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Publications, presentations and other activities
Skill in the trend and internal variability in a multi-model decadal prediction ensemble
2012
by G.J. van Oldenborgh (KNMI), F.J. Doblas-Reyes (IC3, Barcelona, Spain), B. Wouters (KNMI), W. Hazeleger (KNMI),
Abstract
Decadal climate predictions have skill due to predictable components in boundary conditions (mainly greenhouse gases) and initial conditions (mainly the ocean). We investigated the skill of temperature and precipitation hindcasts from a set of four coupled ocean-atmosphere models. Regional variations in skill with and without trend due to global warming point to separate effects of the boundary forcing and the ocean initial state.
In temperature most skill comes from the prescribed boundary forcing. The trend of the global mean temperature is represented well in the hindcasts, but variations around the trend show little skill.
The models have non-trivial skill in hindcasts of North Atlantic SST beyond the trend. The same may hold for the decadal ENSO region, although the signal is less clear. Hence we conclude that the ocean initial state contributes significantly to skill in forecasting SST in these regions.
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Correlation skill of T2m/SST hindcasts for yrs2–5 (a,c) and yrs 6–9 (b,d) including the trend (a,b) and the skill that is left after subtracting the local trends (regressions on the CO2 concentration) of both model and observations (c,d). For comparison the 5-yr and 9-yr lag correlations of 4-yr averaged detrended observations are given (e,f). Correlations that are not significant at p<0.1 are plotted in light colours. SST: ERSST v3b from NCDC, T2m: GHCN/CAMS from NCEP, polar regions: GISTEMP (1200 km decorrelation).
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Biblographic data
| Oldenborgh, G.J. van, F.J. Doblas-Reyes, B. Wouters and W. Hazeleger, Skill in the trend and internal variability in a multi-model decadal prediction ensemble Abstract (html) Complete text (pdf) |  |
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