Abstract
The rising rate [\(\beta _{\mathrm{a}}\)] of a solar cycle is a good indicator for the subsequent maximum amplitude [\(S_{\mathrm{m}}\)] of sunspot numbers. We compared the correlation between \(S_{\mathrm{m}}\) and \(\beta _{\mathrm{a}}\) and that between \(S_{\mathrm{m}}\) and the early value of the smoothed monthly mean sunspot number [\(S_{\mathrm{N}}\)] \(\Delta m\) months after the solar minimum. Our main conclusions are as follows: i) The correlation coefficient [\(r\)] between \(S_{\mathrm{m}}\) and \(S_{\mathrm{N}}\) is slightly higher than that between \(S_{\mathrm{m}}\) and \(\beta _{\mathrm{a}}\), and both increase with \(\Delta m\) as the cycle progresses; ii) In the first year of the cycle, the correlation is weak [\(r\sim \) 0.56]. At the inflection point [\(\Delta m=21\)], the correlation is stronger [\(r = 0.83\)]. After the inflection point, \(r\) increases slowly with \(\Delta m\). Three years after the solar minimum, \(r\geqslant 0.90\). Around the average rise time [52 months], \(r=0.95\); iii) The correlation between \(S_{\mathrm{m}}\) and \(S_{\mathrm{N}}\) (or \(\beta _{\mathrm{a}}\)) in even-numbered cycles is stronger than that in odd-numbered ones, and the latter is slightly weaker than that for all the cycles; iv) The mean relative error [\(\eta \)] of \(S_{\mathrm{m}}\) decreases and the MSE (Mean Square Error) skill score [\(S_{\mathrm{c}}\)] increases with \(\Delta m\). One, two, three, and four years after the solar minimum: \(\eta \leqslant 19\%\), \(14\%\), \(10\%\), and \(6.5\%\), \(S_{\mathrm{c}}\geqslant 0.24\), 0.68, 0.86, and 0.97, respectively; v) Currently [\(\Delta m=20\)], the maximum amplitude of Cycle 25 is predicted to be \(135.5\pm 33.2\) and to occur around December 2024 (± 11 months).
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Data Availability
The data can be downloaded from the Sunspot Index and Long-term Solar Observations (SILSO) website (wwwbis.sidc.be/silso/datafiles).
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The author is grateful to the anonymous reviewer for valuable suggestions that improved this manuscript.
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This work was supported by National Key R&D Program of China under grant 2021YFA1600504 and the National Science Foundation of China (NSFC) under grants 11873060 and 11973058.
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Appendices
Appendix A: Predicting \(S_{\mathrm{m}}\) of Cycle 24 Using the Sunspot Numbers of Version 1.0
As an example, we examine the predictive ability of the methods in this work and Du (2020b) on the maximum amplitude [\(S_{\mathrm{m}}\)] of Cycle 24 using the sunspot number series [\(S_{\mathrm{N}}\)] of Version V1.0. Du and Wang (2012) predicted \(S_{\mathrm{m}}\) for Cycle 24 [\(S_{\mathrm{p}}=S_{\mathrm{p}}(24)\)] by the rising rate [\(\beta _{\mathrm{a}}\), Equation 1]. The result is shown in Figure 6a (for \(\Delta m>0\)). In the original work, data were available only until February 2011 [\(\Delta m=27\)], and the result at \(\Delta m=27\) was \(r(\Delta m)=0.88\) and \(S_{\mathrm{p}}=84.0\) (marked with an asterisk in Figure 6a), slightly higher than the observed value [\(S_{\mathrm{m}}(24)=81.9\), the horizontal dash-dotted line]. Now, we extended the result to \(\Delta m=60\) months (four months before the peak timing of Cycle 24, April 2014). We see that with the increase of \(\Delta m\), the correlation coefficient [\(r( \Delta m)\), dotted] between \(S_{\mathrm{m}}\) and \(\beta _{\mathrm{a}}\) for Cycles 1 – 23 increases (if \(\Delta m\leqslant 50\)), and the predicted value [\(S_{\mathrm{p}}\), solid] decreases from 102.3 [with an error of \(\Delta S_{\mathrm{p}}=|S_{\mathrm{p}}-S_{\mathrm{m}}(24)|=20.4\), dashed] at \(\Delta m=1\) to 82.8 (\(\Delta S_{\mathrm{p}}= 0.9\)) at \(\Delta m=60\). There is a local peak, \(S_{\mathrm{p}}=96.0\) (\(\Delta S_{\mathrm{p}}=14.1\)) at \(\Delta m=32\), two (three) months earlier than the peak of Cycle 22 (3) and six months earlier than the secondary peak of Cycle 24 [66.9, February 2012]. If \(\Delta m>50\), \(r(\Delta m)\) may decrease. The mean absolute (relative) prediction error is \(\overline{\Delta S}_{\mathrm{p}}= 7.2\) (\(\overline{E}_{\mathrm{r}}=8.8\%\)) over \(\Delta m=[1, 60]\).
Du (2020b) analyzed the correlation between \(S_{\mathrm{m}}\) and the decrease rate [\(\beta _{\mathrm{d}}\)], calculated from the timing of solar minimum [\(t_{\mathrm{min}}\)] to \(\Delta m\) months earlier. They found that the correlation coefficient [\(r(\Delta m)\)] between \(S_{\mathrm{m}}\) and \(\beta _{\mathrm{d}}\) for Cycles 1 – 24 is the highest at \(\Delta m=-39\) months, using the sunspot numbers of Version 2.0. Now, we use the sunspot numbers of Version 1.0 to predict \(S_{\mathrm{m}}(24)\) by \(\beta _{\mathrm{d}}\), as shown in the left part of Figure 6a (for \(\Delta m<0\)). As \(\Delta m\) varies from −1 to −60, \(r(\Delta m)\) for Cycles 1 – 23 tends to increase (if \(\Delta m\geqslant -50\)) and the predicted value [\(S_{\mathrm{p}}\)] decreases from 109.3 (\(\Delta S_{\mathrm{p}}= 27.4\)) at \(\Delta m=-1\) to 58.0 (\(\Delta S_{\mathrm{p}}=23.9\)) at \(\Delta m=-60\). The correlation coefficient decreases if \(\Delta m<-50\) and may be negative if \(\Delta m<-58\). At \(\Delta m=-39\) months, \(r(-39)=0.78\), and \(S_{\mathrm{p}}=87.1\) (\(\Delta S_{\mathrm{p}}= 5.2\)). The mean prediction error is \(\overline{\Delta S}_{\mathrm{p}}= 10.3\) (\(\overline{E}_{\mathrm{r}}=12.6 \%\)) over \(\Delta m=[-1,-60]\).
Figure 6b shows the predicted \(S_{\mathrm{p}}(24)\) by the sunspot number [\(S_{\mathrm{N}}\)] at the preceding declining (\(\Delta m<0\)) and rising (\(\Delta m>0\)) phase \(\Delta m\) months from the solar minimum. As \(\Delta m\) increases from 1 to 60, the correlation coefficient [\(r( \Delta m)\)] between \(S_{\mathrm{m}}\) and \(S_{\mathrm{N}}(\Delta m)\) for Cycles 1 – 23 increases (if \(\Delta m\leqslant 50\)), and \(S_{\mathrm{p}}\) varies in the range [73.9, 93.0] with the largest prediction error [\(\Delta S_{\mathrm{p}}=11.1\)] at \(\Delta m=32\). As \(\Delta m\) varies from −1 to −60, \(r(\Delta m)\) tends to increase (if \(\Delta m\geqslant -50\)), and \(S_{\mathrm{p}}\) decreases from 87.0 (\(\Delta S_{\mathrm{p}}= 5.1\)) at \(\Delta m=-1\) to 58.3 (\(\Delta S_{\mathrm{p}}=23.6\)) at \(\Delta m=-60\). The correlation coefficient decreases if \(\Delta m<-50\) and may be negative if \(\Delta m<-58\). At \(\Delta m=-39\) months, \(r(-39)=0.79\) and \(S_{\mathrm{p}}=83.2\) (\(\Delta S_{\mathrm{p}}= 1.3\)). Over \(\Delta m=[1,60]\), the mean prediction error is \(\overline{\Delta S}_{\mathrm{p}}= 4.4\) (\(\overline{E}_{\mathrm{r}}=5.3\%\)), smaller than that, 7.2 (8.8%), using \(\beta _{\mathrm{a}}\) in Figure 6a. Over \(\Delta m=[-1,-60]\), the mean prediction error is \(\overline{\Delta S}_{\mathrm{p}}= 5.9\) (\(\overline{E}_{\mathrm{r}}=7.3\%\)), smaller than that, 10.3 (12.6%), using \(\beta _{\mathrm{d}}\) in Figure 6a.
In summary, the prediction error by the sunspot number [\(S_{\mathrm{N}}\)] is smaller than the one computed by the rate. The lowest correlation coefficient is around the solar minimum, \(r=0.16\) at \(\Delta m=-1\) for the rate and \(r=0.56\) at \(\Delta m=0\) for \(S_{\mathrm{N}}\). At the rising phase, \(r(\Delta m)\) increases with the increase of \(\Delta m\) and \(r(\Delta m)>0.75\) if \(\Delta m\geqslant 16\). At the declining phase, \(r(\Delta m)\) also tends to increase with the increase of \(|\Delta m|\) and \(r(\Delta m)>0.75\) if \(-52\leqslant \Delta m \leqslant -29\). The prediction error near the solar minimum tends to be larger than those computed at other \(\Delta m\) in the range [−50, 50].
Appendix B: Predicting \(S_{\mathrm{m}}\) of Cycle 24 Using the Sunspot Numbers of Version 2.0
Figure 7 shows the results obtained by using the sunspot numbers of Version 2.0 in a similar manner as was done in Figure 6.
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i)
Using the decrease (\(\Delta m<0\)) and rising (\(\Delta m>0\)) rate (Figure 7a), the lowest correlation coefficient for Cycles 1 – 23 is \(r(\Delta m)=0.19\) at \(\Delta m=3\), also close to the solar minimum in time. With the increase of \(|\Delta m|\), \(r(\Delta m)\) tends to increase and the prediction error [\(\Delta S_{\mathrm{p}}=|S_{\mathrm{p}}-S_{\mathrm{m}}(24)|\)] tends to decrease. \(r(\Delta m)>0.75\) if \(\Delta m\leqslant -30\) or \(\Delta m\geqslant 20\). The maximum prediction error is \(\Delta S_{\mathrm{p}}=61.1\) (\(E_{\mathrm{r}}=52.5\%\)) at \(\Delta m=1\). The mean prediction error is \(\overline{\Delta S}_{\mathrm{p}}= 24.7\) (\(\overline{E}_{\mathrm{r}}=21.2 \%\)) for \(\Delta m>0\) and \(\overline{\Delta S}_{\mathrm{p}}= 23.4\) (\(\overline{E}_{\mathrm{r}}=20.1\%\)) for \(\Delta m<0\). At \(\Delta m=-39\), \(r(-39)=0.80\) and \(\Delta S_{\mathrm{p}}=18.8\) (16.2%). At \(\Delta m=20\) (similar to the time for predicting Cycle 25), \(r(20)=0.77\), \(S_{\mathrm{p}}=132.2\) (asterisk), and \(\Delta S_{\mathrm{p}}=15.8\) (13.6%).
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ii)
Using the sunspot number at the declining (\(\Delta m<0\)) and rising (\(\Delta m>0\)) phase (Figure 7b), the lowest correlation coefficient for Cycles 1 – 23 is \(r(\Delta m)=0.51\) at \(\Delta m=9\). With the increase of \(|\Delta m|\), \(r(\Delta m)\) tends to increase and \(r(\Delta m)>0.75\) if \(\Delta m\leqslant -16\) or \(\Delta m\geqslant 18\). The mean prediction error is \(\overline{\Delta S}_{\mathrm{p}}= 14.4\) (\(\overline{E}_{\mathrm{r}}=12.3 \%\)) for \(\Delta m>0\) and \(\overline{\Delta S}_{\mathrm{p}}= 14.5\) (\(\overline{E}_{\mathrm{r}}=12.4\%\)) for \(\Delta m<0\). At \(\Delta m=-39\), \(r(-39)=0.80\) and \(\Delta S_{\mathrm{p}}=13.2\) (\(E_{\mathrm{r}}=11.3\%\)). For \(\Delta m>0\), the prediction error is minimum (maximum), \(\Delta S_{\mathrm{p}}=0.4\) (30.5), at \(\Delta m=51\) (31) and has a local minimum [6.4] at \(\Delta m=21\). At \(\Delta m=20\) (similar to the time for predicting Cycle 25), \(r(20)=0.81\), \(S_{\mathrm{p}}=123.2\) (asterisk), and \(\Delta S_{\mathrm{p}}=6.8\) (\(E_{\mathrm{r}}=5.8\%\)).
Using the sunspot number (Figure 7b), the correlation coefficient is slightly higher, and the prediction error tends to be smaller than that using either a decrease or rising rate (Figure 7a). Near the solar minimum, the correlation coefficient tends to be weaker, and the prediction error tends to be larger than those at other \(\Delta m\). The mean relative prediction error for Cycle 24 using the data of the new version is larger than that using the data from Version 2.0.
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Du, Z. Predicting the Maximum Amplitude of Solar Cycle 25 Using the Early Value of the Rising Phase. Sol Phys 297, 61 (2022). https://doi.org/10.1007/s11207-022-01991-w
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DOI: https://doi.org/10.1007/s11207-022-01991-w