Neural network prediction of geomagnetic activity: a method using local H\"{o}lder exponents

Local scaling and singularity properties of solar wind and geomagnetic time series were analysed using H\"{o}lder exponents $\alpha$. It was shown that in analysed cases due to multifractality of fluctuations $\alpha$ changes from point to point. We argued there exists a peculiar interplay between regularity / irregularity and amplitude characteristics of fluctuations which could be exploited for improvement of predictions of geomagnetic activity. To this end layered backpropagation artificial neural network model with feedback connection was used for the study of the solar wind - magnetosphere coupling and prediction of geomagnetic $D_{st}$ index. The solar wind input was taken from principal component analysis of interplanetary magnetic field, proton density and bulk velocity. Superior network performance was achieved in cases when the information on local H\"{o}lder exponents was added to the input layer.Comment: 17 pages, 7 figure

Scaling and singularity characteristics of solar wind and magnetospheric fluctuations

Preliminary results are presented which suggest that scaling and singularity characteristics of solar wind and ground based magnetic fluctuations appear to be a significant component in the solar wind - magnetosphere interaction processes. Of key importance is the intermittence of the "magnetic turbulence" as seen in ground based and solar wind magnetic data. The methods used in this paper (estimation of flatness and multifractal spectra) are commonly used in the studies of fluid or MHD turbulence. The results show that single observatory characteristics of magnetic fluctuations are different from those of the multi-observatory AE-index. In both data sets, however, the influence of the solar wind fluctuations is recognizable. The correlation between the scaling/singularity features of solar wind magnetic fluctuations and the corresponding geomagnetic response is demonstrated in a number of cases. The results are also discussed in terms of patchy reconnection processes in magnetopause and forced or/and self-organized criticality (F/SOC) of internal magnetosphere dynamics.Comment: 28 pages, 12 figure

Neural network prediction of geomagnetic activity: a method using local Hölder exponents

Local scaling and singularity properties of solar wind and geomagnetic time series were analysed using Hölder exponents . It was shown that in analysed cases due to the multifractality of fluctuations, α changes from point to point. We argued there exists a peculiar interplay between regularity/irregularity and amplitude characteristics of fluctuations which could be exploited for the improvement of predictions of geomagnetic activity. To this end, a layered back-propagation artificial neural network model with feedback connection was used for the study of the solar wind magnetosphere coupling and prediction of the geomagnetic D_st index. The solar wind input was taken from the principal component analysis of the interplanetary magnetic field, proton density and bulk velocity. Superior network performance was achieved in cases when the information on local Hölder exponents was added to the input layer

The influence of solar wind turbulence on geomagnetic activity

International audienceThe 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

Scaling and singularity characteristics of solar wind and magnetospheric fluctuations

International audiencePreliminary results are presented which suggest that scaling and singularity characteristics of solar wind and ground-based magnetic fluctuations appear to be a significant component in the solar wind-magnetosphere interaction processes. Of key importance is the intermittence of the "magnetic turbulence" as seen in ground-based and solar wind magnetic data. The methods used in this paper (estimation of flatness and multifractal spectra) are commonly used in the studies of fluid or MHD turbulence. The results show that single observatory characteristics of magnetic fluctuations are different from those of the multi-observatory AE-index. In both data sets, however, the influence of the solar wind fluctuations is recognizable. The correlation between the scaling/singularity features of solar wind magnetic fluctuations and the corresponding geomagnetic response is demonstrated in a number of cases. The results are also discussed in terms of patchy reconnection processes in the magnetopause and forced and/or self-organized criticality (F/SOC) of internal magnetosphere dynamics

Formation of regular structures in the process of phase separation

Phase separation under directional quenching has been studied in a Cahn-Hilliard model. In distinct contrast to the disordered patterns which develop under a homogeneous quench periodic stripe patterns are generated behind the quench front. Their wavelength is uniquely defined by the velocity of the quench interface in a wide range. Numerical simulations match perfectly analytical results obtained in the limit of small and large velocities of the quench interface. Additional periodic modulation of the quench interface may lead to cellular patterns. The quenching protocols analyzed in this paper are expected to be an effective tool in technological applications to design nanostructured materials

Study of reconnection-associated multi-scale fluctuations with Cluster and Double Star

The objective of the paper is to asses the specific spectral scaling properties of magnetic reconnection associated fluctuations/turbulence at the Earthward and tailward outflow regions observed simultaneously by the Cluster and Double Star (TC-2) spacecraft on September 26, 2005. Systematic comparisons of spectral characteristics, including variance anisotropy and scale-dependent spectral anisotropy features in wave vector space were possible due to the well-documented reconnection events, occurring between the positions of Cluster (X = -14--16 $R_e$) and TC-2 (X = -6.6 $R_e$). Another factor of key importance is that the magnetometers on the spacecraft are similar. The comparisons provide further evidence for asymmetry of physical processes in Earthward/tailward reconnection outflow regions. Variance anisotropy and spectral anisotropy angles estimated from the multi-scale magnetic fluctuations in the tailward outflow region show features which are characteristic for magnetohydrodynamic cascading turbulence in the presence of a local mean magnetic field. The multi-scale magnetic fluctuations in the Earthward outflow region are exhibiting more power, lack of variance and scale dependent anisotropies, but also having larger anisotropy angles. In this region the magnetic field is more dipolar, the main processes driving turbulence are flow breaking/mixing, perhaps combined with turbulence ageing and non-cascade related multi-scale energy sources.Comment: 30 pages, 6 figure