Journal of Paleolimnology

, Volume 47, Issue 4, pp 583–600 | Cite as

Calibrating biogeochemical and physical climate proxies from non-varved lake sediments with meteorological data: methods and case studies

  • Lucien von Gunten
  • Martin Grosjean
  • Christian Kamenik
  • Marian Fujak
  • Roberto Urrutia
Original paper

Abstract

Lake sediment records are underrepresented in comprehensive, quantitative, high-resolution (sub-decadal), multi-proxy climate reconstructions for the past millennium. This is largely a consequence of the difficulty of calibrating biogeochemical lake sediment proxies to meteorological time series (calibration-in-time). Thanks to recent methodological advances, it is now possible. This paper outlines a step-by-step, specifically tailored methodology, with practical suggestions for calibrating and validating biogeochemical proxies from lake sediments to meteorological data. This approach includes: (1) regional climate data; (2) site selection; (3) coring and core selection; (4) core chronology; (5) data acquisition; and (6) data analysis and statistical methods. We present three case studies that used non-varved lake sediments from remote areas in the Central Chilean Andes, where little a priori information was available on the local climate and lakes, or their responses to climate variability. These case studies illustrate the potential value and application of a calibration-in-time approach to non-varved lake sediments for developing quantitative, high-resolution climate reconstructions.

Keywords

Sedimentology Paleolimnology Climate change Paleoclimate Numerical methods Calibration in time 

Supplementary material

10933_2012_9582_MOESM1_ESM.tif (3.8 mb)
For Laguna Aculeo (black dot), comparison between the nearest meteorological station (Pudahuel Santiago airport (Pu), circle) and grid cells for the 0.5° CRU TS 2.1 (CRU, small square) and 5° HadCRUT3 (Ha, large square) annual and seasonal (DJF, MAM, JJA, SON) temperature reanalysis datasets. Both reanalysis datasets are highly significantly correlated with the (discontinuous) homogenized seasonal and annual records from Pudahuel. (TIFF 3879 kb)
10933_2012_9582_MOESM2_ESM.doc (86 kb)
Parts of the correlation matrix (Pearson correlation coefficient) of (a) Laguna Aculeo, (b) Laguna del Inca and (c) Laguna Negra. df: Degrees of freedom (corrected DFs in parenthesis), P: p-value (corrected for autocorrelation), with **p < 0.01, *p < 0.05. (DOC 85 kb)

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Lucien von Gunten
    • 1
    • 2
    • 3
    • 4
  • Martin Grosjean
    • 1
    • 2
  • Christian Kamenik
    • 1
    • 2
  • Marian Fujak
    • 5
  • Roberto Urrutia
    • 6
  1. 1.Oeschger Centre for Climate Change ResearchUniversity of BernBernSwitzerland
  2. 2.Institute of GeographyUniversity of BernBernSwitzerland
  3. 3.Climate System Research CenterUniversity of MassachusettsAmherstUSA
  4. 4.Geological InstituteSwiss Federal Institute of TechnologyZürichSwitzerland
  5. 5.Surface Waters Research, EAWAGDübendorfSwitzerland
  6. 6.Centro de Ciencias Ambientales EULA-ChileUniversidad de ConcepciónConcepciónChile

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