bluuebunny/crossref_metadata_2025 huggingface dataset:
Multivariate analysis of nonlinearity in sandbar behavior
Authors: Pape L. , Ruessink B. G.
Published: April 2010

Abstract. Alongshore sandbars are often present in the nearshore zones of storm-dominated micro- to mesotidal coasts. Sandbar migration is the result of a large number of small-scale physical processes that are generated by the incoming waves and the interaction between the wave-generated processes and the morphology. The presence of nonlinearity in a sandbar system is an important factor determining its predictability. However, not all nonlinearities in the underlying system are equally expressed in the time-series of sandbar observations. Detecting the presence of nonlinearity in sandbar data is complicated by the dependence of sandbar migration on the external wave forcings. Here, a method for detecting nonlinearity in multivariate time-series data is introduced that can reveal the nonlinear nature of the dependencies between system state and forcing variables. First, this method is applied to four synthetic datasets to demonstrate its ability to qualify nonlinearity for all possible combinations of linear and nonlinear relations between two variables. Next, the method is applied to three sandbar datasets consisting of daily-observed cross-shore sandbar positions and hydrodynamic forcings, spanning between 5 and 9 years. Our analysis reveals the presence of nonlinearity in the time-series of sandbar and wave data, and the relative importance of nonlinearity for each variable. The relation between the results of each sandbar case and patterns in bar behavior are discussed, together with the effects of noise. The small effect of nonlinearity implies that long-term prediction of sandbar positions based on wave forcings might not require sophisticated nonlinear models.
Detecting spatial patterns with the cumulant function – Part 2: An application to El Niño
Authors: Bernacchia A. , Naveau P. , Vrac M. , Yiou P.
Published: April 2010

Abstract. The spatial coherence of a measured variable (e.g. temperature or pressure) is often studied to determine the regions of high variability or to find teleconnections, i.e. correlations between specific regions. While usual methods to find spatial patterns, such as Principal Components Analysis (PCA), are constrained by linear symmetries, the dependence of variables such as temperature or pressure at different locations is generally nonlinear. In particular, large deviations from the sample mean are expected to be strongly affected by such nonlinearities. Here we apply a newly developed nonlinear technique (Maxima of Cumulant Function, MCF) for detection of typical spatial patterns that largely deviate from the mean. In order to test the technique and to introduce the methodology, we focus on the El Niño/Southern Oscillation and its spatial patterns. We find nonsymmetric temperature patterns corresponding to El Niño and La Niña, and we compare the results of MCF with other techniques, such as the symmetric solutions of PCA, and the nonsymmetric solutions of Nonlinear PCA (NLPCA). We found that MCF solutions are more reliable than the NLPCA fits, and can capture mixtures of principal components. Finally, we apply Extreme Value Theory on the temporal variations extracted from our methodology. We find that the tails of the distribution of extreme temperatures during La Niña episodes is bounded, while the tail during El Niños is less likely to be bounded. This implies that the mean spatial patterns of the two phases are asymmetric, as well as the behaviour of their extremes.
Integrable, oblique travelling waves in quasi-charge-neutral two-fluid plasmas
Authors: Webb G. M. , Ko C. M. , Mace R. L. , McKenzie J. F. , Zank G. P.
Published: April 2010

Abstract. A Hamiltonian description of oblique travelling waves in a two-fluid, charge-neutral, electron-proton plasma reveals that the transverse momentum equations for the electron and proton fluids are exactly integrable in cases where the total transverse momentum flux integrals, Py(d) and Pz(d), are both zero in the de Hoffman Teller (dHT) frame. In this frame, the transverse electric fields are zero, which simplifies the transverse momentum equations for the two fluids. The integrable travelling waves for the case Py(d)=Pz(d)=0, are investigated based on the Hamiltonian trajectories in phase space, and also on the longitudinal structure equation for the common longitudinal fluid velocity component ux of the electron and proton fluids. Numerical examples of a variety of travelling waves in a cold plasma, including oscillitons, are used to illustrate the physics. The transverse, electron and proton velocity components ujy and ujz (j=e, p) of the waves exhibit complex, rosette type patterns over several periods for ux. The role of separatrices in the phase space, the rotational integral and the longitudinal structure equation on the different wave forms are discussed.
Transformation of frequency-magnitude relation prior to large events in the model of block structure dynamics
Authors: Soloviev A.
Published: April 2010

Abstract. The b-value change in the frequency-magnitude (FM) distribution for a synthetic earthquake catalogue obtained by means of the model of block structure dynamics has been studied. The catalogue is divided into time periods preceding strong earthquakes and time periods that do not precede strong earthquakes. The separate analysis of these periods shows that the b-value is smaller before strong earthquakes. The similar phenomenon has been found also for the observed seismicity of the Southern California. The model of block structure dynamics represents a seismic region as a system of perfectly rigid blocks divided by infinitely thin plane faults. The blocks interact between themselves and with the underlying medium. The system of blocks moves as a consequence of prescribed motion of the boundary blocks and of the underlying medium. As the blocks are perfectly rigid, all deformation takes place in the fault zones and at the block base in contact with the underlying medium. Relative block displacements take place along the fault zones. Block motion is defined so that the system is in a quasistatic equilibrium state. The interaction of blocks along the fault zones is viscous-elastic ("normal state") while the ratio of the stress to the pressure remains below a certain strength level. When the critical level is exceeded in some part of a fault zone, a stress-drop ("failure") occurs (in accordance with the dry friction model), possibly causing failure in other parts of the fault zones. These failures produce earthquakes. Immediately after the earthquake and for some time after, the affected parts of the fault zones are in a state of creep. This state differs from the normal state because of a faster growth of inelastic displacements, lasting until the stress falls below some other level. This numerical simulation gives rise a synthetic earthquake catalogue.
Robust nonlinear canonical correlation analysis: application to seasonal climate forecasting
Authors: Cannon A. J. , Hsieh W. W.
Published: April 2010

Abstract. Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasonal climate forecasts. The neural network model architecture of standard NLCCA is kept intact, but the cost functions used to set the model parameters are replaced with more robust variants. The Pearson product-moment correlation in the double-barreled network is replaced by the biweight midcorrelation, and the mean squared error (mse) in the inverse mapping networks can be replaced by the mean absolute error (mae). Robust variants of NLCCA are demonstrated on a synthetic dataset and are used to forecast sea surface temperatures in the tropical Pacific Ocean based on the sea level pressure field. Results suggest that adoption of the biweight midcorrelation can lead to improved performance, especially when a strong, common event exists in both predictor/predictand datasets. Replacing the mse by the mae leads to improved performance on the synthetic dataset, but not on the climate dataset except at the longest lead time, which suggests that the appropriate cost function for the inverse mapping networks is more problem dependent.
Generation of weakly nonlinear nonhydrostatic internal tides over large topography: a multi-modal approach
Authors: Maugé R. , Gerkema T.
Published: April 2010

Abstract. A set of evolution equations is derived for the modal coefficients in a weakly nonlinear nonhydrostatic internal-tide generation problem. The equations allow for the presence of large-amplitude topography, e.g. a continental slope, which is formally assumed to have a length scale much larger than that of the internal tide. However, comparison with results from more sophisticated numerical models show that this restriction can in practice be relaxed. It is shown that a topographically induced coupling between modes occurs that is distinct from nonlinear coupling. Nonlinear effects include the generation of higher harmonics by reflection from boundaries, i.e. steeper tidal beams at frequencies that are multiples of the basic tidal frequency. With a seasonal thermocline included, the model is capable of reproducing the phenomenon of local generation of internal solitary waves by a tidal beam impinging on the seasonal thermocline.
Loading rates in California inferred from aftershocks
Authors: Narteau C. , Shebalin P. , Holschneider M.
Published: April 2010

Abstract. We estimate the loading rate in southern California and the change in stress induced by a transient slip event across the San Andreas fault (SAF) system in central California, using a model of static fatigue. We analyze temporal properties of aftershocks in order to determine the time delay before the onset of the power law aftershock decay rate. In creep-slip and stick-slip zones, we show that the rate of change of this delay is related to seismic and aseismic deformation across the SAF system. Furthermore, we show that this rate of change is proportional to the deficit of slip rate along the SAF. This new relationship between geodetic and seismological data is in good agreement with predictions from a Limited Power Law model in which the evolution of the duration of a linear aftershock decay rate over short time results from variations in the load of the brittle upper crust.
Constrained robust estimation of magnetotelluric impedance functions based on a bounded-influence regression M-estimator and the Hilbert transform
Authors: Sutarno D.
Published: April 2010

Abstract. Robust impedance estimation procedures are now in standard use in magnetotelluric (MT) measurements and research. These always yield impedance estimates which are better than the conventional least square (LS) estimation because the 'real' MT data almost never satisfy the statistical assumptions of Gaussian distribution upon which normal spectral analysis is based. The robust estimation procedures are commonly based on M-estimators that have the ability to reduce the influence of unusual data (outliers) in the response (electric field) variables, but are often not sensitive to exceptional predictors (magnetic field) data, which are termed leverage points. This paper proposes an alternative procedure for making reliably robust estimates of MT impedance functions, which simultaneously provide protection from the influence of outliers in both response and input variables. The means for accomplishing this is based on the bounded-influence regression M-estimation and the Hilbert Transform operating on the causal MT impedance functions. In the resulting regression estimates, outlier contamination is removed and the self consistency between the real and imaginary parts of the impedance estimates is guaranteed. Using synthetic and real MT data, it is shown that the method can produce improved MT impedance functions even under conditions of severe noise contamination.
A nudging-based data assimilation method: the Back and Forth Nudging (BFN) algorithm
Authors: Auroux D. , Blum J.
Published: April 2010

Abstract. This paper deals with a new data assimilation algorithm, called Back and Forth Nudging. The standard nudging technique consists in adding to the equations of the model a relaxation term that is supposed to force the observations to the model. The BFN algorithm consists in repeatedly performing forward and backward integrations of the model with relaxation (or nudging) terms, using opposite signs in the direct and inverse integrations, so as to make the backward evolution numerically stable. This algorithm has first been tested on the standard Lorenz model with discrete observations (perfect or noisy) and compared with the variational assimilation method. The same type of study has then been performed on the viscous Burgers equation, comparing again with the variational method and focusing on the time evolution of the reconstruction error, i.e. the difference between the reference trajectory and the identified one over a time period composed of an assimilation period followed by a prediction period. The possible use of the BFN algorithm as an initialization for the variational method has also been investigated. Finally the algorithm has been tested on a layered quasi-geostrophic model with sea-surface height observations. The behaviours of the two algorithms have been compared in the presence of perfect or noisy observations, and also for imperfect models. This has allowed us to reach a conclusion concerning the relative performances of the two algorithms.
Channelling of high-latitude boundary-layer flow
Authors: Nawri N. , Stewart R. E.
Published: April 2010

Abstract. Due to the stability of the boundary-layer stratification, high-latitude winds over complex terrain are strongly affected by blocking and channelling effects. Consequently, at many low-lying communities in the Canadian Archipelago, including Cape Dorset and Iqaluit considered in this study, surface winds for the most part are from two diametrically opposed directions, following the orientation of the elevated terrain. Shifts between the two prevailing wind directions can be sudden and are associated with geostrophic wind directions within a well defined narrow range. To quantitatively investigate the role of large-scale pressure gradients and the quasi-geostrophic overlying flow, an idealised dynamical system for the evolution of channelled surface winds is derived from the basic equations of motion, in which stability of stationary along-channel wind directions is described as a function of the geostrophic wind. In comparison with long-term horizontal wind statistics at the two locations it is shown that the climatologically prevailing wind directions can be identified as stationary states of the idealised wind model, and that shifts between prevailing wind directions can be represented as stability transitions between these stationary states. In that sense, the prevailing local wind conditions can be interpreted as attracting states of the actual flow, with observed surface winds adjusting to a new stable direction as determined by the idealised system within 3–9 h. Over these time-scales and longer it is therefore advantageous to determine the relatively slow evolution of the observationally well-resolved large-scale pressure distribution, instead of modelling highly variable surface winds directly. The simplified model also offers a tool for dynamical downscaling of global climate simulations, and for determining future scenarios for local prevailing wind conditions. In particular, it allows an estimation of the sensitivity of local low-level winds to changes in the large-scale atmospheric circulation.
ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction
Authors: Ross I. , Valdes P. J. , Wiggins S.
Published: April 2010

Abstract. Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. These linear methods may not be appropriate for the analysis of data arising from nonlinear processes occurring in the climate system. Numerous techniques for nonlinear dimensionality reduction have been developed recently that may provide a potentially useful tool for the identification of low-dimensional manifolds in climate data sets arising from nonlinear dynamics. Here, we apply Isomap, one such technique, to the study of El Niño/Southern Oscillation variability in tropical Pacific sea surface temperatures, comparing observational data with simulations from a number of current coupled atmosphere-ocean general circulation models. We use Isomap to examine El Niño variability in the different datasets and assess the suitability of the Isomap approach for climate data analysis. We conclude that, for the application presented here, analysis using Isomap does not provide additional information beyond that already provided by principal component analysis.
Non-stationary temporal characterization of the temperature profile of a soil exposed to frost in south-eastern Canada
Authors: Anctil F. , Pratte A. , Parent L. E. , Bolinder M. A.
Published: April 2010

Abstract. The objective of this work was to compare time and frequency fluctuations of air and soil temperatures (2-, 5-, 10-, 20- and 50-cm below the soil surface) using the continuous wavelet transform, with a particular emphasis on the daily cycle. The analysis of wavelet power spectra and cross power spectra provided detailed non-stationary accounts with respect to frequencies (or periods) and to time of the structure of the data and also of the relationships that exist between time series. For this particular application to the temperature profile of a soil exposed to frost, both the air temperature and the 2-cm depth soil temperature time series exhibited a dominant power peak at 1-d periodicity, prominent from spring to autumn. This feature was gradually damped as it propagated deeper into the soil and was weak for the 20-cm depth. Influence of the incoming solar radiation was also revealed in the wavelet power spectra analysis by a weaker intensity of the 1-d peak. The principal divergence between air and soil temperatures, besides damping, occurred in winter from the latent heat release associated to the freezing of the soil water and the insulation effect of snowpack that cease the dependence of the soil temperature to the air temperature. Attenuation and phase-shifting of the 1-d periodicity could be quantified through scale-averaged power spectra and time-lag estimations. Air temperature variance was only partly transferred to the 2-cm soil temperature time series and much less so to the 20-cm soil depth.
Assessing soil surface roughness decay during simulated rainfall by multifractal analysis
Authors: Vidal Vázquez E. , García Moreno R. , Miranda J. G. V. , Díaz M. C. , Saá Requejo A. , Paz Ferreiro J. , Tarquis A. M.
Published: April 2010

Abstract. Understanding and describing the spatial characteristics of soil surface microrelief are required for modelling overland flow and erosion. We employed the multifractal approach to characterize topographical point elevation data sets acquired by high resolution laser scanning for assessing the effect of simulated rainfall on microrelief decay. Three soil surfaces with different initial states or composition and rather smooth were prepared on microplots and subjected to successive events of simulated rainfall. Soil roughness was measured on a 2×2 mm2 grid, initially, i.e. before rain, and after each simulated storm, yielding a total of thirteen data sets for three rainfall sequences. The vertical microrelief component as described by the statistical index random roughness (RR) exhibited minor changes under rainfall in two out of three study cases, which was due to the imposed wet initial state constraining aggregate breakdown. The effect of cumulative rainfall on microrelief decay was also assessed by multifractal analysis performed with the box-count algorithm. Generalized dimension, Dq, spectra allowed characterization of the spatial variation of soil surface microrelief measured at the microplot scale. These Dq spectra were also sensitive to temporal changes in soil surface microrelief, so that in all the three study rain sequences, the initial soil surface and the surfaces disturbed by successive storms displayed great differences in their degree of multifractality. Therefore, Multifractal parameters best discriminate between successive soil stages under a given rain sequence. Decline of RR and multifractal parameters showed little or no association.
Breeding and predictability in the baroclinic rotating annulus using a perfect model
Authors: Young R. M. B. , Read P. L.
Published: April 2010

Abstract. We present results from a computational study of predictability in fully-developed baroclinically unstable laboratory flows. This behaviour is studied in the Met Office/Oxford Rotating Annulus Laboratory Simulation – a model of the classic rotating annulus laboratory experiment with differentially heated cylindrical sidewalls, which is firmly established as an insightful laboratory analogue for certain kinds of atmospheric dynamical behaviour. This work is the first study of "predictability of the first kind" in the annulus experiment. We devise an ensemble prediction scheme using the breeding method to study the predictability of the annulus in the perfect model scenario. This scenario allows one simulation to be defined as the true state, against which all forecasts are measured. We present results from forecasts over a range of quasi-periodic and chaotic annulus flow regimes. A number of statistical and meteorological techniques are used to compare the predictability of these flows: bred vector growth rate and dimension, error variance, "spaghetti plots", probability forecasts, Brier score, and the Kolmogorov-Smirnov test. These techniques gauge both the predictability of the flow and the performance of the ensemble relative to a forecast using a climatological distribution. It is found that in the perfect model scenario, the two quasi-periodic regimes examined may be indefinitely predictable. The two chaotic regimes (structural vacillation and period doubled amplitude vacillation) show a loss of predictability on a timescale of hundreds to thousands of seconds (65–280 annulus rotation periods, or 1–3 Lyapunov times).
Two- and three-dimensional computation of solitary wave runup on non-plane beach
Authors: Choi B. H. , Pelinovsky E. , Kim D. C. , Didenkulova I. , Woo S.-B.
Published: April 2010

Abstract. Solitary wave runup on a non-plane beach is studied analytically and numerically. For the theoretical approach, nonlinear shallow-water theory is applied to obtain the analytical solution for the simplified bottom geometry, such as an inclined channel whose cross-slope shape is parabolic. It generalizes Carrier-Greenspan approach for long wave runup on the inclined plane beach that is currently used now. For the numerical study, the Reynolds Averaged Navier-Stokes (RANS) system is applied to study soliton runup on an inclined beach and the detailed characteristics of the wave processes (water displacement, velocity field, turbulent kinetic energy, energy dissipation) are analyzed. In this study, it is theoretically and numerically proved that the existence of a parabolic cross-slope channel on the plane beach causes runup intensification, which is often observed in post-tsunami field surveys.
Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF
Authors: Carrassi A. , Trevisan A. , Descamps L. , Talagrand O. , Uboldi F.
Published: April 2010

Abstract. A hybrid scheme obtained by combining 3DVar with the Assimilation in the Unstable Subspace (3DVar-AUS) is tested in a QG model, under perfect model conditions, with a fixed observational network, with and without observational noise. The AUS scheme, originally formulated to assimilate adaptive observations, is used here to assimilate the fixed observations that are found in the region of local maxima of BDAS vectors (Bred vectors subject to assimilation), while the remaining observations are assimilated by 3DVar. The performance of the hybrid scheme is compared with that of 3DVar and of an EnKF. The improvement gained by 3DVar-AUS and the EnKF with respect to 3DVar alone is similar in the present model and observational configuration, while 3DVar-AUS outperforms the EnKF during the forecast stage. The 3DVar-AUS algorithm is easy to implement and the results obtained in the idealized conditions of this study encourage further investigation toward an implementation in more realistic contexts.
The influence of solar wind turbulence on geomagnetic activity
Authors: Jankovičovà D. , Vörös Z. , Šimkanin J.
Published: April 2010

Abstract. The importance of space weather and its forecasting is growing as interest in studying geoeffective processes in the Sun – solar wind – magnetosphere – ionosphere coupled system is increasing. In this paper higher order statistical moments of interplanetary magnetic field and geomagnetic SYM-H index fluctuations are compared. The proper description of fluctuations in the solar wind can elucidate important aspects of the geoeffectivity of upstream turbulence and contribute to our understanding of space weather. Our results indicate that quasi-stationary intervals during both quiet and stormy periods have to be investigated in order to find correlations between upstream and geomagnetic conditions. We found that the fourth statistical moment (kurtosis), which was not considered in previous studies, appears to be a new geoeffective parameter. Intermittency of the magnetic turbulence in the solar wind can influence the efficiency of the solar wind – magnetosphere coupling through affecting magnetic reconnection at the Earth's magnetopause.
Consequences of entropy bifurcation in non-Maxwellian astrophysical environments
Authors: Leubner M. P.
Published: April 2010

Abstract. Non-extensive systems, accounting for long-range interactions and correlations, are fundamentally related to non-Maxwellian distributions where a duality of equilibria appears in two families, the non-extensive thermodynamic equilibria and the kinetic equilibria. Both states emerge out of particular entropy generalization leading to a class of probability distributions, where bifurcation into two stationary states is naturally introduced by finite positive or negative values of the involved entropic index kappa. The limiting Boltzmann-Gibbs-Shannon state (BGS), neglecting any kind of interactions within the system, is subject to infinite entropic index and thus characterized by self-duality. Fundamental consequences of non-extensive entropy bifurcation, manifest in different astrophysical environments, as particular core-halo patterns of solar wind velocity distributions, the probability distributions of the differences of the fluctuations in plasma turbulence as well as the structure of density distributions in stellar gravitational equilibrium are discussed. In all cases a lower entropy core is accompanied by a higher entropy halo state as compared to the standard BGS solution. Data analysis and comparison with high resolution observations significantly support the theoretical requirement of non-extensive entropy generalization when dealing with systems subject to long-range interactions and correlations.
Dust-acoustic solitary structures in plasmas with nonthermal electrons and positive dust
Authors: Verheest F. , Pillay S. R.
Published: April 2010

Abstract. Large dust-acoustic solitons and kinks in dusty plasmas with positive cold dust, nonthermally distributed electrons and Boltzmann ions have been studied in a systematic way, to delimit their compositional parameter space. The existence domain of positive solitons is limited by infinite dust compression, of negative ones by the occurrence of potential kinks, provided the electrons are sufficiently nonthermal and there is sufficient positive charge on the dust. There is a parameter range where both negative and positive solitary structures coexist.
Extreme event return times in long-term memory processes near 1/f
Authors: Blender R. , Fraedrich K. , Sienz F.
Published: April 2010

Abstract. The distribution of extreme event return times and their correlations are analyzed in observed and simulated long-term memory (LTM) time series with 1/f power spectra. The analysis is based on tropical temperature and mixing ratio (specific humidity) time series from TOGA COARE with 1 min resolution and an approximate 1/f power spectrum. Extreme events are determined by Peak-Over-Threshold (POT) crossing. The Weibull distribution represents a reasonable fit to the return time distributions while the power-law predicted by the stretched exponential for 1/f deviates considerably. For a comparison and an analysis of the return time predictability, a very long simulated time series with an approximate 1/f spectrum is produced by a fractionally differenced (FD) process. This simulated data confirms the Weibull distribution (a power law can be excluded). The return time sequences show distinctly weaker long-term correlations than the original time series (correlation exponent γ≈0.56).
Artificial Neural Networks to reconstruct incomplete satellite data: application to the Mediterranean Sea Surface Temperature
Authors: Pisoni E. , Pastor F. , Volta M.
Published: April 2010

Abstract. Satellite data can be very useful in applications where extensive spatial information is needed, but sometimes missing data due to presence of clouds can affect data quality. In this study a methodology for pre-processing sea surface temperature (SST) data is proposed. The methodology, that processes measures in the visible wavelength, is based on an Artificial Neural Network (ANN) system. The effectiveness of the procedure has been also evaluated comparing results obtained using an interpolation method. After the methodology has been identified, a validation is performed on 3 different episodes representative of SST variability in the Mediterranean sea. The proposed technique can process SST NOAA/AVHRR data to simulate severe storm episodes by means of prognostic meteorological models.
Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band
Authors: de Montera L. , Mallet C. , Barthès L. , Golé P.
Published: April 2010

Abstract. This paper shows how nonlinear models originally developed in the finance field can be used to predict rain attenuation level and volatility in Earth-to-Satellite links operating at the Extremely High Frequencies band (EHF, 20–50 GHz). A common approach to solving this problem is to consider that the prediction error corresponds only to scintillations, whose variance is assumed to be constant. Nevertheless, this assumption does not seem to be realistic because of the heteroscedasticity of error time series: the variance of the prediction error is found to be time-varying and has to be modeled. Since rain attenuation time series behave similarly to certain stocks or foreign exchange rates, a switching ARIMA/GARCH model was implemented. The originality of this model is that not only the attenuation level, but also the error conditional distribution are predicted. It allows an accurate upper-bound of the future attenuation to be estimated in real time that minimizes the cost of Fade Mitigation Techniques (FMT) and therefore enables the communication system to reach a high percentage of availability. The performance of the switching ARIMA/GARCH model was estimated using a measurement database of the Olympus satellite 20/30 GHz beacons and this model is shown to outperform significantly other existing models. The model also includes frequency scaling from the downlink frequency to the uplink frequency. The attenuation effects (gases, clouds and rain) are first separated with a neural network and then scaled using specific scaling factors. As to the resulting uplink prediction error, the error contribution of the frequency scaling step is shown to be larger than that of the downlink prediction, indicating that further study should focus on improving the accuracy of the scaling factor.
Projection of compact fractal sets: application to diffusion-limited and cluster-cluster aggregates
Authors: Maggi F.
Published: April 2010

Abstract. The need to assess the three-dimensional fractal dimension of fractal aggregates from the fractal dimension of two-dimensional projections is very frequent in geophysics, soil, and atmospheric sciences. However, a generally valid approach to relate the two- and three-dimensional fractal dimensions is missing, thus questioning the accuracy of the method used until now in practical applications. A mathematical approach developed for application to suspended aggregates made of cohesive sediment is investigated and applied here more generally to Diffusion-Limited Aggregates (DLA) and Cluster-Cluster Aggregates (CCA), showing higher accuracy in determining the three-dimensional fractal dimension compared to the method currently used.
Gyrostatic extensions of the Howard-Krishnamurti model of thermal convection with shear
Authors: Tong C. , Gluhovsky A.
Published: April 2010

Abstract. The Howard & Krishnamurti (1986) low-order model (LOM) of Rayleigh-Bénard convection with spontaneous vertical shear can be extended to incorporate various additional physical effects, such as externally forced vertical shear and magnetic field. Designing such extended LOMs so that their mathematical structure is isomorphic to those of systems of coupled gyrostats, with damping and forcing, allows for a modular approach while respecting conservation laws. Energy conservation (in the limit of no damping and forcing) prevents solutions that diverge to infinity, which are present in the original Howard & Krishnamurti LOM. The first LOM developed here (as a candidate model of transverse rolls) involves adding a new Couette mode to represent externally forced vertical shear. The second LOM is a modification of the Lantz (1995) model for magnetoconvection with shear. The modification eliminates an invariant manifold in the original model that leads to potentially unphysical behavior, namely solutions that diverge to infinity, in violation of energy conservation. This paper reports the first extension of the coupled gyrostats modeling framework to incorporate externally forced vertical shear and magnetoconvection with shear. Its aim is to demonstrate better model building techniques that avoid pathologies present in earlier models; consequently we do not focus here on analysis of dynamics or model validation.
Initial state perturbations in ensemble forecasting
Authors: Magnusson L. , Källén E. , Nycander J.
Published: April 2010

Abstract. Due to the chaotic nature of atmospheric dynamics, numerical weather prediction systems are sensitive to errors in the initial conditions. To estimate the forecast uncertainty, forecast centres produce ensemble forecasts based on perturbed initial conditions. How to optimally perturb the initial conditions remains an open question and different methods are in use. One is the singular vector (SV) method, adapted by ECMWF, and another is the breeding vector (BV) method (previously used by NCEP). In this study we compare the two methods with a modified version of breeding vectors in a low-order dynamical system (Lorenz-63). We calculate the Empirical Orthogonal Functions (EOF) of the subspace spanned by the breeding vectors to obtain an orthogonal set of initial perturbations for the model. We will also use Normal Mode perturbations. Evaluating the results, we focus on the fastest growth of a perturbation. The results show a large improvement for the BV-EOF perturbations compared to the non-orthogonalised BV. The BV-EOF technique also shows a larger perturbation growth than the SVs of this system, except for short time-scales. The highest growth rate is found for the second BV-EOF for the long-time scale. The differences between orthogonal and non-orthogonal breeding vectors are also investigated using the ECMWF IFS-model. These results confirm the results from the Loernz-63 model regarding the dependency on orthogonalisation.
Mitigation of energetic electrons in the magnetosphere by amplified whistler wave under double cyclotron resonances
Authors: Kuo S. P.
Published: April 2010

Abstract. An optimal approach reducing the population of MeV electrons in the magnetosphere is presented. Under a double resonance condition, whistler wave is simultaneously in cyclotron resonance with keV and MeV electrons. The injected whistler waves is first amplified by the background keV electrons via loss-cone negative mass instability to become effective in precipitating MeV electrons via cyclotron resonance elevated chaotic scattering. The numerical results show that a small amplitude whistler wave can be amplified by more than 25 dB. The amplification factor reduces only about 10 dB with a 30 dB increase of the initial wave intensity. Use of an amplified whistler wave to scatter 1.5 MeV electrons from an initial pitch angle of 86.5°to a pitch angle <50° is demonstrated. The ratio of the required wave magnetic field to the background magnetic field is calculated to be about 8×10−4.
Direct and inverse cascades in the geodynamo
Authors: Reshetnyak M. , Hejda P.
Published: April 2010

Abstract. The rapid rotation of planets causes cyclonic thermal turbulence in their cores which may generate the large-scale magnetic fields observed outside the planets. We investigate numerically a model based on the geodynamo equations in simplified geometry, which enables us to reproduce the main features of small-scale geostrophic flows in physical and wave vector spaces. We find fluxes of kinetic and magnetic energy as a function of the wave number and demonstrate the co-existence of forward and inverse cascades. We also explain the mechanism of magnetic field saturation at the end of the kinematic dynamo regime.
Influence of thresholding in mass and entropy dimension of 3-D soil images
Authors: Tarquis A. M. , Heck R. J. , Grau J. B. , Fabregat J. , Sanchez M. E. , Antón J. M.
Published: April 2010

Abstract. With the advent of modern non-destructive tomography techniques, there have been many attempts to analyze 3-D pore space features mainly concentrating on soil structure. This analysis opens a challenging opportunity to develop techniques for quantifying and describe pore space properties, one of them being fractal analysis. Undisturbed soil samples were collected from four horizons of Brazilian soil and 3-D images at 45 μm resolution. Four different threshold criteria were used to transform computed tomography (CT) grey-scale imagery into binary imagery (pore/solid) to estimate their mass fractal dimension (Dm) and entropy dimension (D1). Each threshold criteria had a direct influence on the porosity obtained, varying from 8 to 24% in one of the samples, and on the fractal dimensions. Linear scaling was observed over all the cube sizes, however depending on the range of cube sizes used in the analysis, Dm could vary from 3.00 to 2.20, realizing that the threshold influenced mainly the scaling in the smallest cubes (length of size from 1 to 16 voxels). Dm and D1 showed a logarithmic relation with the apparent porosity in the image, however, the increase of both values respect to porosity defined a characteristic feature for each horizon that can be related to soil texture and depth.
Experimental and numerical study of spatial and temporal evolution of nonlinear wave groups
Authors: Shemer L. , Dorfman B.
Published: April 2010

Abstract. The evolution along the tank of unidirectional nonlinear wave groups with narrow spectrum is studied both experimentally and numerically. Measurements of the instantaneous surface elevation within the tank are carried out using digital processing of video-recorded sequences of images of the contact line movement at the tank side wall. The accuracy of the video-derived results is verified by measurements performed by conventional resistance-type wave gauges. An experimental procedure is developed that enables processing of large volumes of video images and thus allows capturing the spatial structure of the instantaneous wave field along the whole tank. The experimentally obtained data are compared quantitatively with the solutions of the Modified Nonlinear Schrödinger (MNLS, or Dysthe) equation written in either temporal or spatial form. The adopted approach allows studying evolution along the tank of wave frequency spectra, as well as the temporal variation of the wave number spectra. It is demonstrated that accounting for the 2nd order bound (locked) waves is essential for getting a qualitative and quantitative agreement between the measured and the computed spectra. The relation between the frequency and the wave number spectra is discussed.
Solar wind vs magnetosheath turbulence and Alfvén vortices
Authors: Alexandrova O.
Published: April 2010

Abstract. In this paper we give firstly a broad review of the space plasma turbulence around the ion characteristic space and temporal scales within two natural laboratories, the solar wind and the Earth magnetosheath. In both regions power law spectra of magnetic fluctuations are observed. In both regions these spectra have a break in the vicinity of the ion cyclotron frequency. A distinctive feature of the magnetosheath turbulence is the presence of Alfvén vortices at scales of the spectral break. The Alfvén vortices are multi-scale nonlinear structures. We give a review of the main theoretical features of incompressible Alfvén vortsices in the second part of the paper. Finally, we analyze the spectral properties of the Alfvén vortex solution and of the network of such vortices. We show that the observed magnetosheath spectrum in presence of the Alfvén vortices can be described, at least partially, by the vortex network model.
A two-fluid model describing the finite-collisionality, stationary Alfvén wave in anisotropic plasma
Authors: Finnegan S. M. , Koepke M. E. , Knudsen D. J.
Published: April 2010

Abstract. The stationary inertial Alfvén (StIA) wave (Knudsen, 1996) was predicted for cold, collisionless plasma. The model was generalized (Finnegan et al., 2008) to include nonzero values of electron and ion collisional resistivity and thermal pressure. Here, the two-fluid model is further generalized to include anisotropic thermal pressure. A bounded range of values of parallel electron drift velocity is found that excludes periodic stationary Alfvén wave solutions. This exclusion region depends on the value of the local Alfvén speed VA, plasma beta perpendicular to the magnetic field β⊥ and electron temperature anisotropy.
Contribution of 3-D electrical resistivity tomography for landmines detection
Authors: Metwaly M. , El-Qady G. , Matsushima J. , Szalai S. , Al-Arifi N. S. N. , Taha A.
Published: April 2010

Abstract. Landmines are a type of inexpensive weapons widely used in the pre-conflicted areas in many countries worldwide. The two main types are the metallic and non-metallic (mostly plastic) landmines. They are most commonly investigated by magnetic, ground penetrating radar (GPR), and metal detector (MD) techniques. These geophysical techniques however have significant limitations in resolving the non-metallic landmines and wherever the host materials are conductive. In this work, the 3-D electric resistivity tomography (ERT) technique is evaluated as an alternative and/or confirmation detection system for both landmine types, which are buried in different soil conditions and at different depths. This can be achieved using the capacitive resistivity imaging system, which does not need direct contact with the ground surface. Synthetic models for each case have been introduced using metallic and non-metallic bodies buried in wet and dry environments. The inversion results using the L1 norm least-squares optimization method tend to produce robust blocky models of the landmine body. The dipole axial and the dipole equatorial arrays tend to have the most favorable geometry by applying dynamic capacitive electrode and they show significant signal strength for data sets with up to 5% noise. Increasing the burial depth relative to the electrode spacing as well as the noise percentage in the resistivity data is crucial in resolving the landmines at different environments. The landmine with dimension and burial depth of one electrode separation unit is over estimated while the spatial resolutions decrease as the burial depth and noise percentage increase.
Solar wind interaction with the Earth's magnetosphere: the role of reconnection in the presence of a large scale sheared flow
Authors: Califano F. , Faganello M. , Pegoraro F. , Valentini F.
Published: April 2010

Abstract. The Earth's magnetosphere and solar wind environment is a laboratory of excellence for the study of the physics of collisionless magnetic reconnection. At low latitude magnetopause, magnetic reconnection develops as a secondary instability due to the stretching of magnetic field lines advected by large scale Kelvin-Helmholtz vortices. In particular, reconnection takes place in the sheared magnetic layer that forms between adjacent vortices during vortex pairing. The process generates magnetic islands with typical size of the order of the ion inertial length, much smaller than the MHD scale of the vortices and much larger than the electron inertial length. The process of reconnection and island formation sets up spontaneously, without any need for special boundary conditions or initial conditions, and independently of the initial in-plane magnetic field topology, whether homogeneous or sheared.
Seismic entangled patterns analyzed via multiresolution decomposition
Authors: Leite F. E. A. , Montagne R. , Corso G. , Lucena L. S.
Published: April 2010

Abstract. This article explores a method for distinguishing entangled coherent structures embedded in geophysical images. The original image is decomposed in a series of j-scale-images using multiresolution decomposition. To improve the image processing analysis each j-image is divided in l-spacial regions generating set of (j, l)-regions. At each (j, l)-region we apply a continuous wavelet transform to evaluate Eν, the spectrum of energy. Eν has two maxima in the original data. Otherwise, at each scale Eν hast typically one peak. The localization of the peaks changes according to the (j, l)-region. The intensity of the peaks is linked with the presence of coherent structures, or patterns, at the respective (j, l)-region. The method is successfully applied to distinguish, in scale and region, the ground roll noise from the relevant geologic information in the signal.
Correlated earthquakes in a self-organized model
Authors: Baiesi M.
Published: April 2010

Abstract. Motivated by the fact that empirical time series of earthquakes exhibit long-range correlations in space and time and the Gutenberg-Richter distribution of magnitudes, we propose a simple fault model that can account for these types of scale-invariance. It is an avalanching process that displays power-laws in the event sizes, in the epicenter distances as well as in the waiting-time distributions, and also aftershock rates obeying a generalized Omori law. We thus confirm that there is a relation between temporal and spatial clustering of the activity in this kind of models. The fluctuating boundaries of possible slipping areas show that the size of the largest possible earthquake is not always maximal, and the average correlation length is a fraction of the system size. This suggests that there is a concrete alternative to the extreme interpretation of self-organized criticality as a process in which every small event can cascade to an arbitrary large one: the new picture includes fluctuating domains of coherent stress field as part of the global self-organization. Moreover, this picture can be more easily compared with other scenarios discussing fluctuating correlations lengths in seismicity.