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  Detecting and quantifying palaeoseasonality in stalagmites using geochemical and modelling approaches

Baldini, J. U. L., Lechleitner, F. A., Breitenbach, S. F. M., van Hunen, J., Baldini, L. M., Wynn, P. M., Jamieson, R. A., Ridley, H. E., Baker, A. J., Walczak, I. W., Fohlmeister, J. (2021): Detecting and quantifying palaeoseasonality in stalagmites using geochemical and modelling approaches. - Quaternary Science Reviews, 254, 106784.
https://doi.org/10.1016/j.quascirev.2020.106784

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Baldini, J. U. L., Author
Lechleitner, F. A., Author
Breitenbach, S. F. M., Author
van Hunen, J., Author
Baldini, L. M., Author
Wynn, P. M., Author
Jamieson, R. A., Author
Ridley, H. E., Author
Baker, A. J., Author
Walczak, I. W., Author
Fohlmeister, Jens1, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Stalagmites are an extraordinarily powerful resource for the reconstruction of climatological palaeoseasonality. Here, we provide a review of different types of seasonality preserved by stalagmites and methods for extracting this information. A new drip classification scheme is introduced, which facilitates the identification of stalagmites fed by seasonally responsive drips and which highlights the wide variability in drip types feeding stalagmites. This hydrological variability, combined with seasonality in Earth atmospheric processes, meteoric precipitation, biological processes within the soil, and cave atmosphere composition means that every stalagmite retains a different and distinct (but correct) record of environmental conditions. Replication of a record is extremely useful but should not be expected unless comparing stalagmites affected by the same processes in the same proportion. A short overview of common microanalytical techniques is presented, and suggested best practice discussed. In addition to geochemical methods, a new modelling technique for extracting meteoric precipitation and temperature palaeoseasonality from stalagmite δ18O data is discussed and tested with both synthetic and real-world datasets. Finally, world maps of temperature, meteoric precipitation amount, and meteoric precipitation oxygen isotope ratio seasonality are presented and discussed, with an aim of helping to identify regions most sensitive to shifts in seasonality.

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 Dates: 2020-03-192020-12-212021-01-072021-01-16
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: PIKDOMAIN: RD4 - Complexity Science
DOI: 10.1016/j.quascirev.2020.106784
Organisational keyword: RD4 - Complexity Science
Organisational keyword: FutureLab - Artificial Intelligence in the Anthropocene
Regional keyword: Global
Research topic keyword: Paleoclimate
Research topic keyword: Weather
Research topic keyword: Extremes
Research topic keyword: Complex Networks
Model / method: Qualitative Methods
MDB-ID: No data to archive
Working Group: Development of advanced time series analysis techniques
 Degree: -

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Title: Quaternary Science Reviews
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 254 Sequence Number: 106784 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals418
Publisher: Elsevier