Comment on 'Can multi-model combination really enhance the prediction skill of probabilistic ensemble forecasts?'

摘要

This note refers to the study of Weigel et al, (2008), where the success of multi-model ensemble combination has been evaluated with a Gaussian stochastic toy model. The authors concluded that multi-models can outperform the best participating singlemodels, but only if the single model ensembles are under-dispersive. Here we introduce two improved versions of the toy model of Weigel et al. For one of these models the combination of well-dispersed (i.e. reliable) forecasts can improve the predictionskill, but for the other model this possibility is excluded. It is argued that, for normally distributed variables, the first model may be applicable in the context of short- and medium-range forecasting, but the latter may be more appropriate to seasonal forecasting.