02 Dec 2021

02 Dec 2021

Review status: this preprint is currently under review for the journal CP.

crestr An R package to perform probabilistic climate reconstructions using fossil proxies

Manuel Chevalier1,2 Manuel Chevalier
  • 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.

Manuel Chevalier

Status: open (until 27 Jan 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on cp-2021-153', Anonymous Referee #1, 02 Jan 2022 reply
  • RC2: 'Comment on cp-2021-153', Patrick Bartlein, 09 Jan 2022 reply

Manuel Chevalier

Model code and software

crestr R package Manuel Chevalier

Manuel Chevalier


Total article views: 718 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
562 152 4 718 29 5 3
  • HTML: 562
  • PDF: 152
  • XML: 4
  • Total: 718
  • Supplement: 29
  • BibTeX: 5
  • EndNote: 3
Views and downloads (calculated since 02 Dec 2021)
Cumulative views and downloads (calculated since 02 Dec 2021)

Viewed (geographical distribution)

Total article views: 705 (including HTML, PDF, and XML) Thereof 705 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 21 Jan 2022
Short summary
This paper introduces a new R package to perform quantitative climate reconstructions from fossil ecological datasets, such as pollen records. The package includes calibration data for several commonly-used terrestrial and marine climate proxies and is, as such, readily usable. In addition, the multiple diagnostic illustrations of the data simplify the evaluation and interpretations of the results. Possibly most importantly, no coding skills are required to use crestr.