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A chain of processes ­ from past climate variations to paleoclimate reconstructions

Kira Rehfeld & Thomas Laepple (krehfeld@awi.de)

ECUS – Estimating climate variability by quantifying proxy uncertainty and synthesizing information across archives Past climate variations

are recorded, through nature's sampling, in paleoclimate archives. It is essential to

quantify estimation uncertainties, to which each step along the way contributes.

Integrating techniques and information across archives and proxies, allows to identify

complimentary archive­proxy combinations which can improve past climate estimates

across timescales. We find common challenges for many archives, where techniques developed in different communities could reduce the final uncertainy of paleoclimate reconstructions.

Kirchner, J. Aliasing in 1∕fα noise spectra: Origins, consequences, and remedies. Phys. Rev. E, 2005.

Laepple, T & Huybers, P. Reconciling discrepancies between Uk37 and Mg/Ca reconstructions of Holocene marine temperature variability.

EPSL, 2013.

Rehfeld, K & Kurths, J. Similarity estimators for irregular and age­

uncertain time series, CP 2014.

Rehfeld et al. Comparison of correlation analysis techniques for irregularly sampled time series, NPG, 2011.

Laepple, Werner & Lohmann. Synchronicity of Antarctic Temperatures and Local Solar Insolation on Orbital Timescales. Nature, 2011.

Berger, WH, Johnson, RF, Killingley JS. 'Unmixing' of the deep­sea record and the deglacial meltwater spike. Nature, 1977.

Breitenbach et al. COnstructing Proxy Records from Age models (COPRA), CP, 2012.

Rhines, A & Huybers, P. Estimation of spectral power laws in time uncertain series of data with application to the Greenland Ice Sheet Project 2 d18O record. JGR, 2011.

Cross­pollination potential

Age­uncertainty can be evaluated in time series analyses using Monte­Carlo techniques (Fig. 4A, Rehfeld & Kurths, 2014). Some age­modeling approaches allow for the combination of layer

counting and point­based ages. This, along with cross­dating as for tree­ring chronologies, could reduce age

uncertainties.

When the fundamental processes

affecting the proxy signal are known, a proxy error model can be used to quantify the uncertainties if the

essential parameters can be

estimated. As an example, Fig.

4B shows a synthetic marine core resembling tropical MD03­2707, with proxy modelling as in

Laepple & Huybers, 2013.

The structure of the archive and proxy landscape is complex. Which processes affect archives (2A) ­ and which are proxy­dependent (2B)? Which proxies can be measured on the same archive sample?

References

Common challenges across archives and proxies 1

3 4

5

2 A

2 B

4 A

4 B

2

Referenzen

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