crestr An R package to perform probabilistic climate reconstructions using fossil proxies
- 1Institute of Geosciences, Sect. Meteorology, Rheinische Friedrich-Wilhelms-Universität Bonn, Auf dem Hügel 20, 53121 Bonn, Germany
- 2Institute of Earth Surface Dynamics, Geopolis, University of Lausanne, Lausanne, Switzerland
Abstract. Statistical climate reconstruction techniques are practical tools to study past climate variability from fossil proxy data. In particular, the methods based on probability density functions (PDFs) are powerful at producing robust results from various environments and proxies. However, accessing and curating the necessary calibration data, as well as the complexity of interpreting probabilistic results, often limit their use in palaeoclimatological studies. To address these problems, I present a new R package (crestr) to apply the CREST method (Climate REconstruction SofTware) on diverse palaeoecological datasets. crestr includes a globally curated calibration dataset for six common climate proxies (i.e. plants, beetles, chironomids, rodents, foraminifera, and dinoflagellate cysts) that enables its use in most terrestrial and marine regions. The package can also be used with private data collections instead of, or in combination with, the provided dataset. It also includes a suite of graphical diagnostic tools to represent the data at each step of the reconstruction process and provide insights into the effect of the different modelling assumptions and external factors that underlie a reconstruction. With this R package, the CREST method can now be used in a scriptable environment, thus simplifying its use and integration in existing workflows. It is hoped that crestr will contribute to producing the much-needed quantified records from the many regions where climate reconstructions are currently lacking, despite the existence of suitable fossil records.
Status: open (until 27 Jan 2022)
Model code and software
crestr R package https://github.com/mchevalier2/crestr
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