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Forecasting the Time Series of Sunspot Numbers

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Abstract

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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Authors and Affiliations

  1. Departamento de Engenharia Eletrônica, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, 31.270-901, Belo Horizonte, MG, Brazil

    L. A. Aguirre

  2. CORIA/CNRS UMR 6614, Université et INSA de Rouen, Av. de l’Université, BP 12, 76801, Saint-Etienne du Rouvray cedex, France

    C. Letellier & J. Maquet

Authors
  1. L. A. Aguirre
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  2. C. Letellier
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  3. J. Maquet
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Correspondence to L. A. Aguirre.

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Aguirre, L.A., Letellier, C. & Maquet, J. Forecasting the Time Series of Sunspot Numbers. Sol Phys 249, 103–120 (2008). https://doi.org/10.1007/s11207-008-9160-5

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  • DOI: https://doi.org/10.1007/s11207-008-9160-5

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