Accessibility navigation


Evaluation of Earth system models using modern and palaeo-observations: the state-of-the-art

Foley, A. M., Dalmonech, D., Friend, A. .D., Aires, F., Archibald, A., Bartlein, P. J., Bopp, L., Chappellaz, J., Cox, P., Edwards, N. R., Feulner, G., Friedlingstein, P., Harrison, S. P., Hopcroft, P. O., Jones, C. D., Kolassa, J., Levine, J., Prentice, I. C., Pyle, J., Vasquez Riveiros, N. , Wolff, E. and Zaele, S. (2013) Evaluation of Earth system models using modern and palaeo-observations: the state-of-the-art. Biogeosciences Discussions, 10 (7). pp. 10937-10995. ISSN 1810-6285

WarningThere is a more recent version of this item available.

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.5194/bgd-10-10937-2013

Abstract/Summary

Earth system models are increasing in complexity and incorporating more processes than their predecessors, making them important tools for studying the global carbon cycle. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes, with coupled climate-carbon cycle models that represent land-use change simulating total land carbon stores by 2100 that vary by as much as 600 Pg C given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous model evaluation methodologies. Here we assess the state-of-the-art with respect to evaluation of Earth system models, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeo data and (ii) metrics for evaluation, and discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute towards the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but it is also a challenge, as more knowledge about data uncertainties is required in order to determine robust evaluation methodologies that move the field of ESM evaluation from "beauty contest" toward the development of useful constraints on model behaviour.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Walker Institute
Faculty of Science > School of Archaeology, Geography and Environmental Science > Earth Systems Science
Faculty of Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
ID Code:33670
Publisher:Copernicus GmbH

Available Versions of this Item

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation