Ramisch, Arne, Brauser, Alexander, Dorn, Mario, Blanchet, Cecile, Brademann, Brian, Köppl, Matthias, Mingram, Jens, Neugebauer, Ina, Nowaczyk, Norbert, Ott, Florian, Pinkerneil, Sylvia, Plessen, Birgit, Schwab, Markus J., Tjallingii, Rik and Brauer, Achim (2020) VARDA (VARved sediments DAtabase) – providing and connecting proxy data from annually laminated lake sediments. Earth System Science Data Discussions, 12 . pp. 2311-2332. DOI 10.5194/essd-2020-55.

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Abstract

Varved lake sediments provide long climatic records with high temporal resolution and low associated age uncertainty. Robust and detailed comparison of well-dated and annually laminated sediment records is crucial for reconstructing abrupt and regionally time-transgressive changes as well as validation of spatial and temporal trajectories of past climatic changes. The VARved sediments DAtabase (VARDA) presented here is the first data compilation for varve chronologies and associated palaeoclimatic proxy records. The current version 1.0 allows detailed comparison of published varve records from 95 lakes. VARDA is freely accessible and was created to assess outputs from climate models with high-resolution terrestrial palaeoclimatic proxies. VARDA additionally provides a technical environment that enables to explore the database of varved lake sediments using a connected data-model and can generate a state-of-the-art graphic representation of multi-site comparison. This allows to reassess existing chronologies and tephra events to synchronize and compare even distant varved lake records. Furthermore, the present version of VARDA permits to explore varve thickness data. In this paper, we report in detail on the data mining and compilation strategies for the identification of varved lakes and assimilation of high-resolution chronologies as well as the technical infrastructure of the database. Additional paleoclimate proxy data will be provided in forthcoming updates. The VARDA graph-database and user interface can be accessed online at https://varve.gfz-potsdam.de, all datasets of version 1.0 are available at http://doi.org/10.5880/GFZ.4.3.2019.003 (Ramisch et al., 2019).

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