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Multimodel ensemble combination (MMEC) has become an accepted technique to improve probabilistic forecasts from short- to long-range time scales. MMEC techniques typically widen ensemble spread, thus improving the dispersion characteristics and the reliability of the forecasts. This raises the question as to whether the same effect could be achieved in a potentially cheaper way by rescaling single model ensemble forecasts a posteriori such that they become reliable. In this study a climate conserving recalibration (CCR) technique is derived and compared with MMEC. With a simple stochastic toy model it is shown that both CCR and MMEC successfully improve forecast reliability. The difference between these two methods is that CCR conserves resolution but inevitably dilutes the potentially predictable signal while MMEC is in the ideal case able to fully retain the predictable signal and to improve resolution. Therefore, MMEC is conceptually to be preferred, particularly since the effect of CCR depend...

Seasonal Ensemble Forecasts: Are Recalibrated Single Models Better than Multimodels?