<i>crestr</i>: an R package to perform probabilistic climate reconstructions from palaeoecological datasets

Chevalier, Manuel

doi:https://doi.org/10.5194/cp-18-821-2022

Articles | Volume 18, issue 4

https://doi.org/10.5194/cp-18-821-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/cp-18-821-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 4

Research article

|

19 Apr 2022

Research article |

| 19 Apr 2022

crestr: an R package to perform probabilistic climate reconstructions from palaeoecological datasets

Manuel Chevalier

Supplement

https://doi.org/10.5194/cp-18-821-2022-supplement

Data sets

Mean Annual Temperature changes reconstructions from marine core MD96-2048 M. Chevalier, B. M. Chase, L. J. Quick, L. M. Dupont, and T. C. Johnson https://doi.org/10.1594/PANGAEA.915923

Daily high-resolution-blended analyses for sea surface temperature (https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html) R. W. Reynolds, T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax https://doi.org/10.1175/2007JCLI1824.1

Model code and software

crestr R package Manuel Chevalier https://CRAN.R-project.org/package=crestr

crestr: v1.01 Manuel Chevalier https://doi.org/10.5281/zenodo.6458405

Short summary

This paper introduces a new R package to perform quantitative climate reconstructions from palaeoecological datasets. The package includes calibration data for several commonly used terrestrial (e.g. pollen) and marine (e.g. foraminifers) climate proxies to enable its use in various environments globally. In addition, the built-in graphical diagnostic tools simplify the evaluation and interpretations of the results. No coding skills are required to use crestr.