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Spectral biases in tree-ring climate proxies

Nature Climate Change volume 3, pages 360–364 (2013)Cite this article

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Abstract

External forcing and internal dynamics result in climate system variability ranging from sub-daily weather to multi-centennial trends and beyond1,2. State-of-the-art palaeoclimatic methods routinely use hydroclimatic proxies to reconstruct temperature (for example, refs 3, 4), possibly blurring differences in the variability continuum of temperature and precipitation before the instrumental period. Here, we assess the spectral characteristics of temperature and precipitation fluctuations in observations, model simulations and proxy records across the globe. We find that whereas an ensemble of different general circulation models represents patterns captured in instrumental measurements, such as land–ocean contrasts and enhanced low-frequency tropical variability, the tree-ring-dominated proxy collection does not. The observed dominance of inter-annual precipitation fluctuations is not reflected in the annually resolved hydroclimatic proxy records. Likewise, temperature-sensitive proxies overestimate, on average, the ratio of low- to high-frequency variability. These spectral biases in the proxy records seem to propagate into multi-proxy climate reconstructions for which we observe an overestimation of low-frequency signals. Thus, a proper representation of the high- to low-frequency spectrum in proxy records is needed to reduce uncertainties in climate reconstruction efforts.

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Figure 1: Spectral colour maps and distributions.
Figure 2: Long instrumental, GCM and proxy spectra.
Figure 3: Spectral colour of climate reconstructions.

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References

  1. Ghil, M. in Encyclopedia of Global Environmental Change Vol. 1 (eds MacCracken, M. C. et al.) 544–549 (Wiley, 2001).

    Google Scholar 

  2. Huybers, P. & Curry, W. Links between annual, Milankovitch and continuum temperature variability. Nature 441, 329–332 (2006).

    Article  CAS  Google Scholar 

  3. Mann, M. E. et al. Global signatures and dynamical origins of the Little Ice Age and Medieval Climate Anomaly. Science 326, 1256–1260 (2009).

    Article  CAS  Google Scholar 

  4. Jones, P. D. et al. High-resolution palaeoclimatology of the last millennium: A review of current status and future prospects. Holocene 19, 3–49 (2009).

    Article  Google Scholar 

  5. Mitchell, J. An overview of climatic variability and its causal mechanisms. Quat. Res. 6, 481–493 (1976).

    Article  Google Scholar 

  6. Büntgen, U. et al. Growth/climate response shift in a long subalpine spruce chronology. Trees 20, 99–110 (2006).

    Article  Google Scholar 

  7. Frank, D. et al. A noodle, hockey stick, and spaghetti plate: A perspective on high-resolution paleoclimatology. WIRes Clim. Change 1, 507–516 (2010).

    Article  Google Scholar 

  8. Esper, J., Cook, E. R & Schweingruber, F. H. Low-frequency signals in long tree-ring chronologies for reconstructing past temperature variability. Science 295, 2250–2253 (2002).

    Article  CAS  Google Scholar 

  9. Frank, D. et al. Warmer early instrumental measurements versus colder reconstructed temperatures: shooting at a moving target. Quat. Sci. Rev. 26, 3298–3310 (2007).

    Article  Google Scholar 

  10. Mitchell, T. D. & Jones, P. D. An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int. J. Climatol. 25, 693–712 (2005).

    Article  Google Scholar 

  11. Compo, G. P. et al. The twentieth century reanalysis project. Q. J. R. Meteorol. Soc. 137, 1–28 (2011).

    Article  Google Scholar 

  12. González-Rouco, J. F. et al. in Solar Variability as an Input to the Earth’s Environment (ed. Wilson, A.) 329–338 (ESA Publications Division, 2003).

    Google Scholar 

  13. Tett, S. F. B. et al. The impact of natural and anthropogenic forcings on climate and hydrology since 1550. Clim. Dynam. 28, 3–34 (2007).

    Article  Google Scholar 

  14. Hofer, D., Raible, C. C. & Stocker, T. F. Variations of the Atlantic meridional overturning circulation in control and transient simulations of the last millennium. Clim. Past 7, 133–150 (2011).

    Article  Google Scholar 

  15. Jungclaus, J. H. et al. Climate and carbon-cycle variability over the last millennium. Clim. Past 6, 1009–1044 (2010).

    Article  Google Scholar 

  16. Neukom, R. et al. Multi-centennial summer and winter precipitation variability in southern South America. Geophys. Res. Lett. 37, L14708 (2010).

    Article  Google Scholar 

  17. Neukom, R. et al. Multiproxy summer and winter surface air temperature field reconstructions for southern South America covering the past centuries. Clim. Dynam. 37, 35–51 (2011).

    Article  Google Scholar 

  18. Pelletier, J. D. The power spectral density of atmospheric temperature from time scales of 10−2 to 106 yr. Earth Planet. Sci. Lett. 158, 157–164 (1998).

    Article  CAS  Google Scholar 

  19. Fraedrich, K. & Blender, R. Scaling of atmosphere and ocean temperature correlations in observations and climate models. Phys. Rev. Lett. 90, 108501 (2003).

    Article  Google Scholar 

  20. Barnett, T. P. et al. Estimates of low frequency natural variability in near-surface air temperature. Holocene 6, 255–263 (1996).

    Article  Google Scholar 

  21. Collins, M. et al. A comparison of the variability of a climate model with paleotemperature estimates from a network of tree-ring densities. J. Clim. 15, 1497–1515 (2002).

    Article  Google Scholar 

  22. Schiermeier, Q. The real holes in climate science. Nature 463, 284–287 (2010).

    Article  CAS  Google Scholar 

  23. Vose, R. S. et al. Global historical climatology network, 1753–1990. (Oak Ridge National Laboratory, 1998); available at http://www.daac.ornl.gov.

  24. Böhm, R. et al. The early instrumental bias: A solution for long central European temperature series 1760–2007. Climatic Change 101, 41–67 (2010).

    Article  Google Scholar 

  25. Osborn, T. J. & Briffa, K. R. Climate: The real color of climate change? Science 306, 621–622 (2004).

    Article  CAS  Google Scholar 

  26. Von Storch, H. et al. Assessment of three temperature reconstruction methods in the virtual reality of a climate simulation. Int. J. Earth Sci. 98, 67–82 (2009).

    Article  Google Scholar 

  27. Moberg, A. et al. Analysis of the Moberg et al. (2005) hemispheric temperature reconstruction. Clim. Dynam. 31, 957–971 (2008).

    Article  Google Scholar 

  28. Casty, C. et al. A European pattern climatology 1766–2000. Clim. Dynam. 29, 791–805 (2007).

    Article  Google Scholar 

  29. Bhend, J. et al. An ensemble-based approach to climate reconstructions. Clim. Past 8, 963–976 (2012).

    Article  Google Scholar 

  30. Percival, D. & Walden, A. Spectral Analysis for Physical Applications (Cambridge Univ. Press, 1993).

    Book  Google Scholar 

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Acknowledgements

This study was financially supported by the EU project MILLENNIUM (#017008-GOCE) and by the Swiss National Science Foundation (SNSF) through its National Center of Competence in Research on Climate (NCCR Climate). C.R. and S.B. are also supported by the Synergia project FUPSOL, and C.R. additionally by the EU project Past4Future. We thank NOAA/DOE/OBER for providing 20CR and everyone else who contributed model or proxy data for this study. We thank E. Gleeson for her editing efforts.

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Authors and Affiliations

  1. Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland

    Jörg Franke & David Frank

  2. Institute of Geography, University of Bern, 3012 Bern, Switzerland

    Jörg Franke & Stefan Brönnimann

  3. Oeschger Centre for Climate Change Research, 3012 Bern, Switzerland

    Jörg Franke, David Frank, Christoph C. Raible & Stefan Brönnimann

  4. Physics Institute, University of Bern, 3012 Bern, Switzerland

    Christoph C. Raible

  5. Department of Geography, Johannes Gutenberg University, 55099 Mainz, Germany

    Jan Esper

Authors
  1. Jörg Franke
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  2. David Frank
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  3. Christoph C. Raible
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  4. Jan Esper
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  5. Stefan Brönnimann
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Contributions

J.E., J.F. and D.F. designed the study. J.F. performed the analysis with input from D.F., C.C.R. and S.B. All authors contributed to the discussion and to writing the paper.

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Correspondence to Jörg Franke.

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The authors declare no competing financial interests.

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Franke, J., Frank, D., Raible, C. et al. Spectral biases in tree-ring climate proxies. Nature Clim Change 3, 360–364 (2013). https://doi.org/10.1038/nclimate1816

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