bluuebunny/crossref_metadata_2025 huggingface dataset:
An experimental investigation on elliptical instability of a strongly asymmetric vortex pair in a stable density stratification
Authors: Cariteau B. , Flór J.-B.
Published: April 2010

Abstract. We investigate the elliptical instability of a strongly asymmetric vortex pair in a stratified fluid, generated by the acceleration and deceleration of the rotation of a single flap. The dominant parameter is the Froude number, Fr=U/(NR), based on the maximum azimuthal velocity, U, and corresponding radius, R, of the strongest vortex, i.e. the principal vortex, and buoyancy frequency N. For Fr>1, both vortices are elliptically unstable while the instability is suppressed for Fr<1. In an asymmetric vortex pair, the principal vortex is less – and the secondary vortex more – elliptical than the vortices in an equivalent symmetric dipolar vortex. The far more unstable secondary vortex interacts with the principal vortex and increases the strain on the latter, thus increasing its ellipticity and its instability growth rate. The nonlinear interactions render the elliptical instability more relevant. An asymmetric dipole can be more unstable than an equivalent symmetric dipole. Further, the wavelength of the instability is shown to be a function of the Froude number for strong stratifications corresponding to small Froude numbers, whereas it remains constant in the limit of a homogenous fluid.
Nonlinear effects in a conceptual multilayer cloud model
Authors: Wacker U.
Published: April 2010

Abstract. As conceptual model for a cloud a system is considered which is open for condensate mass transport and subject to internal processes such as cloud microphysical transformation and vertical condensate transport. The effects of microphysical processes are represented in parameterized form and the system is divided into two layers to account for the vertical structure. The evolution is mathematically described in terms of four coupled nonlinear ODEs; the prognostic variables are the mass concentrations of cloud water as well as precipitation condensate in each of the layers. In the absence of vertical velocity the evolution in the lower layer is triggered by the evolution in the upper layer. In the presence of an upwind, the dynamics in both layers is mutually coupled. Depending on the chosen parameter values up to four steady states are found. When varying the parameter upwind velocity, three regimes are distinguished: For week upwind the long-term evolution is steered by the external sources; for stronger upwind the cloud condensate is blown out of the cloud in the final state and does not contribute to formation of precipitation; for intermediate upwind multiple steady state solution branches arise which characterize the transition between those two regimes.
Anomalies of critical state in fracturing geophysical objects
Authors: Chmel A. , Kuksenko V. S. , Smirnov V. S. , Tomilin N. G.
Published: April 2010

Abstract. Non-linear time-sequences of fracture-related events were studied in drifting sea-ice and fracturing rock. A reversible drop of the b-value was detected prior to the large-scale sea-ice cover fragmentation, when the time sequence of impact interactions between ice-fields was fully decorrelated. A similar loss of the temporal invariance of the fracture process was revealed in the time sequence of microfracture events detected in a loaded rock sample. These temporal gaps in the continuous critical state of the considered self-organizing, open systems were attributed to the property of hierarchicity inherent in the geophysical objects. A combination of scaling and hierarchic features in the behavior of fracturing solids manifests itself in the heterogeneity of the temporal pattern of fracture process.
Lacunarity, predictability and predictive instability of the daily pluviometric regime in the Iberian Peninsula
Authors: Martínez M. D. , Lana X. , Burgueño A. , Serra C.
Published: April 2010

Abstract. The complexity of the daily pluviometric regime of the Iberian Peninsula is analysed from the point of view of its lacunarity, predictability and predictive instability. The database consists of daily pluviometric records obtained from 43 rain gauges in Spain and Portugal for the period 1950–1990. Five different series are generated for every rain gauge. The first series is constituted by the consecutive daily amounts. The other four consist of dry spell lengths with respect to daily amount thresholds of 0.1, 1.0, 5.0 and 10.0 mm/day. A dry spell length is defined as the number of consecutive days with rainfall amounts below one of these thresholds. The empirical lacunarity for every rain gauge is well reproduced by two power laws, the exponents varying notably from one gauge to another. The spatial distribution of the lacunarity is characterised by a north to south or southeast gradient, thus suggesting that this parameter can be a useful tool to distinguish between different pluviometric regimes. The predictability of the five series is quantified by means of the rescaled analysis and the interpretation of the Hurst exponent. Its patterns reveal that most part of the Iberian Peninsula shows signs of persistence for the daily rainfall and the dry spell series, although persistence is only clearly manifested in some small domains. The instability of possible predictive algorithms is analysed through the Lyapunov exponents. They are only computed for the series of daily amounts and for dry lengths respect to the threshold level of 0.1 mm/day due to the short number of dry spells for larger threshold levels. The series of daily amounts depict the highest instability along the Mediterranean coast. The series of dry spells show an increasing instability from NE to SW Spain, with a relevant nucleus of high Lyapunov values in the south-western Atlantic coast. As a summary, lacunarity and Hurst and Lyapunov exponents depict a relevant spatial variation, which is in agreement with well known patterns of the pluviometric regime, such as annual amount spatial distribution and return periods of dry spells.
A case for variational geomagnetic data assimilation: insights from a one-dimensional, nonlinear, and sparsely observed MHD system
Authors: Fournier A. , Eymin C. , Alboussière T.
Published: April 2010

Abstract. Secular variations of the geomagnetic field have been measured with a continuously improving accuracy during the last few hundred years, culminating nowadays with satellite data. It is however well known that the dynamics of the magnetic field is linked to that of the velocity field in the core and any attempt to model secular variations will involve a coupled dynamical system for magnetic field and core velocity. Unfortunately, there is no direct observation of the velocity. Independently of the exact nature of the above-mentioned coupled system – some version being currently under construction – the question is debated in this paper whether good knowledge of the magnetic field can be translated into good knowledge of core dynamics. Furthermore, what will be the impact of the most recent and precise geomagnetic data on our knowledge of the geomagnetic field of the past and future? These questions are cast into the language of variational data assimilation, while the dynamical system considered in this paper consists in a set of two oversimplified one-dimensional equations for magnetic and velocity fields. This toy model retains important features inherited from the induction and Navier-Stokes equations: non-linear magnetic and momentum terms are present and its linear response to small disturbances contains Alfvén waves. It is concluded that variational data assimilation is indeed appropriate in principle, even though the velocity field remains hidden at all times; it allows us to recover the entire evolution of both fields from partial and irregularly distributed information on the magnetic field. This work constitutes a first step on the way toward the reassimilation of historical geomagnetic data and geomagnetic forecast.
Models for strongly-nonlinear evolution of long internal waves in a two-layer stratification
Authors: Sakai T. , Redekopp L. G.
Published: April 2010

Abstract. Models describing the evolution of long internal waves are proposed that are based on different polynomial approximations of the exact expression for the phase speed of uni-directional, fully-nonlinear, infinitely-long waves in the two-layer model of a density stratified environment. It is argued that a quartic KdV model, one that employs a cubic polynomial fit of the separately-derived, nonlinear relation for the phase speed, is capable of describing the evolution of strongly-nonlinear waves with a high degree of fidelity. The marginal gains obtained by generating higher-order, weakly-nonlinear extensions to describe strongly-nonlinear evolution are clearly demonstrated, and the limitations of the quite widely-used quadratic-cubic KdV evolution model obtained via a second-order, weakly-nonlinear analysis are assessed. Data are presented allowing a discriminating comparison of evolution characteristics as a function of wave amplitude and environmental parameters for several evolution models.
Wavelet analysis in a structured clay soil using 2-D images
Authors: Piñuela J. A. , Andina D. , McInnes K. J. , Tarquis A. M.
Published: April 2010

Abstract. The spatial variability of preferential pathways for water and chemical transport in a field soil, as visualized through dye infiltration experiments, was studied by applying multifractal and wavelet transform analysis (WTA). After dye infiltration into a 4 m² plot located on a Vertisol soil near College Station, Texas, horizontal planes in the subsoil were exposed at 5 cm intervals, and dye stain patterns were photographed. Box-counting methods and WTA were applied to all of the 16 digitalized high-resolution dye images and to the dye-mass image obtained merging all sections. The well-known Devil's staircase multifractal was also used to illustrate wavelet-based analysis. Our results suggest that wavelet methods can complement box-counting analysis in the context of multiscaling structure analysis.
Plankton blooms in vortices: the role of biological and hydrodynamic timescales
Authors: Sandulescu M. , López C. , Hernández-García E. , Feudel U.
Published: April 2010

Abstract. We study the interplay of hydrodynamic mesoscale structures and the growth of plankton in the wake of an island, and its interaction with a coastal upwelling. Our focus is on a mechanism for the emergence of localized plankton blooms in vortices. Using a coupled system of a kinematic flow mimicking the mesoscale structures behind the island and a simple three component model for the marine ecosystem, we show that the long residence times of nutrients and plankton in the vicinity of the island and the confinement of plankton within vortices are key factors for the appearance of localized plankton blooms.
An artificial neural network predictor for tropospheric surface duct phenomena
Authors: Isaakidis S. A. , Dimou I. N. , Xenos T. D. , Dris N. A.
Published: April 2010

Abstract. In this work, an artificial neural network (ANN) model is developed and used to predict the presence of ducting phenomena for a specific time, taking into account ground values of atmospheric pressure, relative humidity and temperature. A feed forward backpropagation ANN is implemented, which is trained, validated and tested using atmospheric radiosonde data from the Helliniko airport, for the period from 1991 to 2004. The network's quality and generality is assessed using the Area Under the Receiver Operating Characteristics (ROC) Curves (AUC), which resulted to a mean value of about 0.86 to 0.90, depending on the observation time. In order to validate the ANN results and to evaluate any further improvement options of the proposed method, the problem was additionally treated using Least Squares Support Vector Machine (LS-SVM) classifiers, trained and tested with identical data sets for direct performance comparison with the ANN. Furthermore, time series prediction and the effect of surface wind to the presence of tropospheric ducts appearance are discussed. The results show that the ANN model presented here performs efficiently and gives successful tropospheric ducts predictions.
Energetic particle parallel diffusion in a cascading wave turbulence in the foreshock region
Authors: Otsuka F. , Omura Y. , Verkhoglyadova O.
Published: April 2010

Abstract. We study parallel (field-aligned) diffusion of energetic particles in the upstream of the bow shock with test particle simulations. We assume parallel shock geometry of the bow shock, and that MHD wave turbulence convected by the solar wind toward the shock is purely transverse in one-dimensional system with a constant background magnetic field. We use three turbulence models: a homogeneous turbulence, a regular cascade from a large scale to smaller scales, and an inverse cascade from a small scale to larger scales. For the homogeneous model the particle motions along the average field are Brownian motions due to random and isotropic scattering across 90 degree pitch angle. On the other hand, for the two cascade models particle motion is non-Brownian due to coherent and anisotropic pitch angle scattering for finite time scale. The mean free path λ|| calculated by the ensemble average of these particle motions exhibits dependence on the distance from the shock. It also depends on the parameters such as the thermal velocity of the particles, solar wind flow velocity, and a wave turbulence model. For the inverse cascade model, the dependence of λ|| at the shock on the thermal energy is consistent with the hybrid simulation done by Giacalone (2004), but the spatial dependence of λ|| is inconsistent with it.
Comparison of gliding box and box-counting methods in river network analysis
Authors: Saa A. , Gascó G. , Grau J. B. , Antón J. M. , Tarquis A. M.
Published: April 2010

Abstract. We use multifractal analysis to estimate the Rényi dimensions of river basins by two different partition methods. These methods differ in the way that the Euclidian plane support of the measure is covered, partitioning it by using mutually exclusive boxes or by gliding a box over the plane. Images of two different drainage basins, for the Ebro and Tajo rivers, located in Spain, were digitalized with a resolution of 0.5 km, giving image sizes of 617×1059 pixels and 515×1059, respectively. Box sizes were chosen as powers of 2, ranging from 2×4 pixels to 512×1024 pixels located within the image, with the purpose of covering the entire network. The resulting measures were plotted versus the logarithmic value of the box area instead of the box size length. Multifractal Analysis (MFA) using a box counting algorithm was carried out according to the method of moments ranging from −5<q<5, and the Rényi dimensions were calculated from the log/log slope of the probability distribution for the respective moments over the box area. An optimal interval of box sizes was determined by estimating the characteristic length of the river networks and by taking the next higher power of 2 as the smallest box size. The optimized box size for both river networks ranges from 64×128 to 512×1024 pixels and illustrates the multiscaling behaviour of the Ebro and Tajo. By restricting the multifractal analysis to the box size range, good generalized dimension (Dq) spectra were obtained but with very few points and with a low number of boxes for each size due to image size restrictions. The gliding box method was applied to the same box size range, providing more consistent and representative Dq values. The numerical differences between the results, as well as the standard error values, are discussed.
Vlasov simulation of Langmuir wave packets
Authors: Umeda T.
Published: April 2010

Abstract. Amplitude modulation and packet formation of Langmuir waves are commonly observed during a nonlinear interaction between electron beams and plasmas. In this paper, we briefly review the history of Langmuir wave packets as developed by recent spacecraft observations and computer simulations. New one-dimensional electrostatic Vlasov simulations are performed to study their formation processes. It is found that the formation of Langmuir wave packets involves both an incoherent turbulent process and a coherent nonlinear trapping process. Existence of cold ions does not affect nonlinear processes of the weak-electron-beam instability in which the ion distribution is hardly modified by the excited Langmuir wave packets.
A simple conceptual model of abrupt glacial climate events
Authors: Braun H. , Ganopolski A. , Christl M. , Chialvo D. R.
Published: April 2010

Abstract. Here we use a very simple conceptual model in an attempt to reduce essential parts of the complex nonlinearity of abrupt glacial climate changes (the so-called Dansgaard-Oeschger events) to a few simple principles, namely (i) the existence of two different climate states, (ii) a threshold process and (iii) an overshooting in the stability of the system at the start and the end of the events, which is followed by a millennial-scale relaxation. By comparison with a so-called Earth system model of intermediate complexity (CLIMBER-2), in which the events represent oscillations between two climate states corresponding to two fundamentally different modes of deep-water formation in the North Atlantic, we demonstrate that the conceptual model captures fundamental aspects of the nonlinearity of the events in that model. We use the conceptual model in order to reproduce and reanalyse nonlinear resonance mechanisms that were already suggested in order to explain the characteristic time scale of Dansgaard-Oeschger events. In doing so we identify a new form of stochastic resonance (i.e. an overshooting stochastic resonance) and provide the first explicitly reported manifestation of ghost resonance in a geosystem, i.e. of a mechanism which could be relevant for other systems with thresholds and with multiple states of operation. Our work enables us to explicitly simulate realistic probability measures of Dansgaard-Oeschger events (e.g. waiting time distributions, which are a prerequisite for statistical analyses on the regularity of the events by means of Monte-Carlo simulations). We thus think that our study is an important advance in order to develop more adequate methods to test the statistical significance and the origin of the proposed glacial 1470-year climate cycle.
Percolating magmas in three dimensions
Authors: Gaonac'h H. , Lovejoy S. , Carrier-Nunes M. , Schertzer D. , Lepine F.
Published: April 2010

Abstract. The classical models of volcanic eruptions assume that they originate as a consequence of critical stresses or critical strain rates being exceeded in the magma followed by catastrophic fragmentation. In a recent paper (Gaonac'h et al., 2003) we proposed an additional mechanism based on the properties of complex networks of overlapping bubbles; that extreme multibubble coalescence could lead to catastrophic changes in the magma rheology at a critical vesicularity. This is possible because at a critical vesicularity Pc (the percolation threshold), even in the absence of external stresses the magma fragments. By considering 2-D percolation with the (observed) extreme power law bubble distributions, we showed numerically that P2c had the apparently realistic value ≈0.7. The properties of percolating systems are, however, significantly different in 2-D and 3-D. In this paper, we discuss various new features relevant to 3-D percolation and compare the model predictions with empirical data on explosive volcanism. The most important points are a) bubbles and magma have different 3-D critical percolation points; we show numerically that with power law bubble distributions that the important magma percolation threshold P3c,m has the high value ≈0.97±0.01, b) a generic result of 3-D percolation is that the resulting primary fragments will have power law distributions with exponent B3f≈1.186±0.002, near the empirical value (for pumice) ≈1.1±0.1; c) we review the relevant percolation literature and point out that the elastic properties may have lower – possibly more realistic – critical vesicularities relevant to magmas; d) we explore the implications of long range correlations (power law bubble distributions) and discuss this in combination with bubble anisotropy; e) we propose a new kind of intermediate "elliptical" dimensional percolation involving differentially elongated bubbles and show that it can lead to somewhat lower critical thresholds. These percolation mechanisms for catastrophically weakening magma would presumably operate in conjunction with the classical critical stress and critical strain mechanisms. We conclude that percolation theory provides an attractive theoretical framework for understanding highly vesicular magma.
Investigating turbulent structure of ionospheric plasma velocity using the Halley SuperDARN radar
Authors: Abel G. A. , Freeman M. P. , Chisham G. , Watkins N. W.
Published: April 2010

Abstract. We present a detailed analysis of the spatial structure of the ionospheric plasma velocity in the nightside F-region ionosphere, poleward of the open-closed magnetic field line boundary (OCB), i.e. in regions magnetically connected to the turbulent solar wind. We make use of spatially distributed measurements of the ionospheric plasma velocity made with the Halley Super Dual Auroral Radar Network (SuperDARN) radar between 1996 and 2003. We analyze the spatial structure of the plasma velocity using structure functions and P(0) scaling (where P(0) is the value of the probability density function at 0), which provide simple methods for deriving information about the scaling, intermittency and multi-fractal nature of the fluctuations. The structure functions can also be compared to values predicted by different turbulence models. We find that the limited range of velocity that can be measured by the Halley SuperDARN radar restricts our ability to calculate structure functions. We correct for this by using conditioning (removing velocity fluctuations with magnitudes larger than 3 standard deviations from our calculations). The resultant structure functions suggest that Kraichnan-Iroshnikov versions of P and log-normal models of turbulence best describe the velocity structure seen in the ionosphere.
Estimation of soil types by non linear analysis of remote sensing data
Authors: Hahn C. , Gloaguen R.
Published: April 2010

Abstract. The knowledge of soil type and soil texture is crucial for environmental monitoring purpose and risk assessment. Unfortunately, their mapping using classical techniques is time consuming and costly. We present here a way to estimate soil types based on limited field observations and remote sensing data. Due to the fact that the relation between the soil types and the considered attributes that were extracted from remote sensing data is expected to be non-linear, we apply Support Vector Machines (SVM) for soil type classification. Special attention is drawn to different training site distributions and the kind of input variables. We show that SVM based on carefully selected input variables proved to be an appropriate method for soil type estimation.
Detecting spatial patterns with the cumulant function – Part 1: The theory
Authors: Bernacchia A. , Naveau P.
Published: April 2010

Abstract. In climate studies, detecting spatial patterns that largely deviate from the sample mean still remains a statistical challenge. Although a Principal Component Analysis (PCA), or equivalently a Empirical Orthogonal Functions (EOF) decomposition, is often applied for this purpose, it provides meaningful results only if the underlying multivariate distribution is Gaussian. Indeed, PCA is based on optimizing second order moments, and the covariance matrix captures the full dependence structure of multivariate Gaussian vectors. Whenever the application at hand can not satisfy this normality hypothesis (e.g. precipitation data), alternatives and/or improvements to PCA have to be developed and studied. To go beyond this second order statistics constraint, that limits the applicability of the PCA, we take advantage of the cumulant function that can produce higher order moments information. The cumulant function, well-known in the statistical literature, allows us to propose a new, simple and fast procedure to identify spatial patterns for non-Gaussian data. Our algorithm consists in maximizing the cumulant function. Three families of multivariate random vectors, for which explicit computations are obtained, are implemented to illustrate our approach. In addition, we show that our algorithm corresponds to selecting the directions along which projected data display the largest spread over the marginal probability density tails.
Sequence of eruptive events in the Vesuvio area recorded in shallow-water Ionian Sea sediments
Authors: Taricco C. , Alessio S. , Vivaldo G.
Published: April 2010

Abstract. The dating of the cores we drilled from the Gallipoli terrace in the Gulf of Taranto (Ionian Sea), previously obtained by tephroanalysis, is checked by applying a method to objectively recognize volcanic events. This automatic statistical procedure allows identifying pulse-like features in a series and evaluating quantitatively the confidence level at which the significant peaks are detected. We applied it to the 2000-years-long pyroxenes series of the GT89-3 core, on which the dating is based. The method confirms the dating previously performed by detecting at a high confidence level the peaks originally used and indicates a few possible undocumented eruptions. Moreover, a spectral analysis, focussed on the long-term variability of the pyroxenes series and performed by several advanced methods, reveals that the volcanic pulses are superimposed to a millennial trend and a 400 years oscillation.
Nonadiabatic interaction between a charged particle and an MHD pulse
Authors: Kuramitsu Y. , Hada T.
Published: April 2010

Abstract. Interaction between a magnetohydrodynamic~(MHD) pulse and a charged particle is discussed both numerically and theoretically. Charged particles can be accelerated efficiently in the presence of spatially correlated MHD waves, such as short large amplitude magnetic structures, by successive mirror reflection (Fermi process). In order to understand this process, we study the reflection probability of particles by the MHD pulses, focusing on the adiabaticity on the particle motion. When the particle velocity is small (adiabatic regime), the probability that the particle is reflected by the MHD pulse is essentially determined only by the pitch angle, independent from the velocity. On the other hand, in the non-adiabatic regime, the reflection probability is inversely proportional to the square root of the normalized velocity. We discuss our numerical as well as analytical results of the interaction process with various pulse amplitude, pulse shape, and the pulse winding number. The reflection probability is universally represented as a power law function independent from above pulse properties.
Coronal heating and wind acceleration by nonlinear Alfvén waves – global simulations with gravity, radiation, and conduction
Authors: Suzuki T. K.
Published: April 2010

Abstract. We review our recent results of global one-dimensional (1-D) MHD simulations for the acceleration of solar and stellar winds. We impose transverse photospheric motions corresponding to the granulations, which generate outgoing Alfvén waves. We treat the propagation and dissipation of the Alfvén waves and consequent heating from the photosphere by dynamical simulations in a self-consistent manner. Nonlinear dissipation of Alfven waves becomes quite effective owing to the stratification of the atmosphere (the outward decrease of the density). We show that the coronal heating and the solar wind acceleration in the open magnetic field regions are natural consequence of the footpoint fluctuations of the magnetic fields at the surface (photosphere). We find that the properties of the solar wind sensitively depend on the fluctuation amplitudes at the solar surface because of the nonlinearity of the Alfvén waves, and that the wind speed at 1 AU is mainly controlled by the field strength and geometry of flux tubes. Based on these results, we point out that both fast and slow solar winds can be explained by the dissipation of nonlinear Alfvén waves in a unified manner. We also discuss winds from red giant stars driven by Alfvén waves, focusing on different aspects from the solar wind.
A delay differential model of ENSO variability: parametric instability and the distribution of extremes
Authors: Ghil M. , Zaliapin I. , Thompson S.
Published: April 2010

Abstract. We consider a delay differential equation (DDE) model for El-Niño Southern Oscillation (ENSO) variability. The model combines two key mechanisms that participate in ENSO dynamics: delayed negative feedback and seasonal forcing. We perform stability analyses of the model in the three-dimensional space of its physically relevant parameters. Our results illustrate the role of these three parameters: strength of seasonal forcing b, atmosphere-ocean coupling κ, and propagation period τ of oceanic waves across the Tropical Pacific. Two regimes of variability, stable and unstable, are separated by a sharp neutral curve in the (b, τ) plane at constant κ. The detailed structure of the neutral curve becomes very irregular and possibly fractal, while individual trajectories within the unstable region become highly complex and possibly chaotic, as the atmosphere-ocean coupling κ increases. In the unstable regime, spontaneous transitions occur in the mean "temperature" (i.e., thermocline depth), period, and extreme annual values, for purely periodic, seasonal forcing. The model reproduces the Devil's bleachers characterizing other ENSO models, such as nonlinear, coupled systems of partial differential equations; some of the features of this behavior have been documented in general circulation models, as well as in observations. We expect, therefore, similar behavior in much more detailed and realistic models, where it is harder to describe its causes as completely.
Improved preservation of autocorrelative structure in surrogate data using an initial wavelet step
Authors: Keylock C. J.
Published: April 2010

Abstract. Surrogate data generation algorithms are useful for hypothesis testing or for generating realisations of a process for data extension or modelling purposes. This paper tests a well known surrogate data generation method against a stochastic and also a hybrid wavelet-Fourier transform variant of the original algorithm. The data used for testing vary in their persistence and intermittency, and include synthetic and actual data. The hybrid wavelet-Fourier algorithm outperforms the others in its ability to match the autocorrelation function of the data, although the advantages decrease for high intermittencies and when attention is only directed towards the early part of the autocorrelation function. The improved performance is attributed to the wavelet step of the algorithm.
Climate of utopia
Authors: Gedalin M. , Balikhin M.
Published: April 2010

Abstract. Climate is usually considered to depend on a large number of parameters, this being essentially a functional in multi-dimensional parameter space. We propose a low-dimensional model of a climate where the temperature field on a thermally conducting planet depends on the external energy input and very limited number of internal parameters, like thermal conductivity and reflectivity. Equilibrium temperature and quasistatic variations of climate following slow variations of the energy input are studied. The single phase model exhibits adiabatic behavior and stability with respect to small axisymmetric perturbation. The two phase model shows a non-trivial response to the variations of the external parameter. History dependence, global instabilities and hysteresis behavior characterize the surface temperature evolution.
Analysis of phase coherence in fully developed atmospheric turbulence: Amazon forest canopy
Authors: Chian A. C.-L. , Miranda R. A. , Koga D. , Bolzan M. J. A. , Ramos F. M. , Rempel E. L.
Published: April 2010

Abstract. In a recent paper (Koga et al., 2007) it was shown that the intermittent nature of solar wind turbulence can be characterized by kurtosis and phase coherence index. In this paper, we apply these two nonlinear time series techniques to characterize the intermittent nature of atmospheric turbulence above and within the Amazon forest canopy using the day-time data of temperature and vertical wind velocity measured by a micrometeorological tower at two different heights. By applying kurtosis and phase coherence index to quantify the degree of phase coherence, we identify an enhanced scalar-velocity similarity for in-canopy turbulence compared to the above-canopy turbulence, during the interval of data analysis.
A new method for abrupt change detection in dynamic structures
Authors: He W. P. , Feng G. L. , Wu Q. , Wan S. Q. , Chou J. F.
Published: April 2010

Abstract. Based on Detrended Fluctuation Analysis (DFA), we propose a new method – Moving Detrended Fluctuation Analysis (MDFA) – to detect abrupt change in dynamic structures. Application of this technique shows that this method may be of use in detecting time-instants of abrupt change in dynamic structures and we even find that the MDFA results almost do not depend on length of subseries, and are less affected by noise.
Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM – perfect model experiments
Authors: Liu J. , Fertig E. J. , Li H. , Kalnay E. , Hunt B. R. , Kostelich E. J. , Szunyogh I. , Todling R.
Published: April 2010

Abstract. This paper compares the performance of the Local Ensemble Transform Kalman Filter (LETKF) with the Physical-Space Statistical Analysis System (PSAS) under a perfect model scenario. PSAS is a 3D-Var assimilation system used operationally in the Goddard Earth Observing System Data Assimilation System (GEOS-4 DAS). The comparison is carried out using simulated winds and geopotential height observations and the finite volume Global Circulation Model with 72 grid points zonally, 46 grid points meridionally and 55 vertical levels. With forty ensemble members, the LETKF obtains analyses and forecasts with significantly lower RMS errors than those from PSAS, especially over the Southern Hemisphere and oceans. This observed advantage of the LETKF over PSAS is due to the ability of the 40-member ensemble LETKF to capture flow-dependent errors and thus create a good estimate of the evolving background uncertainty. An initial decrease of the forecast errors in the Northern Hemisphere observed in the PSAS but not in the LETKF suggests that the LETKF analysis is more balanced.
Dispersive MHD waves and alfvenons in charge non-neutral plasmas
Authors: Stasiewicz K. , Ekeberg J.
Published: April 2010

Abstract. Dispersive properties of linear and nonlinear MHD waves, including shear, kinetic, electron inertial Alfvén, and slow and fast magnetosonic waves are analyzed using both analytical expansions and a novel technique of dispersion diagrams. The analysis is extended to explicitly include space charge effects in non-neutral plasmas. Nonlinear soliton solutions, here called alfvenons, are found to represent either convergent or divergent electric field structures with electric potentials and spatial dimensions similar to those observed by satellites in auroral regions. Similar solitary structures are postulated to be created in the solar corona, where fast alfvenons can provide acceleration of electrons to hundreds of keV during flares. Slow alfvenons driven by chromospheric convection produce positive potentials that can account for the acceleration of solar wind ions to 300–800 km/s. New results are discussed in the context of observations and other theoretical models for nonlinear Alfvén waves in space plasmas.
Multivariate non-normally distributed random variables in climate research – introduction to the copula approach
Authors: Schölzel C. , Friederichs P.
Published: April 2010

Abstract. Probability distributions of multivariate random variables are generally more complex compared to their univariate counterparts which is due to a possible nonlinear dependence between the random variables. One approach to this problem is the use of copulas, which have become popular over recent years, especially in fields like econometrics, finance, risk management, or insurance. Since this newly emerging field includes various practices, a controversial discussion, and vast field of literature, it is difficult to get an overview. The aim of this paper is therefore to provide an brief overview of copulas for application in meteorology and climate research. We examine the advantages and disadvantages compared to alternative approaches like e.g. mixture models, summarize the current problem of goodness-of-fit (GOF) tests for copulas, and discuss the connection with multivariate extremes. An application to station data shows the simplicity and the capabilities as well as the limitations of this approach. Observations of daily precipitation and temperature are fitted to a bivariate model and demonstrate, that copulas are valuable complement to the commonly used methods.
Enhancing predictability by increasing nonlinearity in ENSO and Lorenz systems
Authors: Ye Z. , Hsieh W. W.
Published: April 2010

Abstract. The presence of nonlinear terms in the governing equations of a dynamical system usually leads to the loss of predictability, e.g. in numerical weather prediction. However, for the El Niño-Southern Oscillation (ENSO) phenomenon, in an intermediate coupled equatorial Pacific model run under the 1961–1975 and the 1981–1995 climatologies, the latter climatology led to longer-period oscillations, thus greater predictability. In the Lorenz (1963) 3-component chaos system, by adjusting the model parameters to increase the nonlinearity of the system, a similar increase in predictability was found. Thus in the ENSO and Lorenz systems, enhanced nonlinearity from changes in the governing equations could produce longer period oscillations with increased predictability.
Study of nonlinear ion- and electron-acoustic waves in multi-component space plasmas
Authors: Lakhina G. S. , Singh S. V. , Kakad A. P. , Verheest F. , Bharuthram R.
Published: April 2010

Abstract. Large amplitude ion-acoustic and electron-acoustic waves in an unmagnetized multi-component plasma system consisting of cold background electrons and ions, a hot electron beam and a hot ion beam are studied using Sagdeev pseudo-potential technique. Three types of solitary waves, namely, slow ion-acoustic, ion-acoustic and electron-acoustic solitons are found provided the Mach numbers exceed the critical values. The slow ion-acoustic solitons have the smallest critical Mach numbers, whereas the electron-acoustic solitons have the largest critical Mach numbers. For the plasma parameters considered here, both type of ion-acoustic solitons have positive potential whereas the electron-acoustic solitons can have either positive or negative potential depending on the fractional number density of the cold electrons relative to that of the ions (or total electrons) number density. For a fixed Mach number, increases in the beam speeds of either hot electrons or hot ions can lead to reduction in the amplitudes of the ion-and electron-acoustic solitons. However, the presence of hot electron and hot ion beams have no effect on the amplitudes of slow ion-acoustic modes. Possible application of this model to the electrostatic solitary waves (ESWs) observed in the plasma sheet boundary layer is discussed.
Scale-dependency of surface fluxes in an atmospheric mesoscale model: effect of spatial heterogeneity in atmospheric conditions
Authors: Hong Jinkyu , Kim Joon
Published: April 2010

Abstract. We examined the nonlinear effect of spatial heterogeneity in atmospheric conditions on the simulation of surface fluxes in the mesoscale model, MM5 by testing their scale-invariance from a tower footprint to regional scales. The test domain was a homogeneous shortgrass prairie in the central part of the Tibetan Plateau with an eddy-covariance flux tower at the center. We found that the spatial variability resulting from changing distribution of clouds and precipitation in the model domain affected radiative forcing at the ground surface, thereby altering the partitioning of surface fluxes. Consequently, due to increasing spatial variability in atmospheric conditions, the results of MM5 did not produce convergent estimates of surface fluxes with increasing grid sizes. Our finding demonstrates that an atmospheric model can underestimate surface fluxes in regional scale not necessarily due to intrinsic model inaccuracy (e.g., inaccurate parameterization) but due to scale-dependent nonlinear effect of spatial variability in atmospheric conditions.
Model of strong stationary vortex turbulence in space plasmas
Authors: Aburjania G. D. , Chargazia Kh. Z. , Zelenyi L. M. , Zimbardo G.
Published: April 2010

Abstract. This paper investigates the macroscopic consequences of nonlinear solitary vortex structures in magnetized space plasmas by developing theoretical model of plasma turbulence. Strongly localized vortex patterns contain trapped particles and, propagating in a medium, excite substantial density fluctuations and thus, intensify the energy, heat and mass transport processes, i.e., such vortices can form strong vortex turbulence. Turbulence is represented as an ensemble of strongly localized (and therefore weakly interacting) vortices. Vortices with various amplitudes are randomly distributed in space (due to collisions). For their description, a statistical approach is applied. It is supposed that a stationary turbulent state is formed by balancing competing effects: spontaneous development of vortices due to nonlinear twisting of the perturbations' fronts, cascading of perturbations into short scales (direct spectral cascade) and collisional or collisionless damping of the perturbations in the short-wave domain. In the inertial range, direct spectral cascade occurs through merging structures via collisions. It is shown that in the magneto-active plasmas, strong turbulence is generally anisotropic Turbulent modes mainly develop in the direction perpendicular to the local magnetic field. It is found that it is the compressibility of the local medium which primarily determines the character of the turbulent spectra: the strong vortex turbulence forms a power spectrum in wave number space. For example, a new spectrum of turbulent fluctuations in k−8/3 is derived which agrees with available experimental data. Within the framework of the developed model particle diffusion processes are also investigated. It is found that the interaction of structures with each other and particles causes anomalous diffusion in the medium. The effective coefficient of diffusion has a square root dependence on the stationary level of noise.
Seismo-ionospheric coupling correlation analysis of earthquakes in Greece, using empirical mode decomposition
Authors: Tsolis G. S. , Xenos T. D.
Published: April 2010

Abstract. Ionospheric variability as a result of earthquake events is a confirmed phenomenon as published in various seismo-ionospheric coupling studies. Generally, ionospheric variations resulting from earthquake activity are much weaker than disturbances generated by different sources, e.g. geomagnetic storms. However, geomagnetic storm disturbances exhibit more global behaviour, whereas seismo-ionospheric variations occur only locally in an area that is specified by the magnitude of the earthquake. Cross-correlation coefficient analysis is a technique proposed some years ago, and ensures cancelation of geomagnetic storm variations of the ionospheric plasma, provided that the measurements are taken from stations with similar behaviour in these phenomena. In this paper we will use the aforementioned technique for analyzing data from ionospheric stations in Rome and Athens, and apply it to a series of earthquakes in Greece. Considering the local behaviour of the seismo-ionospheric variations, we expect that the Athens station, which happens to be inside the area affected by the earthquake, will accurately capture the disturbances. Due to its distance from the activity, we also do not expect the Rome station measurements to be affected by the seismic events in Greece. In addition, due to the fact that ionospheric plasma parameters exhibit non-stationary and nonlinear behaviour, we propose a novel signal processing technique known as the Hilbert-Huang transform in order to denoise the data before we calculate the cross-correlation coefficient of the two signals. Results from our analysis are in accordance with previously-conducted studies covering the same topic, clearly demonstrating that there are ionospheric precursors 1 to 7 days prior to strong seismic events as well as 1 to 2 days following such events.
Image-model coupling: a simple information theoretic perspective for image sequences
Authors: Smith N. D. , Mitchell C. N. , Budd C. J.
Published: April 2010

Abstract. Images are widely used to visualise physical processes. Models may be developed which attempt to replicate those processes and their effects. The technique of coupling model output to images, which is here called "image-model coupling", may be used to help understand the underlying physical processes, and better understand the limitations of the models. An information theoretic framework is presented for image-model coupling in the context of communication along a discrete channel. The physical process may be regarded as a transmitter of images and the model as part of a receiver which decodes or recognises those images. Image-model coupling may therefore be interpreted as image recognition. Of interest are physical processes which exhibit "memory". The response of such a system is not only dependent on the current values of driver variables, but also on the recent history of drivers and/or system description. Examples of such systems in geophysics include the ionosphere and Earth's climate. The discrete channel model is used to help derive expressions for matching images and model output, and help analyse the coupling.
Limitations of Hall MHD as a model for turbulence in weakly collisional plasmas
Authors: Howes G. G.
Published: April 2010

Abstract. The limitations of Hall MHD as a model for turbulence in weakly collisional plasmas are explored using quantitative comparisons to Vlasov-Maxwell kinetic theory over a wide range of parameter space. The validity of Hall MHD in the cold ion limit is shown, but spurious undamped wave modes exist in Hall MHD when the ion temperature is finite. It is argued that turbulence in the dissipation range of the solar wind must be one, or a mixture, of three electromagnetic wave modes: the parallel whistler, oblique whistler, or kinetic Alfvén waves. These modes are generally well described by Hall MHD. Determining the applicability of linear kinetic damping rates in turbulent plasmas requires a suite of fluid and kinetic nonlinear numerical simulations. Contrasting fluid and kinetic simulations will also shed light on whether the presence of spurious wave modes alters the nonlinear couplings inherent in turbulence and will illuminate the turbulent dynamics and energy transfer in the regime of the characteristic ion kinetic scales.