Assessment of the amplitude of variations in total solar irradiance in the past

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Аннотация

An assessment was made of how reliably various modern reconstructions of total solar irradiance reconstruct long-term changes in this value in the past. To solve this problem, a forecast of long-term changes in total solar radiation in 1978−2017 was made using seven reconstructions covering the last 12−13 centuries. The paleoreconstructions used describe long-term variations with average amplitudes from 0.22 W m–2 (series with low amplitude) to 2.36 W m–2 (series with high amplitude). A nonlinear analog prediction method was applied, and the prediction results were compared with the actually measured values. It turned out that the experimentally measured variations in total solar radiation are better predicted by the low-amplitude reconstructions. However, the possibility that solar radiation in the past experienced more significant variations and the increase in total solar radiation after the Maunder Minimum reached 2.5 W m–2 cannot be completely excluded yet. Possible climatic consequences of such solar radiation variations are discussed.

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Авторлар туралы

М. Ogurtdov

Ioffe institute; Central Astronomical Observatory of the Russian Academy of Sciences at Pulkovo

Хат алмасуға жауапты Автор.
Email: maxim.ogurtsov@mail.ioffe.ru
Ресей, St. Petersburg; St. Petersburg

Әдебиет тізімі

  1. Bard E., Raisbeck G., Yiou F., Jouzel J. Solar irradiance during the last 1200 years based on cosmogenic nuclides // Tellus B. V. 52. № 3. P. 985−992. 2000. https://doi.org/10.1034/j.1600-0889.2000.d01-7.x
  2. Chatzistergos T., Krivova N.A., Yeo K.L. Long-term changes in solar activity and irradiance // J. Atmos. Sol.-Terr. Phy. V. 252. ID 106150. 2023. https://doi.org/10.1016/j.jastp.2023.106150
  3. Connolly R., Soon W., Connolly M. et al. How much has the Sun influenced Northern Hemisphere temperature trends? An ongoing debate // Res. Astron. Astrophys. V. 21. № 6. ID 131. 2021. https://doi.org/10.1088/1674-4527/21/6/131
  4. Delaygue G., Bard E. An Antarctic view of Beryllium-10 and solar activity for the past millennium // Clim. Dynam. V. 36. № 11. P. 2201−2218. 2011. https://doi.org/10.1007/s00382-010-0795-1
  5. Dewitte S., Cornelis J., Meftah M. Centennial total solar irradiance variation // Remote Sensing. V. 14. № 5. ID 1072. https://doi.org/10.3390/rs14051072.2022
  6. Dudok de Wit T., Kopp G., Fröhlich C., Schöll M. Methodology to create a new total solar irradiance record: making a composite out of multiple data records // Geophys. Res. Lett. V. 44. № 3. P. 1196−1203. 2017. https://doi.org/10.1002/2016GL071866
  7. Egorova T., Schmutz W., Rozanov E., Shapiro A.I., Usoskin I., Beer J., Tagirov R.V., Peter T. Revised historical solar irradiance forcing // Astron. Astrophys. V. 615. ID A85. 2018. https://doi.org/10.1051/0004-6361/201731199
  8. Farmer J.D., Sidorowich J. Predicting chaotic time series // Phys. Rev. Lett. V. 59. № 8. P. 845−848. 1987. https://doi.org/10.1103/PhysRevLett.59.845
  9. Gulev S.K., Thorne P.W., Ahn J. et al. Changing state of the climate system / Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Eds. P. Masson-Delmotte, V. Zhai, A. Pirani et al. Cambridge, UK and New York, NY, USA: Cambridge University Press. P. 287–422. 2021. https://doi.org/10.1017/9781009157896.004
  10. IPCC. 2014 / Climate Change 2014: Synthesis Report. Contribution of Working Groups I. II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Core Writing Team). Eds. R.K. Pachauri, L.A. Meyer. Geneva, Switzerland: IPCC, 151 p. 2014.
  11. IPCC. 2021- Summary for Policymakers / Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Eds. P. Masson-Delmotte, V. Zhai, A. Pirani et al. Cambridge, UK and New York, NY, USA: Cambridge University Press. P. 3−32. 2021. 10.1017/9781009157896.001' target='_blank'>https://doi: 10.1017/9781009157896.001
  12. Judge P.G., Lockwood G.W., Radick R.R., Henry G.W., Shapiro A.I., Schmutz W., Lindsey C. Confronting a solar irradiance reconstruction with solar and stellar data // Astron. Astrophys. V. 544. ID A88. 2012. https://doi.org/10.1051/0004-6361/201218903
  13. Jungclaus J.H., Bard E., Baroni M. et al. The PMIP4 contribution to CMIP6 – Part 3: The last millennium, scientific objective, and experimental design for the PMIP4 past1000 simulations // Geosci. Model Dev. V.10. № 11. P. 4005–4033. 2017. https://doi.org/10.5194/gmd-10-4005-2017
  14. Kopp G. Magnitudes and timescales of total solar irradiance variability // J. Space Weather Spac. V. 6. ID A30. 2016. https://doi.org/10.1051/swsc/2016025
  15. Lean J. Evolution of the Sun’s spectral irradiance Since the Maunder Minimum // Geophys. Res. Lett. V. 27. № 16. P. 2425−2428. 2000. https://doi.org/10.1029/2000GL000043
  16. Lean J.L., Coddington O., Marchenko S.V., Machol J., DeLand M.T., Kopp G. Solar irradiance variability: Modeling the measurements // Earth and Space Science. V. 7. № 8. ID e2019EA000645. 2020. https://doi.org/10.1029/2019EA000645
  17. Lockwood M., Ball W.T. Placing limits on long-term variations in quiet-Sun irradiance and their contribution to total solar irradiance and solar radiative forcing of climate // P. Roy. Soc. A. –Mat. Phy. V. 476. № 2238. ID 20200077. 2020. https://doi.org/10.1098/rspa.2020.0077
  18. Matthes K., Funke B., Anderson M. et al. Solar Forcing for CMIP6 (v3.2) // Geosci. Model Dev. V. 10. № 6. P. 2247−2302. 2017. https://doi.org/10.5194/gmd-10-2247-2017
  19. Montillet J.-P., Finsterle W., Kermarrec G., Sikonja R., Haberreiter M., Schmutz W., Dudok de Wit T. Data fusion of total solar irradiance composite time series using 41 years of satellite measurements // J. Geophys. Res. – Atmos. V. 127. № 13. ID e2021JD036146. 2022. https://doi.org/10.1029/2021JD036146
  20. Ogurtsov M. Prediction of cycle 24 based on information about solar activity during the last 10000 years // Geomagn. Aeronomy. V. 49. № 3. P. 408−411. 2009. https://doi.org/10.1134/S0016793209030165
  21. Ogurtsov M. New paleoclimatic evidence of an extraordinary rise in temperature in the Northern Hemisphere in the last 3−4 decades // Geogr. Ann. A. V. 104. № 4. P. 288−297. 2022. https://doi.org/10.1080/04353676.2022.2136454
  22. Penza V., Berrilli F., Bertello L., Cantoresi M., Criscuoli S., Giobbi P. Total solar irradiance during the last five centuries // Astrophys. J. V. 937. № 2. ID 84. 2022. https://doi.org/10.3847/1538-4357/ac8a4b
  23. Roth R., Joos F. A reconstruction of radiocarbon production and total solar irradiance from the Holocene 14C and CO2 records: Implications of data and model uncertainties // Clim. Past. V. 9. № 4. P. 1879−1909. 2013. https://doi.org/10.5194/cp-9-1879-2013
  24. Sarp V., Kilcik A., Yurchyshyn V., Rozelot J.P., Ozguc A. Prediction of solar cycle 25: A non-linear approach // Mon. Not. R. Astron. Soc. V. 481. № 3. P. 2981−2985. 2018. https://doi.org/10.1093/mnras/sty2470
  25. Shapiro A.I., Schmutz W., Rozanov E., Schoell M., Haberreiter M., Shapiro A.V., Nyeki S. A new approach to the long-term reconstruction of the solar irradiance leads to large historical solar forcing // Astron. Astrophys. V. 529. ID A67. 2011. https://doi.org/10.1051/0004-6361/201016173.
  26. Solanki S.K., Krivova N.A., Haigh J.D. Solar irradiance variability and climate // Annu. Rev. Astron. Astr. V. 51. № 1. P. 311−351. 2013. https://doi.org/10.1146/annurev-astro-082812-141007
  27. Steinhilber F., Abreu J.A., Beer J. et al. 9.400 years of cosmic radiation and solar activity from ice cores and tree rings // P. Natl. Acad. Sci. USA. V. 109. № 16. P. 5967−5971. 2012. https://doi.org/10.1073/pnas.1118965109
  28. Sugihara G., May R.M. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series // Nature. V. 344. № 6268. P. 734−741. 1990. https://doi.org/10.1038/344734a0
  29. Sugihara G. Nonlinear forecasting for the classification of natural time series // Phil. T. Roy. Soc. A. V. 348. № 1688. P. 477−495. 1994. https://doi.org/10.1098/rsta.1994.0106
  30. Wu C.-J., Krivova N.A., Solanki S.K., Usoskin I.G. Solar total and spectral irradiance reconstruction over the last 9000 year // Astron. Astrophys. V. 620. ID A120. 2018. https://doi.org/10.1051/0004-6361/201832956
  31. Yeo K.L., Solanki S.K., Krivova N.A., Rempel M., Anusha L.S., Shapiro A.I., Tagirov R.V., Witzke V. The dimmest state of the Sun // Geophys. Res. Lett. V. 47. № 19. ID e2020GL090243. 2020. https://doi.org/10.1029/2020GL090243

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Әрекет
1. JATS XML
2. Fig. 1. (a) - year-averaged composite data series of instrumentally measured TSI. Black line with full squares - unadjusted TSIDU series; gray line with full squares - adjusted TSIDC series; dashed line with empty squares - adjusted TSIPMOD series. (b) - decade-averaged data on instrumentally measured TSI. Black line with full squares is TSIDU, gray line with full squares is TSIDC, dashed line with empty squares is TSIPMOD.

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3. Fig. 2. TSI reconstructions normalized to the experimentally measured TSIDC series. (a) - Delaygue and Bard [2011]; (b) - Roth and Joos [2013]; (c) - Wu et al. [2018]; (d) - Steinhilber et al. [2012]; (e) - Bard et al. [2000]; (e) - Egorova et al. [2018], PHI-MC17; (g) - Shapiro et al. [2011].

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4. Fig. 3. (a) - correlation coefficient between the actually observed and predicted value calculated for the four solar reconstructions used in the paper; (b) - prediction error for these four reconstructions. The calculations were performed using the reconstructions of Steinhilber et al. [2012] (thin black line with full squares); Delaygue and Bard et al. [2011] (bold black line with empty circles); Roth and Joos [2013] (dashed black line with empty squares), Egorova et al. [2018] (dashed gray line with empty circles). Prediction errors were estimated using the uncertainties of the TSI reconstructions.

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5. Fig. 4.The actually observed TSIDC magnitude (gray line with full circles) and its predictions (black lines with empty circles) based on paleoreconstructions: (a) Wu et al.[2018]; (b) Steinhilber et al.[2012]; (c) Delaygue and Bard et al.[2011]; (d) Roth and Joos [2013]; (e) Bard et al. [2000]; (f) Shapiro et al.[2011]; (g) Egorova et al.[2018].

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6. Fig. 5.Dependence of nonlinear prediction quality on STD for different paleoreconstructions.(a) - prediction error made for TSIDU; (b) - probability of P2 prediction made for TSIDU; (c) - prediction error made for TSIDU; (d) - probability of P2 prediction made for TSIDU; (e) - prediction error made for TSIPMOD; (f) - probability of P2 prediction made for TSIPMOD.

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