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  • 1
    Publication Date: 2020-09-25
    Description: Varved lake sediments provide climatic records with seasonal to annual 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 us to explore the database of varved lake sediments using a connected data model and can generate a state-of-the-art graphic representation of a multisite comparison. This allows the reassessment of existing chronologies and tephra events to synchronize and compare even distant varved lake records. Furthermore, the present version of VARDA permits the exploration of 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 palaeoclimatic 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 (last access: 15 September 2020), all datasets of version 1.0 are available at https://doi.org/10.5880/GFZ.4.3.2019.003 (Ramisch et al., 2019).
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 2
    Publication Date: 2020-05-13
    Description: The data collection presented here is the data inventory of the VARved sediments DAtabase (VARDA) in version 1.1. VARDA is freely accessible and was created to assess outputs from climate models with high-resolution terrestrial palaeoclimatic proxies. All data were collected as raw data from freely available online sources, either from online data repositories (Pangaea, NOAA, and Neotoma) or data archives within the supplementary materials section of online publications. The current data collection consists of meta information and datasets from 95 lake archives. The data is stored in JSON and CSV format. All datasets are stored as individual files (JSON and CSV). Each dataset consists of samples for either i) chronologies; ii) radiocarbon data; iii) tephra layer; or iv) varve thickness data. Meta-information for each dataset is summarized in one csv and seven JSON files. Additional paleoclimate proxy data will be provided in forthcoming updates of VARDA. The data collection of VARDA Version 1.1 is provided as an archive (.tar.gz) with the following files/folders. Overview lists with categories, cores, countries, datasets, lakes and publications included in VARDA. Each item in the lists is cross-referenced with the other files via its $ref property which includes the corresponding list index or the dataset's UUID (from the VARDA database). The data points themselves are provided in the "records" folder and named with each dataset's UUID respectively. For more information on the data structure please read the "index.html" file included in the archive and available on the DOI landing page.
    Type: Other , NonPeerReviewed
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  • 3
    Publication Date: 2021-12-03
    Description: Abstract
    Description: The data collection presented here is the data inventory of the VARved sediments DAtabase (VARDA) in version 1.3. VARDA is freely accessible and was created to assess outputs from climate models with high-resolution terrestrial palaeoclimatic proxies. All data were collected as raw data from freely available online sources, either from online data repositories (Pangaea, NOAA, and Neotoma) or data archives within the supplementary materials section of online publications. The current data collection consists of meta information and datasets from 95 lake archives. The data is stored in JSON and CSV format. All datasets are stored as individual files (JSON and CSV). Each dataset consists of samples for either i) chronologies; ii) radiocarbon data; iii) tephra layer; or iv) varve thickness data. Meta-information for each dataset is summarized in one csv and seven JSON files. Additional paleoclimate proxy data will be provided in forthcoming updates of VARDA. The data collection of VARDA Version 1.3 is provided as an archive (.tar.gz) with the following files/folders. Overview lists with categories, cores, countries, datasets, lakes and publications included in VARDA. Each item in the lists is cross-referenced with the other files via its $ref property which includes the corresponding list index or the dataset's UUID (from the VARDA database). The data points themselves are provided in the "records" folder and named with each dataset's UUID respectively. For more information on the data structure please read the "index.html" file included in the archive and available on the DOI landing page. VERSION HISTORY: 26 July 2020: release of Version 1.3: 1. Fix issues with chronologies in the export 2. Provide recalculated machine readable error estimates 3. Correct some metadata values (e.g. core labels) 5 March 2020: release of Version 1.1 1. Added fields: "distributor" - Field containing name of data distributor "url" - Field containing DOIs and URLs, which lead to the original data publications 2. Correction of publication DOIs in 9 cases The version 1.0 is available in the "previous-versions" subfolder via the Data Download link. The index file is unchanged.
    Keywords: Varda ; varves ; compound material 〉 sedimentary material ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 LAND RECORDS 〉 VOLCANIC DEPOSITS ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 OCEAN/LAKE RECORDS 〉 RADIOCARBON ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 OCEAN/LAKE RECORDS 〉 SEDIMENTS ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 OCEAN/LAKE RECORDS 〉 STRATIGRAPHIC SEQUENCE ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 OCEAN/LAKE RECORDS 〉 VARVE DEPOSITS ; environment 〉 natural environment 〉 aquatic environment ; environment 〉 natural environment 〉 terrestrial environment ; In Situ/Laboratory Instruments 〉 Corers 〉 SEDIMENT CORERS ; Phanerozoic 〉 Cenozoic 〉 Quaternary 〉 Holocene ; Phanerozoic 〉 Cenozoic 〉 Quaternary 〉 Pleistocene 〉 Late/Upper Pleistocene ; science 〉 natural science 〉 earth science 〉 geology ; science 〉 natural science 〉 earth science 〉 sedimentology
    Type: Dataset , Dataset
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  • 4
    Publication Date: 2023-01-04
    Description: 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).
    Type: Article , PeerReviewed
    Format: text
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  • 5
    Publication Date: 2023-10-16
    Description: Abstract
    Description: This database contains major and trace element compositions of European tephra and metadata for the datasets and lakes they were found in. It was created by collecting data from scientific literature to support the synchronisation of annually-resolved lake sediment records during the Last Glacial Interglacial Transition (25 ka BP to 8 ka BP). 49 individual tephra layers across 19 varved lake records have been included, with Lago di Grande Monticchio being the largest contributor of geochemical data with 28 layers. The Vedde Ash and Laacher See tephra are the most common layers, being found in 6 different varved records, and highlight the potential of refining the absolute age estimates for these tephra layers using varve chronologies and for synchronising regional paleoclimate archives. This project is the first stage in a 5-years plan funded by the Past Global Changes (PAGES) Data Stewardship Scholarship to incorporate a global dataset of tephra geochemical data in varved sediment records. Further stages of this project will focus on different regions and timescales.
    Keywords: Terrestrial Records; Varved Sediments; Lakes; Chronology; Tephra; Volcano Ash; Geochemistry; Major Elements; Trace Elements; Europe; ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 LAND RECORDS 〉 VOLCANIC DEPOSITS ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 OCEAN/LAKE RECORDS 〉 SEDIMENTS ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 OCEAN/LAKE RECORDS 〉 VARVE DEPOSITS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOCHEMISTRY ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 ELEMENTS 〉 MAJOR ELEMENTS ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 ELEMENTS 〉 TRACE ELEMENTS
    Type: Dataset , Dataset
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