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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 1
Nonlin. Processes Geophys., 16, 43-56, 2009
https://doi.org/10.5194/npg-16-43-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nonlin. Processes Geophys., 16, 43-56, 2009
https://doi.org/10.5194/npg-16-43-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  05 Feb 2009

05 Feb 2009

Climate spectrum estimation in the presence of timescale errors

M. Mudelsee1,2, D. Scholz3,4, R. Röthlisberger1, D. Fleitmann5,6, A. Mangini3, and E. W. Wolff1 M. Mudelsee et al.
  • 1British Antarctic Survey, Cambridge, UK
  • 2Climate Risk Analysis, Hannover, Germany
  • 3Heidelberg Academy of Sciences, Heidelberg, Germany
  • 4Bristol Isotope Group, School of Geographical Sciences, University of Bristol, Bristol, UK
  • 5Institute of Geological Sciences, University of Bern, Bern, Switzerland
  • 6Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland

Abstract. We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation.

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