Title of article :
Actual and potential skill of seasonal predictions using the CNRM contribution to DEMETER: coupled versus uncoupled model
Author/Authors :
JEAN-FRANCOIS GUEREMY، نويسنده , , MICHEL DEQUE، نويسنده , , ALAIN BRAUN ، نويسنده , , JEAN-PHILIPPE PIEDELIEVRE، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Pages :
12
From page :
308
To page :
319
Abstract :
The skill of seasonal forecasts carried out with the CNRM general circulation model (GCM) is assessed over the winter and summer seasons during the period 1958–2001. Three types of forecasts are considered. Two of them, compatible with real-time forecasting, make use of the ocean–atmosphere coupled model and the sea surface temperature (SST) statistical model, while the third provides an upper limit of the skill taking the observed SSTs into account. The nine-member ensemble skill is evaluated with the help of anomaly correlation coefficients (deterministic skill) and economical values (probabilistic skill). The coupled model skill is larger than that of the statistical SST forced model, from both deterministic and probabilistic point of views. Moreover, the coupled forecast skill is not far from that of the observed SST forecasts. Over the tropics, the correlations (above 0.3) and economical values are significant. Over Europe, only observed SST forecasts reach the level of significance in both seasons. For the years of the largest observed normalized anomalies (tropical precipitation and temperature at 850 hPa over Europe), composites of the atmospheric response are constructed in a trial of understanding the nature of predictability in the GCM, in comparison with the observation. The teleconnection patterns between the tropics and the Northern Hemisphere are not well reproduced by the GCM. However, it shows a rather good potential skill in the sense that the years characterized by the largest internal ensemble consistency give an atmospheric response very similar to that obtained during the years for which the observed anomalies are the largest.
Journal title :
Tellus. Series A
Serial Year :
2005
Journal title :
Tellus. Series A
Record number :
436531
Link To Document :
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