Articles | Volume 21, issue 2
https://doi.org/10.5194/cp-21-357-2025
https://doi.org/10.5194/cp-21-357-2025
Research article
 | 
04 Feb 2025
Research article |  | 04 Feb 2025

New probabilistic methods for quantitative climate reconstructions applied to palynological data from Lake Kinneret

Timon Netzel, Andrea Miebach, Thomas Litt, and Andreas Hense

Model code and software

Reconstruction code in R (includes the data sets) Timon Netzel https://zenodo.org/record/8214297

Reconstruction code in python (includes the data sets) Timon Netzel https://zenodo.org/record/8214290

Download
Short summary
New probabilistic methods for local quantitative paleoclimate reconstructions are introduced within a Bayesian framework and applied to plant proxy data from Lake Kinneret (Israel). Recent climate data and arboreal pollen from the lake's sediment are added as predefined boundary conditions. The results provide a reconstruction of the mean December–February temperature and annual precipitation, along with their associated uncertainty ranges, in this region during the Holocene.
Share