Forecasting the 23rd and 24th solar cycles on the basis of MGM spectrum

Tsirulnik, L. B.; Kuznetsova, T. V.; Oraevsky, V. N.

doi:10.1016/s0273-1177(97)00909-5

Cited by 33 publications

(12 citation statements)

References 3 publications

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“…Maris and Oncica (2006) reported that the solar cycle maximum in cycle 24 will occur in December 2009 with a sunspot number of 145. Tsirulnik et al (1997) reported that solar cycle 24 presents your maximum in 2014 with a sunspot number of 180. Echer et al (2004) predicted that solar maximum 24 will happen in 2013 with a sunspot number of 117713.2.…”

Section: Resultsmentioning

confidence: 99%

“…#24 Prediction Max. #24 Tsirulnik et al (1997) 180 Hathaway and Wilson (2006) 160 Kane (1999) 1407 9 Hamid and Galal (2006) 91 Wang et al (2002) 83.2-119.4 Maris and Oncica (2006) 145 Khramova et al (2002) 123-124 Chopra and Dabas (2006) 140 Duhau (2003) 87.57 23.5 Dikpati andGilman (2006) 160-180 Echer et al (2004) 115-1177 13.2 Kane (2007) 124 Gholipour et al (2005) 145 Quassim et al (2007) 110 Tlatov andMakarov (2005) 757 10 Javaraiah (2007) Errors that have been observed in this prediction scheme seem to be due to the limitation of the method itself and also because part of the nature (nonlinear features, Waldmeier effect) of the time series is not very well described by the model (Kane, 2008). It is important to comment that, although the solar cycle is asymmetric (e.g.…”

Section: Predictionmentioning

confidence: 99%

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Prediction of sunspot number amplitude and solar cycle length for cycles 24 and 25

Rigozo

Echer

Evangelista

et al. 2011

Journal of Atmospheric and Solar-Terrestrial Physics

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Section: Resultsmentioning

confidence: 99%

Section: Predictionmentioning

confidence: 99%

Prediction of sunspot number amplitude and solar cycle length for cycles 24 and 25

Rigozo

Echer

Evangelista

et al. 2011

Journal of Atmospheric and Solar-Terrestrial Physics

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“…If the latter hypothesis turned out to be the true one, then the best predictor would simply be the average cycle (Aguirre et al, 2008). Some works have appeared in the literature that explain the fluctuations in the peak values of the sunspot time series using some kind of stochastic process (Tsirulnik, Kuznetsova, and Oraevsky, 1997;Mininni, Gómez, and Mindlin, 2000) or nonlinear spectral model (Nikonova, Klochek, and Smolkov, 2000).…”

Section: Introductionmentioning

confidence: 99%

Forecasting the Time Series of Sunspot Numbers

2008

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Forecasting the solar cycle is of great importance for weather prediction and environmental monitoring, and also constitutes a difficult scientific benchmark in nonlinear dynamical modeling. This paper describes the identification of a model and its use in the forecasting the time series comprised of Wolf's sunspot numbers. A key feature of this procedure is that the original time series is first transformed into a symmetrical space where the dynamics of the solar dynamo are unfolded in a better way, thus improving the model. The nonlinear model obtained is parsimonious and has both deterministic and stochastic parts. Monte Carlo simulation of the whole model produces very consistent results with the deterministic part of the model but allows for the determination of confidence bands. The obtained model was used to predict cycles 24 and 25, although the forecast of the latter is seen as a crude approximation, given the long prediction horizon required. As for the 24th cycle, two estimates were obtained with peaks of 65 ± 16 and of 87 ± 13 units of sunspot numbers. The simulated results suggest that the 24th cycle will be shorter and less active than the preceding one.

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“…Our latest prediction of Rz(max)=58±25 is in the (a) range of <70, much lower than the average of all predictions (∼115). Thus, if our prediction comes true, predictions in the high range (g) like Rz(max) 150-180 (Dikpati et al, 2006), Rz(max)=180 (Tsirulnik et al, 1997), Rz(max)=185 (Horstman, 2005) would prove grossly erroneous, while predictions in the very low range (a) Rz(max)=42±34 (Clilverd et al, 2006) and Rz(max)<50 (Badalyan et al, 2001) would prove to be true.…”

Section: Conclusion and Discussionmentioning

confidence: 77%

Size of the coming solar cycle 24 based on Ohl's Precursor Method, final estimate

Kane

2010

Ann. Geophys.

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Abstract. In Ohl's Precursor Method (Ohl, 1966(Ohl, , 1976, the geomagnetic activity during the declining phase of a sunspot cycle is shown to be well correlated with the size (maximum sunspot number Rz(max)) of the next cycle. For solar cycle 24, Kane (2007a) used aa(min)=15.5 (12-month running mean), which occurred during March-May of 2006 and made a preliminary estimate Rz(max)=124±26 (12-month running mean). However, in the next few months, the aa index first increased and then decreased to a new low value of 14.8 in July 2007. With this new low value, the prediction was Rz(max)=117±26 (12-month running mean). However, even this proved a false signal. Since then, the aa values have decreased considerably and the last 12-monthly value is 8.7, centered at May 2009. For solar cycle 24, using aa(min)=8.7, the latest prediction is, Rz(max)=58.0±25.0.

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Forecasting the 23rd and 24th solar cycles on the basis of MGM spectrum

Cited by 33 publications

References 3 publications

Prediction of sunspot number amplitude and solar cycle length for cycles 24 and 25

Prediction of sunspot number amplitude and solar cycle length for cycles 24 and 25

Forecasting the Time Series of Sunspot Numbers

Size of the coming solar cycle 24 based on Ohl's Precursor Method, final estimate

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