Predicted amplitude of the next solar cycle 26 using the strength of current solar cycle 25 as precursor
Heading:
| 1Pishkalo, MI 1Main Astronomical Observatory of the National Academy of Sciences of Ukraine, Kyiv, Ukraine |
| Space Sci. & Technol. 2025, 31 ;(5):50-54 |
| https://doi.org/10.15407/knit2025.05.050 |
| Publication Language: English |
Abstract: Solar activity affects space weather and many space-borne and ground-based high-technological systems. Knowing the solar activity level in advance is important for modern humans’ lives. Among the many methods proposed to date for the prediction of the strength of the next solar cycle, the most in demand are the numerous precursor methods focused on a single chosen parameter at a given time as the dominant indicator of future solar activity. Here, we used the amplitude of the previous cycle as a precursor. A significant positive correlation was found between the amplitudes of the odd-numbered and the next even-numbered cycles. The correlation coefficient was equal to 0.57 when the pair of cycles 7-8 was not taken into account. Using the obtained regression equation for maxima of odd-even cycles and the amplitude of the current Solar Cycle 25 (160.8 in October 2024), we estimated the strength of the next Solar Cycle 26. Solar Cycle 26 is predicted to have an amplitude of 142.2 ± 52.7. This means that it will be higher than Solar Cycle 24 but lower than Solar Cycle 25. Using the predicted amplitude of Solar Cycle 26 and the regression equation for maxima of even-odd cycles, we can also estimate the amplitude of Solar Cycle 27 to be equal to 188.4±67.4. Solar activity is expected to increase in the next decades, and there is no evidence of a grand solar minimum like the Dalton or Maunder minimum.
|
| Keywords: : solar activity, solar cycle prediction, sunspot number |
References:
1. Asikainen T., Mantere J. (2023). Prediction of even and odd sunspot cycles. J. Space Weather Space Clim., 13, 25.
https://doi.org/10.1051/swsc/2023024
2. Cao J., Xu T., Deng L., Zhou X., Li Sh., Liu Y., Wang W., Zhou W. (2024). An improved prediction of solar cycles 25 and 26 using the Informer model: Gnevyshev peaks and north-south asymmetry. Astrophys. J., 969(2). 120.
https://doi.org/10.1051/swsc/2023024
2. Cao J., Xu T., Deng L., Zhou X., Li Sh., Liu Y., Wang W., Zhou W. (2024). An improved prediction of solar cycles 25 and 26 using the Informer model: Gnevyshev peaks and north-south asymmetry. Astrophys. J., 969(2). 120.
https://doi.org/10.3847/1538-4357/ad4551
3. Gnevyshev M.N., Ohl A.I. (1948). On the 22-year cycle of solar activity. Astron. Zhurn.. 25(1), 18.
4. Hathaway D.H. (2015). The solar cycle. Living Rev. Solar Phys., 12, 4.
https://doi.org/10.1007/lrsp-2015-4
5. Kalkan M.Y., Fawzy D.E., Saygac A.T. (2023) Predictions of solar activity cycles 25 and 26 using non-linear autoregressive exogenous neural networks. Mon. Not. Roy. Astron. Soc., 523(1), 1175.
https://doi.org/10.1093/mnras/stad1460
6. Liu X., Zeng Sh., Deng L., Zeng X., Zheng Sh. (2023). Predicting the 25th and 26th solar cycles using the long short-term memory method. Publs Astron. Soc. Japan, 75(3), 691.
https://doi.org/10.1093/pasj/psad029
7. Luo P.-X., Tan B.-L. (2024). Long-term evolution of solar activity and prediction of the following solar cycles. Res. Astron. Astrophys., 24(3), 035016.
https://doi.org/10.1088/1674-4527/ad1ed2
8. Pesnell W.D. (2012). Solar cycle predictions (invited review). Solar Phys., 281, 507.
https://doi.org/10.1007/s11207-012-9997-5
9. Petrovay K. (2020). Solar cycle prediction. Living Rev. Solar Phys., 17, 2.
https://doi.org/10.1007/s41116-020-0022-z
10. Petrovay K. (2024). Predicting solar cycles with a parametric time series model. Universe, 10, 364.
https://doi.org/10.3390/universe10090364
11. Pishkalo M.I., Vasiljeva I.E. (2023). Prediction of maximum of solar cycle 25: total power at the cycle beginning and in the previous cycle as precursor. Kinemat. Phys. Celest. Bodies, 39(4), 225.
3. Gnevyshev M.N., Ohl A.I. (1948). On the 22-year cycle of solar activity. Astron. Zhurn.. 25(1), 18.
4. Hathaway D.H. (2015). The solar cycle. Living Rev. Solar Phys., 12, 4.
https://doi.org/10.1007/lrsp-2015-4
5. Kalkan M.Y., Fawzy D.E., Saygac A.T. (2023) Predictions of solar activity cycles 25 and 26 using non-linear autoregressive exogenous neural networks. Mon. Not. Roy. Astron. Soc., 523(1), 1175.
https://doi.org/10.1093/mnras/stad1460
6. Liu X., Zeng Sh., Deng L., Zeng X., Zheng Sh. (2023). Predicting the 25th and 26th solar cycles using the long short-term memory method. Publs Astron. Soc. Japan, 75(3), 691.
https://doi.org/10.1093/pasj/psad029
7. Luo P.-X., Tan B.-L. (2024). Long-term evolution of solar activity and prediction of the following solar cycles. Res. Astron. Astrophys., 24(3), 035016.
https://doi.org/10.1088/1674-4527/ad1ed2
8. Pesnell W.D. (2012). Solar cycle predictions (invited review). Solar Phys., 281, 507.
https://doi.org/10.1007/s11207-012-9997-5
9. Petrovay K. (2020). Solar cycle prediction. Living Rev. Solar Phys., 17, 2.
https://doi.org/10.1007/s41116-020-0022-z
10. Petrovay K. (2024). Predicting solar cycles with a parametric time series model. Universe, 10, 364.
https://doi.org/10.3390/universe10090364
11. Pishkalo M.I., Vasiljeva I.E. (2023). Prediction of maximum of solar cycle 25: total power at the cycle beginning and in the previous cycle as precursor. Kinemat. Phys. Celest. Bodies, 39(4), 225.
https://doi.org/10.3103/S0884591323040062
12. Rodríguez J.V., Carrasco V.M.S., Rodríguez-Rodríguez I., Aparicio A.J.P., Vaquero J.M. (2024). Predicting solar cycle 26 using the polar flux as a precursor, spectral analysis, and machine learning: crossing a Gleissberg minimum? Solar Phys., 299. 117.
https://doi.org/10.1007/s11207-024-02361-4
13. Thompson R.J. (1993). A technique for predicting the amplitude of the solar cycle. Solar Phys., 148(2), 383.
https://doi.org/10.1007/BF00645097
14. Yoshida A. (2014). Difference between even- and odd-numbered cycles in the predictability of solar activity and prediction of the amplitude of cycle 25. Ann. Geophys., 32, 1035-1042.
https://doi.org/10.5194/angeo-32-1035-2014
15. Zeng Sh., Zhu Sh., Huang Y., Zeng X., Zheng Sh., Deng L. (2025). Prediction of solar cycles 26 and 27 based on LSTM-FCN. New Astronomy, 117, 102353.
https://doi.org/10.1016/j.newast.2025.102353
16. Zermane M.A., Oulebsir N., Bekli M.R., Belhadi Z., Becheker K., Zaidi A., Hammou A.H. (2025). Magnitude prediction of solar cycle 26 using a new precursor approach. Solar Phys., 300, 53.
https://doi.org/10.1007/s11207-025-02459-3
17. Zharkova V.V., Vasilieva I., Popova E., Shepherd S.J. (2023) Comparison of solar activity proxies: eigenvectors versus averaged sunspot numbers. Mon. Not. Roy. Astron. Soc. 521, 6247-6265.
https://doi.org/10.1093/mnras/stad1001
12. Rodríguez J.V., Carrasco V.M.S., Rodríguez-Rodríguez I., Aparicio A.J.P., Vaquero J.M. (2024). Predicting solar cycle 26 using the polar flux as a precursor, spectral analysis, and machine learning: crossing a Gleissberg minimum? Solar Phys., 299. 117.
https://doi.org/10.1007/s11207-024-02361-4
13. Thompson R.J. (1993). A technique for predicting the amplitude of the solar cycle. Solar Phys., 148(2), 383.
https://doi.org/10.1007/BF00645097
14. Yoshida A. (2014). Difference between even- and odd-numbered cycles in the predictability of solar activity and prediction of the amplitude of cycle 25. Ann. Geophys., 32, 1035-1042.
https://doi.org/10.5194/angeo-32-1035-2014
15. Zeng Sh., Zhu Sh., Huang Y., Zeng X., Zheng Sh., Deng L. (2025). Prediction of solar cycles 26 and 27 based on LSTM-FCN. New Astronomy, 117, 102353.
https://doi.org/10.1016/j.newast.2025.102353
16. Zermane M.A., Oulebsir N., Bekli M.R., Belhadi Z., Becheker K., Zaidi A., Hammou A.H. (2025). Magnitude prediction of solar cycle 26 using a new precursor approach. Solar Phys., 300, 53.
https://doi.org/10.1007/s11207-025-02459-3
17. Zharkova V.V., Vasilieva I., Popova E., Shepherd S.J. (2023) Comparison of solar activity proxies: eigenvectors versus averaged sunspot numbers. Mon. Not. Roy. Astron. Soc. 521, 6247-6265.
https://doi.org/10.1093/mnras/stad1001