, but the computational costs of each time step is larger. We focus here on two issues: (i) the computational efficiency in the range of time steps where the chosen explicit method is still numerically stable and (ii) the performance of 4D-Var in the implicit model for time steps out of reach for the explicit model. For the same time step Δt and the same number of points n per assimilation interval, the analyses in the implicit model is always more accurate than that in the explicit model. Due to this property the use of 4D-Var combined with the implicit model can be computationally more efficient than its use in the explicit model.
Modeling pairwise dependencies in precipitation intensities
Authors: Vrac M. , Naveau P. , Drobinski P.
Published: April 2010

Abstract. In statistics, extreme events are classically defined as maxima over a block length (e.g. annual maxima of daily precipitation) or as exceedances above a given large threshold. These definitions allow the hydrologist and the flood planner to apply the univariate Extreme Value Theory (EVT) to their time series of interest. But these strategies have two main drawbacks. Firstly, working with maxima or exceedances implies that a lot of observations (those below the chosen threshold or the maximum) are completely disregarded. Secondly, this univariate modeling does not take into account the spatial dependence. Nearby weather stations are considered independent, although their recordings can show otherwise. To start addressing these two issues, we propose a new statistical bivariate model that takes advantages of the recent advances in multivariate EVT. Our model can be viewed as an extension of the non-homogeneous univariate mixture. The two strong points of this latter model are its capacity at modeling the entire range of precipitation (and not only the largest values) and the absence of an arbitrarily fixed large threshold to define exceedances. Here, we adapt this mixture and broaden it to the joint modeling of bivariate precipitation recordings. The performance and flexibility of this new model are illustrated on simulated and real precipitation data.
On the interaction of wind and steep gravity wave groups using Miles' and Jeffreys' mechanisms
Authors: Touboul J. , Kharif C. , Pelinovsky E. , Giovanangeli J.-P.
Published: April 2010

Abstract. The interaction of wind and water wave groups is investigated theoretically and numerically. A steep wave train is generated by means of dispersive focusing, using both the linear theory and fully nonlinear equations. The linear theory is based on the Schrödinger equation while the nonlinear approach is developed numerically within the framework of the potential theory. The interaction between the chirped wave packet and wind is described by the Miles' mechanism. The differences between both approaches are discussed, and the influence of nonlinearity is emphasized. Furthermore, a different mechanism is considered, described by the modified Jeffreys' sheltering theory. From comparison between the two mechanisms, it is found that the persistence of the steep wave group depends on the physical model used, and is significantly increased when we use the latter mechanism.
Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis
Authors: Bocquet M.
Published: April 2010

Abstract. For a start, recent techniques devoted to the reconstruction of sources of an atmospheric tracer at continental scale are introduced. A first method is based on the principle of maximum entropy on the mean and is briefly reviewed here. A second approach, which has not been applied in this field yet, is based on an exact Bayesian approach, through a maximum a posteriori estimator. The methods share common grounds, and both perform equally well in practice. When specific prior hypotheses on the sources are taken into account such as positivity, or boundedness, both methods lead to purposefully devised cost-functions. These cost-functions are not necessarily quadratic because the underlying assumptions are not Gaussian. As a consequence, several mathematical tools developed in data assimilation on the basis of quadratic cost-functions in order to establish a posteriori analysis, need to be extended to this non-Gaussian framework. Concomitantly, the second-order sensitivity analysis needs to be adapted, as well as the computations of the averaging kernels of the source and the errors obtained in the reconstruction. All of these developments are applied to a real case of tracer dispersion: the European Tracer Experiment [ETEX]. Comparisons are made between a least squares cost function (similar to the so-called 4D-Var) approach and a cost-function which is not based on Gaussian hypotheses. Besides, the information content of the observations which is used in the reconstruction is computed and studied on the application case. A connection with the degrees of freedom for signal is also established. As a by-product of these methodological developments, conclusions are drawn on the information content of the ETEX dataset as seen from the inverse modelling point of view.
How does the quality of a prediction depend on the magnitude of the events under study?
Authors: Hallerberg S. , Kantz H.
Published: April 2010

Abstract. We investigate the predictability of extreme events in time series. The focus of this work is to understand, under which circumstances large events are better predictable than smaller events. Therefore we use a simple prediction algorithm based on precursory structures which are identified via the maximum likelihood principle. Using theses precursory structures we predict threshold crossings in autocorrelated processes of order one, which are either Gaussian, exponentially or Pareto distributed. The receiver operating characteristic curve is used as a measure for the quality of predictions we find that the dependence on the event magnitude is closely linked to the probability distribution function of the underlying stochastic process. We evaluate this dependence on the probability distribution function numerically and in the Gaussian case also analytically. Furthermore, we study predictions of threshold crossings in correlated data, i.e., velocity increments of a free jet flow. The velocity increments in the free jet flow are in dependence on the time scale either asymptotically Gaussian or asymptotically exponential distributed. If we assume that the optimal precursory structures are used to make the predictions, we find that large threshold crossings are for all different types of distributions better predictable. These results are in contrast to previous results, obtained for the prediction of large increments, which showed a strong dependence on the probability distribution function of the underlying process.
Spatial relationship between δ15N and elevation in agricultural landscapes
Authors: Biswas A. , Si B. C. , Walley F. L.
Published: April 2010

Abstract. Understanding of the nitrogen (N) cycle and its spatial variability is important for managing ecosystems. Soil δ15N, as an important indicator of different soil nitrogen cycling processes, may provide critical information about the spatial variability in soil N cycling. The objective of this study was to examine the dominant landscape scale variability of δ15N, the location of the variability and its spatial relationship with elevation. Soil δ15N and elevation were measured along two transects (Davidson and Elstow, Saskatchewan, Canada). Each transect had 128 points with 3 m sampling intervals. Higher δ15N values typically occurred in topographic depressions as compared to knolls. The coefficient of determination revealed a significant linear relationship between δ15N and elevation (r2=0.27) at Davidson whereas no relationship (r2=0.00) was detected for the Elstow transect. However, wavelet spectra, cross wavelet, and squared wavelet coherency analysis revealed spatial relationships between δ15N and elevation at both sites. A strong coherency between δ15N and elevation at large scales (96 m or more) was detected for both transects. The Davidson transect showed an out of phase coherency at a topographically elevated area at the beginning and the end of the transect. The Elstow transect had a strong out of phase correlation (negative relationship) at the middle of the transect (corresponding to a depressions) indicating a location dependent relationship between δ15N and elevation. The relationship between δ15N and elevation reflects the effects of hydrology and soil water content over the landscape on N cycling processes.
Solar cycle dependence of scaling in solar wind fluctuations
Authors: Chapman S. C. , Hnat B. , Kiyani K.
Published: April 2010

Abstract. In this review we collate recent results for the statistical scaling properties of fluctuations in the solar wind with a view to synthesizing two descriptions: that of evolving MHD turbulence and that of a scaling signature of coronal origin that passively propagates with the solar wind. The scenario that emerges is that of coexistent signatures which map onto the well known "two component" picture of solar wind magnetic fluctuations. This highlights the need to consider quantities which track Alfvénic fluctuations, and energy and momentum flux densities to obtain a complete description of solar wind fluctuations.
The effect of upstream turbulence and its anisotropy on the efficiency of solar wind – magnetosphere coupling
Authors: Jankovičová D. , Vörös Z. , Šimkanin J.
Published: April 2010

Abstract. The importance of space weather and its forecasting is growing as interest in studying geoeffective processes in the Sun – solar wind – magnetosphere – ionosphere coupled system is increasing. This paper introduces the proper selection criteria for solar wind magnetic turbulence events during duskward electric field and southward Bz driven geomagnetic storms. Two measures for the strength of solar wind fluctuations were investigated: the standard deviations of magnetic field components and a proxy for the so-called Shebalin anisotropy angles. These measures were compared to the strength of geomagnetic storms obtained from a SYM-H index time series. We found a weak correlation between standard deviation of interplanetary magnetic field GSM component Bz and SYM-H index, and a strong correlation between Shebalin anisotropy angle and the SYM-H index, which can be the result of an increase of probability of magnetic reconnection in fluctuating magnetic fields.
A propagation-separation approach to estimate the autocorrelation in a time-series
Authors: Divine D. V. , Polzehl J. , Godtliebsen F.
Published: April 2010

Abstract. The paper presents an approach to estimate parameters of a local stationary AR(1) time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1) model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes.
Statistical analysis of transfer of fluctuations in solar wind turbulence
Authors: Strumik M. , Macek W. M.
Published: April 2010

Abstract. We present results of statistical analysis of the transfer of fluctuations in solar wind turbulence. We investigate the dynamics of the slow solar wind using an approach based on the Markov processes theory and experimental data measured by ACE spacecraft. In particular, we test whether the Chapman-Kolmogorov equation is approximately satisfied for the turbulent cascade. We consider the following cases of transfer of fluctuations: magnetic-to-magnetic, velocity-to-velocity, velocity-to-magnetic, and magnetic-to-velocity. In all these cases, the obtained results confirm local character of the transfer of fluctuations.
Time averaged properties along unstable periodic orbits and chaotic orbits in two map systems
Authors: Saiki Y. , Yamada M.
Published: April 2010

Abstract. Unstable periodic orbit (UPO) recently has become a keyword in analyzing complex phenomena in geophysical fluid dynamics and space physics. In this paper, sets of UPOs in low dimensional maps are theoretically or systematically found, and time averaged properties along UPOs are studied, in relation to those of chaotic orbits.
Turning the resistive MHD into a stochastic field theory
Authors: Materassi M. , Consolini G.
Published: April 2010

Abstract. Classical systems stirred by random forces of given statistics may be described via a path integral formulation in which their degrees of freedom are stochastic variables themselves, undergoing a multiple-history probabilistic evolution. This framework seems to be easily applicable to resistive Magneto-Hydro-Dynamics (MHD). Indeed, MHD equations form a dynamic system of classical variables in which the terms representing the density, the pressure and the conductivity of the plasma are irregular functions of space and time when turbulence occurs. By treating those irregular terms as random stirring forces, it is possible to introduce a Stochastic Field Theory which should represent correctly the impulsive phenomena caused by the spece- and time-irregularity of plasma turbulence. This work is motivated by the recent observational evidences of the crucial role played by stochastic fluctuations in space plasmas.
Mapping soil fractal dimension in agricultural fields with GPR
Authors: Oleschko K. , Korvin G. , Muñoz A. , Velazquez J. , Miranda M. E. , Carreon D. , Flores L. , Martínez M. , Velásquez-Valle M. , Brambila F. , Parrot J.-F. , Ronquillo G.
Published: April 2010

Abstract. We documented that the mapping of the fractal dimension of the backscattered Ground Penetrating Radar traces (Fractal Dimension Mapping, FDM) accomplished over heterogeneous agricultural fields gives statistically sound combined information about the spatial distribution of Andosol' dielectric permittivity, volumetric and gravimetric water content, bulk density, and mechanical resistance under seven different management systems. The roughness of the recorded traces was measured in terms of a single number H, the Hurst exponent, which integrates the competitive effects of volumetric water content, pore topology and mechanical resistance in space and time. We showed the suitability to combine the GPR traces fractal analysis with routine geostatistics (kriging) in order to map the spatial variation of soil properties by nondestructive techniques and to quantify precisely the differences under contrasting tillage systems. Three experimental plots with zero tillage and 33, 66 and 100% of crop residues imprinted the highest roughness to GPR wiggle traces (mean HR/S=0.15), significantly different to Andosol under conventional tillage (HR/S=0.47).
Denoising gravity and geomagnetic signals from Etna volcano (Italy) using multivariate methods
Authors: Del Negro C. , Greco F. , Napoli R. , Nunnari G.
Published: April 2010

Abstract. Multivariate methods were applied to denoise the gravity and geomagnetic signals continuously recorded by the permanent monitoring networks on the Etna volcano. Gravity and geomagnetic signals observed in volcanic areas are severely influenced by meteorological variables (i.e. pressure, temperature and humidity), whose disturbances can make the detection of volcanic source effects more difficult. For volcano monitoring it is necessary, therefore, to reduce the effects of these perturbations. To date filtering noise is a very complex problem since the spectrum of each noise component has wide intervals of superposition and, some times, traditional filtering techniques provide unsatisfactory results. We propose the application of two different approaches, the adaptive neuro-fuzzy inference system (ANFIS) and the Independent Component Analysis (ICA) to remove noise effects from gravity and geomagnetic time series. Results suggest a good efficiency of the two proposed approaches since they are capable of finding and effectively representing the underlying factors or sources, and allow local features of the signal to be detected.
Solute transport in fractured media – analysis of non-reversibility in tracer tests
Authors: Rodrigues N. E. V. , de Lima J. L. M. P. , Cruz F. F.
Published: April 2010

Abstract. This paper describes several small-scale (laboratory) experiments designed to simulate solute transport through fractured formations. A block of granite was broken to produce a fracture similar to those found in natural environments. Seven holes were drilled in the block to intersect the fracture. Later these holes functioned as either inlet or outlet points. All the possible combinations of pairs of inlet-outlet points were used to set up the tracer tests that provided the data analysed in this paper. The results indicate that reverse tracer tests do not necessarily provide symmetric results. Under some circumstances, the non-reversibility might be used to detect differences in the morphology of the fracture. The results also indicate that it is possible to estimate reasonably well the volume available for the circulation of the fluid by using transport models that neglect diffusion.
The formation of relativistic plasma structures and their potential role in the generation of cosmic ray electrons
Authors: Dieckmann M. E.
Published: April 2010

Abstract. Recent particle-in-cell (PIC) simulation studies have addressed particle acceleration and magnetic field generation in relativistic astrophysical flows by plasma phase space structures. We discuss the astrophysical environments such as the jets of compact objects, and we give an overview of the global PIC simulations of shocks. These reveal several types of phase space structures, which are relevant for the energy dissipation. These structures are typically coupled in shocks, but we choose to consider them here in an isolated form. Three structures are reviewed. (1) Simulations of interpenetrating or colliding plasma clouds can trigger filamentation instabilities, while simulations of thermally anisotropic plasmas observe the Weibel instability. Both transform a spatially uniform plasma into current filaments. These filament structures cause the growth of the magnetic fields. (2) The development of a modified two-stream instability is discussed. It saturates first by the formation of electron phase space holes. The relativistic electron clouds modulate the ion beam and a secondary, spatially localized electrostatic instability grows, which saturates by forming a relativistic ion phase space hole. It accelerates electrons to ultra-relativistic speeds. (3) A simulation is also revised, in which two clouds of an electron-ion plasma collide at the speed 0.9c. The inequal densities of both clouds and a magnetic field that is oblique to the collision velocity vector result in waves with a mixed electrostatic and electromagnetic polarity. The waves give rise to growing corkscrew distributions in the electrons and ions that establish an equipartition between the electron, the ion and the magnetic energy. The filament-, phase space hole- and corkscrew structures are discussed with respect to electron acceleration and magnetic field generation.
Structure functions and intermittency in ionospheric plasma turbulence
Authors: Dyrud L. , Krane B. , Oppenheim M. , Pécseli H. L. , Trulsen J. , Wernik A. W.
Published: April 2010

Abstract. Low frequency electrostatic turbulence in the ionospheric E-region is studied by means of numerical and experimental methods. We use the structure functions of the electrostatic potential as a diagnostics of the fluctuations. We demonstrate the inherently intermittent nature of the low level turbulence in the collisional ionospheric plasma by using results for the space-time varying electrostatic potential from two dimensional numerical simulations. An instrumented rocket can not directly detect the one-point potential variation, and most measurements rely on records of potential differences between two probes. With reference to the space observations we demonstrate that the results obtained by potential difference measurements can differ significantly from the one-point results. It was found, in particular, that the intermittency signatures become much weaker, when the proper rocket-probe configuration is implemented. We analyze also signals from an actual ionospheric rocket experiment, and find a reasonably good agreement with the appropriate simulation results, demonstrating again that rocket data, obtained as those analyzed here, are unlikely to give an adequate representation of intermittent features of the low frequency ionospheric plasma turbulence for the given conditions.
Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier
Authors: Hashemi H. , Tax D. M. J. , Duin R. P. W. , Javaherian A. , de Groot P.
Published: April 2010

Abstract. Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of input seismic attributes extracted at locations labeled by a human expert using regularized discriminant analysis (RDA). In order to find the RDA score for each seismic attribute, forward and backward search strategies are used. Subsequently, two non-linear classifiers: multilayer perceptron (MLP) and support vector classifier (SVC) are run on the ranked seismic attributes. Finally, to capitalize on the intrinsic differences between both classifiers, the MLP and SVC results are combined using logical rules of maximum, minimum and mean. The proposed method optimizes the ranked feature space size and yields the lowest classification error in the final combined result. We will show that the logical minimum reveals gas chimneys that exhibit both the softness of MLP and the resolution of SVC classifiers.
Comparative rainfall data analysis from two vertically pointing radars, an optical disdrometer, and a rain gauge
Authors: Nikolopoulos E. I. , Kruger A. , Krajewski W. F. , Williams C. R. , Gage K. S.
Published: April 2010

Abstract. The authors present results of a comparative analysis of rainfall data from several ground-based instruments. The instruments include two vertically pointing Doppler radars, S-band and X-band, an optical disdrometer, and a tipping-bucket rain gauge. All instruments were collocated at the Iowa City Municipal Airport in Iowa City, Iowa, for a period of several months. The authors used the rainfall data derived from the four instruments to first study the temporal variability and scaling characteristics of rainfall and subsequently assess the instrumental effects on these derived properties. The results revealed obvious correspondence between the ground and remote sensors, which indicates the significance of the instrumental effect on the derived properties.
Granulometric characterization of sediments transported by surface runoff generated by moving storms
Authors: de Lima J. L. M. P. , Souza C. S. , Singh V. P.
Published: April 2010

Abstract. Due to the combined effect of wind and rain, the importance of storm movement to surface flow has long been recognized, at scales ranging from headwater scales to large basins. This study presents the results of laboratory experiments designed to investigate the influence of moving rainfall storms on the dynamics of sediment transport by surface runoff. Experiments were carried out, using a rain simulator and a soil flume. The movement of rainfall was generated by moving the rain simulator at a constant speed in the upstream and downstream directions along the flume. The main objective of the study was to characterize, in laboratory conditions, the distribution of sediment grain-size transported by rainfall-induced overland flow and its temporal evolution. Grain-size distribution of the eroded material is governed by the capacity of flow that transports sediments. Granulometric curves were constructed using conventional hand sieving and a laser diffraction particle size analyser (material below 0.250 mm) for overland flow and sediment deliveries collected at the flume outlet. Surface slope was set at 2%, 7% and 14%. Rainstorms were moved with a constant speed, upslope and downslope, along the flume or were kept static. The results of laboratory experiments show that storm movement, affecting the spatial and temporal distribution of rainfall, has a marked influence on the grain-size characteristics of sediments transported by overland flow. The downstream-moving rainfall storms have higher stream power than do other storm types.
Head-on collision of two solitary waves and residual falling jet formation
Authors: Chambarel J. , Kharif C. , Touboul J.
Published: April 2010

Abstract. The head-on collision of two equal and two unequal steep solitary waves is investigated numerically. The former case is equivalent to the reflection of one solitary wave by a vertical wall when viscosity is neglected. We have performed a series of numerical simulations based on a Boundary Integral Equation Method (BIEM) on finite depth to investigate during the collision the maximum runup, phase shift, wall residence time and acceleration field for arbitrary values of the non-linearity parameter a/h, where a is the amplitude of initial solitary waves and h the constant water depth. The initial solitary waves are calculated numerically from the fully nonlinear equations. The present work extends previous results on the runup and wall residence time calculation to the collision of very steep counter propagating solitary waves. Furthermore, a new phenomenon corresponding to the occurrence of a residual jet is found for wave amplitudes larger than a threshold value.
The effect of third-order nonlinearity on statistical properties of random directional waves in finite depth
Authors: Toffoli A. , Benoit M. , Onorato M. , Bitner-Gregersen E. M.
Published: April 2010

Abstract. It is well established that third-order nonlinearity produces a strong deviation from Gaussian statistics in water of infinite depth, provided the wave field is long crested, narrow banded and sufficiently steep. A reduction of third-order effects is however expected when the wave energy is distributed on a wide range of directions. In water of arbitrary depth, on the other hand, third-order effects tend to be suppressed by finite depth effects if waves are long crested. Numerical simulations of the truncated potential Euler equations are here used to address the combined effect of directionality and finite depth on the statistical properties of surface gravity waves; only relative water depth kh greater than 0.8 are here considered. Results show that random directional wave fields in intermediate water depths, kh=O(1), weakly deviate from Gaussian statistics independently of the degree of directional spreading of the wave energy.