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Progress in Solar Cycle Predictions: Sunspot Cycles 24–25 in Perspective

Invited Review

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Abstract

The dynamic activity of the Sun—sustained by a magnetohydrodynamic dynamo mechanism working in its interior—modulates the electromagnetic, particulate, and radiative environment in space. While solar activity variations on short timescale create space weather, slow long-term modulation forms the basis of space climate. Space weather impacts diverse space-reliant technologies while space climate influences planetary atmospheres and climate. Having prior knowledge of the Sun’s activity is important in these contexts. However, forecasting solar-stellar magnetic activity has remained an outstanding challenge. In this review, predictions for Sunspot Cycle 24 and the upcoming Solar Cycle 25 are summarized, and critically assessed. The analysis demonstrates that while predictions based on diverse techniques disagree across Solar Cycles 24–25, physics-based predictions for Solar Cycle 25 have converged and indicates a weak to moderate–weak sunspot cycle. I argue that this convergence in physics-based predictions is indicative of progress in the fundamental understanding of solar cycle predictability. Based on this understanding, resolutions to several outstanding questions related to solar cycle predictions are discussed; these questions include: is it possible to predict the solar cycle, what is the best proxy for predictions, how early can we predict the solar cycle and how many cycles into the future can we predict relying on our current understanding? Based on our analysis, we also suggest a rigorous pathway towards generating and disseminating a “consensus forecast” by any solar cycle prediction panels tasked with such a challenge.

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References

  • Abdusamatov, K.I.: 2007, Optimal prediction of the peak of the next 11-year activity cycle and of the peaks of several succeeding cycles on the basis of long-term variations in the solar radius or solar constant. Kinemat. Phys. Celest. Bodies 23, 97. DOI.

    Article  ADS  Google Scholar 

  • Aguirre, L.A., Letellier, C., Maquet, J.: 2008, Forecasting the time series of sunspot numbers. Solar Phys. 249, 103. DOI.

    Article  ADS  Google Scholar 

  • Ahluwalia, H.S.: 2008, Development of solar activity cycle 24: Some comments. 37th COSPAR Scientific Assembly 37, 36.

    Google Scholar 

  • Attia, A.-F., Ismail, H.A., Basurah, H.M.: 2013, A Neuro-Fuzzy modeling for prediction of Solar Cycles 24 and 25. Astrophys. Space Sci. 344, 5. DOI.

    Article  ADS  Google Scholar 

  • Babcock, H.W.: 1961, The topology of the Sun’s magnetic field and the 22-YEAR cycle. Astrophys. J. 133, 572. DOI.

    Article  ADS  Google Scholar 

  • Babcock, H.W., Babcock, H.D.: 1955, The Sun’s magnetic field, 1952-1954. Astrophys. J. 121, 349. DOI.

    Article  ADS  Google Scholar 

  • Baranovski, A.L., Clette, F., Nollau, V.: 2008, Nonlinear solar cycle forecasting: Theory and perspectives. Ann. Geophys. 26, 231. DOI.

    Article  ADS  Google Scholar 

  • Bhowmik, P.: 2019, Polar flux imbalance at the sunspot cycle minimum governs hemispheric asymmetry in the following cycle. Astron. Astrophys. 632, A117. DOI.

    Article  ADS  Google Scholar 

  • Bhowmik, P., Nandy, D.: 2018, Prediction of the strength and timing of sunspot cycle 25 reveal decadal-scale space environmental conditions. Nat. Commun. 9, 5209. DOI.

    Article  ADS  Google Scholar 

  • Biesecker, D.: 2007, The Solar Cycle 24 Prediction Panel: 2007, Consensus statement of the solar cycle 24 prediction panel, released March 2007.

  • Brajša, R., Wöhl, H., Hanslmeier, A., Verbanac, G., Ruždjak, D., Cliver, E., Svalgaard, L., Roth, M.: 2009, On solar cycle predictions and reconstructions. Astron. Astrophys. 496, 855. DOI.

    Article  ADS  Google Scholar 

  • Brun, A.S., García, R.A., Houdek, G., Nandy, D., Pinsonneault, M.: 2015, The solar-stellar connection. Space Sci. Rev. 196, 303. DOI.

    Article  ADS  Google Scholar 

  • Bushby, P.J., Tobias, S.M.: 2007, On predicting the solar cycle using mean-field models. Astrophys. J. 661, 1289. DOI.

    Article  ADS  Google Scholar 

  • Cameron, R.H., Jiang, J., Schüssler, M.: 2016, Solar cycle 25: Another moderate cycle? Astrophys. J. Lett. 823, L22. DOI.

    Article  ADS  Google Scholar 

  • Cameron, R., Schüssler, M.: 2015, The crucial role of surface magnetic fields for the solar dynamo. Science 347, 1333. DOI.

    Article  ADS  Google Scholar 

  • Charbonneau, P.: 2020, Dynamo models of the solar cycle. Living Rev. Solar Phys. 17, 4. DOI.

    Article  ADS  Google Scholar 

  • Charvátová, I.: 2009, Long-term predictive assessments of solar and geomagnetic activities made on the basis of the close similarity between the solar inertial motions in the intervals 1840 1905 and 1980 2045. New Astron. 14, 25. DOI.

    Article  ADS  Google Scholar 

  • Chistyakov, V.F.: 1983, A forecast of solar activity till the year 2030. Bull. Soln. Dannye Akad. Nauk SSSR 1983, 97.

    ADS  Google Scholar 

  • Chopra, P., Dabas, R.S.: 2006, Prediction of maximum amplitude of the next Solar Cycle 24 using modified Precursor Method. 36th COSPAR Scientific Assembly 36, 909.

    Google Scholar 

  • Choudhuri, A.R., Chatterjee, P., Jiang, J.: 2007, Predicting solar cycle 24 with a solar dynamo model. Phys. Rev. Lett. 98, 131103. DOI.

    Article  ADS  Google Scholar 

  • Choudhuri, A.R., Schussler, M., Dikpati, M.: 1995, The solar dynamo with meridional circulation. Astron. Astrophys. 303, L29. ADS.

    ADS  Google Scholar 

  • Clette, F., Lefèvre, L.: 2016, The new sunspot number: Assembling all corrections. Solar Phys. 291, 2629. DOI.

    Article  ADS  Google Scholar 

  • Clette, F., Svalgaard, L., Vaquero, J.M., Cliver, E.W.: 2015, In: Balogh, A., Hudson, H., Petrovay, K., von Steiger, R. (eds.) Revisiting the Sunspot Number, Springer, New York, 35. ISBN 978-1-4939-2584-1. DOI.

    Chapter  Google Scholar 

  • Clilverd, M.A., Clarke, E., Ulich, T., Rishbeth, H., Jarvis, M.J.: 2006, Predicting Solar Cycle 24 and beyond. Space Weather 4, S09005. DOI.

    Article  ADS  Google Scholar 

  • Covas, E., Peixinho, N., Fernandes, J.: 2019, Neural network forecast of the sunspot butterfly diagram. Solar Phys. 294, 24. DOI.

    Article  ADS  Google Scholar 

  • Crosson, I.J., Binder, P.-M.: 2009, Chaos-based forecast of sunspot cycle 24. J. Geophys. Res. 114, A01108. DOI.

    Article  ADS  Google Scholar 

  • Dabas, R.S., Sharma, K., Das, R.M., Pillai, K.G.M., Chopra, P., Sethi, N.K.: 2008, A prediction of solar cycle 24 using a modified precursor method. Solar Phys. 250, 171. DOI.

    Article  ADS  Google Scholar 

  • Dani, T., Sulistiani, S.: 2019, Prediction of maximum amplitude of Solar Cycle 25 using machine learning. Journal of Physics Conf. Ser. 1231, 012022. DOI.

    Chapter  Google Scholar 

  • Das, S.B., Basak, A., Nandy, D., Vaidya, B.: 2019, Modeling star-planet interactions in far-out planetary and exoplanetary systems. Astrophys. J. 877, 80. DOI.

    Article  ADS  Google Scholar 

  • Dasi-Espuig, M., Solanki, S.K., Krivova, N.A., Cameron, R., Peñuela, T.: 2010, Sunspot group tilt angles and the strength of the solar cycle. Astron. Astrophys. 518, A7. DOI.

    Article  ADS  Google Scholar 

  • de Meyer, F.: 2003, A transfer function model for the sunspot cycle. Solar Phys. 217, 349. DOI.

    Article  ADS  Google Scholar 

  • Dikpati, M., Charbonneau, P.: 1999, A Babcock–Leighton flux transport dynamo with solar-like differential rotation. Astrophys. J. 518, 508. DOI.

    Article  ADS  Google Scholar 

  • Dikpati, M., de Toma, G., Gilman, P.A.: 2006, Predicting the strength of Solar Cycle 24 using a flux-transport dynamo-based tool. Geophys. Res. Lett. 33, L05102. DOI.

    Article  ADS  Google Scholar 

  • D’Silva, S., Choudhuri, A.R.: 1993, A theoretical model for tilts of bipolar magnetic regions. Astron. Astrophys. 272, 621.

    ADS  Google Scholar 

  • Du, Z., Du, S.: 2006, The relationship between the amplitude and descending time of a solar activity cycle. Solar Phys. 238, 431. DOI.

    Article  ADS  Google Scholar 

  • Du, Z.-L., Wang, H.-N., Zhang, L.-Y.: 2008, A running average method for predicting the size and length of a solar cycle. Chin. J. Astron. Astrophys. 8, 477. DOI.

    Article  ADS  Google Scholar 

  • Du, Z.L., Wang, H.N., He, H., Zhang, L.Y., Li, R., Cui, Y.M.: 2008, A summary of the applications of a weighted average method determining times of solar cycle extrema. Adv. Space Res. 42, 1457. DOI.

    Article  ADS  Google Scholar 

  • Duhau, S.: 2003, An early prediction of maximum sunspot number in solar cycle 24. Solar Phys. 213, 203. DOI.

    Article  ADS  Google Scholar 

  • Durney, B.R.: 1995, On a Babcock–Leighton dynamo model with a deep-seated generating layer for the toroidal magnetic field. Solar Phys. 160, 213. DOI.

    Article  ADS  Google Scholar 

  • Durney, B.R., De Young, D.S., Roxburgh, I.W.: 1993, On the generation of the largescale and turbulent magnetic fields in the solar type stars. Solar Phys. 145, 207. DOI.

    Article  ADS  Google Scholar 

  • Echer, E., Rigozo, N., Nordemann, D., Vieira, L.: 2004, Prediction of solar activity on the basis of spectral characteristics of sunspot number. Ann. Geophys. 22, 2239. DOI.

    Article  ADS  Google Scholar 

  • Euler, H.J., Smith, S.: 2006, Future solar activity estimates for use in prediction of space environmental effects on spacecraft orbital lifetime and performance. Technical report, NASA, Marshall Space Flight Center, quoted in Pesnell (2008).

  • Fan, Y., Fisher, G.H., Deluca, E.E.: 1993, The origin of morphological asymmetries in bipolar active regions. Astrophys. J. 405, 390. DOI.

    Article  ADS  Google Scholar 

  • Gholipour, A., Lucas, C., Araabi, B.N., Shafiee, M.: 2005, Solar activity forecast: Spectral analysis and neurofuzzy prediction. J. Atmos. Solar-Terr. Phys. 67, 595. DOI.

    Article  ADS  Google Scholar 

  • Gopalswamy, N., Mäkelä, P., Yashiro, S., Akiyama, S.: 2018, Long-term solar activity studies using microwave imaging observations and prediction for Solar Cycle 25. J. Atmos. Solar-Terr. Phys. 176, 26. DOI.

    Article  ADS  Google Scholar 

  • Hale, G.E.: 1908, On the probable existence of a magnetic field in Sun-spots. Astrophys. J. 28, 315. DOI.

    Article  ADS  Google Scholar 

  • Hale, G.E., Ellerman, F., Nicholson, S.B., Joy, A.H.: 1919, The magnetic polarity of Sun-spots. Astrophys. J. 49, 153. DOI.

    Article  ADS  Google Scholar 

  • Hamid, R.H., Galal, A.A.: 2006, Preliminary prediction of the strength of the 24th 11-year solar cycle. In: Bothmer, V., Hady, A.A. (eds.) Solar Activity and Its Magnetic Origin, IAU Symposium 233, 413. DOI.

    Chapter  Google Scholar 

  • Han, Y.B., Yin, Z.Q.: 2019, A decline phase modeling for the prediction of solar cycle 25. Solar Phys. 294, 107. DOI.

    Article  ADS  Google Scholar 

  • Hathaway, D.H.: 2015, The solar cycle. Living Rev. Solar Phys. 12, 4. DOI.

    Article  ADS  Google Scholar 

  • Hathaway, D.H., Wilson, R.M.: 2004, What the sunspot record tells us about space climate. Solar Phys. 224, 5. DOI.

    Article  ADS  Google Scholar 

  • Hathaway, D.H., Wilson, R.M.: 2006, Geomagnetic activity indicates large amplitude for sunspot cycle 24. Geophys. Res. Lett. 33, L18101. DOI.

    Article  ADS  Google Scholar 

  • Hawkes, G., Berger, M.A.: 2018, Magnetic helicity as a predictor of the solar cycle. Solar Phys. 293, 109. DOI.

    Article  ADS  Google Scholar 

  • Hazra, S., Brun, A.S., Nandy, D.: 2020, Does the mean-field \(\alpha \) effect have any impact on the memory of the solar cycle? Astron. Astrophys. 642, A51. DOI.

    Article  Google Scholar 

  • Hazra, G., Choudhuri, A.R.: 2019, A new formula for predicting solar cycles. Astrophys. J. 880, 113. DOI.

    Article  ADS  Google Scholar 

  • Hazra, S., Nandy, D.: 2016, A proposed paradigm for solar cycle dynamics mediated via turbulent pumping of magnetic flux in Babcock–Leighton-type solar dynamos. Astrophys. J. 832, 9. DOI.

    Article  ADS  Google Scholar 

  • Hazra, S., Nandy, D.: 2019, The origin of parity changes in the solar cycle. Mon. Not. Roy. Astron. Soc. 489, 4329. DOI.

    Article  ADS  Google Scholar 

  • Hazra, S., Passos, D., Nandy, D.: 2014, A stochastically forced time delay solar dynamo model: Self-consistent recovery from a maunder-like grand minimum necessitates a mean-field alpha effect. Astrophys. J. 789, 5. DOI.

    Article  ADS  Google Scholar 

  • Helal, H.R., Galal, A.A.: 2013, An early prediction of the maximum amplitude of the Solar Cycle 25. J. Adv. Res. 4, 275. DOI.

    Article  Google Scholar 

  • Hiremath, K.M.: 2008, Prediction of Solar Cycle 24 and beyond. Astrophys. Space Sci. 314, 45. DOI.

    Article  ADS  Google Scholar 

  • Horstman, M.: 2005, Varying solar flux models and their effect on the future debris environment projections. Orbital Debris Q. News 9, 4.

    Google Scholar 

  • Iijima, H., Hotta, H., Imada, S., Kusano, K., Shiota, D.: 2017, Improvement of solar-cycle prediction: Plateau of solar axial dipole moment. Astron. Astrophys. 607, L2. DOI.

    Article  ADS  Google Scholar 

  • Jain, R.: 2006, Prediction of the amplitude in sunspot cycle 24. 36th COSPAR Scientific Assembly 36, 642.

    Google Scholar 

  • Javaraiah, J.: 2007, North–South asymmetry in solar activity: Predicting the amplitude of the next solar cycle. Mon. Not. Roy. Astron. Soc. Lett. 377, L34. DOI.

    Article  ADS  Google Scholar 

  • Javaraiah, J.: 2008, Predicting the amplitude of a solar cycle using the North - South asymmetry in the previous cycle: II. An improved prediction for solar cycle 24. Solar Phys. 252, 419. DOI.

    Article  ADS  Google Scholar 

  • Javaraiah, J.: 2015, Long-term variations in the North-South asymmetry of solar activity and solar cycle prediction, III: Prediction for the amplitude of solar cycle 25. New Astron. 34, 54. DOI.

    Article  ADS  Google Scholar 

  • Jiang, J., Cameron, R.H., Schmitt, D., Isık, E.: 2013, Modeling solar cycles 15 to 21 using a flux transport dynamo. Astron. Astrophys. 553, A128. DOI.

    Article  ADS  Google Scholar 

  • Jiang, J., Hathaway, D.H., Cameron, R.H., Solanki, S.K., Gizon, L., Upton, L.: 2014, Magnetic flux transport at the solar surface. Space Sci. Rev. 186, 491. DOI.

    Article  ADS  Google Scholar 

  • Jiang, J., Wang, J.X., Jiao, Q.R., Cao, J.B.: 2018, Predictability of the solar cycle over one cycle. Astrophys. J. 863, 159. DOI.

    Article  ADS  Google Scholar 

  • Kakad, B., Kakad, A., Ramesh, D.S.: 2017, Shannon entropy-based prediction of solar cycle 25. Solar Phys. 292, 95. DOI.

    Article  ADS  Google Scholar 

  • Kakad, B., Kumar, R., Kakad, A.: 2020, Randomness in sunspot number: A clue to predict solar cycle 25. Solar Phys. 295, 88. DOI.

    Article  ADS  Google Scholar 

  • Kane, R.P.: 1999, Prediction of the sunspot maximum of Solar Cycle 23 by extrapolation of spectral components. Solar Phys. 189, 217. DOI.

    Article  ADS  Google Scholar 

  • Kane, R.P.: 2007a, A preliminary estimate of the size of the coming solar cycle 24, based on Ohl’s precursor method. Solar Phys. 243, 205. DOI.

    Article  ADS  Google Scholar 

  • Kane, R.P.: 2007b, Solar cycle predictions based on extrapolation of spectral components: An update. Solar Phys. 246, 487. DOI.

    Article  ADS  Google Scholar 

  • Kane, R.P.: 2008, How useful is the Waldmeier effect for prediction of a sunspot cycle? J. Atmos. Solar-Terr. Phys. 70, 1533. DOI.

    Article  ADS  Google Scholar 

  • Karak, B.B., Nandy, D.: 2012, Turbulent pumping of magnetic flux reduces solar cycle memory and thus impacts predictability of the Sun’s activity. Astrophys. J. Lett. 761, L13. DOI.

    Article  ADS  Google Scholar 

  • Kennewell, J., Patterson, G.: 2006, Prediction, quoted in Pesnell (2008).

  • Khramova, M.N., Krasotkin, S.A., Kononovich, E.V.: 2002, New aspects of solar activity forecast. In: Sawaya-Lacoste, H. (ed.) Solspa 2001, ESA SP-477, 229.

    Google Scholar 

  • Kilcik, A., Anderson, C.N.K., Rozelot, J.P., Ye, H., Sugihara, G., Ozguc, A.: 2009, Nonlinear prediction of solar cycle 24. Astrophys. J. 693, 1173. DOI.

    Article  ADS  Google Scholar 

  • Kim, M.Y., Wilson, J.W., Cucinotta, F.A.: 2006, A solar cycle statistical model for the projection of space radiation environment. Adv. Space Res. 37, 1741. DOI.

    Article  ADS  Google Scholar 

  • Kitiashvili, I.N.: 2020, Application of synoptic magnetograms to global solar activity forecast. Astrophys. J. 890, 36. DOI.

    Article  ADS  Google Scholar 

  • Kitiashvili, I., Kosovichev, A.G.: 2008, Application of data assimilation method for predicting solar cycles. Astrophys. J. 688, L49. DOI.

    Article  ADS  Google Scholar 

  • Kitiashvili, I., Kosovichev, A.G.: 2016, Data assimilation approach for forecast of solar activity cycles. Astrophys. J. 831, 15. DOI.

    Article  ADS  Google Scholar 

  • Kontor, N.N.: 2006, Statistics-based regular extrapolation, quoted in Pesnell (2008).

  • Kontor, N.N., Lyubimov, G.P., Pereslegina, N.V., Khotilovskaya, T.G.: 1984, A prediction of the sunspot maxima for solar cycles NN 22-44. Bull. Soln. Dannye Akad. Nauk SSSR 1983, 74.

    ADS  Google Scholar 

  • Krausmann, E., Andersson, E., Murtagh, W., Gibbs, M.: 2016, Space Weather & Critical Infrastructures: Findings and Outlook. DOI.

    Book  Google Scholar 

  • Kryachko, A.V., Nusinov, A.A.: 2008, Standard prediction of solar cycles. Geomagn. Aeron. 48, 145. DOI.

    Article  ADS  Google Scholar 

  • Kumar, R., Jouve, L., Nandy, D.: 2019, A 3D kinematic Babcock Leighton solar dynamo model sustained by dynamic magnetic buoyancy and flux transport processes. Astron. Astrophys. 623, A54. DOI.

    Article  ADS  Google Scholar 

  • Labonville, F., Charbonneau, P., Lemerle, A.: 2019, A dynamo-based forecast of solar cycle 25. Solar Phys. 294, 82. DOI.

    Article  ADS  Google Scholar 

  • Lantos, P.: 2005, Predictions of galactic cosmic ray intensity deduced from that of sunspot number. Solar Phys. 229, 373. DOI.

    Article  ADS  Google Scholar 

  • Leamon, R.J., McIntosh, S.W., Chapman, S.C., Watkins, N.W.: 2020, Timing terminators: Forecasting sunspot cycle 25 onset. Solar Phys. 295, 36. DOI.

    Article  ADS  Google Scholar 

  • Leighton, R.B.: 1969, A magneto-kinematic model of the solar cycle. Astrophys. J. 156, 1. DOI.

    Article  ADS  Google Scholar 

  • Lekshmi, B., Nandy, D., Antia, H.M.: 2018, Asymmetry in solar torsional oscillation and the sunspot cycle. Astrophys. J. 861, 121. DOI.

    Article  ADS  Google Scholar 

  • Lekshmi, B., Nandy, D., Antia, H.M.: 2019, Hemispheric asymmetry in meridional flow and the sunspot cycle. Mon. Not. Roy. Astron. Soc. 489, 714. DOI.

    Article  ADS  Google Scholar 

  • Lemerle, A., Charbonneau, P.: 2017, A coupled 2 × 2D Babcock–Leighton solar dynamo model. II. Reference dynamo solutions. Astrophys. J. 834, 133. DOI.

    Article  ADS  Google Scholar 

  • Li, K.J., Feng, W., Li, F.Y.: 2015, Predicting the maximum amplitude of Solar Cycle 25 and its timing. J. Atmos. Solar-Terr. Phys. 135, 72. DOI.

    Article  ADS  Google Scholar 

  • Li, F.Y., Kong, D.F., Xie, J.L., Xiang, N.B., Xu, J.C.: 2018, Solar cycle characteristics and their application in the prediction of cycle 25. J. Atmos. Solar-Terr. Phys. 181, 110. DOI.

    Article  ADS  Google Scholar 

  • Lorenz, E.N.: 1963, Deterministic nonperiodic flow. J. Atmos. Sci. 20, 130. DOI.

    Article  MathSciNet  MATH  ADS  Google Scholar 

  • Maris, G., Oncica, A.: 2006, Solar cycle 24 forecasts. Sun Geosph. 1, 8. https://www.researchgate.net/publication/228638413_Solar_Cycle_24_Forecasts.

    ADS  Google Scholar 

  • McIntosh, S.W., Chapman, S., Leamon, R.J., Egeland, R., Watkins, N.W.: 2020, Overlapping magnetic activity cycles and the sunspot number: Forecasting sunspot cycle 25 amplitude. Solar Phys. 295, 163. DOI.

    Article  ADS  Google Scholar 

  • Mininni, P.D., Gómez, D.O., Mindlin, G.B.: 2002, Biorthogonal decomposition techniques unveil the nature of the irregularities observed in the solar cycle. Phys. Rev. Lett. 89, 061101. DOI. ADS.

    Article  ADS  Google Scholar 

  • Mininni, P.D., López Fuentes, M., Mandrini, C.H., Gómez, D.O.: 2004, Study of bi-orthogonal modes in magnetic butterflies. Solar Phys. 219, 367. DOI. ADS.

    Article  ADS  Google Scholar 

  • Miyahara, V.: 2008, Prediction based on radiocarbon record, quoted in Pesnell (2008).

  • Muñoz-Jaramillo, A., Nandy, D., Martens, P.C.H.: 2009, Helioseismic data inclusion in solar dynamo models. Astrophys. J. 698, 461. DOI.

    Article  ADS  Google Scholar 

  • Muñoz-Jaramillo, A., Nandy, D., Martens, P.C.H.: 2010, Magnetic quenching of turbulent diffusivity: Reconciling mixing-length theory estimates with kinematic dynamo models of the solar cycle. Astrophys. J. 727, L23. DOI.

    Article  ADS  Google Scholar 

  • Muñoz-Jaramillo, A., Nandy, D., Martens, P.C.H., Yeates, A.R.: 2010, A double-ring algorithm for modeling solar active regions: Unifying kinematic dynamo models and surface flux transport simulations. Astrophys. J. 720, L20. DOI.

    Article  ADS  Google Scholar 

  • Muñoz-Jaramillo, A., Sheeley, N.R., Zhang, J., DeLuca, E.E.: 2012, Calibrating 100 years of polar faculae measurements: Implications for the evolution of the heliospheric magnetic field. Astrophys. J. 753, 146. DOI.

    Article  ADS  Google Scholar 

  • Mursula, K., Zieger, B., Vilppola, J.H.: 2003, Mid-term quasi-periodicities in geomagnetic activity during the last 15 solar cycles: Connection to solar dynamo strength to the memory of Karolen I. Paularena (1957-2001). Solar Phys. 212, 201. DOI.

    Article  ADS  Google Scholar 

  • Nagy, M., Lemerle, A., Labonville, F., Petrovay, K., Charbonneau, P.: 2017, The effect of “rogue” active regions on the solar cycle. Solar Phys. 292, 167. DOI.

    Article  ADS  Google Scholar 

  • Nandy, D.: 2002, Constraints on the solar internal magnetic field from a buoyancy driven solar dynamo. Astrophys. Space Sci. 282, 209. DOI.

    Article  ADS  Google Scholar 

  • Nandy, D.: 2004, Exploring magnetic activity from the Sun to the stars. Solar Phys. 224, 161. DOI.

    Article  ADS  Google Scholar 

  • Nandy, D., Choudhuri, A.R.: 2001, Toward a mean field formulation of the Babcock-Leighton type solar dynamo. I. \(\alpha \)-coefficient versus Durney’s double-ring approach. Astrophys. J. 551, 576. DOI.

    Article  Google Scholar 

  • Nandy, D., Choudhuri, A.R.: 2002, Explaining the latitudinal distribution of sunspots with deep meridional flow. Science 296, 1671. DOI.

    Article  ADS  Google Scholar 

  • Nandy, D., Martens, P.C.H.: 2007, Space Climate and the Solar Stellar connection: What can we learn from the stars about long-term solar variability? Adv. Space Res. 40, 891. DOI. ADS.

    Article  ADS  Google Scholar 

  • Nandy, D., Muñoz-Jaramillo, A., Martens, P.C.H.: 2011, The unusual minimum of sunspot cycle 23 caused by meridional plasma flow variations. Nature 471, 80. DOI. ADS.

    Article  ADS  Google Scholar 

  • National Research Council: 1997, Space Weather: A Research Perspective, The National Academies Press, Washington. DOI.

    Book  Google Scholar 

  • National Research Council: 2013, Solar and Space Physics: A Science for a Technological Society, The National Academies Press, Washington. ISBN 978-0-309-16428-3. DOI.

    Book  Google Scholar 

  • National Science and Technology Council: 2019, National Space Weather Strategy and Action Plan, The White House Office of Science and Technology, Washington. https://www.whitehouse.gov/wp-content/uploads/2019/03/National-Space-Weather-Strategy-and-Action-Plan-2019.pdf.

    Google Scholar 

  • Nevanlinna, H.: 2007, Geomagnetic precursor based on aa, quoted in Pesnell (2008).

  • Obridko, V.: 2008, Average of four separate precursor predictions, quoted in Pesnell (2008).

  • Okoh, D.I., Seemala, G.K., Rabiu, A.B., Uwamahoro, J., Habarulema, J.B., Aggarwal, M.: 2018, A Hybrid Regression-Neural Network (HR-NN) method for forecasting the solar activity. Space Weather 16, 1424. DOI.

    Article  ADS  Google Scholar 

  • Osherovich, V., Fainberg, J.: 2008, New method of solar maximum prediction with application to the next solar cycle. In: AGU Fall Meeting Abs. 2008, SH13A.

    Google Scholar 

  • Parker, E.N.: 1955a, Hydromagnetic dynamo models. Astrophys. J. 122, 293. DOI.

    Article  MathSciNet  ADS  Google Scholar 

  • Parker, E.N.: 1955b, The formation of sunspots from the solar toroidal field. Astrophys. J. 121, 491. DOI.

    Article  ADS  Google Scholar 

  • Passos, D., Nandy, D., Hazra, S., Lopes, I.: 2014, A solar dynamo model driven by mean-field alpha and Babcock–Leighton sources: Fluctuations, grand-minima-maxima, and hemispheric asymmetry in sunspot cycles. Astron. Astrophys. 563, A18. DOI.

    Article  ADS  Google Scholar 

  • Pesnell, W.D.: 2008, Predictions of Solar Cycle 24. Solar Phys. 252, 209. DOI.

    Article  ADS  Google Scholar 

  • Pesnell, W.D.: 2009, Predicting solar cycle 24 with geomagnetic precursors. AAS/Solar Phys. Div. Meet. 40, 11.05.

    Google Scholar 

  • Pesnell, W.D.: 2012, Solar cycle predictions (invited review). Solar Phys. 281, 507. DOI.

    Article  ADS  Google Scholar 

  • Pesnell, W.D., Schatten, K.H.: 2018, An early prediction of the amplitude of solar cycle 25. Solar Phys. 293, 112. DOI.

    Article  ADS  Google Scholar 

  • Pesnell, W.D., Thompson, B.J., Chamberlin, P.C.: 2012, The Solar Dynamics Observatory (SDO). Solar Phys. 275, 3. DOI.

    Article  ADS  Google Scholar 

  • Petrovay, K.: 2020, Solar cycle prediction. Living Rev. Solar Phys. 17, 2. DOI.

    Article  ADS  Google Scholar 

  • Petrovay, K., Nagy, M., Gerják, T., Juhász, L.: 2018, Precursors of an upcoming solar cycle at high latitudes from coronal green line data. J. Atmos. Solar-Terr. Phys. 176, 15. DOI.

    Article  ADS  Google Scholar 

  • Pishkalo, M.I.: 2008, Preliminary prediction of Solar Cycles 24 and 25 based on the correlation between cycle parameters. Kinemat. Phys. Celest. Bodies 24, 242. DOI.

    Article  ADS  Google Scholar 

  • Podladchikova, T., Lefebvre, B., Van der Linden, R.: 2008, Peak sunspot number for Solar Cycle 24, quoted in Pesnell (2008).

  • Prochasta, R.: 2006. Climatological prediction submitted to panel, quoted in Pesnell (2008).

  • Quassim, M.S., Attia, A.-F., Elminir, H.K.: 2007, Forecasting the peak amplitude of the 24th and 25th sunspot cycles and accompanying geomagnetic activity. Solar Phys. 243, 253. DOI.

    Article  ADS  Google Scholar 

  • Rabin, D.M.: 2007, Forecast of the amplitude of solar cycle 24 based on the disturbed days precursor. AAS Meet. Abs., 210, 92.05.

    Google Scholar 

  • Rigozo, N.R., Souza Echer, M.P., Evangelista, H., Nordemann, D.J.R., Echer, E.: 2011, Prediction of sunspot number amplitude and solar cycle length for cycles 24 and 25. J. Atmos. Solar-Terr. Phys. 73, 1294. DOI.

    Article  ADS  Google Scholar 

  • Roth, M.: 2006, Arma prediction of Solar Cycle 24, quoted in Pesnell (2008).

  • Sarp, V., Kilcik, A., Yurchyshyn, V., Rozelot, J.P., Ozguc, A.: 2018, Prediction of Solar Cycle 25: A non-linear approach. Mon. Not. Roy. Astron. Soc. 481, 2981. DOI.

    Article  ADS  Google Scholar 

  • Schatten, K.: 2005, Fair space weather for Solar Cycle 24. Geophys. Res. Lett. 32, L21106. DOI.

    Article  ADS  Google Scholar 

  • Scherrer, P.H., Schou, J., Bush, R.I., Kosovichev, A.G., Bogart, R.S., Hoeksema, J.T., Liu, Y., Duvall, T.L., Zhao, J., Title, A.M., Schrijver, C.J., Tarbell, T.D., Tomczyk, S.: 2012, The Helioseismic and Magnetic Imager (HMI) investigation for the Solar Dynamics Observatory (SDO). Solar Phys. 275, 207. DOI.

    Article  ADS  Google Scholar 

  • Schrijver, C.J., Kauristie, K., Aylward, A.D., Denardini, C.M., Gibson, S.E., Glover, A., Gopalswamy, N., Grande, M., Hapgood, M., Heynderickx, D., Jakowski, N., Kalegaev, V.V., Lapenta, G., Linker, J.A., Liu, S., Mandrini, C.H., Mann, I.R., Nagatsuma, T., Nandy, D., Obara, T., Paul O’Brien, T., Onsager, T., Opgenoorth, H.J., Terkildsen, M., Valladares, C.E., Vilmer, N.: 2015, Understanding space weather to shield society: A global road map for 2015-2025 commissioned by COSPAR and ILWS. Adv. Space Res. 55, 2745. DOI.

    Article  ADS  Google Scholar 

  • Sello, S.: 2003, Solar cycle activity: A preliminary prediction for cycle #24. Astron. Astrophys. 410, 691. DOI.

    Article  ADS  Google Scholar 

  • Sello, S.: 2019. Solar cycle activity: An early prediction for Solar Cycle 25. arXiv.

  • Shetye, J., Tripathi, D., Dikpati, M.: 2015, Observations and modeling of North-South asymmetries using a flux transport dynamo. Astrophys. J. 799, 220. DOI.

    Article  ADS  Google Scholar 

  • Singh, A.K., Bhargawa, A.: 2017, An early prediction of 25th solar cycle using Hurst exponent. Astrophys. Space Sci. 362, 199. DOI.

    Article  ADS  Google Scholar 

  • Solanki, S.K., Krivova, N.A.: 2003, Can solar variability explain global warming since 1970? J. Geophys. Res. 108, 1200. DOI.

    Article  Google Scholar 

  • Solanki, S.K., Usoskin, I.G., Kromer, B., Schüssler, M., Beer, J.: 2004, Unusual activity of the Sun during recent decades compared to the previous 11,000 years. Nature 431, 1084. DOI.

    Article  ADS  Google Scholar 

  • Svalgaard, L., Cliver, E.W., Kamide, Y.: 2005, Sunspot cycle 24: Smallest cycle in 100 years? Geophys. Res. Lett. 32. DOI.

  • Thompson, R.J.: 2008, Prediction for Solar Cycle 24 using minimum value of ap (12-month average), quoted in Pesnell (2008).

  • Tlatov, A.: 2006, Indices of solar activity minimum of sunspot cycles and prediction Solar Cycle 24, quoted in Pesnell (2008).

  • Tritakis, V., Mavromichalaki, H., Giouvanellis, G.: 2006, Prediction of basic elements of the forthcoming Solar Cycles 24 and 25 (years 2005–2027). AIP Conf. Proc. 848, 154. DOI.

    Article  ADS  Google Scholar 

  • Tsirulnik, L.B., Kuznetsova, T.V., Oraevsky, V.N.: 1997, Forecasting the 23rd and 24th solar cycles on the basis of MGM spectrum. Adv. Space Res. 20, 2369. DOI.

    Article  ADS  Google Scholar 

  • UNOOSA Space Weather: 2017, Special report of the inter-agency meeting on outer space activities on developments within the United Nations system related to space weather. http://www.unoosa.org/oosa/oosadoc/data/documents/2017/aac.105/aac.1051146_0.html.

  • Upton, L.A., Hathaway, D.H.: 2018, An updated solar cycle 25 prediction with AFT: The modern minimum. Geophys. Res. Lett. 45, 8091. DOI.

    Article  ADS  Google Scholar 

  • Usoskin, I.G.: 2017, A history of solar activity over millennia. Living Rev. Solar Phys. 14, 3. DOI.

    Article  ADS  Google Scholar 

  • Usoskin, I.G., Mursula, K., Solanki, S.K., Schüssler, M., Kovaltsov, G.A.: 2002, A physical reconstruction of cosmic ray intensity since 1610. J. Geophys. Res. 107, 1374. DOI.

    Article  Google Scholar 

  • Versteegh, G.J.M.: 2005, Solar forcing of climate. 2: Evidence from the past. Space Sci. Rev. 120, 243. DOI.

    Article  ADS  Google Scholar 

  • Wang, Y.M., Sheeley, N.R.: 2009, Understanding the geomagnetic precursor of the solar cycle. Astrophys. J. Lett. 694, L11. DOI.

    Article  ADS  Google Scholar 

  • Wang, J.L., Gong, J.C., Liu, S.Q., Le, G.-M., Sun, J.-L.: 2002, The prediction of maximum amplitudes of solar cycles and the maximum amplitude of solar cycle 24. Chin. J. Astron. Astrophys. 2, 557. DOI.

    Article  ADS  Google Scholar 

  • Wang, J.L., Zong, W.G., Le, G.M., Zhao, H.-J., Tang, Y.-Q., Zhang, Y.: 2009, Predicting the start and maximum amplitude of Solar Cycle 24 using similar phases and a cycle grouping. Res. Astron. Astrophys. 9, 133. DOI.

    Article  ADS  Google Scholar 

  • Watari, S.: 2008, Forecasting Solar Cycle 24 using the relationship between cycle length and maximum sunspot number. Space Weather 6, S12003. DOI.

    Article  ADS  Google Scholar 

  • Wilmot-Smith, A.L., Martens, P.C.H., Nandy, D., Priest, E.R., Tobias, S.M.: 2005, Low-order stellar dynamo models. Mon. Not. Roy. Astron. Soc. 363, 1167. DOI.

    Article  ADS  Google Scholar 

  • Wilmot-Smith, A.L., Nandy, D., Hornig, G., Martens, P.C.H.: 2006, A time delay model for solar and stellar dynamos. Astrophys. J. 652, 696. DOI.

    Article  ADS  Google Scholar 

  • Xu, T., Wu, J., Wu, Z.-S., Li, Q.: 2008, Long-term sunspot number prediction based on EMD analysis and AR model. Chin. J. Astron. Astrophys. 8, 337. DOI.

    Article  ADS  Google Scholar 

  • Yeates, A.R., Nandy, D., Mackay, D.H.: 2008, Exploring the physical basis of solar cycle predictions: Flux transport dynamics and persistence of memory in advection- versus diffusion-dominated solar convection zones. Astrophys. J. 673, 544. DOI.

    Article  ADS  Google Scholar 

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Acknowledgements

This review is dedicated to the memory of Bernard Durney who passed away in 2019 somewhere in the South of France, his last years spent in relative seclusion far away from the solar physics community. Bernard made fundamental contributions to the development of dynamo models of the solar cycle based on the Babcock–Leighton idea, including elucidating the role of meridional circulation in the near-surface evolution of the Sun’s large-scale dipolar magnetic fields. I first started corresponding with him as a PhD student from India and I am indebted to him for his generosity in sharing his knowledge and debating ideas with someone he had never met. In fact, although we corresponded for many years, I never got a chance to meet him in person. I am indebted to many of my students and collaborators who have contributed to my journey of exploring the physics of the sunspot cycle, particularly towards understanding the basis of solar cycle predictability. I am grateful to Soumyaranjan Dash and Shaonwita Pal for assistance with literature survey and preparation of some of the figures. I acknowledge utilization of data from the NASA/SDO HMI instrument maintained by the HMI team, the Royal Greenwich Observatory/USAF-NOAA active region database compiled by David H. Hathaway and MWO calibrated polar faculae data from the solar dynamo database maintained by Andrés Muñoz-Jaramillo. I acknowledge utilization of the hemispheric polar field data obtained by J. Todd Hoeksema and many dedicated graduate students at Stanford University’s Wilcox Solar Observatory. The Wilcox Solar Observatory is currently supported by NASA. I acknowledge usage of the yearly mean sunspot number data from the Solar Influences Data Analysis Centre (SILSO, Royal Observatory of Belgium, Brussels) and useful discussions with Frédéric Clette on the revised sunspot time series. Much of the understanding related to the solar magnetic cycle and its predictability has resulted from confronting theoretical dynamo models with these long-term solar activity databases and the continued sustenance of these databases cannot be overemphasized. This work benefited from discussions with colleagues under the aegis of the VarSITI Solar Evolution and Extrema program of SCOSTEP and the ISWAT cluster on Long-term Solar Variability under the aegis of COSPAR’s Panel on Space Weather. The Center of Excellence in Space Sciences India (CESSI) is funded by the Ministry of Education, Government of India, under the Frontier Areas of Science and Technology (FAST) scheme. Finally, I am grateful to the solar physics community of Argentina, its wonderful people and the beautiful music of tango, all a source of inspiration during my sabbatical visit to that country in connection with the 2019 total solar eclipse—during which the idea and early work for this review was initiated.

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Nandy, D. Progress in Solar Cycle Predictions: Sunspot Cycles 24–25 in Perspective. Sol Phys 296, 54 (2021). https://doi.org/10.1007/s11207-021-01797-2

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