Gnevyshev Peaks and Gaps for Coronal Mass Ejections of Different Widths Originating in Different Solar Position Angles

The sunspot number series at the peak of sunspot activity often has two or three peaks (Gnevyshev peaks; Gnevyshev, Solar Phys. 1, 107, 1967; Solar Phys. 51, 175, 1977). The sunspot group number (SGN) data were examined for 1997 – 2003 (part of cycle 23) and compared with data for coronal mass ejection (CME) events. It was noticed that they exhibited mostly two Gnevyshev peaks in each of the four latitude belts 0° – 10°, 10° – 20°, 20 ° – 30°, and > 30°, in both N (northern) and S (southern) solar hemispheres. The SGN were confined to within latitudes ± 50° around the Equator, mostly around ± 35°, and seemed to occur later in lower latitudes, indicating possible latitudinal migration as in the Maunder butterfly diagrams. In CMEs, less energetic CMEs (of widths < 71°) showed prominent Gnevyshev peaks during sunspot maximum years in almost all latitude belts, including near the poles. The CME activity lasted longer than the SGN activity. However, the CME peaks did not match the SGN peaks and were almost simultaneous at different latitudes, indicating no latitudinal migration. In energetic CMEs including halo CMEs, the Gnevyshev peaks were obscure and ill-defined. The solar polar magnetic fields show polarity reversal during sunspot maximum years, first at the North Pole and, a few months later, at the South Pole. However, the CME peaks and gaps did not match with the magnetic field reversal times, preceding them by several months, rendering any cause – effect relationship doubtful.     

Do Long-Lived Features Really Exist in the Solar Photosphere? II. Contrast of Time-Averaged Granulation Images

The decrease in the rms contrast of time-averaged images with the averaging time is compared between four data sets: (1) a series of solar granulation images recorded at La Palma in 1993, (2) a series of artificial granulation images obtained in numerical simulations by Rieutord et al. (Nuovo Cimento 25, 523, 2002), (3) a similar series computed by Steffen and his colleagues (see Wedemeyer et al. in Astron. Astrophys. 44, 1121, 2004), (4) a random field with some parameters typical of the granulation, constructed by Rast (Astron. Astrophys. 392, L13, 2002). In addition, (5) a sequence of images was obtained from real granulation images by using a temporal and spatial shuffling procedure, and the contrast of the average of n images from this sequence as a function of n is analysed. The series (1) of real granulation images exhibits a considerably slower contrast decrease than do both the series (3) of simulated granulation images and the series (4) of random fields. Starting from some relatively short averaging times t, the behaviour of the contrast in series (3) and (4) resembles the t ^−1/2 statistical law, whereas the shuffled series (5) obeys the n ^−1/2 law from n=2 on. Series (2) demonstrates a peculiarly slow decline of contrast, which could be attributed to particular properties of the boundary conditions used in the simulations. Comparisons between the analysed contrast-variation laws indicate quite definitely that the brightness field of solar granulation contains a long-lived component, which could be associated with locally persistent dark intergranular holes and/or with the presence of quasi-regular structures. The suggestion that the random field (4) successfully reproduces the contrast-variation law for the real granulation (Rast in Astron. Astrophys. 392, L13, 2002) can be dismissed.     

Long-Term Sunspot Number Prediction based on EMD Analysis and AR Model

The Empirical Mode Decomposition (EMD) and Auto-Regressive model (AR) are applied to a long-term prediction of sunspot numbers. With the sample data of sunspot numbers from 1848 to 1992, the method is evaluated by examining the measured data of the solar cycle 23 with the prediction: different time scale components are obtained by the EMD method and multi-step predicted values are combined to reconstruct the sunspot number time series. The result is remarkably good in comparison to the predictions made by the solar dynamo and precursor approaches for cycle 23. Sunspot numbers of the coming solar cycle 24 are obtained with the data from 1848 to 2007, the maximum amplitude of the next solar cycle is predicted to be about 112 in 2011-2012.     

Prediction of Space Weather Using an Asymmetric Cone Model for Halo CMEs

Halo coronal mass ejections (HCMEs) are responsible of the most severe geomagnetic storms. A prediction of their geoeffectiveness and travel time to Earth’s vicinity is crucial to forecast space weather. Unfortunately, coronagraphic observations are subjected to projection effects and do not provide true characteristics of CMEs. Recently, Michalek (Solar Phys. 237, 101, 2006) developed an asymmetric cone model to obtain the space speed, width, and source location of HCMEs. We applied this technique to obtain the parameters of all front-sided HCMEs observed by the SOHO/LASCO experiment during a period from the beginning of 2001 until the end of 2002 (solar cycle 23). These parameters were applied for space weather forecasting. Our study finds that the space speeds are strongly correlated with the travel times of HCMEs to Earth’s vicinity and with the magnitudes related to geomagnetic disturbances.     

A New Look at Mode Conversion in a Stratified Isothermal Atmosphere

Recent numerical investigations of wave propagation near coronal magnetic null points (McLaughlin and Hood: Astron. Astrophys. 459, 641, 2006) have indicated how a fast MHD wave partially converts into a slow MHD wave as the disturbance passes from a low-β plasma to a high-β plasma. This is a complex process and a clear understanding of the conversion mechanism requires the detailed investigation of a simpler model. An investigation of mode conversion in a stratified, isothermal atmosphere with a uniform, vertical magnetic field is carried out, both numerically and analytically. In contrast to previous investigations of upward-propagating waves (Zhugzhda and Dzhalilov: Astron. Astrophys. 112, 16, 1982a; Cally: Astrophys. J. 548, 473, 2001), this paper studies the downward propagation of waves from a low-β to high-β environment. A simple expression for the amplitude of the transmitted wave is compared with the numerical solution.     

Are solar cycles predictable?

Various methods (or recipes) have been proposed to predict future solar activity levels – with mixed success. Among these, some precursor methods based upon quantities determined around or a few years before solar minimum have provided rather high correlations with the strength of the following cycles. Recently, data assimilation with an advection-dominated (flux-transport) dynamo model has been proposed as a predictive tool, yielding remarkably high correlation coefficients. After discussing the potential implications of these results and the criticism that has been raised, we study the possible physical origin(s) of the predictive skill provided by precursor and other methods. It is found that the combination of the overlap of solar cycles and their amplitude-dependent rise time (Waldmeier's rule) introduces correlations in the sunspot number (or area) record, which account for the predictive skill of many precursor methods. This explanation requires no direct physical relation between the precursor quantity and the dynamo mechanism (in the sense of the Babcock-Leighton scheme or otherwise). (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Verification of a Similar Cycle Prediction for the Ascending and Peak Phases of Solar Cycle 23

Reviews of long-term predictions of solar cycles have shown that a precise prediction with a lead time of 2 years or more of a solar cycle remains an unsolved problem. We used a simple method, the method of similar cycles, to make long-term predictions of not only the maximum amplitude but also the smoothed monthly mean sunspot number for every month of Solar Cycle 23. We verify and compare our prediction with the latest available observational results.     

Modeling a Maunder minimum

We introduce on/off intermittency into a mean field dynamo model by imposing stochastic fluctuations in either the alpha effect or through the inclusion of a fluctuating electromotive force. Sufficiently strong small scale fluctuations with time scales of the order of 0.3–3 years can produce long term variations in the system on time scales of the order of hundreds of years. However, global suppression of magnetic activity in both hemispheres at once was not observed. The variation of the magnetic field does not resemble that of the sunspot number, but is more reminiscent of the ¹⁰Be record. The interpretation of our results focuses attention on the connection between the level of magnetic activity and the sunspot number, an issue that must be elucidated if long term solar effects are to be well understood. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Solar Cycle Predictions based on Solar Activity at Different Solar Latitudes

Many methods of predictions of sunspot maximum number use data before or at the preceding sunspot minimum to correlate with the following sunspot maximum of the same cycle, which occurs a few years later. Kane and Trivedi (Solar Phys. 68, 135, 1980) found that correlations of R _z(max) (the maximum in the 12-month running means of sunspot number R _z) with R _z(min) (the minimum in the 12-month running means of sunspot number R _z) in the solar latitude belt 20° – 40°, particularly in the southern hemisphere, exceeded 0.6 and was still higher (0.86) for the narrower belt > 30° S. Recently, Javaraiah (Mon. Not. Roy. Astron. Soc. 377, L34, 2007) studied the relationship of sunspot areas at different solar latitudes and reported correlations 0.95 – 0.97 between minima and maxima of sunspot areas at low latitudes and sunspot maxima of the next cycle, and predictions could be made with an antecedence of more than 11 years. For the present study, we selected another parameter, namely, SGN, the sunspot group number (irrespective of their areas) and found that SGN(min) during a sunspot minimum year at latitudes > 30° S had a correlation +0.78±0.11 with the sunspot number R _z(max) of the same cycle. Also, the SGN during a sunspot minimum year in the latitude belt (10° – 30° N) had a correlation +0.87±0.07 with the sunspot number R _z(max) of the next cycle. We obtain an appropriate regression equation, from which our prediction for the coming cycle 24 is R _z(max )=129.7±16.3.     

Constructing Semi-Empirical Sunspot Models for Helioseismology

One goal of helioseismology is to determine the subsurface structure of sunspots. In order to do so, it is important to understand first the near-surface effects of sunspots on solar waves, which are dominant. Here we construct simplified, cylindrically-symmetric sunspot models that are designed to capture the magnetic and thermodynamics effects coming from about 500 km below the quiet-Sun τ ₅₀₀₀=1 level to the lower chromosphere. We use a combination of existing semi-empirical models of sunspot thermodynamic structure (density, temperature, pressure): the umbral model of Maltby et al. (1986, Astrophys. J. 306, 284) and the penumbral model of Ding and Fang (1989, Astron. Astrophys. 225, 204). The OPAL equation-of-state tables are used to derive the sound-speed profile. We smoothly merge the near-surface properties to the quiet-Sun values about 1 Mm below the surface. The umbral and penumbral radii are free parameters. The magnetic field is added to the thermodynamic structure, without requiring magnetostatic equilibrium. The vertical component of the magnetic field is assumed to have a Gaussian horizontal profile, with a maximum surface field strength fixed by surface observations. The full magnetic-field vector is solenoidal and determined by the on-axis vertical field, which, at the surface, is chosen such that the field inclination is 45° at the umbral – penumbral boundary. We construct a particular sunspot model based on SOHO/MDI observations of the sunspot in active region NOAA 9787. The helioseismic signature of the model sunspot is studied using numerical simulations of the propagation of f, p ₁, and p ₂ wave packets. These simulations are compared against cross-covariances of the observed wave field. We find that the sunspot model gives a helioseismic signature that is similar to the observations.     

Transient Coronal Sigmoids and Rotating Erupting Flux Ropes

To determine the relationship between transient coronal (soft X-ray or EUV) sigmoids and erupting flux ropes, we analyse four events in which a transient sigmoid could be associated with a filament whose apex rotates upon eruption and two further events in which the two phenomena were spatially but not temporally coincident. We find the helicity sign of the erupting field and the direction of filament rotation to be consistent with the conversion of twist into writhe under the ideal MHD constraint of helicity conservation, thus supporting our assumption of flux rope topology for the rising filament. For positive (negative) helicity the filament apex rotates clockwise (counterclockwise), consistent with the flux rope taking on a reverse (forward) S shape, which is opposite to that observed for the sigmoid. This result is incompatible with two models for sigmoid formation: one identifying sigmoids with upward arching kink-unstable flux ropes and one identifying sigmoids with a current layer between two oppositely sheared arcades. We find instead that the observations agree well with the model by Titov and Démoulin (Astron. Astrophys. 351, 707, 1999), which identifies transient sigmoids with steepened current layers below rising flux ropes.     

On Short-Term Periodicity of the Solar Radius Measurements

The aim of the present study is to investigate the short-term periodicity in the solar radius measurements and to compare with the short periods in sunspot numbers, sunspot areas and flare index data. The spectral analysis of data sets covering a time interval from 26 February 2000 to 26 October 2007 during Solar Cycle 23 were made by using the Date Compensated Discrete Fourier Transform (DCDFT). The power spectrum of solar radius data corrected for the seeing effect gives an evident peak at 25.7 days with the amplitude of 0.034 arcsec, which is slightly different from the peaks of 26.2 and 26.7 days produced by sunspot numbers and sunspot areas data, respectively. Besides, the main peak of 25.7 days detected in the power spectrum of solar radius data is in agreement with the period of 25.5 days, suggested to be the fundamental period of the Sun by Bai and Sturrock (in Nature 350, 141, 1991).     

Latitude Dependence of the “Gnevyshev” Peaks and Gaps

The occurrence of double peaks near the maximum of sunspot activity was first emphasized by Gnevyshev (Solar Phys. 1, 107, 1967) for the peak years of solar cycle 19 (1954 – 1964). In the present analysis, it is shown that double peaks in sunspot numbers were clearly visible in solar latitudes 10 – 30° N but almost absent in the southern latitudes, where some single peaks were observed out of phase by several months from any of the peaks in the northern latitudes. The spacing between the double peaks increased from higher to lower northern latitudes, hinting at latitudinal migration. In the next cycle 20 (1965 – 1976), which was of about half the strength of cycle 19, no clear-cut double peaks were seen, and the prominent peak in the early part of 1967 in the northern latitudes was seen a few months later in the southern latitudes. A direct relationship of Gnevyshev peaks with changes in the solar polar magnetic fields seems to be dubious. The commencements do not match.     

Effect of Gravity on the Fast Modes of a Horizontal Coronal Slab

Theoretical studies of the normal modes of a coronal slab often neglect gravity, as in Edwin and Roberts (Solar Phys. 71, 239, 1982). Here we study analytically the effect of gravity acting on a horizontal slab as a first step away from a homogeneous medium. Because of the inclusion of gravity, the symmetry of a homogeneous slab is lost, so the normal modes cannot be classified into kink and sausage modes. The presence of gravity also modifies the oscillatory frequencies of the slab, as well as the lower cutoff frequency, resulting in the possible transition between surface and body modes. For general coronal parameters, the dimensionless gravity term turns out to be small, so these effects are also small. A.J. Díaz’s current affiliation: Universitat de les Illes Balears, Palma, E-07122, Spain.     

A New Forecasting Index for Solar Wind Velocity Based on EIT 284 Å Observations

Various solar wind forecasting methods have been developed during the past decade, such as the Wang?–?Sheeley model and the Hakamada?–?Akasofu?–?Fry Version 2 (HAFv2) model. Also, considerable correlation has been found between the solar wind speed v and the coronal hole (CH) area A _M on the visible side of the Sun, showing quantitative improvement of forecasting accuracy in low CME activity periods (e.g., Vr?nak, Temmer, and Veronig, Solar Phys. 240, 315, 2007a). Properties of lower layers of the solar atmosphere are good indications of the subsequent interplanetary and geomagnetic activities. We analyze the SOHO/EIT 284 Å images and construct a new forecasting factor (Pch) from the brightness of the solar EUV emission, and a good correlation is found between the Pch factor and the 3-day-lag solar wind velocity (v) probed by the ACE spacecraft. The main difference between the Pch and A _M factor is that Pch does not depend on the CH-boundary estimate and can reflect both the area and brightness of CH. A simple method of forecasting the solar wind speed near Earth in low CME activity periods is presented. Between Pch and v from 21 November until 26 December 2003, the linear correlation coefficient is R=0.89. For comparison we also analyze the data in the same period (DOY 25?–?125, 2005) as Vr?nak, Temmer, and Veronig (Solar Phys. 240, 315, 2007a), who used the CH areas A _M for predicting the solar wind parameters. In this period the correlation coefficient between Pch and v is R=0.70, whereas for A _M and v the correlation coefficient is R=0.62. The average relative difference between the calculated and the observed values is $\overline{|\delta|}\approx 12.15\%Various solar wind forecasting methods have been developed during the past decade, such as the Wang – Sheeley model and the Hakamada – Akasofu – Fry Version 2 (HAFv2) model. Also, considerable correlation has been found between the solar wind speed v and the coronal hole (CH) area A _M on the visible side of the Sun, showing quantitative improvement of forecasting accuracy in low CME activity periods (e.g., Vršnak, Temmer, and Veronig, Solar Phys. 240, 315, 2007a). Properties of lower layers of the solar atmosphere are good indications of the subsequent interplanetary and geomagnetic activities. We analyze the SOHO/EIT 284 ? images and construct a new forecasting factor (Pch) from the brightness of the solar EUV emission, and a good correlation is found between the Pch factor and the 3-day-lag solar wind velocity (v) probed by the ACE spacecraft. The main difference between the Pch and A _M factor is that Pch does not depend on the CH-boundary estimate and can reflect both the area and brightness of CH. A simple method of forecasting the solar wind speed near Earth in low CME activity periods is presented. Between Pch and v from 21 November until 26 December 2003, the linear correlation coefficient is R=0.89. For comparison we also analyze the data in the same period (DOY 25 – 125, 2005) as Vršnak, Temmer, and Veronig (Solar Phys. 240, 315, 2007a), who used the CH areas A _M for predicting the solar wind parameters. In this period the correlation coefficient between Pch and v is R=0.70, whereas for A _M and v the correlation coefficient is R=0.62. The average relative difference between the calculated and the observed values is . Furthermore, for the ten peaks during the analysis period, Pch and v show a correlation coefficient of R=0.78, and the average relative difference between the calculated and the observed peak values is . Moreover, the Pch factor can eliminate personal bias in the forecasting process, which existed in the method using CH area as input parameter, because CH area depends on the CH-boundary estimate but Pch does not. Until now the CH-boundary could not be easily determined since no quantitative criteria can be used to precisely locate CHs from observations, which led to differences in forecasting accuracy.     

The Hinode X-Ray Telescope (XRT): Camera Design, Performance and Operations

The X-ray Telescope (XRT) aboard the Hinode satellite is a grazing incidence X-ray imager equipped with a 2048×2048 CCD. The XRT has 1 arcsec pixels with a wide field of view of 34×34 arcmin. It is sensitive to plasmas with a wide temperature range from < 1 to 30 MK, allowing us to obtain TRACE-like low-temperature images as well as Yohkoh/SXT-like high-temperature images. The spacecraft Mission Data Processor (MDP) controls the XRT through sequence tables with versatile autonomous functions such as exposure control, region-of-interest tracking, flare detection, and flare location identification. Data are compressed either with DPCM or JPEG, depending on the purpose. This results in higher cadence and/or wider field of view for a given telemetry bandwidth. With a focus adjust mechanism, a higher resolution of Gaussian focus may be available on-axis. This paper follows the first instrument paper for the XRT (Golub et al., Solar Phys. 243, 63, 2007) and discusses the design and measured performance of the X-ray CCD camera for the XRT and its control system with the MDP.     

Short-Term Periodicities in Sunspot Activity and Flare Index Data during Solar Cycle 23

The short-term periodicities in sunspot numbers, sunspot areas, and flare index data are investigated in detail using the Date Compensated Discrete Fourier Transform (DCDFT) for the full disk of the Sun separately over the rising, the maximum, and the declining portions of solar cycle 23 (1996 – 2006). While sunspot numbers and areas show several significant periodicities in a wide range between 23.1 and 36.4 days, the flare index data do not exhibit any significant periodicity. The earlier conclusion of Pap, Tobiska, and Bouwer (1990, Solar Phys. 129, 165) and Kane (2003, J. Atmos. Solar-Terr. Phys. 65, 1169), that the 27-day periodicity is more pronounced in the declining portion of a solar cycle than in the rising and maximum ones, seems to be true for sunspot numbers and sunspot area data analyzed here during solar cycle 23.     

Search for relationship between duration of the extended solar cycles and amplitude of sunspot cycle

Duration of the extended solar cycles is taken into the consideration. The beginning of cycles is counted from the moment of polarity reversal of large-scale magnetic field in high latitudes, occurring in the sunspot cycle n till the minimum of the cycle n + 2. The connection between cycle duration and its amplitude is established. Duration of the “latent” period of evolution of extended cycle between reversals and a minimum of the current sunspot cycle is entered. It is shown, that the latent period of cycles evolution is connected with the next sunspot cycle amplitude and can be used for the prognosis of a level and time of a sunspot maximum. The 24th activity cycle prognosis is made. The found dependences correspond to transport dynamo model of generation of solar cyclicity, it is possible with various speed of meridional circulation. Long-term behavior of extended cycle's lengths and connection with change of a climate of the Earth is considered. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A Running Average Method for Predicting the Size and Length of a Solar Cycle

The running correlation coefficient between the solar cycle amplitudes and the max-max cycle lengths at a given cycle lag is found to vary roughly in a cyclical wave with the cycle number, based on the smoothed monthly mean Group sunspot numbers available since 1610. A running average method is proposed to predict the size and length of a solar cycle by the use of the varying trend of the coefficients. It is found that, when a condition (that the correlation becomes stronger) is satisfied, the mean prediction error (16.1) is much smaller than when the condition is not satisfied (38.7). This result can be explained by the fact that the prediction must fall on the regression line and increase the strength of the correlation. The method itself can also indicate whether the prediction is reasonable or not. To obtain a reasonable prediction, it is more important to search.for a running correlation coefficient whose varying trend satisfies the proposed condition, and the result does not depend so much on the size of the correlation coefficient. As an application, the peak sunspot number of cycle 24 is estimated as 140.4±15.7, and the peak as May 2012± 11 months.     

The Butterfly Diagram Fine Structure

The present work describes the evolution of the sunspot zone in cycles 20, 21, and 22. In each cycle, and in both hemispheres, the equatorward drift of the spot zone “center of mass” results from the alternation of five or six prograde (namely, equatorward) segments, with other stationary or poleward segments. The duration of the stationary/retrograde phases (resulting from averaging data pertaining to the six semicycles examined here) amounts to ≈36% of the total duration of these semicycles. In the prograde phases, the drift rate is almost twice the “traditional” equatorward rate, resulting only from the extreme positions of the spot zone center of mass (at the beginning and at the end of the cycle). If there were no stationary/retrograde phases, the cycle duration would be half the actual one. We conclude that the retrograde phases should not be regarded as accidental; rather, they are essential features of the 11-year cycle.