Solar Physics

, 292:181 | Cite as

Prediction of the Length of Upcoming Solar Cycles

  • Bharati Kakad
  • Amar Kakad
  • Durbha Sai Ramesh


The forecast of solar cycle (SC) characteristics is crucial particularly for several space-based missions. In the present study, we propose a new model for predicting the length of the SC. The model uses the information of the width of an autocorrelation function that is derived from the daily sunspot data for each SC. We tested the model on Versions 1 and 2 of the daily international sunspot number data for SCs 10 – 24. We found that the autocorrelation width \(A_{\mathrm{w}} ^{n}\) of SC \(n\) during the second half of its ascending phase correlates well with the modified length that is defined as \(T_{\mathrm{cy}}^{n+2} - T_{\mathrm{a}}^{n}\). Here \(T_{\mathrm{cy}}^{n+2}\) and \(T_{ \mathrm{a}}^{n}\) are the length and ascent time of SCs \(n+2\) and \(n\), respectively. The estimated correlation coefficient between the model parameters is 0.93 (0.91) for Version 1 (Version 2) sunspot series. The standard errors in the observed and predicted lengths of the SCs for Version 1 and Version 2 data are 0.38 and 0.44 years, respectively. The advantage of the proposed model is that the predictions of the length of the upcoming two SCs (i.e., \(n+1\), \(n+2\)) are readily available at the time of the peak of SC \(n\). The present model gives a forecast of 11.01, 10.52, and 11.91 years (11.01, 12.20, and 11.68 years) for the length of SCs 24, 25, and 26, respectively, for Version 1 (Version 2).


Solar cycle Sunspots Models 



We thank the SIDC and SILSO teams for the daily and monthly international sunspot data. The revisions of the manuscript were carried out at the Research Institute of Sustainable Humanosphere, Kyoto University, Japan.

Disclosure of Potential Conflicts of Interest

The authors declare that they have no conflicts of interest.


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  • Bharati Kakad
    • 1
    • 2
  • Amar Kakad
    • 1
  • Durbha Sai Ramesh
    • 1
  1. 1.Indian Institute of GeomagnetismNavi MumbaiIndia
  2. 2.Research Institute for Sustainable HumanosphereKyoto UniversityUji, KyotoJapan

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