 |
| Titel |
Evaluation of biospheric components in Earth system models using modern and palaeo-observations: the state-of-the-art |
| VerfasserIn |
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, S. Zaehle |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1726-4170
|
| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 10, no. 12 ; Nr. 10, no. 12 (2013-12-16), S.8305-8328 |
| Datensatznummer |
250085482
|
| Publikation (Nr.) |
 copernicus.org/bg-10-8305-2013.pdf |
|
|
|
|
|
| Zusammenfassung |
| Earth system models (ESMs) are increasing in complexity by incorporating more
processes than their predecessors, making them potentially important tools
for studying the evolution of climate and associated biogeochemical cycles.
However, their coupled behaviour has only recently been examined in any
detail, and has yielded a very wide range of outcomes. For example, coupled
climate–carbon cycle models that represent land-use change simulate total
land carbon stores at 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
methods of model evaluation. Here we assess the state-of-the-art in
evaluation of ESMs, 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 palaeodata
and (ii) metrics for evaluation. We note that the practice of averaging
results from many models is unreliable and no substitute for proper
evaluation of individual models. We 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 to the
development of more robust evaluation schemes. An increasingly data-rich
environment offers more opportunities for model evaluation, but also presents
a challenge. Improved knowledge of data uncertainties is still necessary to
move the field of ESM evaluation away from a "beauty contest" towards the
development of useful constraints on model outcomes. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|