 |
| Titel |
Limiting the parameter space in the Carbon Cycle Data Assimilation System (CCDAS) |
| VerfasserIn |
S. Kemp, M. Scholze, T. Ziehn, T. Kaminski |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1991-959X
|
| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 7, no. 4 ; Nr. 7, no. 4 (2014-08-07), S.1609-1619 |
| Datensatznummer |
250115673
|
| Publikation (Nr.) |
 copernicus.org/gmd-7-1609-2014.pdf |
|
|
|
|
|
| Zusammenfassung |
| Terrestrial ecosystem models are employed to calculate the sources and sinks
of carbon dioxide between land and atmosphere. These models may be heavily
parameterised. Where reliable estimates are unavailable for a parameter, it
remains highly uncertain; uncertainty of parameters can substantially
contribute to overall model output uncertainty. This paper builds on the
work of the terrestrial Carbon Cycle Data Assimilation System (CCDAS),
which, here, assimilates atmospheric CO2 concentrations to optimise 19
parameters of the underlying terrestrial ecosystem model (Biosphere Energy
Transfer and Hydrology scheme, BETHY). Previous experiments have shown that
the identified minimum may contain non-physical parameter values. One way to
combat this problem is to use constrained optimisation and so avoid the
optimiser searching non-physical regions. Another technique is to use
penalty terms in the cost function, which are added when the optimisation
searches outside of a specified region. The use of parameter transformations
is a further method of avoiding this problem, where the optimisation is
carried out in a transformed parameter space, thus ensuring that the optimal
parameters at the minimum are in the physical domain. We compare these
different methods of achieving meaningful parameter values, finding that the
parameter transformation method shows consistent results and that the other two
provide no useful results. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|