Wavelet Analysis of Solar Activity

Using wavelet analysis approach, the temporal variations of solar activity on time scales ranging from days to decades, are examined from the daily time series of sunspot numbers. A hierarchy of changing complex periods are careful detected and related cycles compared with results from recent similar analyses. A general determination of the main Schwabe cycle length variations is also suggested on the basis of the wavelet amplitude distribution extracted from the local wavelet power map.Comment: Postscript v1.1, 11 pages with 3 color figure

Solar cycle activity: an early prediction for cycle #25

Solar activity forecasting is an important topic for numerous scientific and technological areas, such as space mission operations, electric power transmission lines, power transformation stations and earth geophysical and climatic impact. Nevertheless, the well-known difficulty is how to accurately predict, on the basis of various recorded solar activity indices, the complete evolution of future solar cycles, due to highly complex dynamical and stochastic processes involved, mainly related to interaction of different components of internal magnetic fields. There are two main distinct classes of solar cycle prediction methods: the precursor-like ones and the mathematical-numerical ones. The main characteristic of precursor techniques, both purely solar and geomagnetic, is their physical basis. Conversely, the non-precursor methods use different mathematical and/or numerical properties of the known temporal evolution of solar activity indices to extract useful information for predicting future activity. For current solar cycle #24 we obtained fairly good statistical performances from both precursor and purely numerical methods, such as the so-called solar precursor and nonlinear ones. To further check the performances of these prediction techniques, we compared the early predictions for the next solar cycle #25. Preliminary results support some coherence of the prediction methods considered and confirm the current trend of a relatively low solar activity.Comment: 6 pages, 1 figur

Solar cycle full-shape predictions: a global error evaluation for cycle 24

There are many proposed prediction methods for solar cycles behavior. In a previous paper we updated the full-shape curve prediction of the current solar cycle 24 using a non-linear dynamics method and we compared the results with the predictions collected by the NOAA/SEC prediction panel, using observed data up to October 2010. The aim of the present paper is to give a quantitative evaluation, a posteriori, of the performances of these prediction methods using a specific global error, updated on a monthly basis, which is a measure of the global performance on the predicted shape (both amplitude and phase) of the solar cycle. We suggest also the use of a percent cycle similarity degree, to better evaluate the predicted shape of the solar cycle curve.Comment: 12 pages, 4 figure

On the better constraints from the South Pole Telescope Sunyaev-Zel'dovich galaxy clusters survey: a FoM evaluation for the equation of state of Dark Energy

In a recent article by Benson et al., 2011, the authors show the latest measurements from the South Pole Telescope (SPT) Sunyaev Zel'dovich (SZ) cluster survey to better constrain some cosmological parameters. In particular, the authors found that adding the SPT cluster data significantly improves the constraints on equation of state of dark energy, w, beyond those found when using measurements of the CMB, supernovae, BAO and the Hubble constant. The main aim of the present research note is to give a further quantitative estimation of the above better constraints, through the computation of the Figure of Merit (FoM) applied to \Omega_m and w plots for the 68% and 95% confidence regions. This allows a better evaluation and a better comparison of the continuous improvements on the cosmological constraints, obtained using new different cosmological probes and different surveys.Comment: 9 pages, 3 figure

On the Distinct Periodicities of Sunspot Counts in Flaring and Non-flaring Active Regions

In a recent work, Kilcik et al. (2017), have detected the temporal and periodic behavior of sunspot counts (SSC) in flaring (i.e. C, M, or X class flares), and non-flaring active regions for the last two solar cycles, covering the period: 1996 - 2016. The main results obtained are: 1) The temporal behavior of monthly means of daily total SSC in flaring and non-flaring active regions are different and these differences are also varying from cycle to cycle; 2) The periodicities detected in SSC of flaring and non-flaring active regions are quite different and these variations are also different from one cycle to another; the highest detected period in the flaring active regions is 113 days, while there are much higher periodicities (327, 312, and 256 days) in non-flaring regions. The detection of typical different periodicities in flaring and non-flaring regions can suggests both important differences and physical interpretation in the magneto-hydrodynamic behavior of the Sun. For this reason in the present paper we show a further periodicity analysis of the sunspot counts in flaring and in non-flaring active regions using the same data source of that used by the above cited authors and applying a powerful wavelet analysis tool which is particularly useful to detect multiscale features of complex unsteady and unevenly sampled time series. In order to futher support the differences and similarities found in the time behavior of SSC in flaring and non-flaring regions, we also computed the behavior of the wavelet entropy, a proper time function which allow us to measure the degree of complexity in the dynamics of the related time series.Comment: 11 pages, 3 figure

Wavelet entropy as a measure of solar cycle complexity

Using wavelet analysis approach, we can derive a measure of the disorder content of solar activity, following the temporal evolution of the so-called wavelet entropy. The interesting feature of this parameter is its ability to extract a dynamical complexity information, in terms of frequency distribution of the energy content, avoiding restrictions, common in the nonlinear dynamics theory, such as stationarity. The analysis is performed on the monthly time series of sunspot numbers. From the time behaviour of the wavelet entropy we found a clear increase in the disorder content of solar activity for the current 23th solar cycle. This result suggests general low accuracies for current solar cycleprediction methods. Moreover, we pointed out a possible connection between wavelet entropy behaviour and solar excursion phases of solar dipole.Comment: 4 pages with 3 figures. Accepted for publication in Astronomy and Astrophysics Journa

Wavelet analysis of solar magnetic strength indices

Wavelet analysis of different solar activity indices, sunspot numbers, sunspot areas, flare index, magnetic fields, etc., allows us to investigate the time evolution of some specific features of the solar activity and the underlying dynamo mechanism. The main aim of this work is the analysis of the time-frequency behavior of some magnetic strengtht indices currently taken at the Mt. Wilson Observatory 150-Foot Solar Tower. In particular, we analyzed both the long time series (Jan 19, 1970 - Jan 22, 2013) of the Magnetic Plage Strength Index (MPSI) values and of the Mt. Wilson Sunspot Index (MWSI) values, covering the descending phase of cycle 20, the full solar cycles 21-23 and the current part of the 24 solar cycle. This study is a further contribution to detect the changes in the multiscale quasiperiodic variations in the integrated magnetic solar activity with a comparison between past solar cycles and the current one, which is one of the weaker recorded in the past 100 years. Indeed, it is well known that an unusual and deep solar minimum occurred between solar cycles 23 and 24 and the time-frequency behavior of some magnetic strengtht indices can help to better interpret the responsible mechanisms.Comment: 8 pages, 2 figure

On the Solar Component in the Observed Global Temperature Anomalies

In this paper, starting from the updated time series of global temperature anomalies, Ta, we show how the solar component affects the observed behavior using, as an indicator of solar activity, the Solar Sunspot Number SSN. The results that are found clearly show that the solar component has an important role and affects significantly the current observed stationary behavior of global temperature anomalies. The solar activity behavior and its future role will therefore be decisive in determining whether or not the restart of the increase of temperature anomalies observed since 1975 will occur.Comment: 9 pages, 7 figure

Time Series Forecasting: A Multivariate Stochastic Approach

This note deals with a multivariate stochastic approach to forecast the behaviour of a cyclic time series. Particular attention is devoted to the problem of the prediction of time behaviour of sunspot numbers for the current 23th cycle. The idea is to consider the previous known n cycles as n particular realizations of a given stochastic process. The aim is to predict the future behaviour of the current n+1th realization given a portion of the curve and the structure of the previous n realizations. The model derived is based on the cross-correlations between the current n+1th realization and the previous n ones and the solution of the related least squares problem. As example we applied the method to smoothed monthly sunspots numbers from SIDC archives, in order to predict the behaviour of the current 23th solar cycle.Comment: Postscript v1.1, 6 pages with 3 figure

Time Series Forecasting: A Nonlinear Dynamics Approach

The problem of prediction of a given time series is examined on the basis of recent nonlinear dynamics theories. Particular attention is devoted to forecast the amplitude and phase of one of the most common solar indicator activity, the international monthly smoothed sunspot number. It is well known that the solar cycle is very difficult to predict due to the intrinsic complexity of the related time behaviour and to the lack of a succesful quantitative theoretical model of the Sun magnetic cycle. Starting from a previous recent work, we checked the reliability and accuracy of a forecasting model based on concepts of nonlinear dynamical systems applied to experimental time series, such as embedding phase space, Lyapunov spectrum, chaotic behaviour. The model is based on a local hypothesis of the behaviour on the embedding space, utilizing an optimal number k of neighbour vectors to predict the future evolution of the current point with the set of characteristic parameters determined by several previous parametric computations. The performances of this method suggest its valuable insertion in the set of the so-called statistical-numerical prediction techniques, like Fourier analyses, curve fitting, neural networks, climatological, etc. The main task is to set up and to compare a promising numerical nonlinear prediction technique, essentially based on an inverse problem, with the most accurate predictive methods like the so-called "precursor methods" which appear now reasonably accurate in predicting "long term" Sun activity, with particular reference to the "solar" precursor methods based on a solar dynamo theory.Comment: Postscript v1.2, 22 pages with 12 color figure