 |
| Titel |
Mechanistic site-based emulation of a global ocean biogeochemical model (MEDUSA 1.0) for parametric analysis and calibration: an application of the Marine Model Optimization Testbed (MarMOT 1.1) |
| VerfasserIn |
J. C. P. Hemmings, P. G. Challenor, A. Yool |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1991-959X
|
| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 3 ; Nr. 8, no. 3 (2015-03-23), S.697-731 |
| Datensatznummer |
250116183
|
| Publikation (Nr.) |
 copernicus.org/gmd-8-697-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
Biogeochemical ocean circulation models used to investigate the role
of plankton ecosystems in global change rely on adjustable parameters
to capture the dominant biogeochemical dynamics of a complex biological system. In principle, optimal
parameter values can be estimated by fitting models to observational
data, including satellite ocean colour products such as chlorophyll
that achieve good spatial and temporal coverage of the surface
ocean. However, comprehensive parametric analyses require large
ensemble experiments that are computationally infeasible with global
3-D simulations. Site-based simulations provide an efficient
alternative but can only be used to make reliable inferences about
global model performance if robust quantitative descriptions of their
relationships with the corresponding 3-D simulations can be
established.
The feasibility of establishing such a relationship is investigated
for an intermediate complexity biogeochemistry model (MEDUSA) coupled
with a widely used global ocean model (NEMO). A site-based mechanistic
emulator is constructed for surface chlorophyll output from this
target model as a function of model parameters. The emulator comprises
an array of 1-D simulators and a statistical quantification of the
uncertainty in their predictions. The unknown parameter-dependent
biogeochemical environment, in terms of initial tracer concentrations
and lateral flux information required by the simulators, is
a significant source of uncertainty. It is approximated by a mean
environment derived from a small ensemble of 3-D simulations
representing variability of the target model behaviour over the
parameter space of interest. The performance of two alternative
uncertainty quantification schemes is examined: a direct method based
on comparisons between simulator output and a sample of known target
model "truths" and an indirect method that is only partially reliant
on knowledge of the target model output.
In general, chlorophyll records at a representative array of oceanic
sites are well reproduced. The use of lateral flux information reduces
the 1-D simulator error considerably, consistent with a major
influence of advection at some sites. Emulator robustness is assessed
by comparing actual error distributions with those predicted. With the
direct uncertainty quantification scheme, the emulator is reasonably
robust over all sites. The indirect uncertainty quantification scheme
is less reliable at some sites but scope for improving its performance
is identified. The results demonstrate the strong potential of the
emulation approach to improve the effectiveness of site-based
methods. This represents important progress towards establishing
a robust site-based capability that will allow comprehensive
parametric analyses to be achieved for improving global models and
quantifying uncertainty in their predictions. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|