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Muted multidecadal climate variability in central Europe during cold stadial periods


During the last ice age, the Northern Hemisphere experienced a series of abrupt millennial-scale climatic changes linked to variations in the strength of the Atlantic Meridional Overturning Circulation and sea-ice extent. However, our understanding of their impacts on decadal-scale climate variability in central Europe has been limited by the lack of high-resolution continental archives. Here, we present a near annual-resolution climate proxy record of central European temperature reconstructed from the Eifel maar lakes of Holzmaar and Auel in Germany, spanning the past 60,000 years. The lake sediments reveal a series of previously undocumented multidecadal climate cycles of around 20 to 150 years that persisted through the last glacial cycle. The periodicity of these cycles suggests that they are related to the Atlantic multidecadal climate oscillations found in the instrumental record and in other climate archives during the Holocene. Our record shows that multidecadal variability in central Europe was strong during all warm interstadials, but was substantially muted during all cold stadial periods. We suggest that this decrease in multidecadal variability was the result of the atmospheric circulation changes associated with the weakening of the Atlantic Meridional Overturning Circulation and the expansion of North Atlantic sea-ice cover during the coldest parts of the last ice age.

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Fig. 1: Location of the Auel Maar with respect to modern climatology.
Fig. 2: Temperature changes in Greenland and central Europe over the past 60,000 years.
Fig. 3: Reduced high-frequency climate variability in central Europe during the coldest parts of the last ice age.
Fig. 4: Evolution of decadal- to centennial-scale climate cycles across the stadial/interstadial events of the last ice age.
Fig. 5: Lomb–Scargle spectra for selected times of the Holocene, interstadial GI3 and Heinrich 3.

Data availability

The ELSA-20 data are available in the Supplementary Information and the PANGAEA data repository ( More information on ELSA is accessible from the ELSA webpage ( Source data are provided with this paper.


  1. 1.

    North Greenland Ice Core Project Members. High-resolution record of Northern Hemisphere climate extending into the last interglacial period. Nature 431, 147–151 (2004).

    Article  Google Scholar 

  2. 2.

    Böhm, E. et al. Strong and deep Atlantic meridional overturning circulation during the last glacial cycle. Nature 517, 73–76 (2015).

    Article  Google Scholar 

  3. 3.

    Rahmstorf, S. Ocean circulation and climate during the past 120,000 years. Nature 419, 207–214 (2002).

    Article  Google Scholar 

  4. 4.

    Li, C. & Born, A. Coupled atmosphere–ice–ocean dynamics in Dansgaard–Oeschger events. Quat. Sci. Rev. 203, 1–20 (2019).

    Article  Google Scholar 

  5. 5.

    Sadatzki, H. et al. Sea ice variability in the southern Norwegian sea during glacial Dansgaard–Oeschger climate cycles. Sci. Adv. 5, eaau6174 (2019).

    Article  Google Scholar 

  6. 6.

    Martrat, B. et al. Four climate cycles of recurring deep and surface water destabilizations on the Iberian margin. Science 317, 502–507 (2007).

    Article  Google Scholar 

  7. 7.

    Peterson, L. C., Haug, G. H., Hughen, K. A. & Röhl, U. Rapid changes in the hydrologic cycle of the tropical Atlantic during the last glacial. Science 290, 1947–1951 (2000).

    Article  Google Scholar 

  8. 8.

    Deplazes, G. et al. Links between tropical rainfall and North Atlantic climate during the last glacial period. Nat. Geosci. 6, 213–217 (2013).

    Article  Google Scholar 

  9. 9.

    Fleitmann, D. et al. Timing and climatic impact of Greenland interstadials recorded in stalagmites from northern Turkey. Geophys. Res. Lett. 36, L19707 (2009).

    Article  Google Scholar 

  10. 10.

    Cheng, H. et al. The Asian monsoon over the past 640,000 years and ice age terminations. Nature 534, 640–646 (2016).

    Article  Google Scholar 

  11. 11.

    Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G. & Saba, V. Observed fingerprint of a weakening Atlantic Ocean overturning circulation. Nature 556, 191–196 (2018).

    Article  Google Scholar 

  12. 12.

    Thornalley, D. J. R. et al. Anomalously weak Labrador Sea convection and Atlantic overturning during the past 150 years. Nature 556, 227–230 (2018).

    Article  Google Scholar 

  13. 13.

    Srokosz, M. A. & Bryden, H. L. Observing the Atlantic meridional overturning circulation yields a decade of inevitable surprises. Science 348, 1255575 (2015).

    Article  Google Scholar 

  14. 14.

    Sirocko, F. et al. Multi-proxy dating of Holocene maar lakes and Pleistocene dry maar sediments in the Eifel, Germany. Quat. Sci. Rev. 62, 56–76 (2013).

    Article  Google Scholar 

  15. 15.

    Sirocko, F. et al. The ELSA-vegetation-stack: reconstruction of landscape evolution zones (LEZ) from laminated Eifel maar sediments of the last 60,000 years. Glob. Planet. Change 142, 108–135 (2016).

    Article  Google Scholar 

  16. 16.

    Rein, B. & Sirocko, F. In-situ reflectance spectroscopy—analyzing techniques for high resolution pigment logging in sediment cores. Int. J. Earth Sci. 91, 950–954 (2002).

    Article  Google Scholar 

  17. 17.

    Rasmussen, S. O. et al. A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy. Quat. Sci. Rev. 106, 14–28 (2014).

    Article  Google Scholar 

  18. 18.

    Lücke, A., Schleser, G. H., Zolitschka, B. & Negendank, J. F. W. A Late-glacial and Holocene organic carbon isotope record of lacustrine palaeoproductivity and climatic change derived from varved lake sediments of Lake Holzmaar, Germany. Quat. Sci. Rev. 22, 569–580 (2003).

    Article  Google Scholar 

  19. 19.

    Brüchmann, C. & Negendank, J. F. W. Indication of climatically induced natural eutrophication during the early Holocene period, based on annually laminated sediment from Lake Holzmaar, Germany. Quat. Int. 123–125, 117–134 (2004).

    Article  Google Scholar 

  20. 20.

    Li, C., Battisti, D. S. & Bitz, C. M. Can North Atlantic sea ice anomalies account for Dansgaard–Oeschger climate signals? J. Clim. 23, 5457–5475 (2010).

    Article  Google Scholar 

  21. 21.

    Masson-Delmotte, V. GRIP deuterium excess reveals rapid and orbital-scale changes in Greenland moisture origin. Science 309, 118–121 (2005).

    Article  Google Scholar 

  22. 22.

    Sánchez Goñi, M. F., Landais, A., Cacho, I., Duprat, J. & Rossignol, L. Contrasting intrainterstadial climatic evolution between high and middle North Atlantic latitudes: a close‐up of Greenland Interstadials 8 and 12. Geochem. Geophys. Geosyst. 10, 1–16 (2009).

    Article  Google Scholar 

  23. 23.

    Van Kreveld, S. et al. Potential links between surging ice sheets, circulation changes and the Daansgaard–Oeschger cycles in the Irminger Sea, 60–18 kyr. Paleoceanography 15, 425–442 (2004).

    Article  Google Scholar 

  24. 24.

    Mudelsee, M. Climate Time Series Analysis: Classical Statistical and Bootstrap Methods (Springer International Publishing, 2014).

  25. 25.

    Schlesinger, M. E. & Ramankutty, N. An oscillation in the global climate system of period 65–70 years. Nature 367, 723–726 (1994).

    Article  Google Scholar 

  26. 26.

    Mann, M. E., Park, J. & Bradley, R. S. Global interdecadal and century-scale climate oscillations during the past five centuries. Nature 378, 266–270 (1995).

    Article  Google Scholar 

  27. 27.

    Fleitmann, D. et al. Holocene forcing of the Indian monsoon recorded in a stalagmite from southern Oman. Science 300, 1737–1739 (2003).

    Article  Google Scholar 

  28. 28.

    Knudsen, M. F., Seidenkrantz, M.-S., Jacobsen, B. H. & Kuijpers, A. Tracking the Atlantic multidecadal oscillation through the last 8,000 years. Nat. Commun. 2, 178 (2011).

    Article  Google Scholar 

  29. 29.

    Hodell, D. A., Curtis, J. H. & Brenner, M. Possible role of climate in the collapse of Classic Maya civilization. Nature 375, 391–394 (1995).

    Article  Google Scholar 

  30. 30.

    Haug, G. H., Hughen, K., Sigman, D. M., Peterson, L. C. & Röhl, U. Southward migration of the intertropical convergence zone through the holocene. Science 293, 1304–1308 (2001).

    Article  Google Scholar 

  31. 31.

    Kerr, R. A. A North Atlantic climate pacemaker for the centuries. Science 288, 1984–1985 (2000).

    Article  Google Scholar 

  32. 32.

    Sutton, R. T. & Hodson, D. L. R. Atlantic Ocean forcing of North American and European summer climate. Science 309, 115–118 (2005).

    Article  Google Scholar 

  33. 33.

    Zhang, R. et al. A review of the role of the Atlantic meridional overturning circulation in Atlantic multidecadal variability and associated climate impacts. Rev. Geophys. 57, 316–375 (2019).

    Article  Google Scholar 

  34. 34.

    Goldenberg, S. B., Landsea, C. W., Mestas-Nuñez, A. M. & Gray, W. M. The recent increase in Atlantic hurricane activity: causes and implications. Science 293, 474–479 (2001).

    Article  Google Scholar 

  35. 35.

    Knight, J. R., Folland, C. K. & Scaife, A. A. Climate impacts of the Atlantic multidecadal oscillation. Geophys. Res. Lett. 33, L02706 (2006).

    Article  Google Scholar 

  36. 36.

    Levine, A. F. Z., McPhaden, M. J. & Frierson, D. M. W. The impact of the AMO on multidecadal ENSO variability. Geophys. Res. Lett. 44, 3877–3886 (2017).

    Article  Google Scholar 

  37. 37.

    Dong, B., Sutton, R. T. & Scaife, A. A. Multidecadal modulation of El Niño–Southern Oscillation (ENSO) variance by Atlantic Ocean sea surface temperatures. Geophys. Res. Lett. 33, 286 (2006).

    Google Scholar 

  38. 38.

    Li, F., Orsolini, Y. J., Wang, H., Gao, Y. & He, S. Atlantic multidecadal oscillation modulates the impacts of Arctic sea ice decline. Geophys. Res. Lett. 45, 2497–2506 (2018).

    Article  Google Scholar 

  39. 39.

    Lean, J. L. in Oxford Research Encyclopedia of Climate Science (Oxford Univ. Press, 2017);

  40. 40.

    Steinhilber, F. et al. 9,400 years of cosmic radiation and solar activity from ice cores and tree rings. Proc. Natl Acad. Sci. USA 109, 5967–5971 (2012).

    Article  Google Scholar 

  41. 41.

    Wang, Y. et al. The Holocene Asian monsoon: links to solar changes and North Atlantic climate. Science 308, 854–857 (2005).

    Article  Google Scholar 

  42. 42.

    Seidenglanz, A., Prange, M., Varma, V. & Schulz, M. Ocean temperature response to idealized Gleissberg and de Vries solar cycles in a comprehensive climate model. Geophys. Res. Lett. 39, L22602 (2012).

    Article  Google Scholar 

  43. 43.

    Otterå, O. H., Bentsen, M., Drange, H. & Suo, L. External forcing as a metronome for Atlantic multidecadal variability. Nat. Geosci. 3, 688–694 (2010).

    Article  Google Scholar 

  44. 44.

    Knight, J. R., Allan, R. J., Folland, C. K., Vellinga, M. & Mann, M. E. A signature of persistent natural thermohaline circulation cycles in observed climate. Geophys. Res. Lett. 32, L20708 (2005).

    Article  Google Scholar 

  45. 45.

    Muscheler, R., Beer, J., Kubik, P. W. & Synal, H.-A. Geomagnetic field intensity during the last 60,000 years based on 10Be and 36Cl from the Summit ice cores and 14C. Quat. Sci. Rev. 24, 1849–1860 (2005).

    Article  Google Scholar 

  46. 46.

    Wagner, G. et al. Presence of the solar de Vries cycle (205 years) during the last Ice Age. Geophys. Res. Lett. 28, 303–306 (2001).

    Article  Google Scholar 

  47. 47.

    Muscheler, R. & Beer, J. Solar forced Dansgaard/Oeschger events? Geophys. Res. Lett. 33, L20706 (2006).

    Article  Google Scholar 

  48. 48.

    Justino, F. & Peltier, W. R. The glacial North Atlantic oscillation. Geophys. Res. Lett. 32, L21803 (2005).

    Article  Google Scholar 

  49. 49.

    Pausata, F. S. R., Li, C., Wettstein, J. J., Kageyama, M. & Nisancioglu, K. H. The key role of topography in altering North Atlantic atmospheric circulation during the last glacial period. Clim. Past 7, 1089–1101 (2011).

    Article  Google Scholar 

  50. 50.

    Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).

    Article  Google Scholar 

  51. 51.

    Förster, M. W., Zemlitskaya, A., Otter, L., Buhre, S. & Sirocko, F. Late Pleistocene Eifel eruptions: insights from clinopyroxene and glass geochemistry of tephra layers from Eifel Laminated Sediment Archive sediment cores. J. Quat. Sci. 35, 186–198 (2019).

    Article  Google Scholar 

  52. 52.

    Büchel, G. Vulkanologische Karte der West- und Hocheifel (Landesvermessungsamt Rheinland-Pfalz, 1994).

  53. 53.

    Sirocko, F. et al. A late Eemian aridity pulse in central Europe during the last glacial inception. Nature 436, 833–836 (2005).

    Article  Google Scholar 

  54. 54.

    Förster, M. W. & Sirocko, F. The ELSA tephra stack: volcanic activity in the Eifel during the last 500,000 years. Glob. Planet. Change 142, 100–107 (2016).

    Article  Google Scholar 

  55. 55.

    Butz, C. et al. Hyperspectral imaging spectroscopy: a promising method for the biogeochemical analysis of lake sediments. J. Appl. Remote Sens. 9, 096031 (2015).

    Article  Google Scholar 

  56. 56.

    Michelutti, N. & Smol, J. P. Visible spectroscopy reliably tracks trends in paleo-production. J. Paleolimnol. 56, 253–265 (2016).

    Article  Google Scholar 

  57. 57.

    Sanchini, A. & Grosjean, M. Quantification of chlorophyll a, chlorophyll b and pheopigments a in lake sediments through deconvolution of bulk UV-VIS absorption spectra. J. Paleolimnol. 64, 243–256 (2020).

    Article  Google Scholar 

  58. 58.

    Louda, J. W. & Baker, E. W. in Organic Marine Geochemistry Vol. 305 (ed. Sohn, M. L.) 107–126 (American Chemical Society, 1986).

  59. 59.

    Rosell-Melé, A., Maslin, M. A., Maxwell, J. R. & Schaeffer, P. Biomarker evidence for ‘Heinrich’ events. Geochim. Cosmochim. Acta 61, 1671–1678 (1997).

    Article  Google Scholar 

  60. 60.

    Das, B., Vinebrooke, R. D., Sanchez-Azofeifa, A., Rivard, B. & Wolfe, A. P. Inferring sedimentary chlorophyll concentrations with reflectance spectroscopy: a novel approach to reconstructing historical changes in the trophic status of mountain lakes. Can. J. Fish. Aquat. Sci. 62, 1067–1078 (2005).

    Article  Google Scholar 

  61. 61.

    Méléder, V., Jesus, B., Barnett, A., Barillé, L. & Lavaud, J. Microphytobenthos primary production estimated by hyperspectral reflectance. PLoS ONE 13, e0197093 (2018).

    Article  Google Scholar 

  62. 62.

    Wolfe, A. P., Vinebrooke, R. D., Michelutti, N., Rivard, B. & Das, B. Experimental calibration of lake-sediment spectral reflectance to chlorophyll a concentrations: methodology and paleolimnological validation. J. Paleolimnol. 36, 91–100 (2006).

    Article  Google Scholar 

  63. 63.

    Blackburn, G. A. Hyperspectral remote sensing of plant pigments. J. Exp. Bot. 58, 855–867 (2007).

    Article  Google Scholar 

  64. 64.

    Richter, T. O. et al. The Avaatech XRF Core Scanner: technical description and applications to NE Atlantic sediments. Geol. Soc. Lond. Spec. Publ. 267, 39–50 (2006).

    Article  Google Scholar 

  65. 65.

    Hajdas, I. et al. AMS radiocarbon dating of annually laminated sediments from Lake Holzmaar, Germany. Quat. Sci. Rev. 14, 137–143 (1995).

    Article  Google Scholar 

  66. 66.

    Litt, T., Schölzel, C., Kühl, N. & Brauer, A. Vegetation and climate history in the Westeifel Volcanic Field (Germany) during the past 11,000 years based on annually laminated lacustrine maar sediments. Boreas 38, 679–690 (2009).

    Article  Google Scholar 

  67. 67.

    Christl, M. et al. The ETH Zurich AMS facilities: performance parameters and reference materials. Nucl. Instrum. Methods Phys. Res. B 294, 29–38 (2013).

    Article  Google Scholar 

  68. 68.

    Nishiizumi, K. et al. Absolute calibration of 10Be AMS standards. Nucl. Instrum. Methods Phys. Res. B 258, 403–413 (2007).

    Article  Google Scholar 

  69. 69.

    Korschinek, G. et al. A new value for the half-life of 10Be by heavy-ion elastic recoil detection and liquid scintillation counting. Nucl. Instrum. Methods Phys. Res. B 268, 187–191 (2010).

    Article  Google Scholar 

  70. 70.

    Chmeleff, J., von Blanckenburg, F., Kossert, K. & Jakob, D. Determination of the 10Be half-life by multicollector ICP-MS and liquid scintillation counting. Nucl. Instrum. Methods Phys. Res. B 268, 192–199 (2010).

    Article  Google Scholar 

  71. 71.

    Mudelsee, M. Ramp function regression: a tool for quantifying climate transitions. Comput. Geosci. 26, 293–307 (2000).

    Article  Google Scholar 

  72. 72.

    Mudelsee, M. Break function regression. Eur. Phys. J. Spec. Top. 174, 49–63 (2009).

    Article  Google Scholar 

  73. 73.

    Haslett, J. & Parnell, A. A simple monotone process with application to radiocarbon-dated depth chronologies. J. R. Stat. Soc. C 57, 399–418 (2008).

    Article  Google Scholar 

  74. 74.

    Abramowitz, M. & Stegun, I. A. (eds) Handbook of Mathematical Functions: with Formulas, Graphs and Mathematical Tables (Dover Publications, 1965).

  75. 75.

    Rach, O., Brauer, A., Wilkes, H. & Sachse, D. Delayed hydrological response to Greenland cooling at the onset of the Younger Dryas in western Europe. Nat. Geosci. 7, 109–112 (2014).

    Article  Google Scholar 

  76. 76.

    Obreht, I. et al. An annually resolved record of Western European vegetation response to Younger Dryas cooling. Quat. Sci. Rev. 231, 106198 (2020).

    Article  Google Scholar 

  77. 77.

    Schulz, M. & Mudelsee, M. REDFIT: estimating red-noise spectra directly from unevenly spaced paleoclimatic time series. Comput. Geosci. 28, 421–426 (2002).

    Article  Google Scholar 

  78. 78.

    von Storch, H. & Zwiers, F. W. Statistical Analysis in Climate Research (Cambridge Univ. Press, 2001).

  79. 79.

    Torrence, C. & Compo, G. P. A practical guide to wavelet analysis. Bull. Am. Meteor. Soc. 79, 61–78 (1998).

    Article  Google Scholar 

  80. 80.

    Vinther, B. M. et al. A synchronized dating of three Greenland ice cores throughout the Holocene. J. Geophys. Res. Atmospheres 111, D13102 (2006).

    Article  Google Scholar 

  81. 81.

    Andersen, K. K. et al. The Greenland Ice Core Chronology 2005, 15–42 ka. Part 1: constructing the time scale. Quat. Sci. Rev. 25, 3246–3257 (2006).

    Article  Google Scholar 

  82. 82.

    Svensson, A. A 60,000 year Greenland stratigraphic ice core chronology. Clim. Past 4, 47–57 (2008).

    Article  Google Scholar 

  83. 83.

    Haug, G. H. et al. Glacial/interglacial variations in production and nitrogen fixation in the Cariaco Basin during the last 580 kyr. Paleoceanography 13, 427–432 (1998).

    Article  Google Scholar 

  84. 84.

    Cannariato, K. G., Kennett, J. P. & Behl, R. J. Biotic response to late Quaternary rapid climate switches in Santa Barbara basin: ecological and evolutionary implications. Geology 27, 63–66 (1999).

    Google Scholar 

  85. 85.

    Correa-Metrio, A. et al. The influence of abrupt climate change on the ice-age vegetation of the Central American lowlands: abrupt climate change in ice-age Central America. J. Biogeogr. 39, 497–509 (2012).

    Article  Google Scholar 

  86. 86.

    Sun, Y., Wang, X., Liu, Q. & Clemens, S. C. Impacts of post-depositional processes on rapid monsoon signals recorded by the last glacial loess deposits of northern China. Earth Planet. Sci. Lett. 289, 171–179 (2010).

    Article  Google Scholar 

  87. 87.

    Bronk Ramsey, C. et al. A complete terrestrial radiocarbon record for 11.2 to 52.8 kyr B.P. Science 338, 370–374 (2012).

    Article  Google Scholar 

  88. 88.

    Brauer, A. et al. Evidence for last interglacial chronology and environmental change from Southern Europe. Proc. Natl Acad. Sci. USA 104, 450–455 (2007).

    Article  Google Scholar 

  89. 89.

    Mingram, J. et al. Millennial-scale East Asian monsoon variability of the last glacial deduced from annually laminated sediments from Lake Sihailongwan, N.E. China. Quat. Sci. Rev. 201, 57–76 (2018).

    Article  Google Scholar 

  90. 90.

    Kliem, P. et al. Lithology, radiocarbon chronology and sedimentological interpretation of the lacustrine record from Laguna Potrok Aike, southern Patagonia. Quat. Sci. Rev. 71, 54–69 (2013).

    Article  Google Scholar 

  91. 91.

    Rasmussen, S. O. et al. A new Greenland ice core chronology for the last glacial termination. J. Geophys. Res. 111, D06102 (2006).

    Article  Google Scholar 

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We thank the Stölben Drilling Company (Cochem, Germany) for years of fruitful cooperation in optimizing the drilling technique in the Eifel maar lakes and B. Stoll, F. Rubach, B. Hinenberg, C. Liebl, L. Marsiske, A. Blum, A. Mack, R. Deutsch, and P. Sigl for technical support. M. Zech (Dresden) provided Corg data for calibration of the ISRS670. The work was funded by the University of Mainz and Max Planck Institute for Chemistry, Mainz. We thank I. Obreht for very helpful suggestions and comments during the review process.

Author information




F.S. coordinated the ELSA drillings and proposed and directed the research. F.S., A.M.-G. and G.H.H. led the interpretation of the data. F.S. and A.M.-G. wrote the manuscript and generated the figures. R.S. and R.F. provided 14C dates. R.M. and M.C. analysed the 10Be on the Auel samples. F.F., S.B., K.S. and J.A. worked on the age assignment. B.D. constructed the Auel stack by dynamic time warp. M.M. calculated the Bayesian age model. A.M.-G. and M.M. performed the spectral analysis of the records. Y.H. directed the µXRF analysis.

Corresponding author

Correspondence to Frank Sirocko.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Geoscience thanks Igor Obreht and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: James Super.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 The AU3/AU4 drilling site.

a, Photo of the infilled maar lake of Auel with drilling sites and locations of seismic lines. b, Seismic line 1 and core locations. Core AU2 is included in the figures, because this core was studied by Sirocko et al.15 for the pioneering work on the Auel maar.

Extended Data Fig. 2 Maar lake sediment cores SMf, HM4 and AU4.

a, Photo of freeze core SMf2 from Schalkenmehrener Maar with 137Cs profile and varve counts for the last 800 years. b, Core photo of sediment core HM4 with depth of palynostratigraphical fix-points for the Bayesian age model of the Holocene section. The ages for the palynological markers are taken from Litt et al.66, see also Supplementary Data 2. c, Core photo of sediment core AU4 with depth and age (all yr b2k) of interstadials from Rasmussen et al.17, see also Supplementary Data 2. d, Sedimentary disturbances between 75,5 and 78,0 m in core AU4. This interval represents GS12 and GI12 for which only selected parts of the Corg(chlorins) data have been used. All ages are given in the yr b2k notation.

Extended Data Fig. 3 The ISRS method.

a, reflectance of visible light wavelength, measured with a Gretag Spectrolino at 1 mm step size with 2x2 mm sensor field and spectral resolution of 10 nm. The red line characterizes the absorption at 670 nm. Examples are given for three samples: rich, intermediate, low in organic carbon content. Reflectance spectra from fresh and withered plant leaves and needles are given for comparison to the adsorption of organic carbon from diatoms at 670 nm16. b, Quantification of the Absorption Depth at wavelength of 670 nm. The approach follows the “In Situ Reflectance Spectroscopy – ISRS” method for chlorophyll derivates (mainly chlorins) in marine sediments off Peru16, but is now adapted to the lake sediments of the Eifel maar lakes. c, Organic carbon measurements of 10 discrete samples versus ISRS of the same samples. Each sample represents a homogenized 10 cm long section from core AU2. The homogenized sample was measured 10 times and averaged. The relation between ISRS at 670nm and Corg content is linear and can be expressed by the equation Corg = ISRS670 x 22.7.

Extended Data Fig. 4 Age-depth relation.

a, The Corg(chlorins) data for cores SMf, HM4, AU3 and AU4 are shown versus depth to document the basis for the Age-Depth model, calculated according to Fig. ED5.The ELSA-20 age is plotted together with 14C dates and 10Be data. The error is calculated with a Bayesian approach. The Age-Depth model is compared to other high resolution marine and terrestrial records. Cariaco Basin: ODP-1002C83; St. Barbara Basin ODP89384; Guatemala: Lake Petén-Itzá85; China: Jingyuan loess plateau86; Japan: Lake Suigetsu87; Italy: Lago Grande di Monticchio88; China: Sihailongwan Maar Lake89; S-Patagonia: Laguna Potrok Aike90. The sedimentation rate of the SMf and HM4 cores is similar to other global records, but the sedimentation rate of the Auel cores is globally exceptional during MIS3. b, The Corg(chlorins) are shown versus depth for cores AU3 and AU4, which have been drilled with an 0.5 m offset. Both cores reveal an identical interstadial pattern, which allows for the Dynamic Time Warp of short AU3 sections into the AU4 core. Background colors are the pattern of Landscape Evolution Zones (LEZ) as defined by Sirocko et al.15. 8 tephra have been observed in the cores of HM Förster & Sirocko54 and Förster et al.51. The ages for the Eltville Tephra (EVT), Wartgesberg Tephra (WBT), Dreiser Weiher Tephra (DWT) and Meefelder Maar Tephra (MMT) are presented here on the updated ELSA-20 timescale. c, The lithology of all ELSA-20 cores is presented with its main characteristics.

Extended Data Fig. 5 Ice core tuning, 23 - 36 ka.

δ18O and chronology of the NGRIP ice core1,17,80,81,82,91 in comparison to ELSA-20 Corg(chlorins) content and Si/Al. The ELSA-20 Corg(chlorins) data are also shown in the kernel detrended version used for the wavelet and spectra as shown in Figs. 3-5.

Extended Data Fig. 6 Ice core tuning, 36–48 ka.

δ18O and chronology of the NGRIP ice core1,17,80,81,82,91 in comparison to ELSA-20 Corg(chlorins) content and Si/Al. The ELSA-20 Corg(chlorins) data are also shown in the kernel detrended version used for the wavelet and spectra as shown in Figs. 3-5.

Extended Data Fig. 7 Ice core tuning, 48–59 ka.

δ18O and chronology of the NGRIP ice core1,17,80,81,82,91 in comparison to ELSA-20 Corg(chlorins) content and Si/Al. The ELSA-20 Corg(chlorins) data are also shown in the kernel detrended version used for the wavelet and spectra as shown in Figs. 3-5.

Extended Data Fig. 8 Uncertainty determination.

Control points for the Bayesian error calculation of the AU4 Corg(chlorins) to δ18O from NGRIP1 for selected GI events except the disturbed sections of GI12 - GS12.

Extended Data Fig. 9 Statistical Analysis.

(a-r) Corg(chlorins) Lomb-Scargle spectral power estimation for selected time intervals for the ELSA-20 Corg(chlorins) record. Employed were a Welch taper and following estimation parameters: a, number of segments (n50) = 10, 6-dB bandwidth (BW) = 8.0 × 10–4 yr–1; b, n50 = 2, BW = 9.9 × 10–3 yr–1; c, n50 = 2, BW = 8.0 × 10–3 yr–1; d, n50 = 4, BW = 8.6 × 10–3 yr–1; e, n50 = 3, BW = 8.4 × 10–3 yr–1; f, n50 = 5, BW = 2.9 × 10–3 yr–1; g, n50 = 2, BW = 2.2 × 10–3 yr–1; h, n50 = 10, BW = 1.7 × 10–3 –1; i, n50 = 6, BW = 1.9 × 10–3 yr–1; j, n50 = 3, BW = 3.2 × 10–3 yr–1; k, n50 = 6, BW = 2.8 × 10–3 yr–1; l, n50 = 3, BW = 8.0 × 10–3 yr–1; m, n50 = 5, BW = 4.8 × 10–3 yr–1; n, n50 = 7, BW = 4.2 × 10–3 yr–1; o, n50 = 4, BW = 5.7 × 10–3 yr–1; p, n50 = 5, BW = 4.8 × 10–3 yr–1; q, n50 = 4, BW = 5.0 × 10–3 yr–1; and r, n50 = 11, BW = 1.8 × 10–3 yr–1. Each panel indicates (italics) name and time interval (yr b2k) and shows spectral power (black line), AR(1) red noise upper 99% percentile (red line), white noise upper 99% percentile (grey line) and the periods for significant and (within BW) separable spectral peaks. The low-frequency peak marked by an asterisk (a) may have a biased power estimate due to the kernel detrending. The high-frequency spectrum parts (up to 0.5 yr–1) do not exhibit relevant peaks. (s-aj) Si/Al Lomb-Scargle spectral power estimation for selected time intervals for the ELSA-20 Si/Al record. Employed were a Welch taper and following estimation parameters: s, number of segments (n50) = 10, 6-dB bandwidth (BW) = 8.1 × 10–4 yr–1; t, n50 = 2, BW = 9.9 × 10–3 yr–1; u, n50 = 2, BW = 8.0 × 10–3 yr–1; v, n50 = 4, BW = 8.6 × 10–3 yr–1; w, n50 = 3, BW = 8.4 × 10–3 yr–1; x, n50 = 5, BW = 2.9 × 10–3 yr–1; y, n50 = 2, BW = 2.2 × 10–3 yr–1; z, n50 = 10, BW = 1.7 × 10–3 yr–1; aa, n50 = 6, BW = 1.9 × 10–3 yr–1; ab, n50 = 3, BW = 3.2 × 10–3 yr–1; ac, n50 = 6, BW = 2.8 × 10–3 yr–1; ad, n50 = 3, BW = 8.0 × 10–3 yr–1; ae, n50 = 5, BW = 4.8 × 10–3 yr–1; af, n50 = 7, BW = 4.2 × 10–3 yr–1; ag, n50 = 4, BW = 5.7 × 10–3 yr–1; ah, n50 = 5, BW = 4.8 × 10–3 yr–1; ai, n50 = 4, BW = 5.0 × 10–3 yr–1; and aj, n50 = 11, BW = 1.8 × 10–3 yr–1. Each panel indicates (italics) name and time interval (yr b2k) and shows spectral power (black line), AR(1) red noise upper 99% percentile (red line), white noise upper 99% percentile (grey line) and the periods for significant and (within BW) separable spectral peaks. The low-frequency peaks marked by an asterisk (a, f, r) may have biased power estimates due to the kernel detrending. The high-frequency spectrum parts (up to 0.5 yr–1) do not exhibit relevant peaks.

Supplementary information

Supplementary Information

Descriptions of Supplementary Data 1 and 2.

Supplementary Data 1

The ELSA-20 data.

Supplementary Data 2

Table of chronological control points.

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Sirocko, F., Martínez-García, A., Mudelsee, M. et al. Muted multidecadal climate variability in central Europe during cold stadial periods. Nat. Geosci. 14, 651–658 (2021).

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