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| Titel |
Partially coupled spin-up of the MPI-ESM: implementation and first results |
| VerfasserIn |
M. Thoma, R. Gerdes, R. J. Greatbatch, H. Ding |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 1 ; Nr. 8, no. 1 (2015-01-19), S.51-68 |
| Datensatznummer |
250116029
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| Publikation (Nr.) |
 copernicus.org/gmd-8-51-2015.pdf |
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| Zusammenfassung |
| Large-scale fully coupled Earth system models (ESMs) are usually applied in
climate projections like the IPCC (Intergovernmental Panel on Climate Change) reports. In these models internal
variability is often within the correct order of magnitude compared with the
observed climate, but due to internal variability and arbitrary initial
conditions they are not able to reproduce the observed timing of climate
events or shifts as for instance observed in the El Niño–Southern
Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), or the Atlantic
Meridional Overturning Circulation (AMOC). Additional information about the
real climate history is necessary to constrain ESMs; not only to emulate the
past climate, but also to introduce a potential forecast skill into these
models through a proper initialisation. We attempt to do this by extending
the fully coupled climate model Max Planck Institute Earth System Model
(MPI-ESM) using a partial coupling technique (Modini-MPI-ESM). This method is
implemented by adding reanalysis wind-field anomalies to the MPI-ESM's
inherent climatological wind field when computing the surface wind stress
that is used to drive the ocean and sea ice model. Using anomalies instead of
the full wind field reduces potential model drifts, because of different mean
climate states of the unconstrained MPI-ESM and the partially coupled
Modini-MPI-ESM, that could arise if total observed wind stress was used. We
apply two different reanalysis wind products (National Centers for
Environmental Prediction, Climate Forecast System Reanalysis (NCEPcsfr) and
ERA-Interim reanalysis (ERAI)) and analyse the skill of Modini-MPI-ESM with
respect to several observed oceanic, atmospheric, and sea ice indices. We
demonstrate that Modini-MPI-ESM has a significant skill over the time period
1980–2013 in reproducing historical climate fluctuations, indicating the
potential of the method for initialising seasonal to decadal forecasts.
Additionally, our comparison of the results achieved with the two reanalysis
wind products NCEPcsfr and ERAI indicates that in general applying NCEPcsfr
results in a better reconstruction of climate variability since 1980. |
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