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The description of the relationship between interplanetary plasma and geomagnetic activity requires complex models. Drastically reducing the ambition of describing this detailed complex interaction and, if we are interested only in the fractality properties of the time series of its characteristic parameters, a magnetohydrodynamic (MHD) shell model forced using solar wind data might provide a possible novel approach. In this paper we study the relation between the activity of the magnetic energy dissipation rate obtained in one such model, which may describe geomagnetic activity, and the fractal dimension of the forcing. In different shell model simulations, the forcing is provided by the solution of a Langevin equation where a white noise is implemented. This forcing, however, has been shown to be unsuitable for describing the solar wind action on the model. Thus, we propose to consider the fluctuations of the product between the velocity and the magnetic field solar wind data as the noise in the Langevin equation, the solution of which provides the forcing in the magnetic field equation. We compare the fractal dimension of the magnetic energy dissipation rate obtained, of the magnetic forcing term, and of the fluctuations of v⋅bz , with the activity of the magnetic energy dissipation rate. We examine the dependence of these fractal dimensions on the solar cycle. We show that all measures of activity have a peak near solar maximum. Moreover, both the fractal dimension computed for the fluctuations of v⋅bz time series and the fractal dimension of the magnetic forcing have a minimum near solar maximum. This suggests that the complexity of the noise term in the Langevin equation may have a strong effect on the activity of the magnetic energy dissipation rate. [ABSTRACT FROM AUTHOR]

The description of the relationship between interplanetary plasma and geomagnetic activity requires complex models. Drastically reducing the ambition of describing this detailed complex interaction, and if we are interested only in the fractality properties of the time-series of its characteristic parameters, a magnetohydrodynamic (MHD) shell model forced using solar wind data, might provide a possible novel approach. In this paper we study the relation between the activity of the magnetic energy dissipation rate obtained in one such model, which may describe geomagnetic activity, and the fractal dimension of the forcing. In different shell model simulations, the forcing is provided by the solution of a Langevin equation where a white noise is implemented. Since this forcing has shown its unsuitableness in describing the driver due to solar wind action, we propose to consider the fluctuations of the product between the velocity and the magnetic field solar wind data as the noise in Langevin equation, whose solution provides the forcing in the magnetic field equation. We compare the fractal dimension of the magnetic energy dissipation rate obtained, of the magnetic forcing term, and of the fluctuations ofv · bz, with the activity of the magnetic energy dissipation rate. We examine the dependence of these fractal dimensions on the solar cycle. We show that all measures of activity have a peak near solar maximum. Moreover, both the fractal dimension computed for the fluctuations ofv · bz time series and the fractal dimension of the magnetic forcing have a minimum near solar maximum. This suggests that the complexity of the noise term in the Langevin equation may have a strong effect in the activity of the magnetic energy dissipation rate. [ABSTRACT FROM AUTHOR]

An MHD shell model is used to describe the dissipative events that take place in magnetized plasmas. We analyze the activity of the time series of the magnetic energy dissipation rate obtained in the MHD shell model, which evolves under two forcing regimes: quiet and active states. To this purpose, we use solar wind data as the forcing terms of the shell model, covering solar maximum and solar minimum periods. Then, we calculate the fractal dimension of the solar wind data for the thirteen years of the 23rd solar cycle and we compare this with the energy dissipation time series obtained from the shell model description. We discuss the correlation between the fractal dimension of the solar wind data and the corresponding energy dissipation rate. [ABSTRACT FROM AUTHOR]

This article addresses the interesting and important problem of large-scale magnetic field generation in turbulent flows, using a self-consistent dynamo model recently developed. The main idea of this model is to consider the induction equation for the large-scale magnetic field, integrated consistently with the turbulent dynamics at smaller scales described by a magnetohydrodynamic shell model. The questions of dynamo action threshold, magnetic field saturation, magnetic field reversals, nature of the dynamo transition and the changes of small-scale turbulence as a consequence of the dynamo onset are discussed. In particular, the stability curve obtained by the model integration is shown in a very wide range of values of the magnetic Prandtl number not yet accessible by direct numerical simulation but more realistic for natural dynamos. Moreover, from our analysis it is shown that the large-scale dynamo transition displays a hysteretic behaviour and therefore a subcritical nature. The model successfully reproduces magnetic polarity reversals, showing the capability to generate persistence times which are increasing for decreasing magnetic diffusivity. Moreover, when the system reaches a statistically stationary dynamo state, where the large-scale magnetic field can abruptly reverse its polarity (magnetic reversal state) or not, keeping the same polarity (steady state), it shows an unmistakable tendency towards the energy equipartition for the turbulence at small scale. [ABSTRACT FROM PUBLISHER]

The dynamics of fluctuations in a closed coronal structure is regulated both by resonance with motions at bases that stores energy in the structure in form of discrete eigenmodes, and by nonlinear couplings that move this energy along the spectrum to smaller scales. The energy balance is evaluated both analytically and, numerically, using an hybrid shell model. The input energy flux is independent of nonlinear effects and is determined by slow (DC) perturbations. Coherent eigenmode couplings determine the nonlinear energy flux and, consequently, the level of fluctuations at large scales. The estimated velocity fluctuation level is in agreement with measures of nonthermal velocity in corona. The resulting turbulence spectrum contains both a pre-inertial range where coherent interactions dominate, and a standard inertial range where the turbulence behaves as in an unbounded system. [ABSTRACT FROM PUBLISHER]

In the polar ionosphere, the electric field is characterized by broadband and power law spectral densities at small/short spatio-temporal scales, which support a possible turbulent nature of the electric field fluctuations. Here, we investigate the multifractal character of the full three-dimensional electric field in the polar ionosphere as recorded on board the first Chinese Seismo-Electromagnetic Satellite (CSES-01). The results of our analysis prove a clear different degree of multifractality of the electric field fluctuations approaching either the polar cap trailing edge or the auroral region. The observed differences in the multifractal character are interpreted in terms of the different natures of the particle precipitation in the polar cap and in the auroral region. A possible link between the multifractal nature of electric field fluctuations, parallel to the geomagnetic field, and filamentation of field aligned currents (FACs) is established. [ABSTRACT FROM AUTHOR]

We analyse the earthquakes catalogues for Italy, South California, and Greece across the COVID-19 lockdown period for each country. The results for Italy and Greece show that, even if the reduction of the signal to noise ratio has improved the earthquake detection capability, the completeness magnitude remains substantially unchanged, making the improved detection capability ineffective from the statistical point of view. A slight reduction (0.2) of the completeness magnitude is observed for South California, likely related to the relatively higher number of seismic stations located close to urban areas. Our findings suggest that—given the present configuration of the seismic network considered here—only an important decrease in the station spacing can produce a significant decrease of the completeness magnitude. [ABSTRACT FROM AUTHOR]

Photospheric motions are believed to be the source of coronal heating and of velocity fluctuations detected in the solar corona. A numerical model, based on the shell technique applied on reduced magnetohydrodynamics equations, is used to represent energy injection due to footpoint motions, storage and dissipation of energy in a coronal loop. Motions at the loop bases are simulated by random signals whose frequency-wavenumber spectrum reproduces features of photospheric motions: the p-mode peak and the low-frequency continuum. Results indicate that a turbulent state develops, dominated by magnetic energy, where dissipation takes place in an intermittent fashion. The nonlinear cascade is mainly controlled by velocity fluctuations, where resonant modes are dominant at high frequencies. Low frequency fluctuations present a power-law spectra and a bump at p-mode frequency; similar features are observed in velocity spectra detected in the corona. For typical loop parameters the energy input flux is comparable with that necessary to heat the quiet-Sun corona. [ABSTRACT FROM AUTHOR]

Synthetic turbulence models are useful tools that provide realistic representations of turbulence, necessary to test theoretical results, to serve as background fields in some numerical simulations, and to test analysis tools. Models of one-dimensional (1D) and 3D synthetic turbulence previously developed still required large computational resources. A "wavelet-based" model of synthetic turbulence, able to produce a field with tunable spectral law, intermittency, and anisotropy, is presented here. The rapid algorithm introduced, based on the classic p-model of intermittent turbulence, allows us to reach a broad spectral range using a modest computational effort. The model has been tested against the standard diagnostics for intermittent turbulence, i.e., the spectral analysis, the scale-dependent statistics of the field increments, and the multifractal analysis, all showing an excellent response. [ABSTRACT FROM AUTHOR]