Sunspot Number Second Differences as a Precursor of the Following 11-year Sunspot Cycle

Podladchikova, Tatiana; Linden, R. Van der; Veronig, Astrid

doi:10.3847/1538-4357/aa93ef

Cited by 26 publications

(32 citation statements)

References 31 publications

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“…3 http://en.solarstation.ru/. 4 Alternative proposals have been put forward by Muñoz-Jaramillo et al (2012) and Podladchikova et al (2017); who pointed out that Eq. (2) does a poor job of filtering out high-frequency variations, and use better or even optimized weight factors for the R m;i 's instead.…”

Section: Version 10mentioning

confidence: 99%

Solar cycle prediction

Petrovay

2020

Living Rev Sol Phys

194

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A review of solar cycle prediction methods and their performance is given, including early forecasts for Cycle 25. The review focuses on those aspects of the solar cycle prediction problem that have a bearing on dynamo theory. The scope of the review is further restricted to the issue of predicting the amplitude (and optionally the epoch) of an upcoming solar maximum no later than right after the start of the given cycle. Prediction methods form three main groups. Precursor methods rely on the value of some measure of solar activity or magnetism at a specified time to predict the amplitude of the following solar maximum. The choice of a good precursor often implies considerable physical insight: indeed, it has become increasingly clear that the transition from purely empirical precursors to model-based methods is continuous. Model-based approaches can be further divided into two groups: predictions based on surface flux transport models and on consistent dynamo models. The implicit assumption of precursor methods is that each numbered solar cycle is a consistent unit in itself, while solar activity seems to consist of a series of much less tightly intercorrelated individual cycles. Extrapolation methods, in contrast, are based on the premise that the physical process giving rise to the sunspot number record is statistically homogeneous, i.e., the mathematical regularities underlying its variations are the same at any point of time, and therefore it lends itself to analysis and forecasting by time series methods. In their overall performance during the course of the last few solar cycles, precursor methods have clearly been superior to extrapolation methods. One method that has This article is a revised version of

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Section: Version 10mentioning

confidence: 99%

Solar cycle prediction

Petrovay

2020

Living Rev Sol Phys

194

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“…To derive the velocity and acceleration profiles, we first smooth the height-time data and derive the first and second time derivatives. The smoothing algorithm is based on the method described in Podladchikova et al (2017) and applied in Dissauer et al (2019), extended toward non-equidistant data. From the obtained acceleration profiles, we further interpolate to equidistant data points based on the minimization of the second derivatives and reconstruct the corresponding velocity and height profiles by integration.…”

Section: Cme Dynamicsmentioning

confidence: 99%

Solar Flare–CME Coupling throughout Two Acceleration Phases of a Fast CME

Gou

Veronig

Liu

et al. 2020

ApJL

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Solar flares and coronal mass ejections (CMEs) are closely coupled through magnetic reconnection. CMEs are usually accelerated impulsively within the low solar corona, synchronized with the impulsive flare energy release. We investigate the dynamic evolution of a fast CME and its associated X2.8 flare occurring on 2013 May 13. The CME experiences two distinct phases of enhanced acceleration, an impulsive one with a peak value of ∼5 kms −2 , followed by an extended phase with accelerations up to 0.7 kms −2. The two-phase CME dynamics is associated with a two-episode flare energy release. While the first episode is consistent with the "standard" eruption of a magnetic flux rope, the second episode of flare energy release is initiated by the reconnection of a large-scale loop in the aftermath of the eruption and produces stronger nonthermal emission up to γ-rays. In addition, this longduration flare reveals clear signs of ongoing magnetic reconnection during the decay phase, evidenced by extended hard X-ray bursts with energies up to 100-300keV and intermittent downflows of reconnected loops for >4hr. The observations reveal that the two-step flare reconnection substantially contributes to the two-phase CME acceleration, and the impulsive CME acceleration precedes the most intense flare energy release. The implications of this non-standard flare/CME observation are discussed.

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“…In order to obtain robust CME estimates of the velocity and acceleration profiles, we first smooth the heighttime profile. This smoothing algorithm is based on the method described in Podladchikova et al (2017). It optimizes between two criteria: the closeness of the approximating curve to the data and the smoothness of the approximating curve.…”

Section: Cme Kinematicsmentioning

confidence: 99%

Statistics of Coronal Dimmings Associated with Coronal Mass Ejections. II. Relationship between Coronal Dimmings and Their Associated CMEs

Dissauer

Veronig

Temmer

et al. 2019

ApJ

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We present a statistical study of 62 coronal dimming events associated with Earth-directed CMEs during the quasiquadrature period of STEREO and SDO. This unique setting allows us to study both phenomena in great detail and compare characteristic quantities statistically. Coronal dimmings are observed on-disk by SDO/AIA and HMI, while the CME kinematics during the impulsive acceleration phase is studied close to the limb with STEREO/EUVI and COR, minimizing projection effects. The dimming area, its total unsigned magnetic flux and its total brightness, reflecting properties of the total dimming region at its final extent, show the highest correlations with the CME mass (c ∼ 0.6 − 0.7). Their corresponding time derivatives, describing the dynamics of the dimming evolution, show the strongest correlations with the CME peak velocity (c ∼ 0.6). The highest correlation of c = 0.68 ± 0.08 is found with the mean intensity of dimmings, indicating that the lower the CME starts in the corona, the faster it propagates. No significant correlation between dimming parameters and the CME acceleration was found. However, for events where high-cadence STEREO observations were available, the mean unsigned magnetic field density in the dimming regions tends to be positively correlated with the CME peak acceleration (c = 0.42 ± 0.20). This suggests that stronger magnetic fields result in higher Lorentz forces providing stronger driving force for the CME acceleration. Specific coronal dimming parameters correlate with both, CME and flare quantities providing further evidence for the flare-CME feedback relationship. For events in which the CME occurs together with a flare, coronal dimmings statistically reflect the properties of both phenomena.

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Sunspot Number Second Differences as a Precursor of the Following 11-year Sunspot Cycle

Cited by 26 publications

References 31 publications

Solar cycle prediction

Solar cycle prediction

Solar Flare–CME Coupling throughout Two Acceleration Phases of a Fast CME

Statistics of Coronal Dimmings Associated with Coronal Mass Ejections. II. Relationship between Coronal Dimmings and Their Associated CMEs

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