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| Titel |
The regional MiKlip decadal forecast ensemble for Europe: the added value of downscaling |
| VerfasserIn |
S. Mieruch, H. Feldmann, G. Schädler, C.-J. Lenz, S. Kothe, C. Kottmeier |
| 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 ; 7, no. 6 ; Nr. 7, no. 6 (2014-12-17), S.2983-2999 |
| Datensatznummer |
250115796
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| Publikation (Nr.) |
 copernicus.org/gmd-7-2983-2014.pdf |
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| Zusammenfassung |
| The prediction of climate on time scales of years to decades is
attracting the interest of both climate researchers and
stakeholders. The German Ministry for Education and Research (BMBF)
has launched a major research programme on decadal climate
prediction called MiKlip (Mittelfristige Klimaprognosen, Decadal
Climate Prediction) in order to investigate the prediction potential
of global and regional climate models (RCMs). In this paper we describe a
regional predictive hindcast ensemble, its validation, and the added
value of regional downscaling. Global predictions are obtained from an
ensemble of simulations by the MPI-ESM-LR model (baseline 0 runs),
which were downscaled for Europe using the COSMO-CLM regional
model. Decadal hindcasts were produced for the 5 decades starting in
1961 until 2001. Observations were taken from the E-OBS data set. To
identify decadal variability and predictability, we removed the long-term
mean, as well as the long-term linear trend from the data. We
split the resulting anomaly time series into two parts, the first
including lead times of 1–5 years, reflecting the skill which
originates mainly from the initialisation, and the second including
lead times from 6–10 years, which are more related to the
representation of low frequency climate variability and the effects of
external forcing. We investigated temperature averages and
precipitation sums for the summer and winter half-year. Skill
assessment was based on correlation coefficient and reliability. We
found that regional downscaling preserves, but mostly does not
improve the skill and the reliability of the global predictions for
summer half-year temperature anomalies. In contrast, regionalisation
improves global decadal predictions of half-year precipitation sums in
most parts of Europe. The added value results from an increased
predictive skill on grid-point basis together with an improvement of
the ensemble spread, i.e. the reliability. |
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