bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatio-temporal filling of missing points in geophysical data sets
Authors: Kondrashov D. , Ghil M.
Published: April 2010

Abstract. The majority of data sets in the geosciences are obtained from observations and measurements of natural systems, rather than in the laboratory. These data sets are often full of gaps, due to to the conditions under which the measurements are made. Missing data give rise to various problems, for example in spectral estimation or in specifying boundary conditions for numerical models. Here we use Singular Spectrum Analysis (SSA) to fill the gaps in several types of data sets. For a univariate record, our procedure uses only temporal correlations in the data to fill in the missing points. For a multivariate record, multi-channel SSA (M-SSA) takes advantage of both spatial and temporal correlations. We iteratively produce estimates of missing data points, which are then used to compute a self-consistent lag-covariance matrix; cross-validation allows us to optimize the window width and number of dominant SSA or M-SSA modes to fill the gaps. The optimal parameters of our procedure depend on the distribution in time (and space) of the missing data, as well as on the variance distribution between oscillatory modes and noise. The algorithm is demonstrated on synthetic examples, as well as on data sets from oceanography, hydrology, atmospheric sciences, and space physics: global sea-surface temperature, flood-water records of the Nile River, the Southern Oscillation Index (SOI), and satellite observations of relativistic electrons.
On statistical equilibrium in helical fluid flows
Authors: Kurgansky M. V.
Published: April 2010

Abstract. The statistical mechanics of 3-D helical flows is re-examined for a continuum truncated at a top wavenumber. Based on the principle of equipartition of the flow enstrophy between helical modes, the emerging (i) energy spectrum law "–2" and (ii) formal mathematical analogy between the helicity and the thermodynamic entropy are discussed. It is noted that the "–2" scaling law is consistent with both spectral equilibrium and spectral cascade paradigms. In an attempt to apply the obtained results to a turbulent flow regime within the Earth's outer liquid core, where the net helicity of a turbulent flow component is presumably explained by Earth's rotation, it has been noticed that it is the energy spectral law "–1", but not "–2", which is likely realized there and within the logarithmic accuracy corresponds to the case of the velocity structure function [u(l)]2 independency on the spatial scale l, the latter is consistent with observations. It is argued that the "–1" scaling law can also be interpreted in terms of the spectral equilibrium and it is emphasized that the causes of the likely dominance of the spectral law "–1" over the spectral law "–2" in this geophysical application deserve further investigation and clarification.
Influence of stability on the flux-profile relationships for wind speed, Φm, and temperature, Φh, for the stable atmospheric boundary layer
Authors: Yagüe C. , Viana S. , Maqueda G. , Redondo J. M.
Published: April 2010

Abstract. Data from SABLES98 experimental campaign have been used in order to study the influence of stability (from weak to strong stratification) on the flux-profile relationships for momentum, Φm, and heat, Φh. Measurements from 14 thermocouples and 3 sonic anemometers at three levels (5.8, 13.5 and 32 m) for the period from 10 to 28 September 1998 were analysed using the framework of the local-scaling approach (Nieuwstadt, 1984a; 1984b), which can be interpreted as an extension of the Monin-Obukhov similarity theory (Obukhov, 1946). The results show increasing values of Φm and Φh with increasing stability parameter ζ=z/Λ, up to a value of ζ≈1–2, above which the values remain constant. As a consequence of this levelling off in Φm and Φh for strong stability, the turbulent mixing is underestimated when linear similarity functions (Businger et al., 1971) are used to calculate surface fluxes of momentum and heat. On the other hand when Φm and Φh are related to the gradient Richardson number, Ri, a different behaviour is found, which could indicate that the transfer of momentum is greater than that of heat for high Ri. The range of validity of these linear functions is discussed in terms of the physical aspects of turbulent intermittent mixing.
Numerical simulation of helical-vortex effects in Rayleigh-Bénard convection
Authors: Levina G. V. , Burylov I. A.
Published: April 2010

Abstract. A numerical approach is substantiated for searching for the large-scale alpha-like instability in thermoconvective turbulence. The main idea of the search strategy is the application of a forcing function which can have a physical interpretation. The forcing simulates the influence of small-scale helical turbulence generated in a rotating fluid with internal heat sources and is applied to naturally induced fully developed convective flows. The strategy is tested using the Rayleigh-Bénard convection in an extended horizontal layer of incompressible fluid heated from below. The most important finding is an enlargement of the typical horizontal scale of the forming helical convective structures accompanied by a cells merging, an essential increase in the kinetic energy of flows and intensification of heat transfer. The results of modeling allow explaining how the helical feedback can work providing the non-zero mean helicity generation and the mutual intensification of horizontal and vertical circulation, and demonstrate how the energy of the additional helical source can be effectively converted into the energy of intensive large-scale vortex flow.
Charged dust and shock phenomena in the Solar System
Authors: Popel S. I. , Gisko A. A.
Published: April 2010

Abstract. The results on shock phenomena in dusty plasmas of the Solar System are reviewed. The problems of dust ion acoustic bow shock in interaction of the solar wind with dusty cometary coma and formation of transient atmospheres of atmosphereless cosmic bodies such as Moon, Mercury, asteroids and comets are considered. The latter assumes the evolution of meteoroid impact plumes and production of charged dust grains due to the condensation of both the plume substance and the vapor thrown from the crater and the surrounding regolith layer. Physical phenomena occurring during large meteoroid impacts can be modeled with the aid of active rocket experiments, which involve the release of some gaseous substance in near-Earth space. New vistas in investigation of shock processes in natural dusty plasmas are determined.
A nonextensive statistics approach for Langmuir waves in relativistic plasmas
Authors: Muñoz V.
Published: April 2010

Abstract. The nonextensive statistics formalism proposed by Tsallis has found many applications in systems with memory effects, long range spatial correlations, and in general whenever the phase space has fractal or multi-fractal structure. These features may appear naturally in turbulent or non-neutral plasmas. In fact, the equilibrium distribution functions which maximize the nonextensive entropy strongly resemble the non-Maxwellian particle distribution functions observed in space and laboratory and turbulent pure electron plasmas. In this article we apply the Tsallis entropy formalism to the problem of longitudinal oscillations in a proton-electron plasma. In particular, we study the equilibrium distribution function and the dispersion relation of longitudinal oscillations in a relativistic plasma, finding interesting differences with the nonrelativistic treatment.
A Stochastic Iterative Amplitude Adjusted Fourier Transform algorithm with improved accuracy
Authors: Venema V. , Ament F. , Simmer C.
Published: April 2010

Abstract. A stochastic version of the Iterative Amplitude Adjusted Fourier Transform (IAAFT) algorithm is presented. This algorithm is able to generate so-called surrogate time series, which have the amplitude distribution and the power spectrum of measured time series or fields. The key difference between the new algorithm and the original IAAFT method is the treatment of the amplitude adjustment: it is not performed for all values in each iterative step, but only for a fraction of the values. This new algorithm achieves a better accuracy, i.e. the power spectra of the measurement and its surrogate are more similar. We demonstrate the improvement by applying the IAAFT algorithm and the new one to 13 different test signals ranging from rain time series and 3-dimensional clouds to fractal time series and theoretical input. The improved accuracy can be important for generating high-quality geophysical time series and fields. The traditional application of the IAAFT algorithm is statistical nonlinearity testing. Reassuringly, we found that in most cases the accuracy of the original IAAFT algorithm is sufficient for this application.
Time series segmentation with shifting means hidden markov models
Authors: Kehagias Ath. , Fortin V.
Published: April 2010

Abstract. We present a new family of hidden Markov models and apply these to the segmentation of hydrological and environmental time series. The proposed hidden Markov models have a discrete state space and their structure is inspired from the shifting means models introduced by Chernoff and Zacks and by Salas and Boes. An estimation method inspired from the EM algorithm is proposed, and we show that it can accurately identify multiple change-points in a time series. We also show that the solution obtained using this algorithm can serve as a starting point for a Monte-Carlo Markov chain Bayesian estimation method, thus reducing the computing time needed for the Markov chain to converge to a stationary distribution.
GEOFLOW: simulation of convection in a spherical shell under central force field
Authors: Beltrame P. , Travnikov V. , Gellert M. , Egbers C.
Published: April 2010

Abstract. Time-dependent dynamical simulations related to convective motion in a spherical gap under a central force field due to the dielectrophoretic effect are discussed. This work is part of the preparation of the GEOFLOW-experiment which is planned to run in a microgravity environment. The goal of this experiment is the simulation of large-scale convective motion in a geophysical or astrophysical framework. This problem is new because of, on the one hand, the nature of the force field (dielectrophoretic effect) and, on another hand, the high degree of symmetries of the system, e.g. the top-bottom reflection. Thus, the validation of this simulation with well-known results is not possible. The questions concerning the influence of the dielectrophoretic force and the possibility to reproduce the theoretically expected motions in the astrophysical framework, are open. In the first part, we study the system in terrestrial conditions: the unidirectional Earth's force is superimposed on the central dielectrophoretic force field to compare with the laboratory experiments during the development of the equipment. In the second part, the GEOFLOW-experiment simulations in weightless conditions are compared with theoretical studies in the astrophysical framework's, in the first instance a fluid under a self-gravitating force field. We present complex time-dependent dynamics, where the dielectrophoretic force field causes significant differences in the flow compared to the case that does not involve this force field.
Wavelet ridge diagnosis of time-varying elliptical signals with application to an oceanic eddy
Authors: Lilly J. M. , Gascard J.-C.
Published: April 2010

Abstract. A method for diagnosing the physical properties of a time-varying ellipse is presented. This essentially involves extending the notion of instantaneous frequency to the bivariate case. New complications, and possibilities, arise from the fact that there are several meaningful forms in which a time-varying ellipse may be represented. A perturbation analysis valid for the near-circular case clarifies these issues. Diagnosis of the ellipse properties may then be performed using wavelet ridge analysis, and slowly-varying changes in the ellipse structure may be decoupled from the fast orbital motion through the use of elliptic integrals, without the need for additional explicit filtering. The theory is presented in parallel with an application to a position time series of a drifting subsurface float trapped in an oceanic eddy.
Multi-parameter uncertainty analysis of a bifurcation point
Authors: Knopf B. , Flechsig M. , Zickfeld K.
Published: April 2010

Abstract. Parameter uncertainty analysis of climate models has become a standard approach for model validation and testing their sensitivity. Here we present a novel approach that allows one to estimate the robustness of a bifurcation point in a multi-parameter space. In this study we investigate a box model of the Indian summer monsoon that exhibits a saddle-node bifurcation against those parameters that govern the heat balance of the system. The bifurcation brings about a change from a wet summer monsoon regime to a regime that is characterised by low precipitation. To analyse the robustness of the bifurcation point itself and its location in parameter space, we perform a multi-parameter uncertainty analysis by applying qualitative, Monte Carlo and deterministic methods that are provided by a multi-run simulation environment. Our results show that the occurrence of the bifurcation point is robust over a wide range of parameter values. The position of the bifurcation, however, is found to be sensitive on these specific parameter choices.
Nonlinear correlations of daily temperature records over land
Authors: Bartos I. , Jánosi I. M.
Published: April 2010

Abstract. We present a near global statistics on the correlation properties of daily temperature records. Data from terrestrial meteorological stations in the Global Daily Climatology Network are analyzed by means of detrended fluctuation analysis. Long-range temporal correlations extending up to several years are detected for each station. In order to reveal nonlinearity, we evaluated the magnitude of daily temperature changes (volatility) by the same method. The results clearly indicate the presence of nonlinearities in temperature time series, furthemore the geographic distribution of correlation exponents exhibits well defined clustering.
Using earthquake intensities to forecast earthquake occurrence times
Authors: Holliday J. R. , Rundle J. B. , Tiampo K. F. , Turcotte D. L.
Published: April 2010

Abstract. It is well known that earthquakes do not occur randomly in space and time. Foreshocks, aftershocks, precursory activation, and quiescence are just some of the patterns recognized by seismologists. Using the Pattern Informatics technique along with relative intensity analysis, we create a scoring method based on time dependent relative operating characteristic diagrams and show that the occurrences of large earthquakes in California correlate with time intervals where fluctuations in small earthquakes are suppressed relative to the long term average. We estimate a probability of less than 1% that this coincidence is due to random clustering. Furthermore, we show that the methods used to obtain these results may be applicable to other parts of the world.
Complexity and predictability of daily precipitation in a semi-arid region: an application to Ceará, Brazil
Authors: Silva M. E. S. , Carvalho L. M. V. , da Silva Dias M. A. F. , Xavier T. de M. B. S.
Published: April 2010

Abstract. Complexity and predictability of daily precipitation in a tropical semi-arid region (Ceará State, Brazil) is assessed by applying entropy concepts. Precipitation regimes in that region depend on several dynamical forcings, the most important being the displacement and activity of the Inter-tropical Convergence Zone in the Atlantic Ocean. Topography is another important factor that influences the spatial distribution of rainfall in the region. A hierarchical approach based on sequences of events of different lengths is used to estimate complexity of daily precipitation records. It is shown that precipitation in Ceará exhibit more random than periodic sequences, which indicates a large degree of complexity. Nevertheless, there is indication of potentially inherent rules in the precipitation time-series that could ultimately improve prediction on time-scales between 9–11 days. It is suggested that synoptic-scale disturbances (1–8 days) represent important sources of rules in the precipitation regimes in this region.
Time-scale invariant changes in atmospheric radon concentration and crustal strain prior to a large earthquake
Authors: Kawada Y. , Nagahama H. , Omori Y. , Yasuoka Y. , Ishikawa T. , Tokonami S. , Shinogi M.
Published: April 2010

Abstract. Prior to large earthquakes (e.g. 1995 Kobe earthquake, Japan), an increase in the atmospheric radon concentration is observed, and this increase in the rate follows a power-law of the time-to-earthquake (time-to-failure). This phenomenon corresponds to the increase in the radon migration in crust and the exhalation into atmosphere. An irreversible thermodynamic model including time-scale invariance clarifies that the increases in the pressure of the advecting radon and permeability (hydraulic conductivity) in the crustal rocks are caused by the temporal changes in the power-law of the crustal strain (or cumulative Benioff strain), which is associated with damage evolution such as microcracking or changing porosity. As the result, the radon flux and the atmospheric radon concentration can show a temporal power-law increase. The concentration of atmospheric radon can be used as a proxy for the seismic precursory processes associated with crustal dynamics.
Chaos in driven Alfvén systems: unstable periodic orbits and chaotic saddles
Authors: Chian A. C.-L. , Santana W. M. , Rempel E. L. , Borotto F. A. , Hada T. , Kamide Y.
Published: April 2010

Abstract. The chaotic dynamics of Alfvén waves in space plasmas governed by the derivative nonlinear Schrödinger equation, in the low-dimensional limit described by stationary spatial solutions, is studied. A bifurcation diagram is constructed, by varying the driver amplitude, to identify a number of nonlinear dynamical processes including saddle-node bifurcation, boundary crisis, and interior crisis. The roles played by unstable periodic orbits and chaotic saddles in these transitions are analyzed, and the conversion from a chaotic saddle to a chaotic attractor in these dynamical processes is demonstrated. In particular, the phenomenon of gap-filling in the chaotic transition from weak chaos to strong chaos via an interior crisis is investigated. A coupling unstable periodic orbit created by an explosion, within the gaps of the chaotic saddles embedded in a chaotic attractor following an interior crisis, is found numerically. The gap-filling unstable periodic orbits are responsible for coupling the banded chaotic saddle (BCS) to the surrounding chaotic saddle (SCS), leading to crisis-induced intermittency. The physical relevance of chaos for Alfvén intermittent turbulence observed in the solar wind is discussed.
Data assimilation in a sparsely observed one-dimensional modeled MHD system
Authors: Sun Z. , Tangborn A. , Kuang W.
Published: April 2010

Abstract. A one dimensional non-linear magneto-hydrodynamic (MHD) system has been introduced to test a sequential optimal interpolation assimilation technique that uses a Monte-Carlo method to calculate the forecast error covariance. An ensemble of 100 model runs with perturbed initial conditions are used to construct the covariance, and the assimilation algorithm is tested using Observation Simulation Experiments (OSE's). The system is run with a variety of observation types (magnetic and/or velocity fields) and a range of observation densities. The impact of cross covariances between velocity and magnetic fields is investigated by running the assimilation with and without these terms. Sets of twin experiments show that while observing both velocity and magnetic fields has the greatest positive impact on the system, observing the magnetic field alone can also effectively constrain the system. Observations of the velocity field are ineffective as a constraint on the magnetic field, even when observations are made at every point. The implications for geomagnetic data assimilation are discussed.
Mixtures of multiplicative cascade models in geochemistry
Authors: Agterberg F. P.
Published: April 2010

Abstract. Multifractal modeling of geochemical map data can help to explain the nature of frequency distributions of element concentration values for small rock samples and their spatial covariance structure. Useful frequency distribution models are the lognormal and Pareto distributions which plot as straight lines on logarithmic probability and log-log paper, respectively. The model of de Wijs is a simple multiplicative cascade resulting in discrete logbinomial distribution that closely approximates the lognormal. In this model, smaller blocks resulting from dividing larger blocks into parts have concentration values with constant ratios that are scale-independent. The approach can be modified by adopting random variables for these ratios. Other modifications include a single cascade model with ratio parameters that depend on magnitude of concentration value. The Turcotte model, which is another variant of the model of de Wijs, results in a Pareto distribution. Often a single straight line on logarithmic probability or log-log paper does not provide a good fit to observed data and two or more distributions should be fitted. For example, geochemical background and anomalies (extremely high values) have separate frequency distributions for concentration values and for local singularity coefficients. Mixtures of distributions can be simulated by adding the results of separate cascade models. Regardless of properties of background, an unbiased estimate can be obtained of the parameter of the Pareto distribution characterizing anomalies in the upper tail of the element concentration frequency distribution or lower tail of the local singularity distribution. Computer simulation experiments and practical examples are used to illustrate the approach.
Multifractal imaging filtering and decomposition methods in space, Fourier frequency, and eigen domains
Authors: Cheng Qiuming
Published: April 2010

Abstract. The patterns shown on two-dimensional images (fields) used in geosciences reflect the end products of geo-processes that occurred on the surface and in the subsurface of the Earth. Anisotropy of these types of patterns can provide information useful for interpretation of geo-processes and identification of features in the mapped area. Quantification of the anisotropy property is therefore essential for image processing and interpretation. This paper introduces several techniques newly developed on the basis of multifractal modeling in space, Fourier frequency, and eigen domains, respectively. A singularity analysis method implemented in the space domain can be used to quantify the intensity and anisotropy of local singularities. The second method, called S-A, characterizes the generalized scale invariance property of a field in the Fourier frequency domain. The third method characterizes the field using a power-law model on the basis of eigenvalues and eigenvectors of the field. The applications of these methods are demonstrated with a case study of Environment Scan Electric Microscope (ESEM) microimages for identification of sphalerite (ZnS) ore minerals from the Jinding Pb/Zn/Ag mineral deposit in Shangjiang District, Yunnan Province, China.
Merging particle filter for sequential data assimilation
Authors: Nakano S. , Ueno G. , Higuchi T.
Published: April 2010

Abstract. A new filtering technique for sequential data assimilation, the merging particle filter (MPF), is proposed. The MPF is devised to avoid the degeneration problem, which is inevitable in the particle filter (PF), without prohibitive computational cost. In addition, it is applicable to cases in which a nonlinear relationship exists between a state and observed data where the application of the ensemble Kalman filter (EnKF) is not effectual. In the MPF, the filtering procedure is performed based on sampling of a forecast ensemble as in the PF. However, unlike the PF, each member of a filtered ensemble is generated by merging multiple samples from the forecast ensemble such that the mean and covariance of the filtered distribution are approximately preserved. This merging of multiple samples allows the degeneration problem to be avoided. In the present study, the newly proposed MPF technique is introduced, and its performance is demonstrated experimentally.
Long-range correlations of extrapolar total ozone are determined by the global atmospheric circulation
Authors: Kiss P. , Müller R. , Jánosi I. M.
Published: April 2010

Abstract. TOMS (Version 8) ozone records are analysed between latitudes 60° S and 60° N, in order to extract autocorrelation properties with high spatial resolution. After the removal of semi-annual, annual, and quasi-biennial background oscillations, the residuals are evaluated by detrended fluctuation analysis. Long-range correlations are detected everywhere. Surprisingly, the latitude dependence of zonally averaged correlation exponents exhibits the same behaviour as the exponents for daily surface temperature records. This suggests that the correlation properties of total ozone column are dominated by the global atmospheric circulation patterns, and the effect of chemical processes seems to be subsidiary.
Recurrence and interoccurrence behavior of self-organized complex phenomena
Authors: Abaimov S. G. , Turcotte D. L. , Shcherbakov R. , Rundle J. B.
Published: April 2010

Abstract. The sandpile, forest-fire and slider-block models are said to exhibit self-organized criticality. Associated natural phenomena include landslides, wildfires, and earthquakes. In all cases the frequency-size distributions are well approximated by power laws (fractals). Another important aspect of both the models and natural phenomena is the statistics of interval times. These statistics are particularly important for earthquakes. For earthquakes it is important to make a distinction between interoccurrence and recurrence times. Interoccurrence times are the interval times between earthquakes on all faults in a region whereas recurrence times are interval times between earthquakes on a single fault or fault segment. In many, but not all cases, interoccurrence time statistics are exponential (Poissonian) and the events occur randomly. However, the distribution of recurrence times are often Weibull to a good approximation. In this paper we study the interval statistics of slip events using a slider-block model. The behavior of this model is sensitive to the stiffness α of the system, α=kC/kL where kC is the spring constant of the connector springs and kL is the spring constant of the loader plate springs. For a soft system (small α) there are no system-wide events and interoccurrence time statistics of the larger events are Poissonian. For a stiff system (large α), system-wide events dominate the energy dissipation and the statistics of the recurrence times between these system-wide events satisfy the Weibull distribution to a good approximation. We argue that this applicability of the Weibull distribution is due to the power-law (scale invariant) behavior of the hazard function, i.e. the probability that the next event will occur at a time t0 after the last event has a power-law dependence on t0. The Weibull distribution is the only distribution that has a scale invariant hazard function. We further show that the onset of system-wide events is a well defined critical point. We find that the number of system-wide events NSWE satisfies the scaling relation NSWE ∝(α-αC)δ where αC is the critical value of the stiffness. The system-wide events represent a new phase for the slider-block system.
Scaling and multifractal fields in the solid earth and topography
Authors: Lovejoy S. , Schertzer D.
Published: April 2010

Abstract. Starting about thirty years ago, new ideas in nonlinear dynamics, particularly fractals and scaling, provoked an explosive growth of research both in modeling and in experimentally characterizing geosystems over wide ranges of scale. In this review we focus on scaling advances in solid earth geophysics including the topography. To reduce the review to manageable proportions, we restrict our attention to scaling fields, i.e. to the discussion of intensive quantities such as ore concentrations, rock densities, susceptibilities, and magnetic and gravitational fields. We discuss the growing body of evidence showing that geofields are scaling (have power law dependencies on spatial scale, resolution), over wide ranges of both horizontal and vertical scale. Focusing on the cases where both horizontal and vertical statistics have both been estimated from proximate data, we argue that the exponents are systematically different, reflecting lithospheric stratification which – while very strong at small scales – becomes less and less pronounced at larger and larger scales, but in a scaling manner. We then discuss the necessity for treating the fields as multifractals rather than monofractals, the latter being too restrictive a framework. We discuss the consequences of multifractality for geostatistics, we then discuss cascade processes in which the same dynamical mechanism repeats scale after scale over a range. Using the binomial model first proposed by de Wijs (1951) as an example, we discuss the issues of microcanonical versus canonical conservation, algebraic ("Pareto") versus long tailed (e.g. lognormal) distributions, multifractal universality, conservative and nonconservative multifractal processes, codimension versus dimension formalisms. We compare and contrast different scaling models (fractional Brownian motion, fractional Levy motion, continuous (in scale) cascades), showing that they are all based on fractional integrations of noises built up from singularity basis functions. We show how anisotropic (including stratified) models can be produced simply by replacing the usual distance function by an anisotropic scale function, hence by replacing isotropic singularities by anisotropic ones.
An Ising model for earthquake dynamics
Authors: Jiménez A. , Tiampo K. F. , Posadas A. M.
Published: April 2010

Abstract. This paper focuses on extracting the information contained in seismic space-time patterns and their dynamics. The Greek catalog recorded from 1901 to 1999 is analyzed. An Ising Cellular Automata representation technique is developed to reconstruct the history of these patterns. We find that there is strong correlation in the region, and that small earthquakes are very important to the stress transfers. Finally, it is demonstrated that this approach is useful for seismic hazard assessment and intermediate-range earthquake forecasting.
Representative elementary area for multifractal analysis of soil porosity using entropy dimension
Authors: San José Martínez F. , Caniego F. J. , García-Gutiérrez C. , Espejo R.
Published: April 2010

Abstract. The notion of representative elementary area (REA) developed to address heterogeneity and scale problems in quantitative soil pedology comes from the notion of representative elementary volume of fluid dynamics in porous media. The REA allows the identification of the minimum area of a soil block section that is required to represent the pedofeature of interest based on its distribution in soil space. In this paper eight samples were imaged with two different techniques: the confocal microscope and the conventional film camera. These techniques provided information about pore sizes between 3.62 μm and 161.98 μm, and between 39.72 μm and 1776.34 μm, respectively. Sixteen of the resulting digital images were then analyzed to investigate the representative elementary area of the multifractal patterns of the spatial distribution of voids related to the micro and macroporosity by means of the entropy dimension. Our results permit the location of the REA region over the domain of the microstructures rendered by the analysis of the microscope images. They also suggest that this region seemingly spans scales of the macrostructures as revealed by the analysis of the camera pictures.
Multi-point observations of intermittency in the cusp regions
Authors: Echim M. M. , Lamy H. , Chang T.
Published: April 2010

Abstract. In this paper we investigate the statistical properties of magnetic field fluctuations measured by the four Cluster spacecraft in the cusp and close to the interface with the magnetospheric lobes, magnetopause and magnetosheath. At lower altitudes along the outbound orbit of 26 February 2001, the magnetic field fluctuations recorded by all four spacecraft are random and their Probability Distribution Functions (PDFs) are Gaussian at all scales. The flatness parameter, F – related to the kurtosis of the time series, is equal to 3. At higher altitudes, in the cusp and its vicinity, closer to the interface with the magnetopause and magnetosheath, the PDFs from all Cluster satellites are non-Gaussian and show a clear intermittent behavior at scales smaller than τG≈ 61 s (or 170 km). The flatness parameter increases to values greater than 3 for scales smaller than τG. A Haar wavelet transform enables the identification of the "events" that produce sudden variations of the magnetic field and of the scales that have most of the power. The LIM parameter (i.e. normalized wavelet power) indicates that events for scales below 65 s are non-uniformly distributed throughout the cusp passage. PDFs, flatness and wavelet analysis show that at coarse-grained scales larger than τG the intermittency is absent in the cusp. Fluctuations of the magnetic energy observed during the same orbit in the magnetosheath show PDFs that tend toward a Gaussian at scales smaller than τG found in the cusp. The flatness analysis confirms the decreasing of τG from cusp to magnetosheath. Our analysis reveals the turbulent cusp as a transition region from a non-intermittent turbulent state inside the magnetosphere to an intermittent turbulent state in the magnetosheath that has statistical properties resembling the solar wind turbulence. The observed turbulent fluctuations in the cusp suggests a phenomenon of nonlinear interactions of plasma coherent structures as in contemporary models of space plasma turbulence.
On MHD waves, fire-hose and mirror instabilities in anisotropic plasmas
Authors: Hau L.-N. , Wang B.-J.
Published: April 2010

Abstract. Temperature or pressure anisotropies are characteristic of space plasmas, standard magnetohydrodynamic (MHD) model for describing large-scale plasma phenomena however usually assumes isotropic pressure. In this paper we examine the characteristics of MHD waves, fire-hose and mirror instabilities in anisotropic homogeneous magnetized plasmas. The model equations are a set of gyrotropic MHD equations closed by the generalized Chew-Goldberger-Low (CGL) laws with two polytropic exponents representing various thermodynamic conditions. Both ions and electrons are allowed to have separate plasma beta, pressure anisotropy and energy equations. The properties of linear MHD waves and instability criteria are examined and numerical examples for the nonlinear evolutions of slow waves, fire-hose and mirror instabilities are shown. One significant result is that slow waves may develop not only mirror instability but also a new type of compressible fire-hose instability. Their corresponding nonlinear structures thus may exhibit anticorrelated density and magnetic field perturbations, a property used for identifying slow and mirror mode structures in the space plasma environment. The conditions for nonlinear saturation of both fire-hose and mirror instabilities are examined.
Chaotic properties of a fully developed model turbulence
Authors: Yamada M. , Saiki Y.
Published: April 2010

Abstract. Shell models of turbulence have been employed as toy models which, in their chaotic states, show statistical properties similar to real fluid turbulence, including Kolmogorov energy spectrum and intermittency. These models are interesting because, at the present stage, it is still quite difficult or almost impossible to study relations between those traditional statistical properties and the structure of the chaos underlying the real fluid turbulence because of huge dimension of the chaotic attractor. In this paper we will give a brief review on the chaotic properties of a shell model (GOY model), with emphasis on its Lyapunov spectrum and unstable periodic orbits, in relation to the Kolmogorov scaling law of the turbulence.
Fluctuation-Response Relation and modeling in systems with fast and slow dynamics
Authors: Lacorata G. , Vulpiani A.
Published: April 2010

Abstract. We show how a general formulation of the Fluctuation-Response Relation is able to describe in detail the connection between response properties to external perturbations and spontaneous fluctuations in systems with fast and slow variables. The method is tested by using the 360-variable Lorenz-96 model, where slow and fast variables are coupled to one another with reciprocal feedback, and a simplified low dimensional system. In the Fluctuation-Response context, the influence of the fast dynamics on the slow dynamics relies in a non trivial behavior of a suitable quadratic response function. This has important consequences for the modeling of the slow dynamics in terms of a Langevin equation: beyond a certain intrinsic time interval even the optimal model can give just statistical prediction.
Anti-persistence in the global temperature anomaly field
Authors: Carvalho L. M. V. , Tsonis A. A. , Jones C. , Rocha H. R. , Polito P. S.
Published: April 2010

Abstract. In this study, low-frequency variations in temperature anomaly are investigated by mapping temperature anomaly records onto random walks. We show evidence that global overturns in trends of temperature anomalies occur on decadal time-scales as part of the natural variability of the climate system. Paleoclimatic summer records in Europe and New-Zealand provide further support for these findings as they indicate that anti-persistence of temperature anomalies on decadal time-scale have occurred in the last 226 yrs. Atmospheric processes in the subtropics and mid-latitudes of the SH and interactions with the Southern Oceans seem to play an important role to moderate global variations of temperature on decadal time-scales.
Spatiotemporal characterization of Ensemble Prediction Systems – the Mean-Variance of Logarithms (MVL) diagram
Authors: Gutiérrez J. M. , Primo C. , Rodríguez M. A. , Fernández J.
Published: April 2010

Abstract. We present a novel approach to characterize and graphically represent the spatiotemporal evolution of ensembles using a simple diagram. To this aim we analyze the fluctuations obtained as differences between each member of the ensemble and the control. The lognormal character of these fluctuations suggests a characterization in terms of the first two moments of the logarithmic transformed values. On one hand, the mean is associated with the exponential growth in time. On the other hand, the variance accounts for the spatial correlation and localization of fluctuations. In this paper we introduce the MVL (Mean-Variance of Logarithms) diagram to intuitively represent the interplay and evolution of these two quantities. We show that this diagram uncovers useful information about the spatiotemporal dynamics of the ensemble. Some universal features of the diagram are also described, associated either with the nonlinear system or with the ensemble method and illustrated using both toy models and numerical weather prediction systems.
Combination of different types of ensembles for the adaptive simulation of probabilistic flood forecasts: hindcasts for the Mulde 2002 extreme event
Authors: Dietrich J. , Trepte S. , Wang Y. , Schumann A. H. , Voß F. , Hesser F. B. , Denhard M.
Published: April 2010

Abstract. Flood forecasts are essential to issue reliable flood warnings and to initiate flood control measures on time. The accuracy and the lead time of the predictions for head waters primarily depend on the meteorological forecasts. Ensemble forecasts are a means of framing the uncertainty of the potential future development of the hydro-meteorological situation. This contribution presents a flood management strategy based on probabilistic hydrological forecasts driven by operational meteorological ensemble prediction systems. The meteorological ensemble forecasts are transformed into discharge ensemble forecasts by a rainfall-runoff model. Exceedance probabilities for critical discharge values and probabilistic maps of inundation areas can be computed and presented to decision makers. These results can support decision makers in issuing flood alerts. The flood management system integrates ensemble forecasts with different spatial resolution and different lead times. The hydrological models are controlled in an adaptive way, mainly depending on the lead time of the forecast, the expected magnitude of the flood event and the availability of measured data. The aforementioned flood forecast techniques have been applied to a case study. The Mulde River Basin (South-Eastern Germany, Czech Republic) has often been affected by severe flood events including local flash floods. Hindcasts for the large scale extreme flood in August 2002 have been computed using meteorological predictions from both the COSMO-LEPS ensemble prediction system and the deterministic COSMO-DE local model. The temporal evolution of a) the meteorological forecast uncertainty and b) the probability of exceeding flood alert levels is discussed. Results from the hindcast simulations demonstrate, that the systems would have predicted a high probability of an extreme flood event, if they would already have been operational in 2002. COSMO-LEPS showed a reasonably good performance within a lead time of 2 to 3 days. Some of the deterministic very short-range forecast initializations were able to predict the dynamics of the event, but others underpredicted rainfall. Thus a lagged average ensemble approach is suggested. The findings from the case study support the often proposed added value of ensemble forecasts and their probabilistic evaluation for flood management decisions.
Statistical properties of earthquakes clustering
Authors: Vecchio A. , Carbone V. , Sorriso-Valvo L. , De Rose C. , Guerra I. , Harabaglia P.
Published: April 2010

Abstract. Often in nature the temporal distribution of inhomogeneous stochastic point processes can be modeled as a realization of renewal Poisson processes with a variable rate. Here we investigate one of the classical examples, namely, the temporal distribution of earthquakes. We show that this process strongly departs from a Poisson statistics for both catalogue and sequence data sets. This indicate the presence of correlations in the system probably related to the stressing perturbation characterizing the seismicity in the area under analysis. As shown by this analysis, the catalogues, at variance with sequences, show common statistical properties.
Weather regime dependence of extreme value statistics for summer temperature and precipitation
Authors: Yiou P. , Goubanova K. , Li Z. X. , Nogaj M.
Published: April 2010

Abstract. Extreme Value Theory (EVT) is a useful tool to describe the statistical properties of extreme events. Its underlying assumptions include some form of temporal stationarity in the data. Previous studies have been able to treat long-term trends in datasets, to obtain the time dependence of EVT parameters in a parametric form. Since there is also a dependence of surface temperature and precipitation to weather patterns obtained from pressure data, we determine the EVT parameters of those meteorological variables over France conditional to the occurrence of North Atlantic weather patterns in the summer. We use a clustering algorithm on geopotential height data over the North Atlantic to obtain those patterns. This approach refines the straightforward application of EVT on climate data by allowing us to assess the role of atmospheric variability on temperature and precipitation extreme parameters. This study also investigates the statistical robustness of this relation. Our results show how weather regimes can modulate the different behavior of mean climate variables and their extremes. Such a modulation can be very different for the mean and extreme precipitation.
Small world in a seismic network: the California case
Authors: Jiménez A. , Tiampo K. F. , Posadas A. M.
Published: April 2010

Abstract. Recent work has shown that disparate systems can be described as complex networks i.e. assemblies of nodes and links with nontrivial topological properties. Examples include technological, biological and social systems. Among them, earthquakes have been studied from this perspective. In the present work, we divide the Southern California region into cells of 0.1°, and calculate the correlation of activity between them to create functional networks for that seismic area, in the same way that the brain activity is studied from the complex network perspective. We found that the network shows small world features.
Conditional nonlinear optimal perturbations of the double-gyre ocean circulation
Authors: Terwisscha van Scheltinga A. D. , Dijkstra H. A.
Published: April 2010

Abstract. In this paper, we study the development of finite amplitude perturbations on linearly stable steady barotropic double-gyre flows in a rectangular basin using the concept of Conditional Nonlinear Optimal Perturbation (CNOP). The CNOPs depend on a time scale of evolution te and an initial perturbation threshold δ. Under symmetric wind forcing, a perfect pitchfork perturbation occurs in the model. The CNOPs are determined for all linearly stable states and the time evolution of the CNOPs is studied. It is found that the patterns of the CNOPs are similar to those of the non-normal modes for small te and approach those of the normal modes for larger te. With slightly asymmetric winds, an imperfect pitchfork occurs in the model. Indications are found that the time evolution of the CNOPs is related to the value of the dissipation function of the underlying steady state.
Limitations of wind power availability over Europe: a conceptual study
Authors: Kiss P. , Jánosi I. M.
Published: April 2010

Abstract. Wind field statistics are evaluated from the ERA-40 data bank covering a period of 44 years with a temporal resolution of 6 h. Instantaneous wind speed values are provided in geographic cells of size 1°×1° (lat/long) for surface (10 m) and 1000 hPa pressure heights. Potential wind power generation is estimated in two steps. Firstly, the wind speed at hub height is approximated from surface data based on the statistical analysis of the wind and geopotential records for 1000 hPa pressure level. Secondly, the wind speed values are transformed by an idealised power curve fitted for measured data. The model time series are fed into various hypothetical electric networks. The main quantity of interest is the aggregated output from the networks. A reference power time series is determined for a static network connecting each continental site and an envelope of 1° around the shorelines (representing off-shore locations) over Europe. This time series exhibits a low average value and a marked annual periodicity. Wind power integration over limited areas results in higher average outputs at the expense of stronger fluctuations. The long-range spatial correlations of the wind field limit the level of fluctuations strongly which can not be eliminated either by an increase of the area of integration or by dynamic control. This study is fully conceptual, however it demonstrates the limitations of wind power integration over Europe.