177 research outputs found

    A Short-term ESPERTA-based Forecast Tool for Moderate-to-extreme Solar Proton Events

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    The ESPERTA (Empirical model for Solar Proton Event Real Time Alert) forecast tool has a Probability of Detection (POD) of 63% for all >10 MeV events with proton peak intensity ≥10 pfu (i.e., ≥S1 events, S1 referring to minor storms on the NOAA Solar Radiation Storms scale), from 1995 to 2014 with a false alarm rate (FAR) of 38% and a median (minimum) warning time (WT) of ∼4.8 (0.4) hr. The NOAA space weather scale includes four additional categories: moderate (S2), strong (S3), severe (S4), and extreme (S5). As S1 events have only minor impacts on HF radio propagation in the polar regions, the effective threshold for significant space radiation effects appears to be the S2 level (100 pfu), above which both biological and space operation impacts are observed along with increased effects on HF propagation in the polar regions. We modified the ESPERTA model to predict ≥S2 events and obtained a POD of 75% (41/55) and an FAR of 24% (13/54) for the 1995-2014 interval with a median (minimum) WT of ∼1.7 (0.2) hr based on predictions made at the time of the S1 threshold crossing. The improved performance of ESPERTA for ≥S2 events is a reflection of the big flare syndrome, which postulates that the measures of the various manifestations of eruptive solar flares increase as one considers increasingly larger events

    Multiscale fractal dimension analysis of a reduced order model of coupled ocean–atmosphere dynamics

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    Atmosphere and ocean dynamics display many complex features and are characterized by a wide variety of processes and couplings across different timescales. Here we demonstrate the application of multivariate empirical mode decomposition (MEMD) to investigate the multivariate and multiscale properties of a reduced order model of the ocean–atmosphere coupled dynamics. MEMD provides a decomposition of the original multivariate time series into a series of oscillating patterns with time-dependent amplitude and phase by exploiting the local features of the data and without any a priori assumptions on the decomposition basis. Moreover, each oscillating pattern, usually named multivariate intrinsic mode function (MIMF), represents a local source of information that can be used to explore the behavior of fractal features at different scales by defining a sort of multiscale and multivariate generalized fractal dimensions. With these two complementary approaches, we show that the ocean–atmosphere dynamics presents a rich variety of features, with different multifractal properties for the ocean and the atmosphere at different timescales. For weak ocean–atmosphere coupling, the resulting dimensions of the two model components are very different, while for strong coupling for which coupled modes develop, the scaling properties are more similar especially at longer timescales. The latter result reflects the presence of a coherent coupled dynamics. Finally, we also compare our model results with those obtained from reanalysis data demonstrating that the latter exhibit a similar qualitative behavior in terms of multiscale dimensions and the existence of a scale dependency of the statistics of the phase-space density of points for different regions, which is related to the different drivers and processes occurring at different timescales in the coupled atmosphere–ocean system. Our approach can therefore be used to diagnose the strength of coupling in real applications

    Arbitrary-order Hilbert spectral analysis and intermittency in solar wind density fluctuations

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    The properties of inertial and kinetic range solar wind turbulence have been investigated with the arbitrary-order Hilbert spectral analysis method, applied to high-resolution density measurements. Due to the small sample size, and to the presence of strong non-stationary behavior and large-scale structures, the classical structure function analysis fails to detect power law behavior in the inertial range, and may underestimate the scaling exponents. However, the Hilbert spectral method provides an optimal estimation of the scaling exponents, which have been found to be close to those for velocity fluctuations in fully developed hydrodynamic turbulence. At smaller scales, below the proton gyroscale, the system loses its intermittent multiscaling properties, and converges to a monofractal process. The resulting scaling exponents, obtained at small scales, are in good agreement with those of classical fractional Brownian motion, indicating a long-term memory in the process, and the absence of correlations around the spectral break scale. These results provide important constraints on models of kinetic range turbulence in the solar wind

    Reconciling Parker Solar Probe observations and magnetohydrodynamic theory

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    The Parker Solar Probe mission provides a unique opportunity to characterize several features of the solar wind at different heliocentric distances. Recent findings have shown a transition in the inertial range spectral and scaling properties around 0.4-0.5 au when moving away from the Sun. Here we provide, for the first time, how to reconcile these observational results on the radial evolution of the magnetic and velocity field fluctuations with two scenarios drawn from the magnetohydrodynamic theory. The observed breakdown is the result of the radial evolution of magnetic field fluctuations and plasma thermal expansion affecting the distribution between magnetic and velocity fluctuations. The two scenarios point towards an evolving nature of the coupling between fields that can be also reconciled with Kraichnan and Kolmogorov pictures of turbulence. Our findings have important implications for turbulence studies and modeling approaches.Comment: 9 pages, 4 figure

    Dimensional analysis identifies contrasting dynamics of past climate states and critical transitions

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    While one can unequivocally identify past climate transitions, we lack comprehensive knowledge about their underlying mechanisms and timescales. Our study employs a dimensional analysis of benthic stable isotope records to uncover, across different timescales, how the climatic fluctuation of the Cenozoic are associated with changes in the number of effective degrees of freedom. Precession timescales dominate the Hothouse and Warmhouse states, while the Icehouse climate is primarily influenced by obliquity and eccentricity timescales. Notably, the Coolhouse state lacks dominant timescales. Our analysis proves effective in objectively identifying abrupt climate shifts and extremes. This is also demonstrated using high-resolution data from the last glacial cycle, revealing abrupt climate shifts within a single climate state. These findings significantly impact our understanding of the inherent stability of each climate state and the evaluation of (paleo-)climate models' ability to replicate key features of past/future climate states and transitions

    Comprehensive Sun-to-Earth analysis of the Geoeffective Solar event of June 21, 2015: Effects on the Magnetosphere - Plasmasphere - Ionosphere system

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    A full-halo coronal mass ejection left the sun on June 21, 2015 from the active region NOAA 12371 encountering Earth on June 22, 2015, generating a G3 strong geomagnetic storm. The CME was associated with an M2 class flare observed at 01:42 UT, located near the center disk (N12E16). Using satellite data from solar, heliospheric, magnetospheric missions and ground-based instruments, we performed a comprehensive Sun-to-Earth analysis. In particular, we analyzed the active region evolution using ground-based and satellite instruments (BBSO, IRIS, HINODE, SDO/AIA, RHESSI -- Halpha, EUV, UV, X), the AR magnetograms, using data from SDO HMI, the relative particle data, using PAMELA instruments and the effects of interplanetary perturbation on cosmic ray intensity. We also evaluated the 1-8 A˚\AA soft X-ray and low-frequenct (∼\sim 1 MHz) Type III radio burst time-integrated intensity (or fluence) of the flare in order to make a prediction of the associated Solar Energetic Particle (SEP) event by using the model developed by \cite{Laurenza09}. Inaddition, using ground based observations from lower to higher latitudes (INTERMAGNET - EMMA, etc.), we reconstructed the ionospheric current system associated to the geomagnetic Sudden Commencement. Furthermore, SuperDARN measurements are used to image the global ionospheric polar convection during the SSC and during the principal phases of the geomagnetic storm. Moreover, we investigated the dynamics of the plasmasphere during the different phases of the geomagnetic storm by examining the time evolution of the radial profiles of the equatorial plasma mass density derived from field line resonances detected at the EMMA network (1.5 << L << 6.5). Finally, we presented the general features of the geomagnetic response to the CME, by applying innovative data analysis tools that allow to investigate the time variation of ground-based observations of the Earth's magnetic field during the associated geomagnetic storm

    Disentangling nonlinear geomagnetic variability during magnetic storms and quiescence by timescale dependent recurrence properties

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    Understanding the complex behavior of the near-Earth electromagnetic environment is one of the main challenges of Space Weather studies. This includes both the correct characterization of the different physical mechanisms responsible for its configuration and dynamics as well as the efforts which are needed for a correct forecasting of several phenomena. By using a nonlinear multi-scale dynamical systems approach, we provide here new insights into the scale-to-scale dynamical behavior of both quiet and disturbed periods of geomagnetic activity. The results show that a scale-dependent dynamical transition occurs when moving from short to long timescales, i.e., from fast to slow dynamical processes, the latter being characterized by a more regular behavior, while more dynamical anomalies are found in the behavior of the fast component. This suggests that different physical processes are typical for both dynamical regimes: the fast component, being characterized by a more chaotic and less predictable behavior, can be related to the internal dynamical state of the near-Earth electromagnetic environment, while the slow component seems to be less chaotic and associated with the directly driven processes related to the interplanetary medium variability. Moreover, a clear difference has been found between quiet and disturbed periods, the former being more complex than the latter. These findings support the view that, for a correct forecasting in the framework of Space Weather studies, more attention needs to be devoted to the identification of proxies describing the internal dynamical state of the near-Earth electromagnetic environment

    Kramers-Moyal analysis of interplanetary magnetic field fluctuations at sub-ion scales

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    In the framework of statistical time series analysis of complex dynamics we present a multiscale characterization of solar wind turbulence in the near-Earth environment. The data analysis, based on the Markov-process theory, is meant to estimate the Kramers-Moyal coefficients associated with the measured magnetic field fluctuations. In fact, when the scale-to-scale dynamics can be successfully described as a Markov process, first- and second-order Kramers-Moyal coefficients provide a complete description of the dynamics in terms of Langevin stochastic process. The analysis is carried out by using high-resolution magnetic field measurements gathered by Cluster during a fast solar wind period on January 20, 2007. This analysis extends recent findings in the near-Sun environment with the aim of testing the universality of the Markovian nature of the magnetic field fluctuations in the sub-ion/kinetic domain

    The poor man’s magnetohydrodynamic (PMMHD) equations

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    We present a mathematical derivation of a discrete dynamical system by following a Fourier-Galerkin approximation of the 3-D incompressible magnetohydrodynamic (MHD) equations. In this way, a 6-D map, depending on 12 bifurcation parameters, is derived as a truncated set of nonlinear ordinary differential equations (ODEs) to characterize incompressible plasma dynamical behaviors, also conserving total energy and cross-helicity in the ideal MHD approximation. Moreover, three different subspaces, associated with long-living non-trivial solutions (e.g., fixed point solutions), have been found like the fluid, magnetic, and the Alfvenic fixed points. Our set can be seen as a Lorenz-like model to investigate MHD phenomena

    A Short-term ESPERTA-based Forecast Tool for Moderate-to-extreme Solar Proton Events

    Get PDF
    The ESPERTA (Empirical model for Solar Proton Event Real Time Alert) forecast tool has a Probability of Detection (POD) of 63% for all >10 MeV events with proton peak intensity ≥10 pfu (i.e., ≥S1 events, S1 referring to minor storms on the NOAA Solar Radiation Storms scale), from 1995 to 2014 with a false alarm rate (FAR) of 38% and a median (minimum) warning time (WT) of ∼4.8 (0.4) hr. The NOAA space weather scale includes four additional categories: moderate (S2), strong (S3), severe (S4), and extreme (S5). As S1 events have only minor impacts on HF radio propagation in the polar regions, the effective threshold for significant space radiation effects appears to be the S2 level (100 pfu), above which both biological and space operation impacts are observed along with increased effects on HF propagation in the polar regions. We modified the ESPERTA model to predict ≥S2 events and obtained a POD of 75% (41/55) and an FAR of 24% (13/54) for the 1995-2014 interval with a median (minimum) WT of ∼1.7 (0.2) hr based on predictions made at the time of the S1 threshold crossing. The improved performance of ESPERTA for ≥S2 events is a reflection of the big flare syndrome, which postulates that the measures of the various manifestations of eruptive solar flares increase as one considers increasingly larger events
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