Abstract
In this chapter we discuss several methods for forecasting solar activity on different time scales. The solar radiation and particle emission influences on the space around Earth, the Earth’s magnetosphere, the Earth’s atmosphere, and can be harmful for satellites and manned spacecraft missions and disrupt communication systems. In extreme cases even power lines on the Earth’s surface are perturbed or can become disrupted.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
There are also other influences that contribute to space climate such as our galactic neighborhood.
- 2.
Geostationary Operational Environmental Satellite
- 3.
Active Cavity Radiometer Irradiance Monitor (ACRIM) space flight experiment.
- 4.
Launched Feb. 11, 2010.
- 5.
Form: jsocs.stanford.edu.
- 6.
Brajsa, R., Verbanac, G., Bandic, M., Hanslmeier, A., Skokic, I., and Sudar, D. On the minimum - maximum method for prediction of the solar cycle amplitude, submitted to Astronomy and Astrophysics, 2020.
- 7.
Launch: 2006.
References
Bain H, Onsager T, Balch C, Steenburgh R, Carr C, Biesecker D, Adamson E (2019) Solar energetic particle forecasting: current capabilities and future directions from a NOAA space weather prediction center perspective. In: Solar heliospheric and interplanetary environment (SHINE 2019), p 239
Reikard G (2018) Forecasting space weather over short horizons: revised and updated estimates 62:62–69
Krivova NA, Vieira LEA, Solanki SK (2010) Reconstruction of solar spectral irradiance since the Maunder minimum. J Geophys Res (Space Phys) 115(A12):A12112
Feigelson ED, Babu GJ, Caceres GA (2018) Autoregressive times series methods for time domain astronomy. Frontiers Phys 6:80
Bobra MG, Hoeksema JT, Sun X, HMI Magnetic Field Team (2011) SHARP: space-weather HMI active region patches. In: SDO-3: solar dynamics and magnetism from the interior to the atmosphere, p 17
Gleissberg W (1962) Untersuchungen an drei achizigjährigen Zyklen der Sonnentätigkeit. Mit 3 Textabbildungen 55:153
Frick P, Galyagin D, Hoyt DV, Nesme-Ribes E, Schatten KH, Sokoloff D, Zakharov V (1997) Wavelet analysis of solar activity recorded by sunspot groups. Astron Astrophys 328:670–681
Wilson OC (1978) Chromospheric variations in main-sequence stars. Astrophys J 226:379–396
Frick P, Baliunas SL, Galyagin D, Sokoloff D, Soon W (1997) Wavelet analysis of stellar chromospheric activity variations. Astrophys J 483(1):426–434
Saar SH, Brandenburg A (1998) Time evolution of the magnetic activity cycle period: results for an expanded stellar sample. In: American astronomical society meeting abstracts. American astronomical society meeting abstracts, vol 193, p 44.04
Wright NJ, Newton ER, Williams PKG, Drake JJ, Yadav RK (2018) The stellar rotation-activity relationship in fully convective M dwarfs. Mon Notices 479(2):2351–2360
Guinan EF, Ribas I (2002) Our changing sun: the role of solar nuclear evolution and magnetic activity on earth’s atmosphere and climate. In: Montesinos B, Gimenez A, Guinan EF (eds) The evolving sun and its influence on planetary environments. Astronomical society of the pacific conference series, vol 269, p 85
Schrijver JC, Siscoe GL (2010) Evolving Solar Activity and the Climates of Space and Earth. Heliophysics
Benestad RE (2006) Solar activity and earth’s climate, 2nd ed
Rozelot JP (1995) On the chaotic behaviour of the solar activity. Astron Astrophys 297:L45
Gleissberg W (1951) A forecast of solar activity. J Geophys Res 56:292
Tlatov AG (2009) The minimum activity epoch as a precursor of the solar activity. Solar Phys 260(2):465–477
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(3):855–861
Weiss NO, Cattaneo F, Jones CA (1984) Periodic and aperiodic dynamo waves. Geophys Astrophys Fluid Dyn 30(4):305–341
Benson B, Pan WD, Prasad A, Gary GA, Hu Q (2020) Forecasting solar cycle 25 using deep neural networks. Solar Phys 295(5):65
Kennel MB, Brown R, Abarbanel HDI (1992) Determining embedding dimension for phase-space reconstruction using a geometrical construction 45(6):3403–3411
Grassberger P, Procaccia I (1983) Measuring the strangeness of strange attractors. Phys D Nonlinear Phenom 9(1–2):189–208
Hanslmeier A, Brajša R (2010) The chaotic solar cycle. I. Analysis of cosmogenic \(^{14}\)C-data. Astron Astrophys, 509:A5
Kurths J, Ruzmaikin AA (1990) On forecasting the sunspot numbers. Solar Phys 126(2):407–410
Calvo RA, Ceccato HA, Piacentini RD (1995) Neural network prediction of solar activity. Astrophys J 444:916
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Hanslmeier, A. (2020). Solar Cycle Forecasting. In: The Chaotic Solar Cycle. Atmosphere, Earth, Ocean & Space. Springer, Singapore. https://doi.org/10.1007/978-981-15-9821-0_9
Download citation
DOI: https://doi.org/10.1007/978-981-15-9821-0_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9820-3
Online ISBN: 978-981-15-9821-0
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)