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Solar Physics

, Volume 279, Issue 2, pp 551–560 | Cite as

Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24

  • L. C. Uzal
  • R. D. Piacentini
  • P. F. Verdes
Article

Abstract

In this work we predict the maximum amplitude, its time of occurrence, and the total length of Solar Cycle 24 by linear regression to the curvature (second derivative) at the preceding minimum of a smoothed version of the sunspots time series. We characterise the predictive power of the proposed methodology in a causal manner by an incremental incorporation of past solar cycles to the available data base. In regressing maximum cycle intensity to curvature at the leading minimum, we obtain a correlation coefficient R≈0.91 and for the upcoming Cycle 24 a forecast of 78 (90 % confidence interval: 56 – 106). The ascent time also appears to be highly correlated to the second derivative at the starting minimum (R≈−0.77), predicting maximum solar activity for October 2013 (90 % confidence interval: January 2013 to September 2014). Solar Cycle 24 should come to an end by February 2020 (90 % confidence interval: January 2019 to July 2021), although in this case correlational evidence is weaker (R≈−0.56).

Keywords

Ascent time Maximum activity prediction Solar Cycle 24 Total cycle length 

Notes

Acknowledgements

We would like to thank an anonymous reviewer for their useful suggestions to improve this manuscript. Financial support by CONICET, ANPCYT/MINCYT and Universidad Nacional de Rosario is gratefully acknowledged.

References

  1. Calvo, R.A., Ceccatto, H.A., Piacentini, R.D.: 1995, Neural network prediction of solar activity. Astrophys. J. Lett. 444(2), L916 – L921. CrossRefGoogle Scholar
  2. Choudhuri, A.R., Chatterjee, P., Jiang, J.: 2007, Predicting solar cycle 24 with a solar dynamo model. Phys. Rev. Lett. 98(13). Google Scholar
  3. Clilverd, M.A., Clarke, E., Ulich, T., Rishbeth, H., Jarvis, M.J.: 2006, Predicting solar cycle 24 and beyond. Space Weather 4(9). Google Scholar
  4. De Meyer, F.: 2003, A transfer function model for the sunspot cycle. Solar Phys. 217(2), 349 – 366. doi: 10.1023/B:SOLA.0000006856.85960.2e. ADSCrossRefGoogle Scholar
  5. Dikpati, M., de Toma, G., Gilman, P.A.: 2006, Predicting the strength of solar cycle 24 using a flux-transport dynamo-based tool. Geophys. Res. Lett. 33(5). Google Scholar
  6. Dikpati, M., Gilman, P.A., de Toma, G.: 2008, The Waldmeier effect: An artifact of the definition of wolf sunspot number? Astrophys. J. Lett. 673(1), L99. ADSCrossRefGoogle Scholar
  7. Duhau, S.: 2003, An early prediction of maximum sunspot number in solar cycle 24. Solar Phys. 213(1), 203 – 212. doi: 10.1023/A:1023260916825. ADSCrossRefGoogle Scholar
  8. Grassberger, P., Hegger, R., Kantz, H., Schaffrath, C., Schreiber, T.: 1993, On noise reduction methods for chaotic data. Chaos 3(2), 127 – 142. MathSciNetADSMATHCrossRefGoogle Scholar
  9. Hamid, R.H., Galal, A.A.: 2006, Preliminary prediction of the strength of the 24th 11-year solar cycle. In: Bothmer, V., Hady, A.A. (eds.) Proc. Internat. Astron. Union 2, Cambridge University Press, Cambridge, 413 – 416. Google Scholar
  10. Hathaway, D.H., Wilson, R.M.: 2006, Geomagnetic activity indicates large amplitude for sunspot cycle 24. Geophys. Res. Lett. 33(18). Google Scholar
  11. Hathaway, D.H., Wilson, R.M., Reichmann, E.J.: 1994, The shape of the sunspot cycle. Solar Phys. 151, 177 – 190. doi: 10.1007/BF00654090. ADSCrossRefGoogle Scholar
  12. Hathaway, D.H., Wilson, R.M., Reichmann, E.J.: 2002, Group sunspot numbers: Sunspot cycle characteristics. Solar Phys. 211, 357 – 370. doi: 10.1023/A:1022425402664. ADSCrossRefGoogle Scholar
  13. Hiremath, K.M.: 2008, Prediction of solar cycle 24 and beyond. Astrophys. Space Sci. 314, 45 – 49. ADSCrossRefGoogle Scholar
  14. Horstman, M.: 2005, Varying solar flux models and their effect on the future debris environment projection. Orbital Debris Q. News 9, 4 – 5. Google Scholar
  15. Huber, P.J.: 1981, Robust Statistics, Wiley Series in Probability and Mathematical Statistics, Probability and Mathematical Statistics, Wiley, Hoboken. ISBN 9780471418054. MATHCrossRefGoogle Scholar
  16. Jain, R.: 2006, Prediction of the amplitude in sunspot cycle 24. COSPAR 36, 642 (Abstract from CD). ADSGoogle Scholar
  17. Kane, R.P.: 1999, Prediction of the sunspot maximum of solar cycle 23 by extrapolation of spectral components. Solar Phys. 189(1), 217 – 224. doi: 10.1023/A:1005298313886. MathSciNetADSCrossRefGoogle Scholar
  18. Kane, R.P.: 2007, A preliminary estimate of the size of the coming solar cycle 24, based on Ohl’s precursor method. Solar Phys. 243(2), 205 – 217. doi: 10.1007/s11207-007-0475-4. MathSciNetADSCrossRefGoogle Scholar
  19. Kim, M.Y., Wilson, J.W., Cucinotta, F.A.: 2006, A solar cycle statistical model for the projection of space radiation environment. Adv. Space Res. 37(9), 1741 – 1748. ADSCrossRefGoogle Scholar
  20. Krivova, N.A., Solanki, S.K., Beer, J.: 2002, Was one sunspot cycle in the 18th century really lost? Astron. Astrophys. 396(1), 235 – 242. ADSCrossRefGoogle Scholar
  21. Lantos, P.: 2006, The skewness of a solar cycle as a precursor of the amplitude of the next. Solar Phys. 236, 199 – 205. doi: 10.1007/s11207-006-0145-y. ADSCrossRefGoogle Scholar
  22. Maris, G., Oncica, A.: 2006, Solar Cycle 24 forecasts. Sun Geospace 1, 8 – 11. ADSGoogle Scholar
  23. Ossendrijver, M.: 2003, The solar dynamo. Astron. Astrophys. Rev. 11, 287 – 367. ADSCrossRefGoogle Scholar
  24. Pesnell, W.D.: 2008, Predictions of solar cycle 24. Solar Phys. 252(1), 209 – 220. doi: 10.1007/s11207-008-9252-2. ADSCrossRefGoogle Scholar
  25. Savitzky, A., Golay, M.J.E.: 1964, Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36(8), 1627 – 1639. ADSCrossRefGoogle Scholar
  26. Schatten, K.: 2005, Fair space weather for solar cycle 24. Geophys. Res. Lett. 32(21), 1 – 4. CrossRefGoogle Scholar
  27. Svalgaard, L., Cliver, E.W., Kamide, Y.: 2005, Sunspot cycle 24: Smallest cycle in 100 years? Geophys. Res. Lett. 32(1), 1 – 4. CrossRefGoogle Scholar
  28. Usoskin, I.G., Mursula, K., Arlt, R., Kovaltsov, G.A.: 2009, A Solar Cycle Lost in 1793 – 1800: Early Sunspot Observations Resolve the Old Mystery. Astrophys. J. Lett. 700, L154 – L157. ADSCrossRefGoogle Scholar
  29. Usoskin, I.G., Mursula, K., Kovaltsov, G.A.: 2001, Was one sunspot cycle lost in late XVIII Century? Astron. Astrophys. 370(2), L31 – L34. ADSCrossRefGoogle Scholar
  30. Usoskin, I.G., Mursula, K., Kovaltsov, G.A.: 2003, The lost sunspot cycle: reanalysis of sunspot statistics. Astron. Astrophys. 403(2), 743 – 748. ADSCrossRefGoogle Scholar
  31. Verdes, P.F., Granitto, P.M., Ceccatto, H.A.: 2004, Secular behavior of solar magnetic activity: Nonstationary time-series analysis of the sunspot record. Solar Phys. 221(1), 167 – 177. doi: 10.1023/B:SOLA.0000033361.20655.ed. ADSCrossRefGoogle Scholar
  32. Verdes, P.F., Parodi, M.A., Granitto, P.M., Navone, H.D., Piacentini, R.D., Ceccatto, H.A.: 2000, Predictions of the maximum amplitude for solar cycle 23 and its subsequent behavior using nonlinear methods. Solar Phys. 191(2), 419 – 425. doi: 10.1023/A:1005202814071. ADSCrossRefGoogle Scholar
  33. Waldmeier, M.: 1955, Ergebnisse und Probleme der Sonnenforschung, Akademische Verlagsgesellschaft, Leipzig. Google Scholar
  34. Wang, J.L., Gong, J.C., Liu, S.Q., Le, G.M., Sun, J.L.: 2002, The prediction of maximum amplitudes of solar cycles and the maximum amplitude of solar cycle 24. Chin. J. Astron. Astrophys. 2(6), 557 – 562. ADSCrossRefGoogle Scholar
  35. Zolotova, N.V., Ponyavin, D.I.: 2011, Enigma of the solar cycle 4 still not resolved. Astrophys. J. 736(2), 115. ADSCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • L. C. Uzal
    • 1
  • R. D. Piacentini
    • 2
    • 3
  • P. F. Verdes
    • 1
  1. 1.French-Argentine International Centre for Information and Systems Sciences (CIFASIS)AMU (France)/UNR – CONICET (Argentina)RosarioArgentina
  2. 2.Instituto de Fisica Rosario (IFIR)UNR – CONICET (Argentina)RosarioArgentina
  3. 3.Facultad de Ciencias Exactas, Ingenieria y AgrimensuraUniversidad Nacional de RosarioRosarioArgentina

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