Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations

Arora, Vivek K.; Seiler, Christian; Wang, Libo; Kou-Giesbrecht, Sian

doi:https://doi.org/10.5194/bg-20-1313-2023

Articles | Volume 20, issue 7

https://doi.org/10.5194/bg-20-1313-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-20-1313-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 7

Research article

|

06 Apr 2023

Research article |

| 06 Apr 2023

Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations

Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht

Data sets

Full set of AMBER plots for the results presented in this manuscript C. Seiler https://cseiler.shinyapps.io/ShinyCLASSIC/

Model code and software

Model code for the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) J. Melton https://cccma.gitlab.io/classic_pages/

Repository for the data and code required for reproducing the results presented in the paper “Are terrestrial biosphere models fit for simulating the global land carbon sink?” by Seiler et al C. Seiler https://doi.org/10.5281/zenodo.5670387

Short summary

The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.