 |
| Titel |
Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models |
| VerfasserIn |
H. Wan, P. J. Rasch, K. Zhang, Y. Qian, H. Yan, C. Zhao |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1991-959X
|
| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 7, no. 5 ; Nr. 7, no. 5 (2014-09-08), S.1961-1977 |
| Datensatznummer |
250115715
|
| Publikation (Nr.) |
 copernicus.org/gmd-7-1961-2014.pdf |
|
|
|
|
|
| Zusammenfassung |
This paper explores the feasibility of an experimentation strategy
for investigating sensitivities in fast components of atmospheric
general circulation models. The basic idea is to replace the
traditional serial-in-time long-term climate integrations by
representative ensembles of shorter simulations. The key advantage
of the proposed method lies in its efficiency: since fewer days of
simulation are needed, the computational cost is less, and because
individual realizations are independent and can be integrated
simultaneously, the new dimension of parallelism can dramatically
reduce the turnaround time in benchmark tests, sensitivities
studies, and model tuning exercises. The strategy is not appropriate
for exploring sensitivity of all model features, but it is very
effective in many situations.
Two examples are presented using the Community Atmosphere Model,
version 5. In the first example, the method is used to
characterize sensitivities of the simulated clouds to time-step length.
Results show that 3-day ensembles of 20 to 50 members are sufficient
to reproduce the main signals revealed by traditional 5-year simulations.
A nudging technique is applied to an additional set of simulations to
help understand the contribution of physics–dynamics interaction
to the detected time-step sensitivity. In the second example, multiple empirical
parameters related to cloud microphysics and aerosol life cycle are
perturbed simultaneously in order to find out which parameters have
the largest impact on the simulated global mean top-of-atmosphere
radiation balance. It turns out that 12-member ensembles of 10-day
simulations are able to reveal the same sensitivities
as seen in 4-year simulations performed in a previous study.
In both cases, the ensemble method reduces the total
computational time by a factor of about 15, and the turnaround time
by a factor of several hundred.
The efficiency of the method makes it
particularly useful for the development of high-resolution, costly,
and complex climate models. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|