Preliminary prediction of solar cycles 24 and 25 based on the correlation between cycle parameters

Pishkalo, M. І.

doi:10.3103/s0884591308050036

Cited by 34 publications

(13 citation statements)

References 22 publications

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“…The results are 196 ± 52 for 13-month smoothed monthly data and 130 ± 42 for monthly sunspot number. In general, these values are higher compared to the published prediction of other authors [10,11,12,13]. …”

Section: Relation Between and Hcontrasting

confidence: 49%

White light corona during total solar eclipse on March 9, 2016

Imaduddin

Akbar

Putri

2016

J. Phys.: Conf. Ser.

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Abstract.We observed the white-light corona during the total solar eclipse of 2016 March 9 from Corong Beach, East Borneo. The solar corona is nearly circular with exception on the southern part of the Sun. Coronal structures are clearly seen. Based on the data, we obtained the Ludendorff flattening index, Nikolsky geometric flattening index, and phases of solar activity (Φ and P) are 0.129, 1.32, -0.716, and 0.573 respectively. Relation between Ludendorff and Nikolsky index, sunspot number, and phases of solar activity were discussed. We also predicted the amplitude of solar cycle 25 to be 196 ± 52 (based on 13-month smoothed monthly data) and 130 ± 42 (based on monthly sunspot number data).

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Section: Relation Between and Hcontrasting

confidence: 49%

White light corona during total solar eclipse on March 9, 2016

Imaduddin

Akbar

Putri

2016

J. Phys.: Conf. Ser.

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“…6). The relation is linear (Brown 1976), with a correlation coefficient of 0.68 (if the anomalous cycle 19 is ignored- Brajša et al 2009; see also Pishkalo 2008). The best fit is Cycles are labeled with their numbers.…”

Section: Cycle Parameters As Precursors and The Waldmeier Effectmentioning

confidence: 99%

Solar cycle prediction

Petrovay

2020

Living Rev Sol Phys

200

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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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“…In addition, AMS-02 was launched at the beginning of the solar activity maximum. Although solar cycle 24 exhibits a relatively weak maximum compared to former cycles, a first GAPS flight would presumably happen during the next solar activity minimum [220], easing the uncertainties associated with low-energy measurements.…”

Section: Experimental Path Forwardmentioning

confidence: 99%

Review of the theoretical and experimental status of dark matter identification with cosmic-ray antideuterons

et al. 2016

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See paper for full list of authors - 67 pages, 20 figures; submitted to Physics ReportsInternational audienceRecent years have seen increased theoretical and experimental effort towards the first-ever detection of cosmic-ray antideuterons, in particular as an indirect signature of dark matter annihilation or decay. In contrast to indirect dark matter searches using positrons, antiprotons, or gamma-rays, which suffer from relatively high and uncertain astrophysical backgrounds, searches with antideuterons benefit from very suppressed conventional backgrounds, offering a potential breakthrough in unexplored phase space for dark matter. This article is based on the first dedicated cosmic-ray antideuteron workshop, which was held at UCLA in June 2014. It reviews broad classes of dark matter candidates that result in detectable cosmic-ray antideuteron fluxes, as well as the status and prospects of current experimental searches. The coalescence model of antideuteron production and the influence of antideuteron measurements at particle colliders are discussed. This is followed by a review of the modeling of antideuteron propagation through the magnetic fields, plasma currents, and molecular material of our Galaxy, the solar system, the Earth's geomagnetic field, and the atmosphere. Finally, the three ongoing or planned experiments that are sensitive to cosmic-ray antideuterons, BESS, AMS-02, and GAPS, are detailed. As cosmic-ray antideuteron detection is a rare event search, multiple experiments with orthogonal techniques and backgrounds are essential. Many theoretical and experimental groups have contributed to these studies over the last decade, this review aims to provide the first coherent discussion of the relevant dark matter theories that antideuterons probe, the challenges to predictions and interpretations of antideuteron signals, and the experimental efforts toward cosmic antideuteron detection

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Preliminary prediction of solar cycles 24 and 25 based on the correlation between cycle parameters

Cited by 34 publications

References 22 publications

White light corona during total solar eclipse on March 9, 2016

White light corona during total solar eclipse on March 9, 2016

Solar cycle prediction

Review of the theoretical and experimental status of dark matter identification with cosmic-ray antideuterons

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