Annual Review of Earth and Planetary Sciences, 33, 163-193
Representing model uncertainty in weather and climate prediction
Tim N. Palmer, Glenn J. Shutts, Renate Hagedorn, Francisco J. Doblas-Reyes,
Thomas Jung and Martin Leutbecher
ECMWF, Shinfield Park
RG2 9AX, Reading, UK
Weather and climate predictions are uncertain, because both forecast initial
conditions and the computational representation of the known equations of
motion are uncertain. Ensemble prediction systems provide the means to estimate
the flow-dependent growth of uncertainty during a forecast. Sources of
uncertainty must therefore be represented in such systems. In this paper, methods
used to represent model uncertainty are discussed. It is argued that multimodel
and related ensembles are vastly superior to corresponding single-model
ensembles, but do not provide a comprehensive representation of model uncertainty.
A relatively new paradigm is discussed, whereby unresolved processes are represented
by computationally efficient stochastic-dynamic schemes.