21 May 2021

21 May 2021

Review status: a revised version of this preprint is currently under review for the journal CP.

Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

Paul D. Zander1, Maurycy Żarczyński2, Wojciech Tylmann2, Shauna-kay Rainford3, and Martin Grosjean1 Paul D. Zander et al.
  • 1Institute of Geography & Oeschger Centre for Climate Change Research, University of Bern, Switzerland
  • 2Faculty of Oceanography and Geography, University of Gdansk, Poland
  • 3Institute of Plant Sciences & Oeschger Centre for Climate Change Research, University of Bern, Switzerland

Abstract. Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare mainly because the climate-proxy relationships are complex, and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (μXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore (seasonal) climate signals preserved in biochemical varves and, thus, assess the potential for annual resolution climate reconstruction from biochemical varves.

Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and uXRF-inferred elements at very high spatial resolution (60 μm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland over the period 1966–2019 CE. We compare this data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperature were predicted using Ti and total C (R2adj = 0.55; cross-validated root mean square error (CV-RMSE) = 0.7 °C, 14.4%). Windy days from March to December (mean daily wind speed > 7 m/s) were predicted using mass accumulation rate (MAR) and Si (R2adj = 0.48; CV-RMSE = 19.0%). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate-proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual resolution seasonal weather inference from varve biogeochemical data.

Paul D. Zander et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on cp-2021-56', Saija Saarni, 22 Jun 2021
    • AC1: 'Authors’ Response to RC1', Paul Zander, 21 Jul 2021
  • RC2: 'Comment on cp-2021-56', Daniel Schillereff, 11 Jul 2021
    • AC2: 'Authors’ Response to RC2', Paul Zander, 21 Jul 2021
  • EC1: 'Comment on cp-2021-56', Pierre Francus, 12 Jul 2021
    • AC3: 'Authors’ Response to EC1', Paul Zander, 21 Jul 2021

Paul D. Zander et al.

Data sets

Data and code for "Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques" Paul D. Zander, Maurycy Żarczyński, Wojciech Tylmann, Shauna-kay Rainford, Martin Grosjean

Paul D. Zander et al.


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Short summary
High-resolution geochemical imaging techniques provide new opportunities to investigate the biogeochemical composition of sediments at micrometer scale. Here, we compare biogeochemical data from biochemical varves with meteorological data to understand how seasonal meteorological variations are recorded in varve composition. We find that these scanning techniques help to clarify climate-proxy relationships in biochemical varves and show great potential for high-resolution climate reconstruction.