By Heinz Wanner, Martin Grosjean, Regine Röthlisberger, Elena Xoplaki
Heinz Wanner is the pinnacle of the weather examine staff and Director of the NCRR administration Center.
Martin Grosjean is
Regine Rothlisberger is a technological know-how Officer with the NCCR weather administration Center.
Elena Xoplaki is a technological know-how Officer with the NCCR weather administration Center.
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Extra resources for Climate Variability, Predictability and Climate Risks: A European Perspective
In some applications, substitutes of climate models are used that take the form of pulse response models. The latter assume a linearity of the response but dramatically increase the computational efﬁciency (Joos and Bruno 1996). Alternatively a neural-network approach formally removes the linearity assumption but does not necessarily replicate the system’s non-linear characteristics (Knutti et al. 2003). In the next sub-sections we review approaches of assessing uncertainty using models of different complexity.
Here the focus was on estimating the uncertainty of climate projections. Next, we continue to address probabilistic methods and introduce quantitative statistical measures of forecast uncertainty, with a speciﬁc focus on the interface to operational application and the end-user perspective. This will be exempliﬁed on the seasonal time-scale. 1 The rationale A major addition to the forecasting repertoire of weather services in recent years has been the development of operational techniques for seasonal climate predictions.
P. 74 Goosse H, Crwoley TJ, Zorita E, Ammann H, Renssen CM, Driesschaert E (2005) Modelling the climate of the last millennium: What causes the differences between simulations. 1029/2005GL022368 Gr¨otzner A, Latif M, Barnett TP (1998) A decadal cycle in the North Atlantic ocean as simulated by the ECHO coupled GCM. J Climate 11:831–847 Guiot J, Nicault A, Rathgeber C, Edouard J, Guibal F, Pichard G, Till C (2005) Last-millennium summertemperature variations in western Europe based on proxy data.