DOI QR코드

DOI QR Code

PERFORMANCE OF THE AUTOREGRESSIVE METHOD IN LONG-TERM PREDICTION OF SUNSPOT NUMBER

  • Chae, Jongchul (Department of Physics and Astronomy, Seoul National University) ;
  • Kim, Yeon Han (Solar and Space Weather Group, Korea Astronomy and Space Science Institute)
  • Received : 2016.11.25
  • Accepted : 2017.01.06
  • Published : 2017.04.30

Abstract

The autoregressive method provides a univariate procedure to predict the future sunspot number (SSN) based on past record. The strength of this method lies in the possibility that from past data it yields the SSN in the future as a function of time. On the other hand, its major limitation comes from the intrinsic complexity of solar magnetic activity that may deviate from the linear stationary process assumption that is the basis of the autoregressive model. By analyzing the residual errors produced by the method, we have obtained the following conclusions: (1) the optimal duration of the past time for the forecast is found to be 8.5 years; (2) the standard error increases with prediction horizon and the errors are mostly systematic ones resulting from the incompleteness of the autoregressive model; (3) there is a tendency that the predicted value is underestimated in the activity rising phase, while it is overestimated in the declining phase; (5) the model prediction of a new Solar Cycle is fairly good when it is similar to the previous one, but is bad when the new cycle is much different from the previous one; (6) a reasonably good prediction of a new cycle can be made using the AR model 1.5 years after the start of the cycle. In addition, we predict the next cycle (Solar Cycle 25) will reach the peak in 2024 at the activity level similar to the current cycle.

Keywords

References

  1. Kim, K.-T. 1991, Revisit to the Sunspot Cycle, JKAS, 24, 117
  2. Moran, P. A. P. 1954, Some Experiments on the Prediction of Sunspot Numbers, J. Royal Statist. Soc. Ser. B16, 112
  3. Pesnell, W. D. 2008, Predcitions of Solar Cycle 24, Solar Phys., 252, 209 https://doi.org/10.1007/s11207-008-9252-2
  4. Pesnell, W. D. 2012, Solar Cycle Predictions (Invited Review), Solar Phys., 281, 507
  5. Sim, K. J., Moon, Y.-J., Lee, C.-W., Chang, B. H., & Woo, H. S. 2001, The Relative Sunspot Numbers in 2000, JKAS, 34, 119
  6. Walker, G. 1931, On Periodicity in Series of Related Terms, Proceedings of the Royal Society of London, Ser. A, 131, 518 https://doi.org/10.1098/rspa.1931.0069
  7. Werner, R. 2012, Sunspot Number Prediction by an Autoregressive Model, Sun and Geosphere, 7, 75
  8. Yule, G. U. 1927, On a Method of Investigating Periodicities in Disturbed Series, with Special Reference to Wolfer's Sunspot Numbers, Phil. Trans. Royal Soc. Ser. A, 226, 267 https://doi.org/10.1098/rsta.1927.0007