Eleven-year cyclicity of the sun on the 2000-year time scale

Nagovitsyn, Yu. A.; Georgieva, K.; Осипова, А. А.; Kuleshova, A. I.

doi:10.1134/s001679321508023x

Cited by 8 publications

(4 citation statements)

References 16 publications

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“…Figure 3 shows the distribution function for the computed cycle periods. The distribution is similar to the observations-based results of Nagovitsyn et al (2015). The mean duration of computed cycles P cyc = 10.9 years.…”

Section: Cycle Periodssupporting

confidence: 84%

“…The correlation time of fluctuations in the BL mechanism for a generation of the poloidal magnetic field is close to the solar rotation period. This conclusion follows from a comparison of the statistics of computed dynamo-cycle periods with the distributions of periods of 36 directly observed and 119 reconstructed (Nagovitsyn et al 2015) solar cycles. Fluctuations in the BLtype α-effect induce asymmetry in magnetic cycles of the dynamo model with the rise time of simulated cycles being on average shorter than the time of decline.…”

Section: Discussionmentioning

confidence: 82%

“…( 5) D obs = 0.135 for this sample. Periods for a larger number of 119 cycles (measured maximum-to-maximum) have been recovered by Nagovitsyn et al (2015) from solar activity proxies; D rec = 0.185 for their sample. These values are close to D = 0.162 resulting from our model computations for τ = P rot .…”

Section: Cycle Periodsmentioning

confidence: 99%

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Modelling variability of solar activity cycles

Kitchatinov

Мордвинов

Nepomnyashchikh

2018

A&A

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Context. Solar activity cycles vary in amplitude and duration. The variations can be at least partly explained by fluctuations in dynamo parameters. Aims. We want to restrict uncertainty in fluctuating dynamo parameters and find out which properties of the fluctuations control the amplitudes of the magnetic field and energy in variable dynamo cycles. Methods. A flux-transport model for the solar dynamo with fluctuations of the Babcock-Leighton type α-effect was applied to generate statistics of magnetic cycles for our purposes. The statistics were compared with data on solar cycle periods to restrict the correlation time of dynamo fluctuations. Results. A characteristic time of fluctuations in the α-effect is estimated to be close to the solar rotation period. The fluctuations produce asymmetry between the times of rise and descent of dynamo cycles, the rise time being on average shorter. The affect of the fluctuations on cycle amplitudes depends on the phase of the cycle in which the fluctuations occur. Negative fluctuations (decrease in α) in the rise phase delay decay of poloidal field and increase the cycle amplitude in toroidal field and magnetic energy. Negative fluctuation in the decline phase reduces the polar field at the end of a cycle and the amplitude of the next cycle. The low amplitude of the 24th solar cycle compared to the preceding 23rd cycle can be explained by this effect. Positive fluctuations in the descent phase enhance the magnetic energy of the next cycle by increasing the seed poloidal field for the next cycle. The statistics of the computed energies of the cycles suggest that superflares of ≥ 10 34 erg are not possible on the Sun.

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Section: Cycle Periodssupporting

confidence: 84%

Section: Discussionmentioning

confidence: 82%

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Modelling variability of solar activity cycles

Kitchatinov

Мордвинов

Nepomnyashchikh

2018

A&A

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“…noaa.gov/stp/space-weather/solar-data/solar-indices/sunspotnumbers/cycle-data/table cycle-dates maximum-minimum. txt) and with 119 periods reconstructed by Nagovitsyn et al (2015) from activity proxies give the correlation time τ ≈ P rot (Kitchatinov et al 2018). The discussion to follow concerns, therefore, the case of σ = 3 and τ /P rot = 1 from Table 1, which is closest to these estimations.…”

Section: Resultsmentioning

confidence: 79%

Solar Cycle Asymmetry as a Consequence of Fluctuations in Dynamo Parameters

Kitchatinov

Nepomnyashchikh

2018

Astron. Lett.

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The duration of activity growths in solar cycles is on average shorter than the duration of its declines. This asymmetry can result from fluctuations in dynamo parameters. A solar dynamo model with fluctuations in the α-effect shows the statistical asymmetry which increases with both fluctuation amplitude and coherence time. An interpretation for the asymmetry origin is suggested, which predicts a correlation between the asymmetry measure and delay of the polar field reversals relative to the activity maxima. Data on the twelve latest solar cycles confirm such a correlation.

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